The criticality hypothesis: how local cortical networks might optimize information processing

被引:339
作者
Beggs, John M. [1 ]
机构
[1] Indiana Univ, Dept Phys, Bloomington, IN 47405 USA
来源
PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES | 2008年 / 366卷 / 1864期
关键词
edge of chaos; neural network; power law; criticality; cortex; avalanche;
D O I
10.1098/rsta.2007.2092
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Early theoretical and simulation work independently undertaken by Packard, Langton and Kauffman suggested that adaptability and computational power would be optimized in systems at the 'edge of chaos', at a critical point in a phase transition between total randomness and boring order. This provocative hypothesis has received much attention, but biological experiments supporting it have been relatively few. Here, we review recent experiments on networks of cortical neurons, showing that they appear to be operating near the critical point. Simulation studies capture the main features of these data and suggest that criticality may allow cortical networks to optimize information processing. These simulations lead to predictions that could be tested in the near future, possibly providing further experimental evidence for the criticality hypothesis.
引用
收藏
页码:329 / 343
页数:15
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