Thermodynamics for a network of neurons: Signatures of criticality
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arXiv
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| Auteurs principaux: | , , , , , |
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| Format: | Preprint |
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2014
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| _version_ | 1866913686752329728 |
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| author | Tkacik, Gasper Mora, Thierry Marre, Olivier Amodei, Dario Berry II, Michael J. Bialek, William |
| author_facet | Tkacik, Gasper Mora, Thierry Marre, Olivier Amodei, Dario Berry II, Michael J. Bialek, William |
| contents | The activity of a neural network is defined by patterns of spiking and silence from the individual neurons. Because spikes are (relatively) sparse, patterns of activity with increasing numbers of spikes are less probable, but with more spikes the number of possible patterns increases. This tradeoff between probability and numerosity is mathematically equivalent to the relationship between entropy and energy in statistical physics. We construct this relationship for populations of up to N=160 neurons in a small patch of the vertebrate retina, using a combination of direct and model-based analyses of experiments on the response of this network to naturalistic movies. We see signs of a thermodynamic limit, where the entropy per neuron approaches a smooth function of the energy per neuron as N increases. The form of this function corresponds to the distribution of activity being poised near an unusual kind of critical point. Networks with more or less correlation among neurons would not reach this critical state. We suggest further tests of criticality, and give a brief discussion of its functional significance. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_1407_5946 |
| institution | arXiv |
| publishDate | 2014 |
| record_format | arxiv |
| spellingShingle | Thermodynamics for a network of neurons: Signatures of criticality Tkacik, Gasper Mora, Thierry Marre, Olivier Amodei, Dario Berry II, Michael J. Bialek, William Neurons and Cognition Disordered Systems and Neural Networks Statistical Mechanics The activity of a neural network is defined by patterns of spiking and silence from the individual neurons. Because spikes are (relatively) sparse, patterns of activity with increasing numbers of spikes are less probable, but with more spikes the number of possible patterns increases. This tradeoff between probability and numerosity is mathematically equivalent to the relationship between entropy and energy in statistical physics. We construct this relationship for populations of up to N=160 neurons in a small patch of the vertebrate retina, using a combination of direct and model-based analyses of experiments on the response of this network to naturalistic movies. We see signs of a thermodynamic limit, where the entropy per neuron approaches a smooth function of the energy per neuron as N increases. The form of this function corresponds to the distribution of activity being poised near an unusual kind of critical point. Networks with more or less correlation among neurons would not reach this critical state. We suggest further tests of criticality, and give a brief discussion of its functional significance. |
| title | Thermodynamics for a network of neurons: Signatures of criticality |
| topic | Neurons and Cognition Disordered Systems and Neural Networks Statistical Mechanics |
| url | https://arxiv.org/abs/1407.5946 |