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Modeling the Functional Network for Spatial Navigation in the Human Brain
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Visual association learning induces global network reorganization.

Mengxia Yu1, Xueting Li2, Yiying Song3

  • 1Bilingual Cognition and Development Lab, Center for Linguistics and Applied Linguistics, Guangdong University of Foreign Studies, Guangzhou, 510420, China.

Neuropsychologia
|February 15, 2021
PubMed
Summary
This summary is machine-generated.

Visual association learning reshapes brain networks, particularly those involved in attention and cognitive control. This study reveals global network reorganization, highlighting the role of top-down processes in learning.

Keywords:
Multivariate connectivity pattern analysisNetwork reorganizationTop-down processingVisual association learning

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Area of Science:

  • Neuroscience
  • Cognitive Science
  • Neuroimaging

Background:

  • Visual learning involves neural plasticity and interactions between bottom-up and top-down processes.
  • These processes may lead to global brain network reorganization.

Purpose of the Study:

  • To investigate large-scale network reorganization during visual association learning.
  • To examine how functional connectivity (FC) patterns change with learning.

Main Methods:

  • Multivariate analysis of functional connectivity (FC) patterns.
  • fMRI scans of participants trained to associate visual objects with letters.
  • Calculation of pairwise FC between 189 nodes across 10 brain networks.

Main Results:

  • Visual association learning induced global FC pattern changes when viewing trained stimuli.
  • Learned FC patterns resembled those observed when viewing English words.
  • Differences were primarily driven by FC within attention and cognitive control networks.

Conclusions:

  • Visual learning induces global network reorganization, not just localized plasticity.
  • Top-down processes, particularly those in attention and cognitive control networks, are modified during visual learning.