Executive Summary : | This proposal aims to study, characterize, and model the changes in functional dynamics of the brain in mild cognitive impairment Alzheimer disease (MCI-AD) and early Alzheimer's disease (AD) under resting and cognitive task conditions using EEG signals. Deficits reported in AD are due to changes in functional and structural networks. Identifying MCI-AD has a positive effect on the treatment protocol, as it could lead to effective management of the disease by decelerating the disease progression. The clinical measurements will be carried out at SCTIMST, Trivandrum, using a group control study from the age group of 50-80 years. The patients will be categorized into MCI-AD and early AD based on Clinical Dementia Rating (CDR) scores. Neuropsychological testing will be carried out using cognitive screening measures such as Mini Mental State Examination and Addenbrooke’s Cognitive Examination. Functional connectivity (FC) represents the correlation of neural activity between brain regions, and the mechanism involving the rapid transition between different networks is termed as metastability. The study will use the weighted phase lag Index to estimate FC, and a neurocomputational model will be developed to analyze the intricate relation between complexity and connectivity. Simulation studies using lesion will be undertaken to establish the relation between connectivity in the brain and the resultant effect on complexity. The proposed analysis will form an important study and could develop a model network degeneration associated with mild and early Alzheimer's disease. Phenomenological models derived from brain connectivity patterns could provide valuable insights about the disease progression and aid in the development of a reliable biomarker. |