| Paper: | PS-2A.36 |
| Session: | Poster Session 2A |
| Location: | Symphony/Overture |
| Session Time: | Friday, September 7, 17:15 - 19:15 |
| Presentation Time: | Friday, September 7, 17:15 - 19:15 |
| Presentation: |
Poster
|
| Publication: |
2018 Conference on Cognitive Computational Neuroscience, 5-8 September 2018, Philadelphia, Pennsylvania |
| Paper Title: |
Modeling Hippocampal-Cortical Dynamics During Event Processing |
| Manuscript: |
Click here to view manuscript |
| DOI: |
https://doi.org/10.32470/CCN.2018.1048-0 |
| Authors: |
Qihong Lu, Uri Hasson, Kenneth Norman, Princeton University, United States |
| Abstract: |
In this study, we present a two-component neural network model that describes how cortex and hippocampus jointly process event sequences. Cortex is modeled as a recurrent neural network, whose behavior is governed by actively maintained parameters specifying features of the current event. Hippocampus can take “snapshots” of sets of actively maintained parameters and then retrieve these parameter sets in response to partial cues. With functional alignment methods, we qualitatively captured patterns of inter-subject correlation (ISC) from a recent human neuroimaging study. Specifically, we observed enhanced ISC when hippocampus retrieved stored parameters relating to the current event and fed these into the cortex. These results support our formalization of how hippocampus and cortex collaboratively process events, and provide a proof-of-concept demonstration of our computational modeling framework for group-level “brain coupling” phenomena. |
