Differentiation Between Normal and Abnormal Functional Brain Connectivity Using Non-directed Model-Based Approach

Brain Connectivity refers to networks of functional and anatomical connections found throughout the brain. Multiple neural populations are connected by intricate connectivity circuits and interact with one another to exchange information, synchronize their activity, and participate in the accomplishment of complex cognitive tasks. Issues about how various brain regions contribute to cognition and their reciprocal roles have drawn the attention of researchers since the beginning of neuroscience. The interest in brain connection estimation has grown significantly due to the advancement of cutting-edge functional brain imaging techniques and the fine-tuning of sophisticated signal-processing algorithms. This study investigates the difference between functional brain connectivity patterns for normal and abnormal cases. The brain connectivity is quantified by encoding neighborhood relations into a connectivity matrix using a Non-directed Model-based technique, whose columns and rows represent various brain regions. This representation is then translated into a graphical model, which offers a way to quantify different topological data. The proposed approach enables us to study the pairwise relations between interacting brain regions. The results show that the normal subjects have the same functional connectivity pattern with 96% overall normal subjects. Moreover, most abnormal cases have different functional connectivity patterns than normal, depending on their abnormality. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.