Reconstructing Sources Location of Visual Color Cortex by the Task-irrelevant Visual Stimuli Through Machine Learning Decoding

Overview

Journal Heliyon

Specialty Social Sciences

Date 2022 Dec 30

PMID 36582686

Authors

Yijia Wu

Yanni Zhang

Yanjing Mao

Kaiqiang Feng

Donglai Wei

Liang Song

Affiliations

Soon will be listed here.

Abstract

Visual color sensing is generated by electrical discharges from endocranial neuronal sources that penetrate the skull and reach to the cerebral cortex. However, the space location of the source generated by this neural mechanism remains elusive. In this paper, we emulate the generation of visual color signal by task-irrelevant stimuli to activate brain neurons, where its consequences over the cerebral cortex is experimentally tracked. We first document the changes to brain color sensing using electroencephalography (EEG), and find that the sensing classification accuracy of primary visual cortex (V1) regions was positively correlated with the space correlation of visual evoked potential (VEP) power distribution under machine learning decoding. We then explore the decoded results to trace the brain activity neural source location of EEG inversion problem and assess its reconstructive possibility. We show that visual color EEG in V1 can reconstruct endocranial neuronal source location, through the machine learning decoding of channel location.

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