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Updated: May 18, 2026

Modeling the Functional Network for Spatial Navigation in the Human Brain

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

Predicting errors from reconfiguration patterns in human brain networks.

Matthias Ekman¹, Jan Derrfuss, Marc Tittgemeyer

¹Radboud University Nijmegen, Donders Institute for Brain, Cognition, and Behaviour, Nijmegen 6500 HE, The Netherlands. matthias.ekman@gmail.com

Proceedings of the National Academy of Sciences of the United States of America

|September 27, 2012

Summary

This summary is machine-generated.

Brain network topology dynamically reconfigures during task preparation, with a core-periphery structure guiding behavior. Successful task performance relies on these anticipatory network adjustments.

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Area of Science:

Neuroscience
Cognitive Science
Network Science

Background:

Task preparation involves anticipatory cognitive adjustments for future performance.
Quantitative network parameters governing human task preparation remain largely unknown.

Purpose of the Study:

To investigate the large-scale topological network parameters governing human task preparation.
To understand how dynamic network reconfigurations facilitate optimal task performance and guide behavior.

Main Methods:

Functional magnetic resonance imaging (fMRI) to measure brain activity.
Functional connectivity analysis to assess network topology and dynamics.
A novel network decoding approach to identify characteristic network patterns.

Main Results:

The brain network involved in task preparation exhibits a core-periphery structure.
Dynamic adjustments in core-periphery interactions were observed during task preparation.
Task-relevant visual areas showed increased centrality and interconnectivity with the network core.
Failure to reconfigure network topology predicted errors, highlighting its importance for performance.

Conclusions:

Anticipatory network reconfigurations are crucial for successful task performance.
The identified core-periphery network structure dynamically guides behavior during preparation.
A general framework for analyzing dynamic network properties in neuroscience was developed.