Abstract #3558

A Framework for Causal Connectivity Analysis of fMRI in Patient Populations: An Application to Major Depression and Early Life Stress

Karthik Ramakrishnan Sreenivasan¹, Merida M. Grant², Gopikrishna Deshpande,³

¹ AU MRI Research Center, Department of Electrical and Computer Engineering, Auburn University, Auburn, AL, United States; ²Department of Psychiatry, University of Alabama School of Medicine, Birmingham, AL, United States; ³Department of Psychology, Auburn University, Auburn, AL, United States

The current study investigated effective connectivity in patients with Major depressive disorder (MDD). fMRI time series were deconvolved using a cubature Kalman filter to obtain underlying neural response which were input into a dynamic multivariate autoregressive model (dMVAR) to obtain effective connectivity metrics. The results showed that differential amygdala reactivity within MDD based on early life stress history was associated with failure of inhibition from medial or lateral PFC.