*********************************
There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
*********************************
Behnaz Yousefi
BioE PhD Proposal Presentation
March 1, 2019, 9am
Emory HSRB E182
Advisor:
Shella Keilholz (Georgia Institute of Technology and Emory University)
Committee Members:
Dr Bruce Crosson (Emory University and Georgia State University)
Dr Eric Schumacher (Georgia Institute of Technology)
Dr Anabelle Singer (Georgia Institute of Technology and Emory University)
Dr Garth Thompson (Shanghai Tech University)
Quasi-periodic patterns of the brain’s intrinsic activity and their contribution to functional connectivity, cortical and sub-cortical dynamics, and behavioral correlates
The intrinsic activity of the brain exhibits varied dynamics, among which are the infra-slow quasiperiodic spatiotemporal patterns (QPPs). In humans, QPPs involve a ~20s cycle of activation and deactivation of the macroscale networks. Because of the specific dynamics within each QPP, they are likely to be influential contributors to the widely used measures based on the functional connectivity (FC). Intrinsic FC between and within the macroscale networks can predict behavioral traits and states or can be used as biomarker for psychiatric disorders and neurological diseases. Therefore, a better understanding of the contributing patterns to the intrinsic FC entails significance. This project aims to: 1. Improve the method to detect QPPs, examine their relationship with the physiological fluctuations and head motion, and show the extent of their contribution to the functional connectivity by regression. 2. Characterize the dynamics within QPPs at the cortical and subcortical regions, in terms of patterns of coactivity or propagation of activity, compare the results with the existing FC-based parcellations or gradients, and specify the novel messages revealed by QPPs about the intrinsic macroscale functional organization of the brain. 3. Examine the behavioral correlates of QPPs by relating the cognitive and psychological measures to various QPP metrics.
