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Related Experiment Video

Updated: Mar 27, 2026

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Spatiotemporal characterisation of information coding in the multiple demand network.

Hamid Karimi-Rouzbahani1,2, Anina N Rich3, Alexandra Woolgar1,4

  • 1Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, United Kingdom.

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Summary

The multiple-demand network (MDN) dynamically processes information, with distinct sub-networks specializing in stimulus details and task rules. This research clarifies the spatiotemporal coding within the MDN during complex cognitive tasks.

Keywords:
MEGdecodingfMRImultiple-demand networktemporal dynamics

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Area of Science:

  • Cognitive Neuroscience
  • Neuroimaging
  • Human Brain Function

Background:

  • The multiple-demand network (MDN) integrates information across diverse cognitive tasks.
  • The precise spatiotemporal information encoding within MDN nodes is not fully understood.

Purpose of the Study:

  • To investigate how different types of task-related information are encoded in the MDN.
  • To explore the spatiotemporal dynamics of information processing within MDN sub-networks.

Main Methods:

  • Collected fMRI and MEG data during a complex visual stimulus-response mapping task.
  • Utilized multivariate pattern analysis (MVPA) to decode stimulus, response, and rule information.
  • Employed model-based MEG-fMRI fusion to integrate temporal and spatial data.

Main Results:

  • Visual areas initially encoded stimulus hemifield information.
  • The MDN later encoded fine-grained stimulus details and task rules.
  • Distinct temporal coding profiles were observed between MDN sub-networks (cingulo-opercular vs. frontoparietal).

Conclusions:

  • The MDN exhibits dynamic information processing capabilities.
  • Evidence supports at least two distinct sub-networks within the MDN based on information coding.
  • This study enhances understanding of the neural basis of complex cognition.