Discrete scaling and criticality in a chain of adaptive excitable integrators

被引:0
作者
Martinez-Saito, Mario [1 ,2 ]
机构
[1] HSE Univ, Inst Cognit Neurosci, Moscow, Russia
[2] Natl Univ Singapore, Dept Psychol, Singapore, Singapore
关键词
Hierarchical modeling; Diffusion; Self-organization; SELF-ORGANIZED CRITICALITY; RANGE TEMPORAL CORRELATIONS; FREE-ENERGY PRINCIPLE; NEURONAL AVALANCHES; BAYESIAN-INFERENCE; PARIETAL CORTEX; CEREBRAL-CORTEX; VISUAL-CORTEX; DYNAMICS; BRAIN;
D O I
10.1016/j.chaos.2022.112574
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
We describe a chain of unidirectionally coupled adaptive excitable elements slowly driven by a stochastic process from one end and open at the other end, as a minimal toy model of unresolved irreducible uncertainty in a system performing inference through a hierarchical model. Threshold potentials adapt slowly to ensure sensitivity without being wasteful. Activity and energy are released as intermittent avalanches of pulses with a discrete scaling distribution largely independent of the exogenous input form. Subthreshold activities and threshold potentials exhibit Lorentzian temporal spectra, with a power-law range determined by position in the chain. Subthreshold bistability closely resembles empirical measurements of intracellular membrane potential. We suggest that critical cortical cascades emerge from a trade-off between metabolic power consumption and performance requirements in a critical world, and that the temporal scaling patterns of brain electrophysiological recordings ensue from weighted linear combinations of subthreshold activities and pulses from different hierarchy levels.
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页数:35
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