4.5 Article

Visual association learning induces global network reorganization

Journal

NEUROPSYCHOLOGIA
Volume 154, Issue -, Pages -

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.neuropsychologia.2021.107789

Keywords

Visual association learning; Multivariate connectivity pattern analysis; Network reorganization; Top-down processing

Funding

  1. National Natural Science Foundation of China [31861143039, 31872786]
  2. National Basic Research Program of China [2018YFC0810602]

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It has been shown that visual learning involves global network reorganization through complex interactions between bottom-up and top-down processes, with changes mainly driven by high-level networks involved in attention and cognitive control.
It has been proposed that visual learning is accomplished not only by neural plasticity in the visual cortex, but also by complex interactions between bottom-up and top-down processes that may induce global network reorganization. Here, we applied a multivariate analysis to functional connectivity (FC) patterns across the brain to investigate how visual association learning was achieved through large-scale network reorganization. Par-ticipants were trained to associate a set of artificial line-drawing objects with English letters. After three consecutive days of training, participants underwent a functional magnetic resonance imaging scan in which they were presented with the trained stimuli, untrained stimuli, and English words. By calculating pairwise FC between 189 nodes of 10 well-established networks across the brain, we found that the visual association learning induced changes in the global FC pattern when viewing the trained stimuli, rendering it more similar to the FC pattern when viewing English words. Critically, the learning-induced global FC pattern differences were mainly driven by the FC related to the high-level networks involved in attention and cognitive control, suggesting the modification of top-down processes during learning. In sum, our study provides one of the first evidence revealing global network reorganization induced by visual learning and sheds new light on the network mechanisms of top-down influences in learning.

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