How can artificial neural networks approximate the brain?

被引：13

作者：

Shao, Feng ^{[1
]}

Shen, Zheng ^{[1
]}

机构：

[1] Peking Univ, Sch Psychol & Cognit Sci, Beijing Key Lab Behav & Mental Hlth, Beijing, Peoples R China

来源：

FRONTIERS IN PSYCHOLOGY | 2023年 / 13卷

关键词：

dual neural node; neuron type; energy source mode; hierarchical architecture; spike-time encoding; emergent computation; executive control to socially cognitive behavior; HUMAN PREFRONTAL CORTEX; PYRAMIDAL NEURONS; DEFAULT MODE; VON ECONOMO; LIFE-SPAN; COMPUTATION; SPIKE; EVOLUTION; DYNAMICS; STORAGE;

D O I：

10.3389/fpsyg.2022.970214

中图分类号：

B84 [心理学];

学科分类号：

04 ; 0402 ;

摘要：

The article reviews the history development of artificial neural networks (ANNs), then compares the differences between ANNs and brain networks in their constituent unit, network architecture, and dynamic principle. The authors offer five points of suggestion for ANNs development and ten questions to be investigated further for the interdisciplinary field of brain simulation. Even though brain is a super-complex system with 10(11) neurons, its intelligence does depend rather on the neuronal type and their energy supply mode than the number of neurons. It might be possible for ANN development to follow a new direction that is a combination of multiple modules with different architecture principle and multiple computation, rather than very large scale of neural networks with much more uniformed units and hidden layers.

引用

页数：14

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