Different times TMS over fronto-parietal network regulates visual selective attention

Author:

Zhang Qiuzhu1,Zhang Danmei1,Alimu Gulibaier1,Bishal Guragai1,Li WenJuan1,Zhang Junjun1,Jin Zhenlan1,Li Ling1

Affiliation:

1. University of Electronic Science and Technology of China

Abstract

Abstract

Background Individuals pay attention to meaningful information by using visual selective attention. Top-down attention is goal-driven and requires cognitive effort to guide attention. Bottom-up attention is stimuli-driven and automatically attracted by salient stimuli. The fronto-parietal network (FPN) is involved in visual selective attention, and top-down and bottom-up attention from neuron activation in the FPN at different times. To explore how different times of transcranial magnetic stimulation (TMS) over the nodes of FPN modulate visual selective attention behavior. Methods The single-pulse TMS was applied to stimulate the right dorsolateral prefrontal cortex (rDLPFC) and right superior parietal lobule (rSPL) of two groups (active TMS and sham TMS group) at early times (33ms, 50ms, 66ms, and 83ms) and late times (216ms, 233ms, 250ms, and 266ms) after the pop-out and search stimulus displayed onset. Results The behavior results showed late TMS over rDLPFC decreased ACC of top-down attention. Late TMS over rSPL improved ACC of top-down attention and decreased cognitive load difference between top-down and bottom-up attention. Voxel-based morphometry (VBM) results of T1 images showed that gray matter volumes (GMV) in fronto-parietal cortex correlated with visual selective attention behavior, including bilateral superior frontal gyrus, right precentral gyrus, left supramarginal gyrus, right inferior frontal gyrus (orbital part), and left superior frontal gyrus (medial), especially in the active TMS group. Conclusions Our findings reveal the cause role of the FPN on visual selective attention behavior and the relationship between GMV in the fronto-parietal cortex and visual selective attention.

Publisher

Research Square Platform LLC

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