Neural Coding of Cell Assemblies via Spike-Timing Self-Information
| Autor: | Kun Xie, Zhifeng Shi, Liang Chen, Deheng Wang, Hui Kuang, Meng Li, Grace E. Fox, Joe Z. Tsien, Jun Liu, Fang Zhao, Ying Mao |
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| Rok vydání: | 2018 |
| Předmět: |
0301 basic medicine
Computer science Cognitive Neuroscience Carry (arithmetic) Models Neurological Information Theory Action Potentials Information theory Choice Behavior Mice 03 medical and health sciences Cellular and Molecular Neuroscience Discrimination Psychological 0302 clinical medicine Reaction Time Animals Evoked Potentials Anesthetics Neurons Self-information Pareto principle Brain Fear Carbocyanines 030104 developmental biology Time Perception Conditioning Operant Spike (software development) Noise (video) Sleep Neural coding Algorithm 030217 neurology & neurosurgery Decoding methods |
| Zdroj: | Cerebral Cortex. 28:2563-2576 |
| ISSN: | 1460-2199 1047-3211 |
| DOI: | 10.1093/cercor/bhy081 |
| Popis: | Cracking brain's neural code is of general interest. In contrast to the traditional view that enormous spike variability in resting states and stimulus-triggered responses reflects noise, here, we examine the "Neural Self-Information Theory" that the interspike-interval (ISI), or the silence-duration between 2 adjoining spikes, carries self-information that is inversely proportional to its variability-probability. Specifically, higher-probability ISIs convey minimal information because they reflect the ground state, whereas lower-probability ISIs carry more information, in the form of "positive" or "negative surprisals," signifying the excitatory or inhibitory shifts from the ground state, respectively. These surprisals serve as the quanta of information to construct temporally coordinated cell-assembly ternary codes representing real-time cognitions. Accordingly, we devised a general decoding method and unbiasedly uncovered 15 cell assemblies underlying different sleep cycles, fear-memory experiences, spatial navigation, and 5-choice serial-reaction time (5CSRT) visual-discrimination behaviors. We further revealed that robust cell-assembly codes were generated by ISI surprisals constituted of ~20% of the skewed ISI gamma-distribution tails, conforming to the "Pareto Principle" that specifies, for many events-including communication-roughly 80% of the output or consequences come from 20% of the input or causes. These results demonstrate that real-time neural coding arises from the temporal assembly of neural-clique members via silence variability-based self-information codes. |
| Databáze: | OpenAIRE |
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