Conference Proceeding

Understanding the brain through artificial intelligence

Dr. Payel Das

The functional activation pattern within the human brain is known to have a time-varying nature. This dynamic nature of the brain connectome is known to be associated with human learning, behavior, development, and brain disorders, and are therefore is of high importance. In this talk, I will explain development of an analytic framework composed of sophisticated machine learning and network analysis methods. The aim is to automatically define neuro-markers by exploring the brain states and dynamics from high-dimensional brain functional imaging data. I will also talk about results obtained using this analytic framework. A network-dependent association between static and dynamic functional connectivity was revealed, which is related to cognitive flexibility. We further found existence of discrete, inherent brain states that are similarly populated in neuro-typical as well as in autistic subjects, revealing an intrinsic architecture of the brain landscape consistent across different populations. Interestingly, enhanced dynamics was revealed within autistic brain in our analysis, which allows us to define a neuro-marker for autism.

Published: 17 October 2017

Copyright:

Copyright: © 2017 Dr. Payel Das. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.