The article provides a comprehensive overview of voxel-based morphometry (VBM), a technique used to characterize brain differences in vivo using structural magnetic resonance images. VBM involves normalizing high-resolution images to a standard template, segmenting them into gray and white matter, smoothing the segments, and performing voxel-wise statistical analysis to identify significant differences between groups. The method has been applied to both healthy and diseased subjects, revealing subtle changes in brain structure associated with various neurological and psychiatric conditions, as well as gross structural abnormalities in diseases like multiple sclerosis and Alzheimer's disease. Studies on healthy subjects have also shown that learning and practice can lead to changes in brain structure, such as in the hippocampus and motor areas. The article discusses the limitations of VBM, including issues with normalization, segmentation, and the accuracy of localization, and highlights the importance of considering these limitations when interpreting results.The article provides a comprehensive overview of voxel-based morphometry (VBM), a technique used to characterize brain differences in vivo using structural magnetic resonance images. VBM involves normalizing high-resolution images to a standard template, segmenting them into gray and white matter, smoothing the segments, and performing voxel-wise statistical analysis to identify significant differences between groups. The method has been applied to both healthy and diseased subjects, revealing subtle changes in brain structure associated with various neurological and psychiatric conditions, as well as gross structural abnormalities in diseases like multiple sclerosis and Alzheimer's disease. Studies on healthy subjects have also shown that learning and practice can lead to changes in brain structure, such as in the hippocampus and motor areas. The article discusses the limitations of VBM, including issues with normalization, segmentation, and the accuracy of localization, and highlights the importance of considering these limitations when interpreting results.