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Abstract #2385

Effective Connectivity within the Resting-State Network using Spectral Dynamic Causal Modeling

Fatemeh Mohammadian1, Arash Zare Sadeghi2, Hanieh Mobarak Salari3, Mahsa Talebi1, Hassan Hashemi3, Hamid Reza Saligheh Rad1,4, and Maryam Noroozian5
1Department of Medical physics and Biomedical Engineering, Tehran university of medical sciences, TEHRAN, Iran (Islamic Republic of), 2Medical Physics Department, Iran University of Medical Sciences, TEHRAN, Iran (Islamic Republic of), 3Quantitative MR Imaging and Spectroscopy Group, Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, TEHRAN, Iran (Islamic Republic of), 4Quantitative MR Imaging and Spectroscopy Group, Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran (Islamic Republic of), 5Department of Psychiatry, Tehran university of medical sciences, TEHRAN, Iran (Islamic Republic of)

Synopsis

Alzheimer's disease (AD) is a network connection dysfunction syndrome. An approximate picture of functional integration and statistical dependence on responses between different regions of the brain can be defined by functional connectivity (FC). Explanation of the statistical dependencies and estimating how the dynamics of neurons affect each other remotely is done by effective connectivity (EC). Studying directional interactions between different regions of the brain plays a key role in our understanding of the functional integration of brain networks.

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