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timestamp[us]date 2025-04-29 14:36:04
2025-04-29 14:36:04
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timestamp[us]date 2025-04-29 14:36:04
2025-05-27 14:00:52
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fc97138a-760a-4915-b1d9-ad11fb86b345
|
completed
| 2025-04-29T14:36:04.698000 | 2025-05-27T14:00:34.009000 |
b124731c-d4e6-4e5c-bb19-986af26944a4
|
Recent behavioral data have shown that lifelong bilingualism can maintain youthful cognitive control abilities in aging. Here, we provide the first direct evidence of a neural basis for the bilingual cognitive control boost in aging. Two experiments were conducted, using a perceptual task-switching paradigm, including a total of 110 participants. In Experiment 1, older adult bilinguals showed better perceptual switching performance than their monolingual peers. In Experiment 2, younger and older adult monolinguals and bilinguals completed the same perceptual task-switching experiment while functional magnetic resonance imaging (fMRI) was performed. Typical age-related performance reductions and fMRI activation increases were observed. However, like younger adults, bilingual older adults outperformed their monolingual peers while displaying decreased activation in left lateral frontal cortex and cingulate cortex. Critically, this attenuation of age-related over-recruitment associated with bilingualism was directly correlated with better task-switching performance. In addition, the lower blood oxygenation level-dependent response in frontal regions accounted for 82% of the variance in the bilingual task-switching reaction time advantage. These results suggest that lifelong bilingualism offsets age-related declines in the neural efficiency for cognitive control processes.
|
<li> <b>functional magnetic resonance imaging:</b> functionalMagneticResonanceImaging (technique)<li> <b>fMRI:</b> functionalMagneticResonanceImaging (technique)<li> <b>left lateral frontal cortex:</b> lateralOrbitalFrontalCortex (UBERONParcellation)<li> <b>cingulate cortex:</b> cingulateCortex (UBERONParcellation)
|
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b45fd355-f5ce-42d3-a506-d4ead29c5f06
|
completed
| 2025-04-29T14:36:04.698000 | 2025-05-27T14:00:37.502000 |
c57162d2-9166-4067-9725-bb04a8b9a125
|
Participants completed the same perceptual task-switching paradigm described above during fMRI acquisition.The experiment was backprojected onto a screen placed outside the magnet and viewed by the subjects through a mirror attached to the head coil.Behavioral analyses were similar to those for Experiment 1.However, to control for general age-related slowing, RT switch costs were analyzed using proportional scaling ([switch RT Ϫ nonswitch RT]/nonswitch RT ϫ 100).
|
<li> <b>fMRI:</b> functionalMagneticResonanceImaging (technique)
|
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null
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[
{
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3e48c506-4bce-4171-9f5f-26a4edad858d
|
completed
| 2025-04-29T14:36:04.698000 | 2025-05-27T14:00:37.601000 |
a86c1718-9380-4146-9c61-ff6084c9020a
|
AbstractLongitudinal developmental fMRI studies just recently began to focus on within-subject reliability using the intraclass coefficient (ICC). It remains largely unclear which degree of reliability can be achieved in developmental studies and whether this depends on the type of task used. Therefore, we aimed to systematically investigate the reliability of three well-classified tasks: an emotional attention, a cognitive control, and an intertemporal choice paradigm. We hypothesized to find higher reliability in the cognitive task than in the emotional or reward-related task. 104 healthy mid-adolescents were scanned at age 14 and again at age 16 within M = 1.8 years using the same paradigms, scanner, and scanning protocols. Overall, we found both variability and stability (i.e. poor to excellent ICCs) depending largely on the region of interest (ROI) and task. Contrary to our hypothesis, whole brain reliability was fair for the cognitive control task but good for the emotional attention and intertemporal choice task. Subcortical ROIs (ventral striatum, amygdala) resulted in lower ICCs than visual ROIs. Current results add to the yet sparse overall ICC literature in both developing samples and adults. This study shows that analyses of stability, i.e. reliability, are helpful benchmarks for longitudinal studies and their implications for adolescent development.
|
<li> <b>fMRI:</b> functionalMagneticResonanceImaging (technique)<li> <b>ventral striatum:</b> ventralStriatum (UBERONParcellation)<li> <b>amygdala:</b> amygdala (UBERONParcellation)
|
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[
"\n\r\n"
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{
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] | null | null |
6b85c58d-c41c-4b0f-b63e-7a5f8a0c6d13
|
completed
| 2025-04-29T14:36:04.698000 | 2025-05-27T14:00:37.802000 |
4214d418-b9c6-4cb3-b1db-985c358b130b
|
For an overview of the main characteristics of the three paradigms see Table 3.In the emotional attention task, participants had to decide whether a pair of visual target stimuli was identical or not while another pair was presented as a distractor.Participants were not asked to attend to a particular emotional category but cued spatially by an arrow pointing in the direction of the two stimuli.Each trial consisted of a pair of pictures from one of three emotional categories (positive, neutral, negative) and a pair of non-emotional pictures.The emotional pictures were taken from the International Affective Picture System (IAPS 58 ); and the non-emotional pictures were created by shredding the chosen IAPS pictures with GIMP (www.gimp.org).For further details see Vetter et al. 16 and Pilhatsch et al. 15 and Supplement S2. The first screen of the cognitive control task was an arrow consisting of two triangles pointing in one (left, right, up or down) direction and a red dot located either at the tip or the tail of the arrow.Participants were instructed to move a joystick in the direction indicated by the arrow or the dot.The shape of the background served as a task cue: If the background was rectangular, participants had to move the joystick in the direction of the arrow and ignore the position of the dot; conversely, if the background was circular, participants had to respond to the position of the dot while ignoring the arrow direction.Stimuli could be congruent, i.e. dot and arrow were pointing in the same direction, or incongruent, i.e. the dot and the arrow were pointing in opposite directions.For further details see Mennigen et al. 17 , Rodehacke et al. 18 . In the intertemporal choice task participants had to choose between a larger later reward, which changed from trial to trial and a fixed immediate reward, which was instructed beforehand but not shown during scanning.In the current paper, the contrast of interest was the phase of the presentation of the potential later reward, i.e. the intertemporal decision phase, which refers to the process of comparing both alternatives in a given trial (fixed immediate or later reward).The task started with a behavioral training session to estimate the individual impulsivity parameter k, which was used to adapt the scanning paradigm to the subjects' impulsivity.For more details see Ripke et al. 22 and Ripke et al. 56 . Task presentation and order.The paradigms were presented with a LCD-based display system which was mounted on the head-coil (NordicNeuroLab AS, Bergen, Norway).Behavioral data were collected with a joystick (Resonance Technology Inc., Northridge, CA, USA) for the cognitive control task and by ResponseGrips (©NordicNeuroLab) with a button on a grip in each hand for the emotional attention and intertemporal choice task.Task presentation and recording of the behavioral responses was performed using Presentation ® software (version 11.1, Neurobehavioral Systems, Inc., Albany, CA).Each task was preceded by a practice session.Since the tasks were assessed within an overall project including a large behavioral and fMRI battery, the order of tasks varied slightly between time points.At age 14, the order of paradigms was emotional attention, cognitive control and intertemporal choice on three different days within two weeks.At age 16 first the cognitive control and then the intertemporal choice task were assessed on the same day followed by the assessment of the emotional attention task within two weeks. Functional imaging.Image acquisition.For all three paradigms and across both sessions, image acquisition remained the same.MRI data was acquired using a Analysis of fMRI data.FMRI data analyses were performed using SPM5 (Wellcome Trust Center of Neuroimaging, London, UK) and were the same for both time points per paradigm. Preprocessing.For preprocessing, which was identical for all three tasks, functional images were first slice-time corrected by using the middle slice as reference and realigned to the first image (by 6° rigid spatial transformation).Afterwards they were spatially normalized into Montreal Neurological Institute (MNI) space and spatially smoothed with an 8 mm full-width half maximum Gaussian kernel. Statistical analysis.For all paradigms first-level contrasts were computed with a fixed effects analysis for each participant based on the general linear model by modeling the different conditions as regressors of interest within each voxel for the whole brain.For each paradigm, the six subject-specific movement regressors, which were derived from the rigid-body realignment, were included as covariates of no interest.A high-pass filter with cut-off 128 s was applied to remove the low frequency physiological noise 59 for each paradigm.Also an autoregression, AR(1), model was employed for the residual temporal autocorrelation 59 for each paradigm.Contrasts of interest (see Table 3) were computed for each paradigm within each subject.The first-level contrast images from the weighted beta-images were used for second-level whole brain random-effects analyses to allow for population inference.For a detailed description of the first-and second-level analyses for each paradigm see S3 in the supplement.
|
<li> <b>fMRI:</b> functionalMagneticResonanceImaging (technique)<li> <b>MRI:</b> magneticResonanceImaging (technique)
|
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"Correct"
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[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
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[
"submitted"
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[
"Correct"
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[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"brain: Other (UBERONParcellation)"
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[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
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{
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{
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},
{
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729918d1-dc6b-4b19-ad34-f0f61d5a974e
|
completed
| 2025-04-29T14:36:04.698000 | 2025-05-27T14:00:37.909000 |
69f675f9-c08e-43de-9def-9b0d331ecaa6
|
The automated tape-collecting ultramicrotome (ATUM) makes it possible to collect large numbers of ultrathin sections quickly-the equivalent of a petabyte of high resolution images each day. However, even high throughput image acquisition strategies generate images far more slowly (at present ~1 terabyte per day). We therefore developed WaferMapper, a software package that takes a multi-resolution approach to mapping and imaging select regions within a library of ultrathin sections. This automated method selects and directs imaging of corresponding regions within each section of an ultrathin section library (UTSL) that may contain many thousands of sections. Using WaferMapper, it is possible to map thousands of tissue sections at low resolution and target multiple points of interest for high resolution imaging based on anatomical landmarks. The program can also be used to expand previously imaged regions, acquire data under different imaging conditions, or re-image after additional tissue treatments.
|
<li> <b>ultramicrotome:</b> microtomeSectioning (technique)
|
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[
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[
"Correct"
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[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
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[
"submitted"
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[
null
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[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
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[
"submitted"
] |
[
{
"end": 44,
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"start": 30
}
] | null | null |
40434529-2780-4db4-a016-69a694558fae
|
completed
| 2025-04-29T14:36:04.698000 | 2025-05-27T14:00:38.029000 |
49181da3-d909-4ecb-ad05-ffa17ea1f4a6
|
Small EM volumes (<1 terabyte) can be aligned on a powerful desktop computer using publicly available alignment software such as the registration plugins for Fiji (Schindelin et al., 2012).However, the stitching and alignment of high resolution images becomes increasingly difficult as data sets become larger.The computational power required to manipulate and process terabytes of images requires hardware that is not standard in most labs and, while most steps in alignment are amenable to parallelization, running these steps in parallel often requires changes in code and expertise in managing clusters.Because of these problems, aligning multi-terabyte datasets is currently being done by only a few groups.However, the recent production of many multiterabyte EM volumes has spurred efforts to scale up alignment tools to make it easier for the broader research community to turn hundreds of terabytes of EM images into usable 3D tissue maps.
|
<li> <b>EM:</b> electronMicroscopy (technique)
|
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"submitted"
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"Correct"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
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[
"Correct"
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[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
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[
"submitted"
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[
null
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"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
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"submitted"
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{
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"start": 765
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{
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"label": "technique",
"start": 910
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] | null | null |
5b37cb6d-f3b6-48b7-94d8-237bc0aee00d
|
completed
| 2025-04-29T14:36:04.698000 | 2025-05-27T14:00:38.191000 |
38250e21-a250-4634-a90d-dd89232846fd
|
Abstract Objective: To explore potential mechanisms of cognitive changes in patients with anti-NMDAR encephalitis (ANMDARE) from intramodule and intermoduleeffects of brain functional networks. Methods: Resting-state functional MRI and T1-weighted imaging data were collected from 30 ANMDARE patientsand 30 healthy controls (HCs). Abrain functional matrix was constructed, and sparsity was established by module similarity. For both groups, changes in functional connectivity within and between modules was calculated, changes in whole-brain and module gray matter volumes were explored, and whole-brain functional topology was analyzed. Finally, the association of brain functional and structural changes with cognitive function in ANMDARE was further analyzed. Results: Compared to HCs, ANMDARE patients had enhanced connectivity within the modules that included the occipito-parietal-temporal and parahippocampal gyri. ANMDARE patients had significantly higher participation coefficients (PC) in the right inferior frontal gyrus than HCs and significantly lower PC in the left superior parietal lobule, left caudate nucleus, and right putamen. No statistically significant differences in gray matter volume and global topological properties were found between the two groups. No correlations were found between functional and structural brain indicators and the Cognitive Assessment Scale and the Emotional Deficit Scale. Conclusions: Changes in cognitive function in patients with ANMDARE are manifested by enhanced intramodular functional connectivity and intermodularconnectivity changes in the brain, with abnormal intramodular and extramodularconnectivity that do not maintain normal cognitive function.
|
<li> <b>Resting-state functional MRI:</b> functionalMagneticResonanceImaging (technique)<li> <b>T1-weighted imaging:</b> magneticResonanceImaging (technique)<li> <b>right inferior frontal gyrus:</b> inferiorFrontalGyrus (UBERONParcellation)<li> <b>left superior parietal lobule:</b> superiorParietalCortex (UBERONParcellation)<li> <b>left caudate nucleus:</b> caudateNucleus (UBERONParcellation)<li> <b>right putamen:</b> putamen (UBERONParcellation)
|
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"brain: Other (UBERONParcellation)\r\ngray matter: brainGrayMatter (UBERONParcellation)\nparahippocampal gyri: parahippocampalGyrus (UBERONParcellation)\n\r\n"
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{
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476b9a23-7895-44a8-b4f0-775b67c91401
|
completed
| 2025-04-29T14:36:04.698000 | 2025-05-27T14:00:38.308000 |
f2ebe4c2-cc46-4c1b-bd72-34a935d66263
|
To ensure the stability and accuracy of community delineation and to facilitate statistical comparison between two groups, we used a modular similaritybased network thresholding approach (Yu et al., 2020) and a data-driven multi-iterative generalization of the Louvain community detection algorithm to construct a community delineation template at the holistic level (Lancichinetti & Fortunato, 2012;Nour et al., 2019). Network thresholds were obtained based on modularity similarity as follows: (1) A single FC connection matrix was obtained from each subject, and the group-level connectivity matrix (GCM) was obtained by obtaining the mean FC values within the group (i.e., ANMDARE and HCs).( 2) Thresholding of GCMs using a sparsity of 10%-50% with an interval of 1% was performed to obtain two sets of a series of group-level functional networks (GFNs).(3) Cluster detection of GFNs was performed using the algorithm proposed by Newman.Modular Q represents the degree to which the brain network divides community clusters clearly and without overlap, and generally, 0.3 < Q < 0.7 represented the nonrandom cluster structure and indicated a suitable degree of division (Newman, 2004).( 4) According to the modular similarity-based network thresholding method proposed by Yu, Zhinan et al., at the group level, when sparsity s was used, Ms denoted the module lead-in of the node, and the corresponding element in matrix As was set to 1 if two nodes were in the same module; otherwise, it was set to 0. (5) The matrices Cp,q were obtained by comparing two sparsities (e.g., p and q) of the modular structure similarity and calculating the value of d for the community structure.The magnitude of Q determined whether the complex network obtained a nonrandom and clear modular structure, and d represented the similarity of the obtained modular structure at different sparsities.A smaller value of d was determined if the modular structure was more stable at sparsity degrees p and q.Therefore, the sparsity where the lower continuous d value was located indicates that it was optimal for network thresholding.To facilitate comparative statistics between the two groups, the sparsity overlapped by the two lower d values was used for analysis. As shown in Fig. 1, the larger the sparsity is, the smaller the Q value, and the Q value of ANMDARE is less than 0.3, corresponding to a sparsity of 32%.Therefore, only a threshold range of 10-32% (steps 0.5%) was used to calculate modularity similarity.As shown in Fig. 2, the normalized d-value contour plots for the two threshold ranges show that relatively low d-values occur in the sparsity range of 23.5%-27% for ANMDARE, while low d-values occur in the threshold range of 24.5%-28% for HCs.This suggests that the two groups have superior modular similarity in the sparsity of low d values.Therefore, we used a common sparsity value of 25% for both groups for the analysis. Module structuring was performed using the MATLAB2018 Brain Connectivity Toolbox (BCT, https://sites.google.com/site/bctnet/)as follows: (1) An undirected weighted network was constructed for each subject using a sparsity value of 25%. (2) The Louvain community algorithm was run 1000 times for each matrix to obtain 1000 partitions.(3) At the individual subject level, the probability of each node belonging to the same community among 1000 community partitions was calculated, and the matrix D was constructed using the consensus function.(4) The threshold value τ = 0.2 was applied to matrix D. The Louvain community algorithm was applied to this threshold of matrix D running 1000 times to obtain another 1000 partitions.( 5) Steps ( 3)-( 4) were repeated until the consensus matrix formed a stable template for community partitioning at the overall level.
|
None
|
[
[
{
"end": 991,
"label": "UBERONParcellation",
"start": 986
}
]
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"Incorrect"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"Incorrect"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"brain: Other (UBERONParcellation)"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[] | null | null |
20e1268a-e936-4748-8e17-bd6006a2c743
|
completed
| 2025-04-29T14:36:04.698000 | 2025-05-27T14:00:38.408000 |
8e550d5d-439a-4b58-9408-8abb3b8aab9a
|
Prey capture and subjugation are complex behaviors affected by many factors including physiological and behavioral traits of both the predator and the prey. The western banded gecko (Coleonyx variegatus) is a small generalist predator that consumes both evasive prey items, such as spiders, wasps, and orthopterans, and non-evasive prey items, including larvae, pupae, and isopterans. When consuming certain prey (e.g., scorpions), banded geckos will capture and then rapidly oscillate, or shake, their head and anterior part of their body. Banded geckos also have large, active tails that can account for over 20% of their body weight and can be voluntarily severed through the process of caudal autotomy. However, how autotomy influences prey capture behavior in geckos is poorly understood. Using high-speed 3D videography, we studied the effects of both prey type (mealworms and crickets) and tail autotomy on prey capture and subjugation performance in banded geckos. Performance metrics included maximum velocity and distance of prey capture, as well as velocity and frequency of post-capture shaking. Maximum velocity and distance of prey capture were lower for mealworms than crickets regardless of tail state. However, after autotomy, maximum velocity increased for strikes on mealworms but significantly decreased for crickets. After capture, geckos always shook mealworms, but never crickets. The frequency of shaking mealworms decreased after autotomy and additional qualitative differences were observed. Our results highlight the complex and interactive effects of prey type and caudal autotomy on prey capture biomechanics.
|
<li> <b>high-speed 3D videography:</b> high-speedVideoRecording (technique)
|
[
[
{
"end": 825,
"label": "technique",
"start": 800
},
{
"end": 202,
"label": "species",
"start": 183
},
{
"end": 181,
"label": "species",
"start": 161
}
]
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"Partially correct"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"western banded gecko: Other (species)\nColeonyx variegatus: Other (species)\n"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
{
"end": 825,
"label": "technique",
"start": 800
}
] | null | null |
5ce74171-486a-4b41-b368-0edf008d923b
|
pending
| 2025-04-29T14:36:04.698000 | 2025-04-29T14:36:04.698000 |
769ba5bc-0e5b-40f9-8458-5ce439029aa6
|
Prey shaking is a vigorous movement that involves lateral oscillations of the head, forelimbs, and anterior portion of the trunk, with the hindlimbs and tail appearing to serve as anchors during the movement.Although geckos almost always shook the mealworms after capture, both before and after autotomy, the loss of the tail did not have significant effects on most of the kinematic variables measured, with prey shake frequency as the only exception.Variation among individuals was very high for all kinematic variables. Although this decrease in shake frequency does point to a decrease in performance post-autotomy, the ecological relevance of this decrease is not clear.The purpose of the prey shake in this interaction is likely to stun the prey item into immobility given that the mealworms do not have any defensive structures to be removed and do not break up into smaller pieces for easier consumption during the shake.In previous work, most scorpions were still mobile after being shaken by banded geckos, but the shake may have broken off the stinger or at least limited the amount of venom that could be injected (Whitford et al., 2022).Further research is needed to determine if shaking is effective at damaging the prey item.If the purpose of the shake is to slam the mealworm against the substrate hard enough to incapacitate it, maximum shake velocity would be a more important measurement of performance compared to shake frequency. Although few kinematic variables of the prey shake were significantly different after autotomy, we observed several qualitative differences between shakes after tail loss.Post-autotomy many of the most vigorous shakes were accompanied by increased rotation of the trunk and posterior end of the body, resulting in the hindlimbs leaving the ground for a portion of the shake.We hypothesize the tail may be acting as a counterbalance for the body during the oscillations and that the loss of the tail and associated shift in center of mass may have a destabilizing effect on the gecko when it attempts to perform a prey shake.With the mealworms, this instability was visible in the limbs coming off the ground, but the geckos may have compensated for this instability by reducing average velocity of the shake.We found a positive correlation between the time that the back legs spent off the ground and Linear regressions between time gecko feet spent off the ground during the prey shake and maximum prey shake velocity.The time feet spent airborne was positively correlated with maximum shake velocity after, but not before autotomy.Equation of the regression before autotomy was y = -0.357x+ 1.494, R 2 = 0.0002, P > 0.05.Equation of the regression after autotomy was y = 9.08x + 0.090, R 2 = 0.23, P < 0.05.maximum velocity of the shake after autotomy, but not before, indicating balance may be more coupled to shake velocity after tail loss (Figure 3). This relationship points to a tradeoff geckos face postautotomy: to perform a faster, more effective shake but become unbalanced during the oscillations, or reduce velocity to perform a less vigorous shake.The variation observed among individuals supports the existence of this trade-off.The individual that experienced the sharpest increase in time the limbs spent off the ground was also the only individual to have a higher maximum shake velocity post-autotomy, while the only individual to spend less time with its limbs off the ground post-autotomy also experienced the sharpest drop in maximum shake velocity after tail loss (Figure 4).This tradeoff is not likely to have an impact on geckos in nature since mealworms can neither escape nor harm the gecko and do not need to be broken down to be efficiently consumed.However, western banded geckos also prey on dangerous prey such as the dune scorpion (Smeringurus mesaensis) (Whitford et al., 2022).Thus, the shaking behavior that we observed may simply reflect the gecko responding to the potential danger of a different elongated prey, such as a scorpion.Previous data suggest geckos may be shaking scorpions nearly twice as fast as the maximum velocities recorded in our study (Whitford et al., 2022).Thus, future studies should examine how tail autotomy impacts these faster prey shakes on a dangerous prey item.We predict that, in predation events where shaking the prey is essential to safely and effectively consuming the prey, autotomy will have a significant negative effect on the gecko's ability to successfully capture and consume the prey because of the tradeoff between shake velocity and shake stability that is evident post-autotomy.
|
None
|
[
[]
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"discarded"
] |
[
"Correct"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"discarded"
] |
[
"Correct"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"discarded"
] |
[
null
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"discarded"
] |
[] | null | null |
2da16f62-d2e2-4483-b311-acd423609b9f
|
pending
| 2025-04-29T14:36:04.698000 | 2025-04-29T14:36:04.698000 |
57bcdf13-88c5-4d26-a5da-653e6920aa5c
|
Frontiers in Human Neuroscience, 7
|
None
|
[
[]
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"discarded"
] |
[
null
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"discarded"
] |
[
null
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"discarded"
] |
[
null
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"discarded"
] |
[] | null | null |
c69ef07b-9748-4524-9be2-851c8b7a8608
|
completed
| 2025-04-29T14:36:04.699000 | 2025-05-27T14:00:38.508000 |
a9475f17-52a4-4d49-b0eb-fa0c3aa20c40
|
Sixteen healthy, right-handed subjects (9 females) aged 23.6 years (±2.4) participated in Experiment 2. For the participants in the second experiment, the same inclusion criteria as in Experiment 1 were applied (see above).The participants in both experiments did not differ in their age [t (34) = -0.72,p = 0.479] or intellectual abilities [t (34) = 0.42, p = 0.677] as assessed by the KAI (Kurztest für allgemeine Basisgrössen der Infomationsverarbeitung; Lehrl et al., 1992).
|
<li> <b>9 females:</b> female (biologicalSex)
|
[
[
{
"end": 49,
"label": "biologicalSex",
"start": 42
}
]
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"Partially correct"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
null
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
{
"end": 49,
"label": "biologicalSex",
"start": 40
}
] | null | null |
f6ba35e4-edcf-410e-82f8-8b9148aa24cf
|
completed
| 2025-04-29T14:36:04.699000 | 2025-05-27T14:00:38.591000 |
90966938-8e71-4a42-81d6-ac2c07b0e137
|
Abstract Background Intermittent theta burst stimulation (iTBS) is a form of repetitive transcranial magnetic stimulation (TMS) that can increase corticomotor excitability of hand muscles in individuals with spinal cord injury (SCI). The objective of this study was to determine the effect of iTBS on the corticomotor excitability of the biceps brachii in individuals with tetraplegia. Methods Ten individuals with low cervical SCI (C5-C8) and ten nonimpaired individuals completed three independent sessions. Motor evoked potentials (MEPs) served as our measure of corticomotor excitability and were collected before and after iTBS. MEPs were normalized by the electromyography corresponding to maximum voluntary contraction and analyzed using linear mixed effects models to determine the effect of iTBS (active or sham) on normalized MEPs (nMEPs). iTBS effects were compared to a ratio of active and resting motor thresholds as a measurement of corticomotor conductance potential. Results Relative to sham, active iTBS increased nMEPs over time (p < 0.001) in individuals with SCI, but not nonimpaired individuals (p = 0.915). The amplitude of nMEPs were correlated with the biceps corticomotor conductance potential (p < 0.001), with nMEPs decreasing as the ratio increased at different rates after sham or active iTBS. Conclusions Preliminary results suggest that iTBS increases biceps corticomotor excitability in individuals with tetraplegia with effects that may be predicted by corticomotor conductance potential. Clinical trial registration NCT03277521 Registered on clinicaltrials.gov on August 24, 2017
|
<li> <b>electromyography:</b> electromyography (technique)<li> <b>Intermittent theta burst stimulation:</b> Other (technique)<li> <b>repetitive transcranial magnetic stimulation:</b> Other (technique)<li> <b>TMS:</b> Other (technique)<li> <b>Motor evoked potentials:</b> Other (technique)<li> <b>MEPs:</b> Other (technique)
|
[
[
{
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"label": "technique",
"start": 663
},
{
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"label": "technique",
"start": 20
},
{
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"label": "technique",
"start": 77
},
{
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"label": "technique",
"start": 123
},
{
"end": 534,
"label": "technique",
"start": 511
},
{
"end": 219,
"label": "UBERONParcellation",
"start": 208
}
]
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"spinal cord: Other (UBERONParcellation)\n\r\n"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
{
"end": 679,
"label": "technique",
"start": 663
},
{
"end": 56,
"label": "technique",
"start": 20
},
{
"end": 121,
"label": "technique",
"start": 77
},
{
"end": 126,
"label": "technique",
"start": 123
},
{
"end": 534,
"label": "technique",
"start": 511
},
{
"end": 540,
"label": "technique",
"start": 536
},
{
"end": 639,
"label": "technique",
"start": 635
},
{
"end": 841,
"label": "technique",
"start": 837
}
] | null | null |
47866826-1b10-4cbd-9199-4ff6c86d5381
|
completed
| 2025-04-29T14:36:04.699000 | 2025-05-27T14:00:38.700000 |
784c6d83-c86e-4ae4-b390-90546a0e1d78
|
In the SCI group, there was a significant interaction between the biceps AMT/RMT ratio (i.e., corticomotor conductance potential) and stimulation type.While both sham and active iTBS showed a negative relationship with corticomotor conductance potential, nMEPs Fig. 3 Time differentiated normalized motor evoked potential amplitudes (nMEP).A) Mean of recorded nMEP amplitudes for each time point across all 30 sessions for active and sham iTBS are presented for participants with SCI.Error bars represent one standard deviation from the mean.B) In the SCI group, the linear mixed effects model (LMEM) shows a significant difference over time in nMEP amplitudes depending on the type of iTBS, active or sham.C) In the nonimpaired group, the LMEM does not show an effect of stimulation type on nMEP amplitude.D) There was a difference in the effect of iTBS between groups, based on the LMEM, consistent with the excitation seen in the SCI group and not seen in the nonimpaired group.Each point represents all nMEPs across all sessions, for the given group and stimulation type associated with sham stimulation had lower nMEP amplitudes.Sham associated nMEPs also changed at a lower rate as the corticomotor conductance potential increased (p < 0.001, χ 2 = 15.2).Consequently, as the corticomotor conductance potential approached zero, nMEP amplitudes were greater indicating a higher degree of excitation relative to sham (Additional file 1: Fig. S1A).There was an interaction between the corticomotor conductance potential and group (p < 0.001, χ 2 = 13.3)suggesting that while this parameter has predictive potential across both groups, the exact correlation is group specific (Additional file 1: Fig. S1B).There was no difference in corticomotor conductance potential between groups (p = 0.89) (Table 2).
|
<li> <b>iTBS:</b> Other (technique)
|
[
[]
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"Incorrect"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"Incorrect"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
null
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
{
"end": 182,
"label": "technique",
"start": 178
},
{
"end": 443,
"label": "technique",
"start": 439
},
{
"end": 690,
"label": "technique",
"start": 686
},
{
"end": 854,
"label": "technique",
"start": 850
}
] | null | null |
e22bbbac-580b-4e4f-8065-696d5138fe8d
|
pending
| 2025-04-29T14:36:04.699000 | 2025-04-29T14:36:04.699000 |
0c614a10-2215-43b1-abed-5a12892b1bf5
|
Vitamin D is a lipid soluble steroid hormone, which plays a critical role in the calcium homeostasis, neuronal development, cellular differentiation, and growth by binding to vitamin D receptor (VDR). Associations between VDR gene polymorphism and Alzheimer’s disease (AD), Parkinson’s disease (PD), and mild cognitive impairment (MCI) risk has been investigated extensively, but the results remain ambiguous. The aim of this study was to comprehensively assess the correlations between four VDR polymorphisms (FokI, BsmI, TaqI, and ApaI) and susceptibility to AD, PD, and MCI. Crude odds ratios (ORs) and 95% confidence intervals (CIs) were calculated to determine the relationship of interest. Pooled analyses suggested that the ApaI polymorphism decreased the overall AD risk, and the TaqI increased the overall PD susceptibility. In addition, the BsmI and ApaI polymorphisms were significantly correlated with the overall MCI risk. Stratified analysis by ethnicity further showed that the TaqI and ApaI genotypes reduced the AD predisposition among Caucasians, while the TaqI polymorphism enhanced the PD risk among Asians. Intriguingly, carriers with the BB genotype significantly decreased the MCI risk in Asian descents, and the ApaI variant elevated the predisposition to MCI in Caucasians and Asians. Further studies are need to identify the role of VDR polymorphisms in AD, PD, and MCI susceptibility.
|
None
|
[
[]
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"discarded"
] |
[
null
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"discarded"
] |
[
null
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"discarded"
] |
[
null
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"discarded"
] |
[] | null | null |
993e39e9-864a-4c79-8dee-a4e94c68ec45
|
pending
| 2025-04-29T14:36:04.699000 | 2025-04-29T14:36:04.699000 |
7ed0e5aa-8a73-4fa2-b179-2e839e27346d
|
Two experienced authors (YD and PG) independently conducted literature screening, data extraction, literature quality evaluation, and any disagreements could be resolved through discussion or a third analyst (XS).The detailed information extracted from all the selected studies included: first author's surname, publication year, country, type of disease, ethnicity, source of controls, genotyping methods, sample size, and P-value of HWE. The Newcastle-Ottawa Scale (NOS) was used to evaluate the process in terms of queue selection, comparability of queues, and evaluation of results (Stang, 2010).A study with a score of at least six was considered as a high-quality literature.Higher NOS scores showed higher literature quality.
|
None
|
[
[]
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"discarded"
] |
[
"Correct"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"discarded"
] |
[
"Correct"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"discarded"
] |
[
null
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"discarded"
] |
[] | null | null |
193ef40b-8a8a-4e86-bc08-49b1173d26eb
|
completed
| 2025-04-29T14:36:04.699000 | 2025-05-27T14:00:38.814000 |
cd00c030-40ab-4895-abad-f78144347bef
|
Individuals from East Asian (Chinese) backgrounds have been shown to exhibit greater sensitivity to a speaker's perspective than Western (U.S.) participants when resolving referentially ambiguous expressions. We show that this cultural difference does not reflect better integration of social information during language processing, but rather is the result of differential correction: in the earliest moments of referential processing, Chinese participants showed equivalent egocentric interference to Westerners, but managed to suppress the interference earlier and more effectively. A time-series analysis of visual-world eye-tracking data found that the two cultural groups diverged extremely late in processing, between 600 and 1400 ms after the onset of egocentric interference. We suggest that the early moments of referential processing reflect the operation of a universal stratum of processing that provides rapid ambiguity resolution at the cost of accuracy and flexibility. Late components, in contrast, reflect the mapping of outputs from referential processes to decision-making and action planning systems, allowing for a flexibility in responding that is molded by culturally specific demands.
|
<li> <b>visual-world eye-tracking:</b> eyeMovementTracking (technique)
|
[
[
{
"end": 637,
"label": "technique",
"start": 625
}
]
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"Partially correct"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
null
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
{
"end": 637,
"label": "technique",
"start": 612
}
] | null | null |
ae9c1987-a61c-4bf3-b3c4-56b7e1a99b79
|
completed
| 2025-04-29T14:36:04.699000 | 2025-05-27T14:00:38.983000 |
f5dcdc97-ac42-424c-afa5-ac85ca00a028
|
Overall, our findings support the hypothesis that language users from different cultures share a common stratum of referential processing, with cultural variation in how the products of these early referential processes are used in the higher-level processes governing thought and action.Specifically, whereas neither Chinese nor Western participants were able to integrate the situational cue of the speaker's perspective into lexical processing, Chinese participants were better able to suppress the interference. Could our findings of common interference and differential correction be alternatively explained in terms of linguistic differences between Mandarin Chinese and English?One potentially 2 Although an onset of 750 ms is quite late relative to typical visual-world studies (250-350 ms), this is not surprising given that our paradigm presented participants with a more demanding search task than in a typical study.Whereas a typical grid in Wu and Keysar (2007) contained nine alternatives appearing in any of 16 possible locations, a typical visual-world task presents no more than four referential alternatives in fixed locations (Huettig et al., 2011).relevant difference is that Mandarin lacks definite marking, such that the Mandarin version of the English expression "move the candle" might be glossed in English as "move candle."It might be argued that the Chinese participants were interpreting the descriptions as if the speaker had said, "move any candle."This would indeed predict that the Chinese participants would experience less interference than the U.S. participants because they would not need to decide between the two possible referents, but could pick either one.However, if this were the case, then Chinese participants should have shown a stronger tendency than U.S. participants to move the hidden candle, since any candle would suffice.However, the data showed the exact opposite.While the U.S. participants sometimes moved the occluded candle, the Chinese participants never did. One possible concern might be that the later correction for Chinese participants reflects shorter referring expressions in Chinese, or more rapid speech when the confederate spoke Chinese.Although we lack the data to directly address this question, the overall patterns shown in Figure 2 make this explanation seem unlikely.First, if the earlier correction occurred because the Chinese expressions were briefer or spoken more rapidly, then not only would the correction process take place earlier, but so would the egocentric interference; specifically, the initial rising slope of the curve should have been much steeper for the Chinese group than for the Western group, and should have reached its peak much earlier.However, egocentric interference seems to rise at similar rates for both groups, and both seem to initially reach their maximum values at roughly the same time (1000-1200 ms).Second, whereas the correction process seems to begin at around 1000 ms for the Chinese group, it seems delayed until about 2200 ms for the American group.This is far too great of a disparity to be explained by differences in the spoken expressions, given that expressions in these types of experiments typically last no more than 1 s.Finally, the groups differ not only in the timing of the correction, but also in the efficacy of the correction, with a sudden sharp decline for the Chinese group, and more of a lingering pattern for the Western group.Thus, these patterns seem less likely to be driven by differences in the stimuli, and more likely to reflect true cultural differences in linguistic interpretation. Constraint-based views would have difficulty accounting for the extreme delay in the emergence of cultural differences relative to the onset of egocentric interference.If, as constraint-based views predict, language users can integrate perspective information from the earliest moments of processing, and Chinese participants attend more strongly to the shared perspective than Westerners, then Chinese participants should have shown less egocentric interference from the very earliest moments of processing.Our view, then, is that despite attending more strongly to shared information, Chinese participants are no better at integrating it into referential processing.However, an alternative view must be considered, which is that perhaps the late emergence does not reflect a standalone correction process, but simply reflects delayed activation of shared information relative to other kinds of information.Under this view, had the shared knowledge become activated earlier, perhaps we would have seen its effects earlier in processing.However, it is unclear what would account for the delayed activation of shared knowledge within the current paradigm.For one, in the current experimental situation, listeners knew well before hearing the referring expression which items their partner could see and which they could not see.In other words, information about what was shared was available to participants even before any referential information became available.It is therefore not clear why listeners would wait for a referring expression to activate the shared knowledge, rather than using it to predict potential referents in advance.It is not possible to tell whether listeners in fact made such predictions, because this requires comparing shared to privileged objects, and our analysis only considered privileged objects.However, experiments using a similar setup have found that in the interval preceding the onset of the referring expression, listeners are more likely to look at shared objects (Keysar et al., 2000).Furthermore, recent experiments including conditions where competitors/noncompetitors are shared show that listeners spontaneously access shared knowledge prior to the onset of referring expressions, but are unable to integrate this information into early referential processes (Barr, 2008).Specifically, listeners attend less overall to privileged objects than to shared objects, but nonetheless experience similar levels of interference from competitors regardless of whether they are shared or not.It would be of interest to repeat these experiments with East Asian participants.Our account predicts greater access to shared knowledge among East Asians, but without any reduction in the size of the interference produced by competitors. Our view that information about perspective is involved in correction is consistent with an anchoring and adjustment view of perspective taking (Keysar et al., 2000), in which listeners anchor interpretation in their own perspectives, and use information about the speaker's perspective to incrementally adjust away from the anchor.However, distinct from Keysar et al.'s (2000) original formulation, our findings, together with those of Barr (2008), suggest that listeners do not strategically "anchor" in their own egocentric perspective as a kind of reasoning heuristic; rather, their anchoring is forced upon them by the autonomous activation of referents by low-level interpretation processes that are blind to information about the speaker's perspective (Barr, 2008).Under this view, the noted egocentrism of listeners might be best characterized as a form of "mental contamination" -i.e., the result of rapid, automatic processes that are beyond control and possibly even awareness (Wilson and Brekke, 1994). Consistent with the use of common ground in correction, other research shows that perspective taking involves cognitive effort (Rossnagel, 2000;Brown-Schmidt, 2009;Nilsen and Graham, 2009;Lin et al., 2010), and recent neuroimaging evidence suggests a role for the medial pre-frontal cortex in the adjustment process (Tamir and Mitchell, 2010).Furthermore, the correction account is also consistent with dual process views of perspective taking, which assume that social judgments reflect the combination of both efficient but inflexible processing that uses limited information and more flexible but effortful processing that can draw upon a broader set of information (Apperly and Butterfill, 2009).However, the current data offer no insight into why the adjustment process might differ across the groups.One possibility, consistent with the collectivist vs. individualist distinction, is that information about a speaker's perspective is simply more available to people from a collectivist background, since their cultures require greater attunement to one anothers' knowledge.Another is that perhaps Chinese participants are more motivated to perform the task "correctly" due to heightened concerns about self-presentation.A further possibility is that membership in a Chinese culture, where self-control is valued, results in better executive control abilities.This explanation is supported by research that finds enhanced executive control abilities among Chinese as opposed to North American children (Sabbagh et al., 2006), who nonetheless showed comparable performance on a belief reasoning task.As we have argued here and elsewhere (Keysar et al., 2003;Barr, 2008) listeners' difficulty in identifying the intended referent in conversational perspective-taking tasks is unlikely to be the result of a failure to have the appropriate beliefs about what is shared with the speaker.Instead, it seems to reflect difficulty using this information to constrain the processing of the linguistic input.To the extent that early referential processes are not guided by beliefs about the speaker, these processes will boost activation of referents that are pragmatically implausible, even in spite of correct and accessible representations of shared knowledge.Because suppressing this knowledge will involve executive control, it is here where we would expect to see strong individual (and cultural) differences.Although in this respect our view is consistent with Sabbagh et al.'s (2006) developmental findings, it is important to note that it is not yet known whether the differences in executive function that Sabbagh et al. (2006) noted extend into adulthood. Whatever the explanation for the cultural differences, a recent study suggests that it might be possible to induce cultural effects through priming.Luk et al. (2012) replicated Wu and Keysar's (2007) study but with Chinese-Westerner bi-cultural individuals.Participants primed by images from Western culture committed more egocentric errors on the perspective-taking task relative to participants who were primed by images from Chinese culture. The fact that cultural differences can be situationally induced in bicultural individuals suggests that they arise from flexible modes of processing.This flexibility is consistent with our explanation of such differences in terms of differential correction -it would seem easier to override a deliberative and effortful correction process than an integration process that is largely routinized and automatic. In sum, our data suggest that people from different cultures share a common core of ambiguity resolution processes, but differ in how the output from these processes is linked to higher-level systems governing thought and action.The two cultures we have studied show systematic differences in how they prioritize the individual vs. the social (Triandis et al., 1988;Markus and Kitayama, 1991;Ross et al., 2002).Finding equivalent interference from privileged information in spite of such differences suggests that such egocentrism might be a universal consequence of rapid ambiguity resolution during spoken language comprehension.
|
<li> <b>medial pre-frontal cortex:</b> prefrontalCortex (UBERONParcellation)
|
[
[
{
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}
]
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
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[
"submitted"
] |
[
"Partially correct"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"Partially correct"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"pre-frontal cortex: prefrontalCortex (UBERONParcellation)\n"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
{
"end": 7701,
"label": "UBERONParcellation",
"start": 7676
}
] | null | null |
bc1fb690-2b46-446f-95b4-8ba3711b43c2
|
completed
| 2025-04-29T14:36:04.699000 | 2025-05-27T14:00:39.100000 |
803e1def-5d2a-4131-8ed2-60fca7b12e0d
|
AbstractGut microbiome profoundly affects many aspects of host physiology and behaviors. Here we report that gut microbiome modulates aggressive behaviors in Drosophila. We found that germ-free males showed substantial decrease in inter-male aggression, which could be rescued by microbial re-colonization. These germ-free males are not as competitive as wild-type males for mating with females, although they displayed regular levels of locomotor and courtship behaviors. We further found that Drosophila microbiome interacted with diet during a critical developmental period for the proper expression of octopamine and manifestation of aggression in adult males. These findings provide insights into how gut microbiome modulates specific host behaviors through interaction with diet during development.
|
<li> <b>Drosophila:</b> Other (species)
|
[
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[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"male: male (biologicalSex)\nfemale: female (biologicalSex)\n"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
{
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},
{
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"label": "species",
"start": 495
}
] | null | null |
ff34a9f6-6e63-438e-b4aa-1905411cc2fc
|
completed
| 2025-04-29T14:36:04.699000 | 2025-05-27T14:00:39.208000 |
7c65fe99-40d6-442d-b87c-f9e9086ef32a
|
Accumulating evidence indicates that the microbiome affects a broad spectrum of animal physiology and behaviors 1,48,49 .It remains unclear whether/how Drosophila microbiome is required to modulate innate and social behaviors, including locomotion, courtship, and aggression despite of much advanced genetic tools in this animal model 20 .In this study, we demonstrated that microbiome specifically modulates aggressive behaviors in both males and females.Aggression in Drosophila has long been considered to play a critical role in mate selection 50 .Indeed, our findings indicate that GF males are less competitive in copulation with females compared with control CR males, indicating that microbiome depletion impairs optimal sexual fitness of adult males.Recolonization of MB, or specific commensal bacteria species including Acetobacter, Lactobacilli, and Enterococci, equally restored aggressive behaviors in GF males, suggesting that there are common genetic determinants in these bacteria species that promote adult aggression.Identifying these genetic determinants would help to understand in molecular details how microbiome modulates host behavior and enhances sexual fitness.We identified the OA signaling responsible for the microbiome-mediated promotion of aggression.We found that microbiome-depletion resulted in a lower level of Tdc2 expression in both GF male and female brains with qPCR.We further showed that there was a 73% reduction of OA level in GF male brains using the HPLC assay.Our finding that fly microbiome promotes OA production is generally consistent with previous findings in mammals that indigenous bacteria potentially impact behaviors by boosting biosynthesis of biogenic amines (e.g., serotonin) 51 .A previous study reported that pathogenic Wolbachia impairs male aggressive behavior by downregulation of the OA biosynthesis pathway, suggesting that pathogenic and commensal bacteria function oppositely in regulating host OA production and aggressive behaviors 31 . Although depletion of microbiome decreased OA signaling and substantially impaired aggression in both male and female flies, it did not significantly affect other behaviors.Our results are generally consistent with a previous finding that locomotor behaviors, sleep, and courtship behaviors in GF males are not virtually affected by the microbiome 11 .In contrast, Schretter et al. recently reported that depletion of microbiome increased OA signaling and induced hyperactivity in Drosophila females 10 .We suspected that such discrepancy might be due to different axenic culture conditions.However, we still did not find any significant difference in locomotion among CR, GF, and MB flies following their protocol for generating GF flies 10 .As we measured average walking speeds for 24 h, instead of 10 min as used by the previous study, we reanalyzed walking speeds every 10 min for 24 h, and observed locomotion differences in a few time points, but these differences were not consistently higher or lower in GF flies (thus not exist in a longer time scale), which may be due to large variation of locomotion during morning and evening peaks for circadian regulation 38 .Indeed, we note that Schretter et al. tested walking speed of flies between ZT0 and ZT3 (lights are turned on at ZT0 and turned off at ZT12); however, locomotor behaviors vary a lot during this period after morning peak (it peaks at ZT0, and deceases by ~80% at ZT3 [from ~200 to ~30 mm/min], see Fig. 2a, e and Supplementary Fig. 8c,f), which may contribute to their observed locomotor differences.For such reason, we suggest future test of locomotor behaviors in a shorter time window (e.g., 30 min test between ZT1 and ZT2 with control and experimental flies tested simultaneously), or for a longer time (e.g., average walking speed for 3 h or even 24 h as used in this study).Another possible factor that may result in the discrepancy is that we used wild-type Canton-S (wtcs) flies, instead of Oregon-R flies as mainly used by Schretter et al., as wtcs were widely used for most behavioral tests and Oregon-R flies rarely displayed aggressive behaviors in our tests, although they have comparable locomotor activity with Canton-S flies.Regarding to why microbiome only affects aggression but not locomotor or other behaviors, there are at least two possibilities.One is that the OA level is not significantly reduced in specific neurons that may be responsible for a particular behavior.Alternatively, OA reduction in certain neurons is not sufficient to induce a behavioral change, e.g., even tβh or tdc2 mutant flies showed comparable locomotor levels 32,52 although they are defect in starvation-induced hyperactivity 52 . A prominent feature of the role of microbiome on development and behavior is its dependence on diet.Firstly, GF flies have prolonged developmental process if raised with low level of yeast (0.5%), but develop normally with higher level of yeast (2.5 or 10%), consistent with previous studies 5,36,53 .Secondly, GF males showed reduced aggression only if raised with higher level of yeast (2.5 or 10%), as CR, GF, and MB males raised with low level of yeast (0.5%) all showed few and indistinguishable aggression.Furthermore, while CR males have much higher expression of Tdc2 if raised with high level of yeast, GF males have similarly low level of Tdc2 expression.Interestingly, supplement of rich yeast is only required during a critical developmental period, roughly 48-96 h AEL, for microbiome-mediated promotion of OA production and aggression.Thus, gut microbiome and a proper level of yeast consumption during a critical developmental period jointly promote OA production and aggressive behaviors in flies.Previous studies already showed that nutritional environment is a key factor involved in the microbiome-mediated development, metabolism, immunity, and behaviors 5,7,29,36,53,54 .Our results are generally consistent with these findings and further reveal that gut microbiome and diet interact to modulate neurotransmitter signaling and aggressive behaviors.It has been increasingly accepted that gut microbiome relies on diet to generate neuromodulators, provides missing nutrients to hosts, and modifies the availability of specific nutrients derived from the diet, consequently shaping the nutritional environment of hosts 55 .There are at least two underlying mechanisms by which the microbiome changes host physiology and behaviors by absorbing specific nutrients from the diet or de novo synthesizing special nutrients including neuroactive metabolites, amino acids, and short chain fatty acids 56,57 .It is plausible that microbiome may affect absorption/biosynthesis of the precursor of OA (Tyrosine), in addition to expression change of Tdc2, or leading to Tdc2 expression change as a result of adaptation.Future studies on microbiome-induced alterations in the metabolome of Drosophila nervous system would improve the knowledge of microbe-nutrition-aggression interactions. The finding that gut microbiome modulates aggressive behaviors raises a few questions.First, since recolonization of a few commensal bacteria fully restored aggression in GF males, identification of specific bacterial genes involved in OA production, and how they may interact with nutrition environment, are needed to further understand how gut bacteria modulate aggression.Second, it is unclear if there are commensal bacteria that could oppositely modulate aggression.Future studies identifying commensal bacteria that positively or negatively modulate aggression would deepen our understanding and have potential implications utilizing commensal bacteria to modulate aggressive behaviors.Recently, it was reported that the microbiome correlated with conspecific aggression in a small population of dogs 58 , highlighting that the microbiome may be useful for diagnosing aggressive behaviors prior to their manifestation and potentially discerning cryptic etiologies of aggression.Third, that microbiome synergizes with diet to promote aggressive but not other innate behaviors in our study is intriguing, especially given that Drosophila in the wild may be challenged with scare, dynamic, and highly diverse diets.Our results suggest that males fed on rich nutrition during development, with many commensal bacteria in their guts, have an advantage of reproduction.This association of microbiome and aggression thus is beneficial and selected, favoring the hologenome theory of evolution 59 .Our study using Drosophila thus provides a feasible model for elucidating the mechanism of how microbiome and diet interact to modulate biosynthesis of signaling molecules and host behaviors.
|
<li> <b>Drosophila:</b> Other (species)<li> <b>HPLC:</b> Other (technique)
|
[
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] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
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[
"submitted"
] |
[
"Correct"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"males: male (biologicalSex)\nfemales: female (biologicalSex)\nbrain: Other (UBERONParcellation)\nqPCR: Other (technique)\nneurons: Other (UBERONParcellation)\ndogs: Other (species)\n"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
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[
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{
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] | null | null |
f361578a-c102-4e6e-b40f-ee80d43a9838
|
pending
| 2025-04-29T14:36:04.699000 | 2025-04-29T14:36:04.699000 |
ae0842c8-bfc9-4e19-a851-4f5ac17f35c5
|
Frontiers in Neuroscience, 9
|
None
|
[
[]
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"discarded"
] |
[
"Correct"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"discarded"
] |
[
"Correct"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"discarded"
] |
[
null
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"discarded"
] |
[] | null | null |
cb3125d1-776c-408e-85af-f084b26e0e51
|
completed
| 2025-04-29T14:36:04.699000 | 2025-05-27T14:00:39.340000 |
6f06ec9f-6048-4522-b4c9-c79f9d6f0de0
|
The neuron circuit integrated in this chip is derived from the adaptive exponential I&F circuit proposed in Indiveri et al. (2011), which can exhibit a wide range of neural behaviors, such as spike-frequency adaptation properties, refractory period mechanism and adjustable spiking threshold mechanism.The circuit schematic is shown in Figure 3.It comprises an NMDA block (M N1,N2 ), which implements the NMDA voltage gating function, a LEAK DPI circuit (M L1-L7 ) which models the neuron's leak conductance, an AHP DPI circuit (M A1-A7 ) in negative feedback mode, which implements a spike-frequency adaptation behavior, an Na + positive feedback block (M Na1-Na5 ) which models the effect of Sodium activation and inactivation channels for producing the spike, and a K + block (M K1-K7 ) which models the effect of the Potassium conductance, resetting the neuron and implementing a refractory period mechanism.The negative feedback mechanism of the AHP block, and the tunable reset potential of the K + block introduce two extra variables in the dynamic equation of the neuron that can endow it with a wide variety of dynamical behaviors (Izhikevich, 2003).As the neuron circuit equations are essentially the same of the adaptive I&F neuron model, we refer to the work of Brette and Gerstner (2005) for an extensive analysis of the repertoire of behaviors that this neuron model can reproduce, in comparison to, e.g., the Izhikevich neuron model. All voltage bias variables in Figure 3 ending with an exclamation mark represent global tunable parameters which can be precisely set by the on chip Bias Generator (BG).There are a total of 13 tunable parameters, which provide the user with high flexibility for configuring all neurons to produce different sets of behaviors.In addition, by setting the appropriate bits of the relative latches in each neuron, it is possible to configure two different leak time constants ( if_tau1! / if_tau2!) and refractory period settings ( if_rfr1! / if_rfr2!).This gives the user the opportunity to model up to four different types/populations of neurons within the same chip, that have different leak conductances and/or refractory periods. An example of the possible behaviors that can be expressed by the silicon neuron are shown in Figure 4.The top-left quadrant shows measured data from the chip representing the neuron membrane potential in response to a constant current injection for different values of reset voltage.The top-right quadrant shows the neuron response to a constant current injection for different settings of its refractory period.The bottom-left quadrant demonstrates the spike-frequency adaptation behavior, obtained by appropriately tuning the relevant parameters in the AHP block of Figure 3 and stimulating the neuron with a constant injection current.By further increasing the gain of the AHP negative feedback block the neuron can produce bursting behavior (see bottom-right quadrant of Figure 4). Figure 5 shows the F-I curve of all neurons in the ROLLS neuromorphic processor (i.e., their firing rate as a function of the input injection current).The plot shows their average firing rate in solid line, and their standard deviation in the shaded area.The overall mismatch in the circuit, responsible for these deviations, is extremely small, if compared to other analog VLSI implementations of neural systems (Indiveri et al., 2006;Petrovici et al., 2014;Schmuker et al., 2014).The average value obtained from the measurement results of Figure 5 is only 9.4%.The reason for this improvement lies in the increased size of some critical transistors in the soma circuit-major contributor to neuron's mismatch.For example, the M L4 and M L5 Field-Effect Transistors (FETs) that set the neuron's leak time constants are of (W/L) size of (2 µm/4 µm) , while M Na3 and M Na4 , responsible for the firing threshold are of size (4 µm/0.4 µm) and (1 µm/4 µm), respectively. In addition to the neuron soma circuit, this block contains also post-synaptic plasticity circuits that are necessary for evaluating the weight update and "stop-learning" conditions described in Section 2.1.2.In particular these circuits integrate the spikes produced by the neuron into a current that models the neuron's Calcium concentration, and compare this current to three threshold currents that correspond to θ 1 , θ 2 , and θ 3 of Equation (1).In parallel, the neuron's membrane current (which is equivalent to the membrane potential in the theoretical model) is compared to an additional threshold equivalent to θ mem of Equation ( 1).The schematic diagram of this circuit is shown in Figure 6.The post-synaptic neuron's Calcium concentration is computed using the DPI M D1-D5 ; the comparisons with the fixed thresholds are made using three current-mode Winner-Take-All (WTA) circuits M W1-W9 , M WU1-WU12 , and M WD1-WD12 .The digital outcomes of these comparisons set the signals slnup and sldn which are then buffered and transmitted in parallel to all synapses afferent to this neuron belonging to the long-term plasticity array.
|
<li> <b>NMDA:</b> Other (technique)
|
[
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{
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{
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}
]
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"Incorrect"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"Incorrect"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"neuron: Other (UBERONParcellation)"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
{
"end": 365,
"label": "technique",
"start": 361
},
{
"end": 409,
"label": "technique",
"start": 405
}
] | null | null |
43fa0ede-4761-4fb6-8204-8742c8cbbd7e
|
completed
| 2025-04-29T14:36:04.699000 | 2025-05-27T14:00:39.450000 |
4f10da84-5894-4f7a-99ca-340699ff0148
|
The surface Electromyography (sEMG) signal contains information about movement intention generated by the human brain, and it is the most intuitive and common solution to control robots, orthotics, prosthetics and rehabilitation equipment. In recent years, gesture decoding based on sEMG signals has received a lot of research attention. In this paper, the effects of muscle fatigue, forearm angle and acquisition time on the accuracy of gesture decoding were researched. Taking 11 static gestures as samples, four specific muscles (i.e., superficial flexor digitorum (SFD), flexor carpi ulnaris (FCU), extensor carpi radialis longus (ECRL) and finger extensor (FE)) were selected to sample sEMG signals. Root Mean Square (RMS), Waveform Length (WL), Zero Crossing (ZC) and Slope Sign Change (SSC) were chosen as signal eigenvalues; Linear Discriminant Analysis (LDA) and Probabilistic Neural Network (PNN) were used to construct classification models, and finally, the decoding accuracies of the classification models were obtained under different influencing elements. The experimental results showed that the decoding accuracy of the classification model decreased by an average of 7%, 10%, and 13% considering muscle fatigue, forearm angle and acquisition time, respectively. Furthermore, the acquisition time had the biggest impact on decoding accuracy, with a maximum reduction of nearly 20%.
|
<li> <b>Electromyography:</b> electromyography (technique)<li> <b>sEMG:</b> electromyography (technique)
|
[
[
{
"end": 28,
"label": "technique",
"start": 4
},
{
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"label": "technique",
"start": 30
},
{
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"label": "technique",
"start": 283
},
{
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"start": 691
}
]
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"Partially correct"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
null
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
{
"end": 28,
"label": "technique",
"start": 12
},
{
"end": 34,
"label": "technique",
"start": 30
},
{
"end": 287,
"label": "technique",
"start": 283
},
{
"end": 695,
"label": "technique",
"start": 691
}
] | null | null |
918b7f12-b7b3-4c29-82e8-49cb1c9604ed
|
completed
| 2025-04-29T14:36:04.699000 | 2025-05-27T14:00:39.533000 |
56078401-c655-4f2a-acbb-d48be2c8545a
|
The elbows of all subjects were placed on the table when they performed gesture movements, so the forearm angle referred to the angle between the forearm and the tabletop.In order to comprehensively analyze the negative impact of the angle on the sEMG signal from small angle difference and large angle difference, the forearm angle range and the quality of sEMG signal typically utilized in actual gesture decoding were also considered.In this paper, three forearm angles were selected, namely, 30°, 45° and 75° (Figure 3).During the experiment, the upper and lower angle deviation did not exceed ± 5°.
|
<li> <b>sEMG:</b> electromyography (technique)
|
[
[
{
"end": 251,
"label": "technique",
"start": 247
},
{
"end": 362,
"label": "technique",
"start": 358
}
]
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"Partially correct"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
null
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
{
"end": 251,
"label": "technique",
"start": 247
},
{
"end": 362,
"label": "technique",
"start": 358
}
] | null | null |
c8b5499c-3dfc-4c6a-8a88-91545bb0325b
|
completed
| 2025-04-29T14:36:04.699000 | 2025-05-27T14:00:39.617000 |
c9debe8c-ad35-4ab8-b65d-4b9a276961db
|
In general, magnetic resonance (MR) diffusion-weighted imaging (DWI) has shown potential in clinical settings. In testicles parenchyma, the DW imaging helps differentiate and characterize benign from malignant lesions. Placement and size of the region of interest (ROI) may affect the ADC value. Therefore, the aim of this study was to investigate the intra- and interobserver variability in testicular tumors when measuring ADC using various types of regions of interest (ROI). Two observers performed the ADC measurements in testicular lesions based on three ROI methods: (1) whole volume, (2) round, and (3) small sample groups. Intra- and interobserver variability was analyzed for all ROI methods using intraclass correlation coefficients (ICC) and bland-altman plots. The two observers performed the measurements twice, three months apart. A total of 26 malignant testicle tumors were included. Interobserver agreement was excellent in tumor length (ICC = 0.98) and tumor width (ICC = 0.98). In addition, intraobserver agreement was excellent in tumor length (ICC = 0.98) and tumor width (ICC = 0.99). The whole volume interobserver agreement in the first reading was excellent (ICC = 0.93). Round ADC had an excellent (ICC = 0.93) and fair (ICC = 0.58) interobserver agreement, in the first and second reading, respectively. Interobserver agreement in ADC small ROIs was good (ICC = 0.87), and good (ICC = 0.78), in the first and second reading, respectively. Intraobserver agreement varied from fair, good to excellent agreement. The ROI method showed varying inter- and intraobserver agreement in ADC measurement. Using multiple small ROI conceded the highest interobserver variability, and, thus, the whole volume or round seem to be the preferable methods.
|
<li> <b>magnetic resonance:</b> magneticResonanceImaging (technique)<li> <b>MR:</b> magneticResonanceImaging (technique)<li> <b>diffusion-weighted imaging:</b> diffusionWeightedImaging (technique)<li> <b>DWI:</b> diffusionWeightedImaging (technique)
|
[
[
{
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"label": "technique",
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},
{
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"label": "technique",
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},
{
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},
{
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"label": "technique",
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},
{
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"label": "technique",
"start": 140
}
]
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"DW imaging: diffusionWeightedImaging (technique)\n\r\n"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
{
"end": 30,
"label": "technique",
"start": 12
},
{
"end": 34,
"label": "technique",
"start": 32
},
{
"end": 62,
"label": "technique",
"start": 36
},
{
"end": 67,
"label": "technique",
"start": 64
}
] | null | null |
66bb23be-c199-4aac-966d-6a34c8d16fb0
|
pending
| 2025-04-29T14:36:04.699000 | 2025-04-29T14:36:04.699000 |
6b090e19-0f8a-4207-b6ce-fbd7c99502bd
|
The interobserver agreement in tumor length was excellent in the first reading ICC = 0.98 (95% CI 0.93-0.99)and second reading ICC = 0.98 (95% CI 0.94-0.99).Tumor width interobserver agreement was excellent in the first and second reading with ICC = 0.98 (95% CI 0.92-0.99)and ICC = 0.98 (95% CI 0.95-0.99),respectively.
|
None
|
[
[]
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"discarded"
] |
[
"Correct"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"discarded"
] |
[
"Correct"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"discarded"
] |
[
null
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"discarded"
] |
[] | null | null |
f304fbea-c425-4546-a31d-e80936fe17a6
|
pending
| 2025-04-29T14:36:04.699000 | 2025-04-29T14:36:04.699000 |
8a66ae7b-3f3b-470f-ba08-fe87efe88b84
|
In this review paper aimed at the non-specialist, we explore the use that neuroscientists and musicians have made of perceptual illusions based on ambiguity. The pivotal issue is auditory scene analysis (ASA), or what enables us to make sense of complex acoustic mixtures in order to follow, for instance, a single melody in the midst of an orchestra. In general, ASA uncovers the most likely physical causes that account for the waveform collected at the ears. However, the acoustical problem is ill-posed and it must be solved from noisy sensory input. Recently, the neural mechanisms implicated in the transformation of ambiguous sensory information into coherent auditory scenes have been investigated using so-called bistability illusions (where an unchanging ambiguous stimulus evokes a succession of distinct percepts in the mind of the listener). After reviewing some of those studies, we turn to music, which arguably provides some of the most complex acoustic scenes that a human listener will ever encounter. Interestingly, musicians will not always aim at making each physical source intelligible, but rather express one or more melodic lines with a small or large number of instruments. By means of a few musical illustrations and by using a computational model inspired by neuro-physiological principles, we suggest that this relies on a detailed (if perhaps implicit) knowledge of the rules of ASA and of its inherent ambiguity. We then put forward the opinion that some degree perceptual ambiguity may participate in our appreciation of music.
|
None
|
[
[]
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"discarded"
] |
[
"Correct"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"discarded"
] |
[
"Correct"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"discarded"
] |
[
null
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"discarded"
] |
[] | null | null |
ef62218e-490f-47b1-8544-7e416e624a1a
|
pending
| 2025-04-29T14:36:04.699000 | 2025-04-29T14:36:04.699000 |
97b837fa-e9a5-4d33-b233-b0391b7cb469
|
Using the rules of ASA to promote fusion across instruments or, on the contrary, to create distinct voices may be described as implicitly relying on auditory illusions (not all instruments may be heard, and, conversely, not all melodies are produced by a single physical instrument).There are also composers who have made explicit use of illusions as a structural principle for their writing (Risset, 1996;Féron, 2006).Composers known as proponents of "spectral music" built a whole method from the ASA paradox of breaking down the spectral content of natural sounds, which are usually perceived as single sources, to then write complex chords heard as orchestral timbres, thus fusing instruments that are usually heard individually (Grisey and Fineberg, 2000;Pressnitzer and McAdams, 2000). But the work of Gyorgy Ligeti in particular bears the mark of perceptual illusions as musical devices in their own right.Take for instance the two pieces illustrated in Sound Example S5 and S6 in Supplementary Material.In the case of "Lontano," many instruments are fused into a slowly evolving texture and it is extremely difficult to isolate any one of them.In Ligeti's own word, "Polyphony is written but one hears harmony".The same orchestral configuration is used for the "San Francisco Polyphony," but here, the various instruments are individually heard, with indeed a feeling of a rich polyphony.Through these two pieces, most of the rules of ASA are used to create dramatically different perceptual outcomes with a same orchestra.This use of auditory illusions was a fully planned and deliberate musical esthetics, as stated by Ligeti himself (Sabbe, 1979): "Yes, it is true, I often work with acoustical illusions, very analogous to optical illusions, false perspectives, etc.We are not very familiar with acoustical illusions.But they are very analogous and one can make very interesting things in this domain."
|
None
|
[
[]
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"discarded"
] |
[
null
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"discarded"
] |
[
null
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"discarded"
] |
[
null
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"discarded"
] |
[] | null | null |
8bb2d88b-cb8f-4eef-901d-1bb032d4fc46
|
completed
| 2025-04-29T14:36:04.699000 | 2025-05-27T14:00:39.763000 |
9145ebe7-bb3f-4089-a65b-54c1351aebe6
|
AbstractOur objective was to study the incidence, etiology and diagnosis of multifocal osteonecrosis (MFON) and its treatment options to facilitate an earlier diagnosis and to optimize treatment. A radiological investigation was performed in osteonecrosis patients with a high risk of MFON for a more accurate diagnosis between January 2010 and June 2015. For patients with osteonecrosis of both the hip and knee joints or for patients with a history of corticosteroid use or alcohol abuse who had osteonecrosis of one or more joints in the shoulder, ankle, wrist or elbow, magnetic resonance imaging (MRI) was also performed on other joints, regardless of whether these joints were symptomatic. Furthermore, we performed a radiological screening of 102 patients who had a negative diagnosis of MFON but were at a high risk; among them, another 31 MFON cases were successfully identified (30.4%). Thus, the incidence of MFON during the study period increased from 3.1% to 5.2%. Patients diagnosed with osteonecrosis and who are at a high risk of MFON should have their other joints radiologically examined when necessary. This will reduce missed diagnosis of MFON and facilitate an earlier diagnosis and treatment to achieve an optimal outcome.
|
<li> <b>magnetic resonance imaging:</b> magneticResonanceImaging (technique)<li> <b>MRI:</b> magneticResonanceImaging (technique)
|
[
[
{
"end": 600,
"label": "technique",
"start": 574
},
{
"end": 605,
"label": "technique",
"start": 602
}
]
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
null
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
{
"end": 600,
"label": "technique",
"start": 574
},
{
"end": 605,
"label": "technique",
"start": 602
}
] | null | null |
23046eb9-7afc-4020-92df-1221635f5d21
|
completed
| 2025-04-29T14:36:04.699000 | 2025-05-27T14:00:39.858000 |
858a69f1-3b4e-42d8-91a7-71f8b7e01fe9
|
A few reports of MFON have suggested that a high dose of corticosteroids is the main risk factor for MFON.In France, Hernigou 4 reported on 140 MFON cases diagnosed between 1985 and 1995, all of which were associated with corticosteroid use.In the cases reported by Mont et al. 1 , 91% had a history of corticosteroid use, and the rest had a coagulation disorder.Our study showed that 94 of the 96 (98%) MFON patients admitted to our center had a treatment history of high-dose corticosteroids, and the two remaining patients had a history of alcohol use.Moreover, the dosage and route of administration of the corticosteroids were obviously related to the incidence of MFON.A study by Hernigou 4 demonstrated that the total dose and the daily dose of venous injection were closely related to the occurrence of MFON.This was also found in our study of post-SARS osteonecrosis patients caused by the use of corticosteroids 3 . There have been a limited number of MFON case reports and a high occurrence of MFON in asymptomatic patients.Therefore, the exact incidence of MFON in patients with various diseases remains unclear.The incidence of MFON in 200 patients with sickle cell disease was reported to be 44% (87 of 200) 4 .MFON as a complication in the maintenance treatment of acute lymphocytic leukemia and non-Hodgkin's disease, and its incidence in these diseases is also higher than that reported in the literature.Solarino et al. 9 performed MRI screening in patients with acute lymphoblastic leukemia after chemotherapy and found that 82% of them had MFON 9 .In the MFON cases presented in this study, most were SLE, followed by hematological diseases, nephropathy, organ transplantation, dermatomyositis and multiple sclerosis.MFON was especially prevalent in leukemia patients; 17 of the 20 osteonecrosis patients with leukemia under our care were found to have MFON.Three of the four patients who received pulse steroid therapy for trauma emergency had a spinal cord injury, for which steroid therapy was considered appropriate.However, one patient received pulse steroid therapy for only an eye injury and was found to have osteonecrosis in eight joints, including the hips, knees, shoulders and ankles.Caution should be taken for such cases in the future.MFON patients most commonly had osteonecrosis of the femoral head, followed by the knee, shoulder and ankle bones.Osteonecrosis of the shoulder, ankle and wrist never occurred aloneand was always accompanied by osteonecrosis of the hip and knee.Among the three populations of MFON patients presented in this study, 98-100% had femoral head involvement, 78-88% had knee involvement, and 29-67% had humeral head involvement.The average number of osteonecrotic lesions was 5.7 per patient.
|
<li> <b>MRI:</b> magneticResonanceImaging (technique)
|
[
[
{
"end": 1454,
"label": "technique",
"start": 1451
},
{
"end": 1979,
"label": "UBERONParcellation",
"start": 1968
}
]
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"spinal cord: Other (UBERONParcellation)"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
{
"end": 1454,
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"start": 1451
}
] | null | null |
e609cea0-fb4c-4178-b3e1-9ff38d024cc1
|
completed
| 2025-04-29T14:36:04.699000 | 2025-05-27T14:00:39.950000 |
e9208544-5283-485c-90b6-940a015691a2
|
AbstractFor the past several decades, chimeric antigen receptor T cell (CAR T) therapies have shown promise in the treatment of cancers. These treatments would greatly benefit from companion imaging biomarkers to follow the trafficking of T cells in vivo. Using synthetic biology, we engineered T cells with a chimeric receptor SyNthetic Intramembrane Proteolysis Receptor (SNIPR) that induces overexpression of an exogenous reporter gene cassette upon recognition of specific tumor markers. We then applied a SNIPR-based positron emission tomography (PET) reporter system to two cancer-relevant antigens, human epidermal growth factor receptor 2 (HER2) and epidermal growth factor receptor variant III (EGFRvIII), commonly expressed in breast and glial tumors respectively. Antigen-specific reporter induction of the SNIPR-PET T cells was confirmed in vitro using GFP fluorescence, luciferase luminescence, and the HSV-TK PET reporter with [18F]FHBG. T cells associated with their target antigens were successfully imaged using PET in dual xenograft HER2+/HER2- and EGFRvIII+/EGFRvIII-animal models, with > 10-fold higher [18F]FHBG signals seen in antigen-expressing tumors versus the corresponding controls. The main innovation described is therefore PET detection of T cells via specific antigen-induced signals, in contrast to reporter systems relying on constitutive gene expression.
|
<li> <b>positron emission tomography:</b> positronEmissionTomography (technique)<li> <b>PET:</b> positronEmissionTomography (technique)
|
[
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[
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[
"submitted"
] |
[
"Correct"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
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[
"submitted"
] |
[
"Correct"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
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[
"in vitro: inVitro (preparationType)"
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[
{
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{
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{
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{
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{
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"label": "technique",
"start": 1029
},
{
"end": 1256,
"label": "technique",
"start": 1253
}
] | null | null |
6739123b-1e54-4253-abee-0ca218830036
|
completed
| 2025-04-29T14:36:04.699000 | 2025-05-27T14:00:40.040000 |
00bda1d0-13af-45c2-8814-b2c5272dcf39
|
Trastuzumab has the same anti-HER2 scFv binding moiety as our SNIPR, thereby reflecting the affinity-based interaction of the same antigen-antibody pair (40).We used [ 89 Zr]trastuzumab (anti-HER2) PET imaging and [ 18 F]FDG PET in the same animal model as for the SNIPR-CAR system (n 5 4).Overall, different biodistributions of the 2 tracers were observed, consistent with distinct metabolism and excretion pathways (Fig. 3A).Both immuno-PET with [ 89 Zr]trastuzumab and SNIPR PET with [ 18 F]FHBG demonstrated statistically significant increased radiotracer enrichment in HER21 tumor compared with HER2-tumor (9.9-fold, with P , 0.001, and 9.3-fold, with P 5 0.002, respectively) (Fig. 3B).The relative radiotracer enrichment within HER21 tumor compared with HER22 tumor was not statistically significant between immuno-PET and SNIPR PET (P .0.05) (Fig. 3C).Likewise, the relative radiotracer enrichment within HER21 tumor compared with background was also not statistically significant between immuno-PET and SNIPR PET (P .0.05) (Fig. 2D).Imaging results using [ 89 Zr]trastuzumab were corroborated via ex vivo analysis of harvested tissues (Supplemental Fig. 7).Although not statistically significant, the trend of higher [ 18 F]FDG accumulation in HER2-tumor than in HER21 tumor on a %ID/cm 3 basis correlated with the higher growth rate of MD468 (HER2-) than of SKBR3 (HER21) that we observed both in vitro and in vivo (Figs.3B and3D).
|
<li> <b>PET:</b> positronEmissionTomography (technique)<li> <b>PET imaging:</b> positronEmissionTomography (technique)
|
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{
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]
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[
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[
"submitted"
] |
[
"Correct"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"in vitro: inVitro (preparationType)\nin vivo: inVivo (preparationType)\n"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
{
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},
{
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"start": 225
},
{
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},
{
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},
{
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},
{
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},
{
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},
{
"end": 1021,
"label": "technique",
"start": 1018
},
{
"end": 209,
"label": "technique",
"start": 198
}
] | null | null |
4f8c505f-e3a3-4602-84e7-98bbb1a50193
|
completed
| 2025-04-29T14:36:04.699000 | 2025-05-27T14:00:40.142000 |
caab749c-5c4a-4ab1-95cd-d4c6389a7008
|
When individuals interact with others, perceived information is transmitted among their brains. The EEG-based hyperscanning technique, which provides an approach to explore dynamic brain activities between two or more interactive individuals and their underlying neural mechanisms, has been applied to study different aspects of social interactions since 2010. Recently there has been an increase in research on EEG-based hyperscanning of social interactions. This paper summarizes the application of EEG-based hyperscanning on the dynamic brain activities during social interactions according to the experimental designs and contents, discusses the possibility of applying inter-brain synchrony to social communication systems and analyzes the contributions and the limitations of these investigations. Furthermore, this paper sheds light on some new challenges to future EEG-based hyperscanning studies and the emerging field of EEG-based hyperscanning for pursuing the broader research field of social interactions.
|
<li> <b>EEG:</b> electroencephalography (technique)<li> <b>EEG-based hyperscanning:</b> electroencephalography (technique)
|
[
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{
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{
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"label": "UBERONParcellation",
"start": 540
},
{
"end": 94,
"label": "UBERONParcellation",
"start": 88
}
]
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"Partially correct"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"Partially correct"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"brain: Other (UBERONParcellation)"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
{
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{
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},
{
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{
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{
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},
{
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},
{
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"label": "technique",
"start": 873
},
{
"end": 954,
"label": "technique",
"start": 931
}
] | null | null |
a17680ea-7d75-4a1e-83cb-67fc288fb622
|
completed
| 2025-04-29T14:36:04.699000 | 2025-05-27T14:00:40.226000 |
da67f0c3-46a5-4ef7-86ac-62db672019c2
|
Among social signals, the non-verbal signals are deemed to be crucial visual cues for communicative intentions (Jahng et al., 2017).During these processes, people share the same perspective with one another, and this phenomenon is called shared attention (Shteynberg, 2018). Mutual gaze and shared attention play an essential role in our abilities to detect others' focuses of interest, as well as to infer their intentions, desires and thoughts.The importance of mutual gaze and shared attention on the development of social cognition has been underlined (Koike et al., 2016).To investigate the neural mechanisms of interpersonal shared attention, researchers measured the brain activities of two people who engaged in actual mutual gaze or shared attention experimental task with inter-subjective sharing reciprocal information without words by recording simultaneously dual-EEG.Lachat et al. (2012) set up a live shared attention paradigm to investigate the influence of shared attention on oscillatory activities within the alpha-mu (8-12 Hz) frequency band.Compared with the noshared attention periods, a decrease of 11-13 Hz signal was found during the shared attention periods over a large set of left centroparietal electrodes extending to occipital electrodes.Another EEG-based hyperscanning study was performed by Leong et al. (2017) to verify whether direct gaze increased neural coupling between adult-infant partners during social interactions.Dikker et al. (2017) found that the highest pairwise alpha coherence emerged in student pairings who sat face-toface compared to the other two student pairings (adjacent and no face-to-face or no adjacent) and the inter-brain synchrony between students consistently predicted class engagement and social dynamics. The studies mentioned above supported the view that alpha frequency band was involved in visual processing (van den Heuvel et al., 2018), arousal and attentional mechanisms (Foxe and Snyder, 2011).People exchange reciprocal information via eye-to-eye contact and act according to the interpretation of the information.The results in certain degree showed that eye contact enhanced neural coupling between interactive individuals during social interactions.The conclusion was verified by the experiment about autism spectrum disorders (Yates and Couteur, 2016).
|
<li> <b>EEG:</b> electroencephalography (technique)<li> <b>dual-EEG:</b> electroencephalography (technique)<li> <b>EEG-based hyperscanning:</b> electroencephalography (technique)
|
[
[
{
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},
{
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"label": "technique",
"start": 1277
},
{
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"label": "UBERONParcellation",
"start": 674
}
]
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"Partially correct"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"Partially correct"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"brain: Other (UBERONParcellation)\n\r\n"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
{
"end": 880,
"label": "technique",
"start": 877
},
{
"end": 1280,
"label": "technique",
"start": 1277
},
{
"end": 880,
"label": "technique",
"start": 872
},
{
"end": 1300,
"label": "technique",
"start": 1277
}
] | null | null |
f6191925-99d7-420e-a6a1-bb9a2a8fb6f5
|
completed
| 2025-04-29T14:36:04.699000 | 2025-05-27T14:00:40.308000 |
b428a14b-6a5e-4302-9f94-9ac680a6a190
|
Abstract Objectives: To compare the amount of fluid in synovial sheaths of the ankle before and after running. Our hypothesis was that this amount would increase, and that the threshold for what is normally acceptable should be adjusted after physical activity.Methods: Twenty-one healthy volunteers (n=42 ankles) ran for 40 minutes on a treadmill. They underwent 3T MRI before and immediately after running using a dedicated ankle coil. The images were stored and subsequently measured in a standardized way and independently read by two readers for fluid in the tendon sheaths in the retro and inframalleolar area. Statistics were performed for each tendon (Wilcoxon signed rank test), and also for the pooled data. Intraclass correlation coefficients were calculated.Results: For reader 1, for all tendons the values after running increased without reaching statistical significance. For reader 2 this was not the case for all tendons but for most. When all the data were pooled (n=800 measurements), the statistical difference before and after running was significant (p< 0.001).Conclusion: Data pre and post running show a trend of increasing synovial fluid, however not significant for each individual tendon. The pooled data for all tendons, (n=800) show a statistically significant increase after running (p< 0.001). The clinical implication is that the threshold for normally acceptable fluid should be adjusted if the patient undergoes an MR study after recent physical activity.
|
<li> <b>MRI:</b> magneticResonanceImaging (technique)<li> <b>3T MRI:</b> magneticResonanceImaging (technique)
|
[
[
{
"end": 370,
"label": "technique",
"start": 367
},
{
"end": 1451,
"label": "technique",
"start": 1449
}
]
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"MR: magneticResonanceImaging (technique)"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
{
"end": 370,
"label": "technique",
"start": 367
},
{
"end": 370,
"label": "technique",
"start": 364
}
] | null | null |
9aa91f88-855f-4c5e-b509-712004c3cdcc
|
completed
| 2025-04-29T14:36:04.699000 | 2025-05-27T14:00:40.407000 |
8f7ecbf3-e5d9-4ed6-af0a-3e9c46103f96
|
All participants performed the experiment successfully without pain, injury, or becoming unwell. Planning of imaging was organized as such that each participant immediately underwent MR when his running session ended. There were 12 men (57%) and 9 women (43%).The mean age was 24.7 years. All the measurements obtained for all tendons pre and post are shown in Table 2 and3.This Table also shows the 95% confidence interval, the delta (and confidence interval), and the p-value for this specific tendon.Statistical significance was calculated for each tendon separately.Since the number of cases per tendon remained small, we also calculated statistical significance for all measurements pooled.This calculation thus related to 800 cases.The first table relates to reader 1, and the second table to reader 2 (Figs.1,2,3,4,5). All the measurements pre and post were largest for both readers for the TP and FH, followed by the FD, and peroneal tendons but in their inframalleolar location. For all tendons pooled the delta was small and ranged from 0.00 to 0.14 mm.None of the observed differences for both readers per tendon was statistically significant. For reader 1 all measurements post running showed a trend to be higher than pre-running.For reader 2 most values after running showed a trend to be higher, but not all. There was a trend for the post measurement to be larger, although not reaching statistical significance per tendon. When the calculation was performed on the pooled data (n = 800 cases) the result was significant, however (p < 0.001), with the measurement post running being higher. The mean BMI of the volunteers was 23, 2 (N).The BMI range was 19-32.Three individuals were in the obese range, and 3 in the overweight range, all the others having a BMI in the normal range.
|
<li> <b>MR:</b> magneticResonanceImaging (technique)
|
[
[
{
"end": 185,
"label": "technique",
"start": 183
}
]
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"\n"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
{
"end": 185,
"label": "technique",
"start": 183
}
] | null | null |
eaf46979-006a-4f54-a871-605485061b5f
|
completed
| 2025-04-29T14:36:04.699000 | 2025-05-27T14:00:40.500000 |
e4606082-1628-407d-a839-3fbb16e8fb6e
|
AbstractThe complex genetic architecture of Autism Spectrum Disorder (ASD) and its heterogeneous phenotype make molecular diagnosis and patient prognosis challenging tasks. To establish more precise genotype-phenotype correlations in ASD, we developed a novel machine learning integrative approach, which seeks to delineate associations between patients’ clinical profiles and disrupted biological processes inferred from their Copy Number Variants (CNVs) that span brain genes. Clustering analysis of relevant clinical measures from 2446 ASD cases in the Autism Genome Project identified two distinct phenotypic subgroups. Patients in these clusters differed significantly in ADOS-defined severity, adaptive behaviour profiles, intellectual ability and verbal status, the latter contributing the most for cluster stability and cohesion. Functional enrichment analysis of brain genes disrupted by CNVs in these ASD cases identified 15 statistically significant biological processes, including cell adhesion, neural development, cognition and polyubiquitination, in line with previous ASD findings. A Naive Bayes classifier, generated to predict the ASD phenotypic clusters from disrupted biological processes, achieved predictions with a high Precision (0.82) but low recall (0.39), for a subset of patients with higher biological Information Content scores. This study shows that milder and more severe clinical presentations can have distinct underlying biological mechanisms. It further highlights how machine learning approaches can reduce clinical heterogeneity using multidimensional clinical measures, and establish genotype-phenotype correlations in ASD. However, predictions are strongly dependent on patient’s information content. Findings are therefore a first step towards the translation of genetic information into clinically useful applications, but emphasize the need for larger datasets with very complete clinical and biological information.
|
None
|
[
[
{
"end": 471,
"label": "UBERONParcellation",
"start": 466
},
{
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"label": "UBERONParcellation",
"start": 872
}
]
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"Incorrect"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"Incorrect"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"brain: Other (UBERONParcellation)"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[] | null | null |
27ea7ad5-632c-4be6-ab59-8fb1e9930ce5
|
completed
| 2025-04-29T14:36:04.699000 | 2025-05-27T14:00:40.591000 |
b51f304c-e814-424c-ae66-78ac8cee6fa8
|
CNVs (N = 129,754) identified in 2446 subjects with ASD were filtered to select rare, high-confidence CNVs, over 30 kb in size and that contained complete or partial brain-expressed gene sequences.The selected high-confidence, rare CNVs (N = 12,683) disrupted 4025 brainexpressed genes in 2414 subjects with ASD (86.8% males and 13.2% females). Phenotypic cluster and rare CNV data were complete for 1357 individuals with ASD, and available for integration.Functional enrichment analysis of rare CNVs targeting brain-expressed genes (N = 2738) in 1357 patients identified 17 statistically significant biological processes (Supplementary File 1: Table S3).g:Profiler did not recognize 187 genes from the input list.The redundancy of GO terms in functional enrichment analysis, caused by overlapping annotations in ancestor and descendent terms in the DAG structure of GO, was reduced by grouping the terms that had a semantic similarity score greater than 0.7 (Supplementary File 1: Table S3).The Revigo tool used to reduce redundancy did not recognize one biological process (Plasma membranebounded cell projection organization).After redundancy reduction, 16 biological processes remained (Table 3), with the Calcium-dependent cell-cell adhesion via plasma membrane cell adhesion molecules biological process merged with Homophilic cell adhesion via plasma membrane adhesion molecules (similarity score = 0.76).The most significant biological process identified in this dataset was Homophilic cell adhesion via plasma membrane adhesion molecules, which includes 53 brain-expressed genes disrupted by the selected CNVs.The ten most significant biological processes were related to cell adhesion and cellular organization, and also included nervous system development and protein polyubiquitination (Table 3).Moreover, two significant biological processes were related to behavior and cognition.
|
None
|
[
[
{
"end": 342,
"label": "biologicalSex",
"start": 335
},
{
"end": 324,
"label": "biologicalSex",
"start": 319
}
]
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"Incorrect"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"Incorrect"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"male: male (biologicalSex)\nfemale: female (biologicalSex)\n"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[] | null | null |
62892281-552b-480a-a0bb-235327803fe3
|
completed
| 2025-04-29T14:36:04.699000 | 2025-05-27T14:00:40.684000 |
83753522-60ea-4680-b582-e2204a12cbf6
|
AbstractStimuli are represented in the brain by the collective population responses of sensory neurons, and an object presented under varying conditions gives rise to a collection of neural population responses called an object manifold. Changes in the object representation along a hierarchical sensory system are associated with changes in the geometry of those manifolds, and recent theoretical progress connects this geometry with classification capacity, a quantitative measure of the ability to support object classification. Deep neural networks trained on object classification tasks are a natural testbed for the applicability of this relation. We show how classification capacity improves along the hierarchies of deep neural networks with different architectures. We demonstrate that changes in the geometry of the associated object manifolds underlie this improved capacity, and shed light on the functional roles different levels in the hierarchy play to achieve it, through orchestrated reduction of manifolds’ radius, dimensionality and inter-manifold correlations.
|
None
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"submitted"
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"Correct"
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"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
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"submitted"
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[
"object classification: Other (technique)"
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[
"submitted"
] |
[] | null | null |
61e5c56a-810a-4f35-8b38-98504d2e20b7
|
pending
| 2025-04-29T14:36:04.699000 | 2025-04-29T14:36:04.699000 |
0585cebe-c068-445f-9af1-0f84793d4258
|
Changes in the measured classification capacity can be traced back to changes in manifold geometry along the network hierarchy, namely manifold radii and dimensions, which can be estimated from data (see Methods, Eqs. ( 3) and ( 4), and Supplementary Methods 2.1).Mean manifold dimension and radius along DCNNs hierarchies are shown in Fig. 6a,b, respectively.The results exhibit a surprisingly consistent pattern of changes in the geometry of manifolds between different network architectures, along with interesting differences between the behavior of point-cloud and smooth manifolds.Figure 6a (and Supplementary Fig. 5 for ResNet-50 results) suggests that decreased dimension along the deep hierarchies is the main source of the observed increase in capacity from Figs. 4 and5.Both pointcloud and smooth manifolds exhibit non-monotonic behavior of dimension, with increased dimension in intermediate layers; this increase of dimensionality is also be observed in other measures such as participation ratio (Supplementary Fig. 5).A notable result is the very pronounced decrease in dimensions after the pixel layer of smooth translation manifolds (Fig. 6a, bottom), consistent with the expected ability of this convolution layer to average out substantial variability in images due to translation.On the other hand, manifold radii undergo modest decrease along the deep hierarchy and across all manifolds (Fig. 6b, and Supplementary Fig. 6 for ResNet-50).The larger role of dimensions, rather than radii, in contributing to the increase in capacity is demonstrated by comparing the observed capacity to that expected for manifolds with the observed dimensions but radii fixed at their value at the pixel layer, or the other way around (Supplementary Fig. 7).Interestingly, the decrease in radius is roughly linear in point-cloud manifolds while for smooth manifolds we find a substantial decrease in the first layer and the final (fully connected) layers, but not in intermediate layers.Those differences may reflect the fact that the high variability of point-cloud manifolds needs to be reduced incrementally from layer to layer (both in terms of radius and dimension), utilizing the increased complexity of downstream features, while the variability created by local affine transformations is handled mostly by the local processing of the first convolutional layer (consistent with ref. 35 reporting invariance to such transformations in the receptive field of early layers).The layer-wise compression of affine manifold plateaus in the subsequent convolutional layers, as the manifolds are already small enough.As signals propagate beyond the convolutional layers, the fully connected layers add further reduction in size in both manifold types. This geometric description allows us to further shed light on the structure of the smooth manifolds used here.For radius up to 1, the dimension of the manifolds with intrinsic 2-d variations (e.g., created by vertical and horizontal translation) is just the sum of the dimensions of the two corresponding 1-d manifolds with the same maximal object displacement (Supplementary Fig. 8a); only for larger radii, dimensions for 2-d manifolds are superadditive.On the other hand, for all levels of stimulus variability the radius of 2-d manifolds is about the same as the value of the corresponding 1-d manifolds (Supplementary Fig. 8b).This highlights the non-linear structure of those larger manifolds, where the effect of changing multiple manifold coordinates is no longer predicted from the effect of changing each coordinate separately.Network layers reduce correlations between object centers.Manifold geometry considered above characterizes the variability in object manifolds' shape but not the possible relations between them.Here we focus on the correlations between the centers of different manifolds (hereafter: center correlations), which may create clusters of manifolds in the representation state space.Though clustering may be beneficial for specific target classifications, our theory predicts that the overall effect of such manifold clustering on random binary classification is detrimental.Hence, these correlations reduce classification capacity (Supplementary Note 3.1).Thus, the amount of center correlations at each layer of a deep network is a computationally-relevant feature of the underlying manifold representation.Importantly, for both point-cloud and smooth manifolds we find that in an AlexNet network trained for object classification, center correlations decrease along the deep hierarchy (full lines in Fig. 7a,b; additional VGG-16, ResNet-50 results in Supplementary Fig. 9).This decrease is interpreted as incremental improvement of the neural code for objects, and supports the improved capacity (Figs.45).In contrast, center correlations at the same network architectures but prior to training (dashed lines in Fig. 7a,b) do not decrease (except for the affine manifolds in the first convolutional layer, Fig. 7b).Thus this decorrelation of manifold centers is a result of the network training.Interestingly, the center correlations of shuffled manifolds exhibit lower levels of correlations, which remain constant across layers after an initial decrease at the first convolutional layer. Another source of inter-manifold correlations are correlations between the axes of variation of different manifolds; those also decrease along the network hierarchies (Supplementary Fig. 9) but their effect on classification capacity is small (as verified by using surrogate data, Supplementary Fig. 10). Effect of network building blocks on manifolds' geometry.To better understand the enhanced capacity exhibited by DCNNs we study the roles of the different network building blocks.Based on our theory, any operation applied to a neural representation may change capacity by either changing the manifolds' dimensions, radii, or the inter-manifold correlations (where a reduction of these measures is expected to increase capacity). Figure 8a, b shows the effect of single operations used in AlexNet and VGG-16.We find that the ReLU nonlinearity usually reduces center correlations and manifolds' radii, but increases manifolds' dimensions (Fig. 8a).This is expected as the nonlinearity tends to generate a sparse, higher dimensional, representations 50,51 .In contrast, pooling decreases manifolds' radii and dimensions but usually increase correlations (Fig. 8b), presumably due to the underlying spatial averaging.Such clear behavior is not evident when considering convolutional or fully connected operations in isolation (Supplementary Fig. 11). In contrast to single operations, we find that the networks' computational building blocks perform consistent transformation on manifold properties (Fig. 8c,d).The initial building blocks consist of sequences of convolution, ReLU operation followed by pooling, which consistently act to decrease correlations and tend to decrease both manifolds' radii and dimensions (Fig. 8c).On the other hand, the final building block, a fully connected operation followed by ReLU, decreases manifolds' radii and dimensions, but may increase correlations (Fig. 8d), similarly to the max-pooling operation (Fig. 8b).Furthermore, as composite building blocks show more consistent behavior than individual operations, we understand why DCNNs with randomly initialized weights do not improve manifold properties.Only by appropriately trained weights, the combination of operations with often opposing effects yields a net improvement in manifold properties.
|
None
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[] | null | null |
4996bdff-9fc4-45d4-81eb-6951c6eb6ef5
|
completed
| 2025-04-29T14:36:04.699000 | 2025-05-27T14:00:40.782000 |
839ec302-51db-4f77-baac-d8a4cf800375
|
Numerous studies have shown that gradient-echo blood oxygen level dependent (BOLD) fMRI is biased toward large draining veins. However, the impact of this large vein bias on the localization and characterization of semantic category areas has not been examined. Here we address this issue by comparing standard magnitude measures of BOLD activity in the Fusiform Face Area (FFA) and Parahippocampal Place Area (PPA) to those obtained using a novel method that suppresses the contribution of large draining veins: source-localized phase regressor (sPR). Unlike previous suppression methods that utilize the phase component of the BOLD signal, sPR yields robust and unbiased suppression of large draining veins even in voxels with no task-related phase changes. This is confirmed in ideal simulated data as well as in FFA/PPA localization data from four subjects. It was found that approximately 38% of right PPA, 14% of left PPA, 16% of right FFA, and 6% of left FFA voxels predominantly reflect signal from large draining veins. Surprisingly, with the contributions from large veins suppressed, semantic category representation in PPA actually tends to be lateralized to the left rather than the right hemisphere. Furthermore, semantic category areas larger in volume and higher in fSNR were found to have more contributions from large veins. These results suggest that previous studies using gradient-echo BOLD fMRI were biased toward semantic category areas that receive relatively greater contributions from large veins.
|
<li> <b>blood oxygen level dependent:</b> functionalMagneticResonanceImaging (technique)<li> <b>BOLD:</b> functionalMagneticResonanceImaging (technique)<li> <b>fMRI:</b> functionalMagneticResonanceImaging (technique)<li> <b>Fusiform Face Area:</b> fusiformGyrus (UBERONParcellation)<li> <b>FFA:</b> fusiformGyrus (UBERONParcellation)<li> <b>Parahippocampal Place Area:</b> parahippocampalGyrus (UBERONParcellation)<li> <b>PPA:</b> parahippocampalGyrus (UBERONParcellation)
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{
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] | null | null |
b90470c9-9bfb-4f89-a11c-84678d0ea144
|
completed
| 2025-04-29T14:36:04.699000 | 2025-05-27T14:00:40.916000 |
7528882a-76c4-4f78-8c2f-c77a58def920
|
To quantify the hemisphere laterality of FFA and PPA, an ROI size laterality index and an fSNR laterality index for each subject's FFA and PPA were calculated.For a given subject and ROI, ROI size laterality is defined as:
|
<li> <b>FFA:</b> fusiformGyrus (UBERONParcellation)<li> <b>PPA:</b> parahippocampalGyrus (UBERONParcellation)<li> <b>ROI:</b> Other (technique)
|
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{
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{
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}
] | null | null |
756e0db5-2905-4dbd-8743-78a81fece6b1
|
completed
| 2025-04-29T14:36:04.699000 | 2025-05-27T14:00:41.008000 |
81145392-d51a-48af-bc63-8ece8901f77f
|
MicroRNAs (miRNAs) are short-length non-protein-coding RNA sequences that post-transcriptionally regulate gene expression in a broad range of cellular processes including neuro- development and have previously been implicated in fetal alcohol spectrum disorders (FASD). In this study, we use our vervet monkey model of FASD to follow up on a prior multivariate (developmental age × ethanol exposure) mRNA analysis (GSE173516) to explore the possibility that the global mRNA downregulation we observed in that study could be related to miRNA expression and function. We report here a predominance of upregulated and differentially expressed miRNAs. Further, the 24 most upregulated miRNAs were significantly correlated with their predicted targets (Target Scan 7.2). We then explored the relationship between these 24 miRNAs and the fold changes observed in their paired mRNA targets using two prediction platforms (Target Scan 7.2 and miRwalk 3.0). Compared to a list of non-differentially expressed miRNAs from our dataset, the 24 upregulated and differentially expressed miRNAs had a greater impact on the fold changes of their corresponding mRNA targets across both platforms. Taken together, this evidence raises the possibility that ethanol-induced upregulation of specific miRNAs might contribute functionally to the general downregulation of mRNAs observed by multiple investigators in response to prenatal alcohol exposure.
|
<li> <b>vervet monkey:</b> chlorocebusAethiopsSabaeus (species)
|
[
[
{
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}
]
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
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"submitted"
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"Correct"
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[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
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[
"submitted"
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[
"Incorrect"
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[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
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[
"vervet monkey: chlorocebusPygerythrus (species)"
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[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
{
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"start": 296
}
] | null | null |
d51c1f53-7a87-4f1f-9a8c-ec47ff9a7975
|
pending
| 2025-04-29T14:36:04.699000 | 2025-04-29T14:36:04.699000 |
d2e721e8-e67f-49a4-8074-dc9544df1993
|
To our knowledge, this is the first study to observe the simultaneous upregulation of miRNA with correlated downregulation of mRNA in response to prenatal ethanol exposure using paired, concurrently sampled datasets.This is also the first example in which a hypothetical functional impact of global miRNA changes on global old changes in mRNA has been robustly investigated.
|
None
|
[
[]
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
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[
"discarded"
] |
[
"Correct"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"discarded"
] |
[
"Correct"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"discarded"
] |
[
null
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"discarded"
] |
[] | null | null |
32a4594f-7a26-4d86-a839-9dba28701835
|
pending
| 2025-04-29T14:36:04.699000 | 2025-04-29T14:36:04.699000 |
d086c1d7-245b-4448-9c48-21ec69a2bff7
|
In this paper, we report an approach to design nanolayered memristive compositions based on TiO2/Al2O3 bilayer structures with analog non-volatile and volatile tuning of the resistance. The structure of the TiO2 layer drives the physical mechanism underlying the non-volatile resistance switching, which can be changed from electronic to ionic, enabling the synaptic behavior emulation. The presence of the anatase phase in the amorphous TiO2 layer induces the resistive switching mechanism due to electronic processes. In this case, the switching of the resistance within the range of seven orders of magnitude is experimentally observed. In the bilayer with amorphous titanium dioxide, the participation of ionic processes in the switching mechanism results in narrowing the tuning range down to 2–3 orders of magnitude and increasing the operating voltages. In this way, a combination of TiO2/Al2O3 bilayers with inert electrodes enables synaptic behavior emulation, while active electrodes induce the neuronal behavior caused by cation density variation in the active Al2O3 layer of the structure. We consider that the proposed approach could help to explore the memristive capabilities of nanolayered compositions in a more functional way, enabling implementation of artificial neural network algorithms at the material level and simplifying neuromorphic layouts, while maintaining all benefits of neuromorphic architectures.
|
None
|
[
[]
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
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[
"discarded"
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[
null
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"discarded"
] |
[
null
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"discarded"
] |
[
null
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"discarded"
] |
[] | null | null |
a9ee570a-100b-412d-a19c-26125b7fd95b
|
completed
| 2025-04-29T14:36:04.699000 | 2025-05-27T14:00:41.122000 |
0db93650-b115-4b50-963e-cbaf62e718f9
|
As a memristive structure with an analog switching of the resistive state, a sequence of two Al 2 O 3 /TiO 2 thin-film layers was chosen (Figure 1).To form the structures, Pt bottom electrode (100 nm) was deposited at 150 • C on a p-Si/SiO 2 substrate with an adhesive layer of Ti (25 nm).Atomic layer deposition (ALD) was used to synthesize the functional oxide layers (TFS 200 setup, Beneq).ALD of 30-nm-thick titanium dioxide was carried out at temperatures of 150-200 • C using titanium tetraisopropoxide [Ti(OiPr) 4 ] and water vapor (H 2 O) as precursors.Synthesis of a functional 5-nm-thick Al 2 O 3 layer was carried out at 150 • C using trimethylaluminum and water vapor (H 2 O).The structure of the titanium dioxide layer solely depends on ALD temperature T c .At T c = 150 • C, the titanium dioxide layer is completely amorphous, whereas at T c = 200 • C, it is amorphous with the inclusion of the anatase phase crystallites (Grzegorz et al., 2013;Piltaver et al., 2017;Andreeva N. et al., 2018).The initial resistance of the amorphous layer was 10 9 •cm, and that of the layer, containing the anatase phase, was 10 4 •cm.The initial resistance of the two-layer Al 2 O 3 /TiO 2 structures was determined by the resistance of the amorphous aluminum oxide layer and was set to 10 11 -10 12 •cm.The thickness of the deposited layers was controlled with scanning electron microscopy over the cross-section of the structures obtained with a focused ion beam (Quanta FEI, Helios NanoLab).The surface morphology of platinum and titanium oxide films was studied with atomic force microscopy (Dimension 3100, Veeco).The study of local resistive properties was carried out in the mode of tunneling atomic force microscopy using probes with a conductive platinum coating. Top platinum and copper electrodes with a thickness of 100 nm and a diameter of 350 µm were deposited through a mask by ion-plasma sputtering at 150 • C. Mechanisms responsible for the appearance of resistive switching and the switching effect itself were studied based on I-V characteristics measured using the Keithley 4200-SCS semiconductor characterization system.During the measurements, the bottom platinum electrode was grounded. Aluminum oxide was chosen as the active layer responsible for the analog switching of the resistance for the following reasons.First, it is an oxide of a non-transition metal, and the effect of redox reactions on the resistive switching processes may be excluded.Second, it is a high-resistance material [with a band gap of 6.2-6.5 eV for amorphous alumina (Liu et al., 2010)] with low charge carrier mobility and long dielectric relaxation time. At a low concentration of defects (point defects, mainly in the oxygen sublattice), the conductivity of aluminum oxide is electronic in nature (Robert and Doremus, 2006).At that point, the hopping transport of electrons through the trap levels, arising from structural defects, and space-charge-limited currents (SCLC) act as the main mechanisms of charge transport (Hickmott, 1962;Kunitsyn et al., 2018).Taking into account the peculiarities of the ALD technology, it is possible to synthesize layers, in which both chemically bound and adsorbed (OH-) groups will be present in the bulk of the deposited Al 2 O 3 layers.At a certain concentration of (OH-) groups, exceeding 3 × 10 7 (OH-) groups per aluminum atom, a transition in the character of conductivity from electronic to ionic is observed.The ionic conductivity is related to the transport of H 3 O + ions via the formation of bonds with oxygen anions located near the AlO defects (Robert and Doremus, 2006).ALD synthesis makes it possible to vary the concentration of OH-groups in Al 2 O 3 layers by changing the exposure time to water.Thus, the use of ALD-grown aluminum oxide as functional layers in memristive structures allows us to vary the contribution of electronic or ionic processes in the mechanisms of resistive switching. The use of titanium dioxide, which is a transition metal oxide, as the second functional layer in the structure of memristive composition gives us an opportunity to "optionally, " i.e., depending on the synthesis conditions, engage the mechanism of resistive switching related to the redox reactions.For example, a layer of amorphous titanium dioxide exhibited a reversible analog switching of the resistance in the range of three orders of magnitude due to the redox reactions (Andreeva et al., 2021), and it was used in Al 2 O 3 /TiO 2 compositions with a predominance of the ionic resistive switching mechanism.No resistive effects were observed in the titanium dioxide layer with the anatase phase, and its use made it possible to turn to the electronic nature of resistive switching in two-layer memristive compositions (Alekseeva et al., 2016;Andreeva N. et al., 2018). In the ionic switching mechanism, the replacement of platinum with copper as electrode material was aimed to govern the resistance of the aluminum oxide layer by varying the ratio of copper cations and oxygen vacancies.
|
<li> <b>Atomic layer deposition:</b> Other (technique)<li> <b>ALD:</b> Other (technique)<li> <b>scanning electron microscopy:</b> scanningElectronMicroscopy (technique)<li> <b>atomic force microscopy:</b> Other (technique)
|
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de1b67ba-55e3-4311-b397-5eec01632007
|
completed
| 2025-04-29T14:36:04.699000 | 2025-05-27T14:00:41.208000 |
b00073ee-2d4c-4e7b-8441-9c9ff45ccdff
|
Congenital sensory deprivation can lead to reorganization of the deprived cortical regions by another sensory system. Such cross-modal reorganization may either compete with or complement the "original" inputs to the deprived area after sensory restoration and can thus be either adverse or beneficial for sensory restoration. In congenital deafness, a previous inactivation study documented that supranormal visual behavior was mediated by higher-order auditory fields in congenitally deaf cats (CDCs). However, both the auditory responsiveness of "deaf" higher-order fields and interactions between the reorganized and the original sensory input remain unknown. Here, we studied a higher-order auditory field responsible for the supranormal visual function in CDCs, the auditory dorsal zone (DZ). Hearing cats and visual cortical areas served as a control. Using mapping with microelectrode arrays, we demonstrate spatially scattered visual (cross-modal) responsiveness in the DZ, but show that this did not interfere substantially with robust auditory responsiveness elicited through cochlear implants. Visually responsive and auditory-responsive neurons in the deaf auditory cortex formed two distinct populations that did not show bimodal interactions. Therefore, cross-modal plasticity in the deaf higher-order auditory cortex had limited effects on auditory inputs. The moderate number of scattered cross-modally responsive neurons could be the consequence of exuberant connections formed during development that were not pruned postnatally in deaf cats. Although juvenile brain circuits are modified extensively by experience, the main driving input to the cross-modally (visually) reorganized higher-order auditory cortex remained auditory in congenital deafness.In a common view, the "unused" auditory cortex of deaf individuals is reorganized to a compensatory sensory function during development. According to this view, cross-modal plasticity takes over the unused cortex and reassigns it to the remaining senses. Therefore, cross-modal plasticity might conflict with restoration of auditory function with cochlear implants. It is unclear whether the cross-modally reorganized auditory areas lose auditory responsiveness. We show that the presence of cross-modal plasticity in a higher-order auditory area does not reduce auditory responsiveness of that area. Visual reorganization was moderate, spatially scattered and there were no interactions between cross-modally reorganized visual and auditory inputs. These results indicate that cross-modal reorganization is less detrimental for neurosensory restoration than previously thought.
|
<li> <b>congenitally deaf cats:</b> felisCatus (species)<li> <b>CDCs:</b> felisCatus (species)<li> <b>cats:</b> felisCatus (species)<li> <b>auditory dorsal zone:</b> auditoryCortex (UBERONParcellation)<li> <b>DZ:</b> auditoryCortex (UBERONParcellation)<li> <b>visual cortical areas:</b> visualCortex (UBERONParcellation)<li> <b>microelectrode arrays:</b> Other (technique)
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bdbdc84a-51cd-41a1-86e0-94c3e1e0dc37
|
completed
| 2025-04-29T14:36:04.699000 | 2025-05-27T14:00:41.291000 |
dc624efc-6de1-40c9-b102-725fca7d66bb
|
Animals.Experiments were performed in five adult congenitally deaf white cats (Heid et al., 1998) and four adult hearing controls (Ͼ12 months of age, 7 female and 2 male).HCs had normal hearing with click-evoked auditory brainstem response (ABR) thresholds Ͻ40 dB SPL pe .CDCs had been identified from the colony of deaf white cats using a hearing screening with ABRs within the first 4 weeks after birth (Heid et al., 1998).HCs and CDCs lived in the same housing conditions.Experiments were approved by the local state authorities of Lower Saxony (LAVES, Oldenburg) and were performed in compliance with the guidelines of the European Community for the care and use of laboratory animals (EU VD 86/609/EEC) and the German Animal Welfare Act (TierSchG). Surgical preparation and CIs.Animals were premedicated with 0.25 mg of atropine intraperitoneally and then anesthetized with 24.5 mg/kg ketamine hydrochloride (Ketavet; Parker-Davis) and 1 mg/kg xylazine hydrochloride (Rompun 2%; Bayer).The animals were then tracheotomized and artificially ventilated.During artificial ventilation, the anesthetic was switched to isoflurane (Lilly) and maintained throughout the surgical procedures at 1.3-1.5 volume percentage isoflurane concentration in a 1:2 mixture of O 2 /N 2 O. Adequacy of anesthesia depth and the animals' physiological state was monitored by means of ECG, heart rate, end-tidal CO 2 , muscle tone, and EEG signals.End-tidal CO 2 was maintained at Ͻ4.5%.Core temperature was kept Ͼ37.5°C using a homeothermic blanket.Physiological state was additionally monitored by analyzing capillary blood every 12 h for blood gas concentration, pH, bicarbonate concentration, base excess, glycemia, and oxygen saturation.A modified Ringer's solution containing bicarbonate (according to the base excess) was infused intravenously.Each animal's head was fixed in a stereotactic holder (Horsley-Clarke). We then retested the hearing status in all animals by measuring ABR.For this purpose, a small trephination was drilled at the vertex and ABR responses were recorded with an epidural silver-ball electrode (diameter ϳ1 mm) referenced to a silver-wire neck electrode.HCs had click response thresholds Ͻ40 dB SPL.The absence of ABR responses in deaf animals confirmed deafness as diagnosed during early hearing screening soon after birth (Fig. 1A). Stimulation was performed using feline CIs (MED-EL, custom-made, five channels, distance between contacts 1 mm; Fig. 1) inserted bilaterally through the round window into scalae tympani of both ears.This involved exposing both bullae and ear canals.To prevent electrophony in HCs, the hair cells were destroyed pharmacologically before cochlear implantation.This was achieved by intracochlear instillation of 300 l of 2.5% neomycin sulfate solution over a 5 min period and subsequent rinsing using Ringer's solution.The absence of hearing was subsequently confirmed by the absence of ABRs (Fig. 1).To test the functionality of the CIs and to determine the stimulation threshold, we then determined electrical ABRs (eABRs; Fig. 1).eABR thresholds were measured between the epidural silver electrode to a reference in the neck (amplification 100,000ϫ, sixth-order band-pass filter 10 -10,000 Hz).Electrical brainstem responses were recorded for a biphasic pulse (200 s/phase) at different current levels with bipolar stimulation between all possible bipolar electrode contact combinations. As in a previous study in a larger group of animals (Tillein et al., 2012), the eABR thresholds were not different between HCs and CDCs [Fig.1D Recording of electrophysiological activity.For electrophysiological recording, a trephination above the lateral (suprasylvian) sulcus was performed, exposing the dorsal auditory cortex (DZ) on the lateral bank and visual medial suprasylvian sulcus areas (anterior and posterior medial suprasylvian sulcus areas, AMLS/PMLS, subsequently referred to jointly as MLS; Fig. 2A).The dura was opened and the cortex surface was covered with silicone oil.A modified Davies chamber was positioned around the trephination site to stabilize the cortex with a layer of agarose and a closure was created melted bone wax after the electrode arrays were set in place.Cortical activity was recorded with two linear 16 site multielectrode arrays for which the intersite distance was 150 m, surface area 177 m 2 , impedance 1-2 ⌴⍀ (NeuroNexus).The multielectrode arrays were positioned and inserted using micromanipulators, which were attached to the stereotactic frame (TSE Systems).The penetration angle was kept constant throughout the experiment.At least one penetration in each investigated area was stained using DiI (1,1Ј-dioctadecyl-3,3,3Ј,3Јtetramethylindocarbocyanine perchlorate; Invitrogen) that was applied to the noncontact side of the multielectrode array using a micropipette (Eppendorf).An epidural vertex silver-ball electrode served as an electrical reference for both multi electrode arrays.The recorded signals were amplified 5000 -10,000 times with a Neuralynx amplifier, band-pass filtered (1 Hz-9 kHz), digitized (at a sampling rate of 30 kHz), and stored on a computer. Mapping procedure and stimulation design.We mapped the dorsal auditory cortex and visual areas along the medial part of the suprasylvian sulcus in deaf and HCs (Fig. 1B).Multielectrode arrays were inserted on both sides of the sulcus at a distance of ϳ500 m from the midline of the sulcus, thus penetrating the dorsal auditory cortex and the two visual area in MLS.With an intersite distance of 150 m and the uppermost site inserted just into the cortex, the tip of the electrode shank was inserted with a micromanipulator to a depth of ϳ2400 m (Ϯ100 m) from the cortical surface.The depth or position of the multielectrode array was not changed after insertion to search for activity.At each penetration position and after the closure of the modified Davies chamber with agarose and bone wax, we allowed the multielectrode array to settle and stabilize the recordings for 10 -20 min.Each block of sensory stimulation was initiated by 15 min of recording of spontaneous activity and was concluded by 15 min recording of spontaneous activity to exclude drifts of the general state of the animals.This approach allowed us to ensure a constant light anesthetic state.We paid attention to avoid deep anesthesia with burst suppression to prevent possible abnormal heteromodal responses in the cortex (Land et al., 2012).During the neuronal recordings, isoflurane concentration was reduced to 1.0 -1.2 volume percentage, and adequacy of anesthesia depth was monitored to ensure comparable anesthesia levels and to avoid periods of burst suppression. The number of spontaneously active sites was similar for HCs and CDCs, with more spontaneous activity in the visual cortex than in the auditory dorsal cortex in both groups (CDCs: 63 Ϯ 7% in DZ vs 84 Ϯ 6% in MLS, WMW test, p ϭ 0.03; HCs: 53 Ϯ 5% in DZ vs 75 Ϯ 11% in MLS; WMW test, p ϭ 0.029). We analyzed and included all electrode sites in the statistics.In the text, "position" refers to the penetration location in the cortex (Fig. 2B) and "site" refers to electrode sites deep in the cortex, of which there were 16 for each electrode array.In total, we analyzed 1440 recording sites (720 in the auditory and 720 in the visual cortex) in HCs and 1632 sites (816 in the visual and 816 in the auditory cortex) in CDCs. Sensory stimulation.eABR thresholds were determined at the beginning of the experiment (Fig. 1).The eABR threshold of the respective ears then was used as a reference current level.Electrical stimulation was wide bipolar between the apical-most and the basal-most contact of the implant, covering cochlear positions with characteristic frequencies Ͼ10 kHz (Kral et al., 2009). Auditory stimulation.For intracortical recordings, pulses were presented binaurally, from 2 dB below to 6 dB above the eABR threshold in 1 dB steps for each ear.The electrical stimulus was a triplet of biphasic pulses (200 s/phase at 500 pulses/s, giving a total stimulation time of 4.4 ms) applied in bipolar configuration between the basal-most electrode and the apical-most electrode of the CI.Pulse levels were randomized and the interstimulus intervals were 1000 ms.Each electrical stimulus was repeated 30 times. Visual stimulation.Visual stimuli were generated in MATLAB (The MathWorks) with the Psychophysics Toolbox (Brainard, 1997).Stimuli were presented on a TFT display (Model 2009wt; Dell) at a 28 cm distance in front of the contralateral eye.In analogy to the electrical pulse, we used a visual flash stimulus to study general visual responses.This stimulus is simple and broadly activates neurons in the visual system, both in the magnocellular and parvocellular subsystems.We presented 100 ms full-field flashes with positive contrast (white flash) or negative contrast (black flash).Each type of flash was repeated 50 times with an interstimulus interval of 1000 ms consisting of a gray background.Furthermore, to include apparent movement into the stimulus, square-wave phase reversal gratings of different orientations (0°, 45°, 90°, 135°) and spatial frequencies (0.1-2.0 cycles/degree) were used for visual stimulation. Bimodal stimulation.To investigate interactions between the visual and auditory responses, bimodal stimulation was used.Visual stimulus (full-field flash, 16.7 ms duration, one frame, 60 Hz refresh rate) was combined with auditory stimulation (triplet of biphasic pulses, 200 s/ phase, 500 Hz) at 6 dB above threshold.The onset of the stimuli varied across a range from Ϫ30 to 30 ms. Histology.After the experiment, the animals were transcardially perfused.After thoracotomy, 0.5 ml of heparin (Liquemin; Hoffman-La Roche) was injected into the left ventricle.Then, 2 L of phosphate buffer (0.1 M, pH 7.4) and 2 L of fixative (2.5% glutaraldehyde and 2.0% formaldehyde) were infused transcardially with pressure Ͼ100 mmHg.After 24 h of postfixation in 4% formaldehyde, the brain was excised from the skull, photographed, and a block containing the investigated cortical areas was cryoprotected in 30% sucrose, frozen, and cut in frontal plane in 50 m sections using a cryotome (Leica).The sections were first photographed in fluorescence mode to reveal the DiI (Keyence, BZ-9000).Subsequently, the sections were alternatively stained with Nissl and antibodies against SMI 32 (Mellott et al., 2010), allowing us to identify the borders of field A1, DZ, and lateral sulcus regions (LLS and MLS).All stained sections were then digitized and the penetrations were reconstructed (Keyence, BZ-9000).The DiI-stained penetrations were combined with photographs of SMI-32-stained (same) sections. Data analysis.Multiunits (MUs) were derived by band-pass filtering the raw signal between 700 Hz and 9 kHz.First, we determined all spike activity with amplitudes that exceeded a fixed threshold of 50 V (amplifier noise level Ͻ15 V), separating large spikes.A fixed spike threshold was used to ensure comparability between groups and multiunit firing rates.We additionally analyzed "continuous multiunit activity" (cMUA), including the all spike amplitudes (also the so-called "hash") using the 700 Hz high-pass filtered, rectified, and squared signal without thresholding.This signal was denoted as cMUA. Analysis of ongoing activity.To derive ongoing multiunit rate from 15 min intervals before and after stimulation, for each site, we randomly selected 100 intervals with a 1 s window length and calculated the mean rate of these 100 intervals for all sites.We subsequently excluded sites if firing rate was Ͻ0.1 Hz during the entire period (nonactive sites). Analysis of responses.Sites in CDCs and HCs were defined as responsive if neuronal activity was modulated by electrical stimulation via the CI satisfying a fixed statistical criterion for all sites (DZ and PMLS).Mean auditory responses were calculated for each of the 9 stimulation levels (Ϫ2 dB to 6 dB above the eABR threshold).Response strength was defined as the mean number of spikes in the interval 30 ms after stimulus onset; that is, the time window when auditory responses occurred.Auditory responses were ordered by stimulation level and the correlation coefficient between response strength and stimulation level was determined.If the coefficient was significant ( p Ͻ 0.05) or if the unit significantly responded above baseline in five of the nine stimulation levels (two-sided t test against baseline activity, p Ͻ 0.05), then the site was considered responsive to auditory input.For all responsive sites, the response latency was defined as the peak of the response at 6 dB above threshold.Visual responsiveness was considered as present in those neurons that showed a significant increase in firing rate within the 60 ms after the stimulus (␣ ϭ 5%).Visually evoked activity was tested against baseline multiunit activity before stimulus onset.Both rates were compared with a two-sided t test ( p Ͻ 0.05) and, if found significant, were collected as a response for further analysis.Response latency was defined as peak latency. Presence of bimodal enhancement was tested at those stimulus delays where peak responses overlapped.Quantification was performed using the enhancement index (EI) (Meredith and Stein, 1983) where VA is the firing rate with bimodal stimulation, V and A are the firing rates of visual alone and auditory alone stimulation, respectively, and max denotes the maximum function.To determine the additive or superadditive character of bimodal responses, the additive index (AI) was also used (King and Palmer, 1985) If not stated otherwise, all data are presented in the form of mean Ϯ SD.Data from animals were not pooled, statistical comparisons were per- formed at the animal level (5 CDCs vs 4 HCs).We used a nonparametric two-tailed WMW test with 5% significance level to compare data between cortical areas and between HCs and CDCs.
|
<li> <b>congenitally deaf white cats:</b> felisCatus (species)<li> <b>CDCs:</b> felisCatus (species)<li> <b>HCs:</b> felisCatus (species)<li> <b>cats:</b> felisCatus (species)<li> <b>auditory brainstem response:</b> Other (technique)<li> <b>ABR:</b> Other (technique)<li> <b>electrophysiological recording:</b> Other (technique)<li> <b>multielectrode arrays:</b> Other (technique)<li> <b>dorsal auditory cortex:</b> auditoryCortex (UBERONParcellation)<li> <b>DZ:</b> auditoryCortex (UBERONParcellation)<li> <b>visual areas:</b> visualCortex (UBERONParcellation)<li> <b>MLS:</b> Other (UBERONParcellation)
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"label": "UBERONParcellation",
"start": 11890
},
{
"end": 5250,
"label": "UBERONParcellation",
"start": 5238
},
{
"end": 3942,
"label": "UBERONParcellation",
"start": 3939
},
{
"end": 5520,
"label": "UBERONParcellation",
"start": 5517
},
{
"end": 6911,
"label": "UBERONParcellation",
"start": 6908
},
{
"end": 6970,
"label": "UBERONParcellation",
"start": 6967
},
{
"end": 10531,
"label": "UBERONParcellation",
"start": 10528
}
] | null | null |
16aa395a-d665-4f34-a5b2-b26e3ffa6175
|
completed
| 2025-04-29T14:36:04.699000 | 2025-05-27T14:00:41.400000 |
f9aa9a0a-0df4-4b7c-b27d-f87b5d697a10
|
The way an object is released by the passer to a partner is fundamental for the success of the handover and for the experienced fluency and quality of the interaction. Nonetheless, although its apparent simplicity, object handover involves a complex combination of predictive and reactive control mechanisms that were not fully investigated so far. Here, we show that passers use visual-feedback based anticipatory control to trigger the beginning of the release, to launch the appropriate motor program, and adapt such predictions to different speeds of the receiver's reaching out movements. In particular, the passer starts releasing the object in synchrony with the collision with the receiver, regardless of the receiver's speed, but the passer's speed of grip force release is correlated with receiver speed. When visual feedback is removed, the beginning of the passer's release is delayed proportionally with the receiver's reaching out speed; however, the correlation between the passer's peak rate of change of grip force is maintained. In a second study with 11 participants receiving an object from a robotic hand programmed to release following stereotypical biomimetic profiles, we found that handovers are experienced as more fluent when they exhibit more reactive release behaviours, shorter release durations, and shorter handover durations. The outcomes from the two studies contribute understanding of the roles of sensory input in the strategy that empower humans to perform smooth and safe handovers, and they suggest methods for programming controllers that would enable artificial hands to hand over objects with humans in an easy, natural and efficient way.
|
None
|
[
[
{
"end": 1483,
"label": "species",
"start": 1477
},
{
"end": 1642,
"label": "species",
"start": 1636
}
]
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"Incorrect"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"Correct"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"humans: homoSapiens (species)"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[] | null | null |
04dda3fa-c406-4141-966a-d28090fc05bb
|
completed
| 2025-04-29T14:36:04.699000 | 2025-05-27T14:00:41.491000 |
0895709f-39a7-4ebd-93c3-a539cb9e457a
|
We describe the clinical and radiological findings of a pair of siblings with cerebellar vermis hypoplasia and compare them with the literature. Both of them present pregnancies and deliveries uneventful and both presented some grade of hypotonia, ataxia, ocular motor abnormalities and mild motor delay and slurred speech. These siblings meet many of the criteria described in non-progressive congenital ataxia in which can occur familial cases with cerebellar atrophy, including vermis hypoplasia. As differential diagnosis we compare them with related syndromes and with Joubert's syndrome which main radiological finding on MRI is vermis hypoplasia associated with "molar tooth" appearance. The correct answer for these cases will only be possible by molecular genetics.
|
<li> <b>cerebellar vermis hypoplasia:</b> cerebellumVermisCulmen (UBERONParcellation)<li> <b>MRI:</b> magneticResonanceImaging (technique)
|
[
[
{
"end": 631,
"label": "technique",
"start": 628
},
{
"end": 95,
"label": "UBERONParcellation",
"start": 78
}
]
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"Partially correct"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"Partially correct"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
"cerebellar vermis: cerebellarVermis (UBERONParcellation)\r\n\n"
] |
[
"3c769fcb-8d37-41a2-b5e3-943a2a1090ab"
] |
[
"submitted"
] |
[
{
"end": 106,
"label": "UBERONParcellation",
"start": 78
},
{
"end": 631,
"label": "technique",
"start": 628
}
] | null | null |
End of preview. Expand
in Data Studio
Dataset Card for scilake-neuro
This dataset has been created with Argilla. As shown in the sections below, this dataset can be loaded into your Argilla server as explained in Load with Argilla, or used directly with the datasets library in Load with datasets.
Using this dataset with Argilla
To load with Argilla, you'll just need to install Argilla as pip install argilla --upgrade and then use the following code:
import argilla as rg
ds = rg.Dataset.from_hub("SIRIS-Lab/scilake-neuro", settings="auto")
This will load the settings and records from the dataset repository and push them to you Argilla server for exploration and annotation.
Using this dataset with datasets
To load the records of this dataset with datasets, you'll just need to install datasets as pip install datasets --upgrade and then use the following code:
from datasets import load_dataset
ds = load_dataset("SIRIS-Lab/scilake-neuro")
This will only load the records of the dataset, but not the Argilla settings.
Dataset Structure
This dataset repo contains:
- Dataset records in a format compatible with HuggingFace
datasets. These records will be loaded automatically when usingrg.Dataset.from_huband can be loaded independently using thedatasetslibrary viaload_dataset. - The annotation guidelines that have been used for building and curating the dataset, if they've been defined in Argilla.
- A dataset configuration folder conforming to the Argilla dataset format in
.argilla.
The dataset is created in Argilla with: fields, questions, suggestions, metadata, vectors, and guidelines.
Fields
The fields are the features or text of a dataset's records. For example, the 'text' column of a text classification dataset of the 'prompt' column of an instruction following dataset.
| Field Name | Title | Type | Required |
|---|---|---|---|
| text | Text | text | True |
| links | Linked entities | text | True |
Questions
The questions are the questions that will be asked to the annotators. They can be of different types, such as rating, text, label_selection, multi_label_selection, or ranking.
| Question Name | Title | Type | Required | Description | Values/Labels |
|---|---|---|---|---|---|
| span_label | Select and classify the tokens according to the specified categories. | span | True | N/A | ['preparationType', 'technique', 'biologicalSex', 'species', 'UBERONParcellation'] |
| assess_ner | Extracted entity validation | label_selection | True | Are the extracted entities correct? | ['Correct', 'Partially correct', 'Incorrect'] |
| assess_nel | Linked openMINDS entity validation | label_selection | True | Are the linked entities in openMINDS correct? | ['Correct', 'Partially correct', 'Incorrect'] |
| comments | Comments | text | False | Additional comments | N/A |
Data Splits
The dataset contains a single split, which is train.
Dataset Creation
Curation Rationale
[More Information Needed]
Source Data
Initial Data Collection and Normalization
[More Information Needed]
Who are the source language producers?
[More Information Needed]
Annotations
Annotation guidelines
Validation guidelines for selected openMINDS entities
Task Description
Your task is to validate the extraction of the different entities and their linking to their closest matching entries in the instances of the openMINDS controlled terms.
What to Validate
For each record, please verify the following:
- Entity Spans: Are all text spans correctly identified? Are the span boundaries accurate?
- Entity Types: Are entity types correctly assigned?
- Entity Linking: Are the matching entities in openMINDS correctly assigned?
Instructions
- Carefully read the texts.
- Review the NER spans and correct them if:
- The boundaries (start/end) are incorrect
- The entity label is wrong
- Verify that the extracted entities are correctly linked to their closest match in the vocabulary
- Add any comments or feedback you deem relevant
Validation Guidelines
- Entity Annotations: Mark spans as "Correct" only if boundaries and labels are accurate.
- Entity Extraction: Mark as "Correct" if all energy (storage) types mentioned are extracted; "Partially correct" if any are missing or incorrect.
- Vocabulary Linking: Mark as "Correct" if all links are to the appropriate entries. Use "Partially correct" if any are incorrect.
Entities
preparationTypetechniquebiologicalSexspeciesUBERONparcellation
Annotation process
[More Information Needed]
Who are the annotators?
[More Information Needed]
Personal and Sensitive Information
[More Information Needed]
Considerations for Using the Data
Social Impact of Dataset
[More Information Needed]
Discussion of Biases
[More Information Needed]
Other Known Limitations
[More Information Needed]
Additional Information
Dataset Curators
[More Information Needed]
Licensing Information
[More Information Needed]
Citation Information
[More Information Needed]
Contributions
[More Information Needed]
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