Thermodynamics and signatures of criticality in a network of neurons
| Autor: | Thierry Mora, Michael J. Berry, Dario Amodei, Gašper Tkačik, Olivier Marre, William Bialek, Stephanie E. Palmer |
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| Přispěvatelé: | Institute of Science and Technology [Klosterneuburg, Austria] (IST Austria), Laboratoire de Physique Statistique de l'ENS (LPS), Fédération de recherche du Département de physique de l'Ecole Normale Supérieure - ENS Paris (FRDPENS), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Diderot - Paris 7 (UPD7)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Institut de la Vision, Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Princeton University, Marre, Olivier |
| Rok vydání: | 2015 |
| Předmět: |
Hot Temperature
Nerve net [SDV]Life Sciences [q-bio] Entropy Monte Carlo method MESH: Neurons information MESH: Animals Statistical physics Monte Carlo Mathematics Neurons Multidisciplinary Artificial neural network MESH: Retina Brain neural networks MESH: Entropy MESH: Reproducibility of Results [SDV] Life Sciences [q-bio] medicine.anatomical_structure Criticality Physical Sciences Thermodynamics MESH: Thermodynamics Monte Carlo Method Algorithms MESH: Probability Models Neurological Urodela MESH: Algorithms MESH: Monte Carlo Method MESH: Hot Temperature Retina MESH: Brain MESH: Models Neurological medicine Entropy (information theory) Animals Probability Models Statistical Quantitative Biology::Neurons and Cognition Reproducibility of Results Numerosity adaptation effect MESH: Urodela MESH: Nerve Net correlation Thermodynamic limit Neuron Nerve Net Neuroscience MESH: Models Statistical |
| Zdroj: | Proceedings of the National Academy of Sciences of the United States of America Proceedings of the National Academy of Sciences of the United States of America, 2015, 112 (37), pp.11508-11513. ⟨10.1073/pnas.1514188112⟩ |
| ISSN: | 1091-6490 0027-8424 |
| Popis: | International audience; 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. We suggest further tests of criticality, and give a brief discussion of its functional significance. |
| Databáze: | OpenAIRE |
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