English
 
User Manual Privacy Policy Disclaimer Contact us
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  Probing neural networks for dynamic switches of communication pathways

Finger, H., Gast, R., Gerloff, C., Engel, A. K., & König, P. (in press). Probing neural networks for dynamic switches of communication pathways. PLoS Computational Biology.

Item is

Basic

show hide
Item Permalink: http://hdl.handle.net/21.11116/0000-0005-3B3C-7 Version Permalink: http://hdl.handle.net/21.11116/0000-0005-3B3D-6
Genre: Journal Article

Files

show Files

Locators

show

Creators

show
hide
 Creators:
Finger, Holger 1, Author
Gast, Richard1, 2, Author              
Gerloff, Christian 1, Author
Engel, Andreas K. 1, Author
König, Peter 1, Author
Affiliations:
1External Organizations, ou_persistent22              
2Methods and Development Group MEG and Cortical Networks, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_2205650              

Content

show
hide
Free keywords: -
 Abstract: Dynamic communication and routing play important roles in the human brain to facilitate flexibility in task solving and thought processes. Here, we present a network perturbation methodology that allows to investigate dynamic switching between different network pathways based on phase offsets between two external oscillatory drivers. We apply this method in a computational model of the human connectome with delay-coupled neural masses. To analyze dynamic switching of pathways, we define four new metrics that measure dynamic network response properties for pairs of stimulated nodes. Evaluating these metrics for all network pathways, we found a broad spectrum of pathways with distinct dynamic properties and switching behaviors. Specifically, we found that 60.1% of node pairs can switch their communication from one pathway to another depending on their phase offsets. This indicates that phase offsets and coupling delays play an important computational role for the dynamic switching between communication pathways in the brain.

Details

show
hide
Language(s): eng - English
 Dates: 2019-11-18
 Publication Status: Accepted / In Press
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: -
 Identifiers: -
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: PLoS Computational Biology
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: San Francisco, CA : Public Library of Science
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: - Identifier: ISSN: 1553-734X
CoNE: https://pure.mpg.de/cone/journals/resource/1000000000017180_1