fMRI-based spiking neural network verified by anti-damage capabilities under random attacks.

Research on brain-like models with bio-rationality promotes the development of artificial intelligence. However, the topology of a brain-like model still lacks bio-rationality. Bio-brains have self-adaptive robustness. The purpose of this paper is to investigate a more bio-rational brain-like model verified by anti-damage capabilities. Thus, this paper proposes a new spiking neural network (SNN) constrained by a functional brain network based on human-brain functional magnetic resonance imaging (fMRI-SNN). Then, we investigate the anti-damage capabilities of our fMRI-SNN, and discuss the mechanism of these anti-damage capabilities. Our results indicate the following: (i) The fMRI-SNN has anti-damage capabilities under random attacks evaluated by two anti-damage indicators. Based on the relevance analysis, our discussion implies that the intrinsic element of the anti-damage capabilities is the synaptic plasticity. (ii) The anti-damage capabilities of our fMRI-SNN outperform those of the scale-free SNN and the small-world SNN. Our discussion on dynamic topological characteristics further implies that the network topology is an element that impacts the performance level of the anti-damage capabilities. • A more bio-rational brain-like model (fMRI-SNN) is proposed. • The performance of fMRI-SNN is verified by anti-damage capabilities. • The anti-damage mechanism of fMRI-SNN is discussed. [ABSTRACT FROM AUTHOR]