The article discusses the traditional methods for presenting brain lesion data and introduces an alternative method called "spatial normalization." Traditional methods, such as displaying lesions on standard templates, using text descriptions, or showing representative slices from CT or MRI scans, have limitations in terms of accuracy, comparability, and ease of interpretation. Spatial normalization involves scaling, rotating, and warping a patient's MRI scan to align it with a standard atlas, making lesion location and volume more comparable across patients. This technique is advantageous because it preserves the unique features of each brain while allowing for standardized comparisons. The article also addresses technical challenges that have hindered the widespread adoption of normalization, such as the need for high-resolution MRI scans, the complexity of normalization algorithms, and the incompatibility of clinical image formats with normalization software. Recent advances, including the development of free software like MRIcro and improvements in normalization algorithms, have made it easier for neuropsychologists to use normalized scans. The article concludes by emphasizing the importance of presenting anatomical data in a consistent framework to enhance the understanding of neurological syndromes and improve the integration of lesion studies with other cognitive neuroscience techniques.The article discusses the traditional methods for presenting brain lesion data and introduces an alternative method called "spatial normalization." Traditional methods, such as displaying lesions on standard templates, using text descriptions, or showing representative slices from CT or MRI scans, have limitations in terms of accuracy, comparability, and ease of interpretation. Spatial normalization involves scaling, rotating, and warping a patient's MRI scan to align it with a standard atlas, making lesion location and volume more comparable across patients. This technique is advantageous because it preserves the unique features of each brain while allowing for standardized comparisons. The article also addresses technical challenges that have hindered the widespread adoption of normalization, such as the need for high-resolution MRI scans, the complexity of normalization algorithms, and the incompatibility of clinical image formats with normalization software. Recent advances, including the development of free software like MRIcro and improvements in normalization algorithms, have made it easier for neuropsychologists to use normalized scans. The article concludes by emphasizing the importance of presenting anatomical data in a consistent framework to enhance the understanding of neurological syndromes and improve the integration of lesion studies with other cognitive neuroscience techniques.