Systems and methods for detection and prediction of brain disorders based on neural network interaction

摘要

Systems and methods obtain functional connectivity data in the whole brain to detect and predict brain disorders. This whole brain data is regionalized and then manipulated to derive functional connectivity data sets that can be used to show measured functional connectivity changes. This whole brain data may also be analyzed to determine changes in functional activity in both increased and decreased neural network connectivity. By identifying and then quantifying the functional connectivity differences between healthy and diseased subjects, a classification for individual subjects can be made.