upd md

README.md

@@ -14,13 +14,13 @@ language:
 ---
 
 # Dataset Card for "MuGeminorum/AAL-statistics-volumn"
-The AAL (Automated Anatomical Labeling) Statistics Volumetric dataset provides a comprehensive collection of brain volumetric measurements based on the AAL atlas. It encompasses statistical information on brain regions derived from structural magnetic resonance imaging (MRI) scans. Researchers commonly utilize this dataset for investigations related to neuroimaging, neuroscience, and brain structure analysis. The AAL Statistics Volumetric dataset plays a pivotal role in advancing our understanding of brain anatomy, enabling the development and evaluation of algorithms for automated brain region identification and volumetric analysis. With its wealth of volumetric data derived from diverse individuals, this dataset serves as a valuable resource for studies aimed at characterizing variations in brain structures across populations and contributing to advancements in neuroscientific research.
+The AAL (Automated Anatomical Labeling) Statistical Volume Dataset provides a comprehensive collection of brain volume measurements based on AAL atlases. It covers statistical information on brain regions derived from structural magnetic resonance imaging (MRI) scans. Researchers commonly utilize this dataset for studies related to neuroimaging, neuroscience, and structural analysis of the brain.The AAL Statistical Volume Dataset plays a key role in advancing our understanding of brain anatomy by supporting the development and evaluation of automated brain region identification and volume analysis algorithms. With its wealth of volumetric data from diverse individuals, the dataset provides an invaluable resource for studies aimed at characterizing structural changes in the brain between populations and facilitates advances in neuroscience research.
 
 ## Usage
 ```python
 from datasets import load_dataset
 
-data = load_dataset("MuGeminorum/AAL-statistics-volumn", split='train')
+data = load_dataset("MuGeminorum/AAL-statistics-volumn", split="train")
 
 for item in data:
     print(item)