Faculty Contact: Rene Weber
The aim of this module is to gain an understanding of network representations of functional neuroimaging data at multiple scales, from cross-sectional representations of long time scales (such as resting state data) to more dynamic task-dependent network states. This module consists of an extensive reading list in network neuroscience literature as well as some initial analyses of datasets collected in the Media Neuroscience Lab. Finally, an experiment will be developed to collect new data regarding attentional networks during naturalistic tasks. The module will serve as a building block for a future module: “Investigating Dynamic Frontoparietal Network Allegiance Under Cognitive and Perceptual Load” to be completed Spring 2018.
- Fall 2017: Jacob Fisher