Neuron perceptron model based on artificial neural network about decision-making behavior of macaque auditory cortex
Author: 
Yumei GongAuthors Info & Claims
Pages 449 - 453
Abstract
Perceptron is the simplest artificial neural network. As a simplified mathematical model, perceptron can explain how brain neurons work. In the decision making behavior pattern, it is not clear how the response of single or group neurons decodes and determines the subject's behavior choice. In this paper, the neuron perception model is used to study how neurons in different auditory regions cooperate in the decision-making behavior of detecting deviant stimuli, and whether different regions play different roles. Our results have shown that neurons in different regions may act alone, but neurons in the core region (A1 and R) are linearly separable. We believe that neurons in the core region of the auditory cortex may work synergistically in decision-making behavior. This is of great significance for us to study the neural decoding of primate decision-making behavior.
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- Neuron perceptron model based on artificial neural network about decision-making behavior of macaque auditory cortex
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Published In
October 2021
593 pages
ISBN:9781450395588
DOI:10.1145/3500931
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Association for Computing Machinery
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Published: 22 December 2021
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ISAIMS 2021
ISAIMS 2021: 2nd International Symposium on Artificial Intelligence for Medicine Sciences
October 29 - 31, 2021
Beijing, China
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Overall Acceptance Rate 53 of 112 submissions, 47%
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