10.1073/pnas.1514188112
Tkacik, Gasper
Gasper
Tkacik0000-0002-6699-1455
Mora, Thierry
Thierry
Mora
Marre, Olivier
Olivier
Marre
Amodei, Dario
Dario
Amodei
Palmer, Stephanie
Stephanie
Palmer
Berry Ii, Michael
Michael
Berry Ii
Bialek, William
William
Bialek
Thermodynamics and signatures of criticality in a network of neurons
National Academy of Sciences
2015
2018-12-11T11:53:33Z
2020-01-21T13:18:37Z
journal_article
https://research-explorer.app.ist.ac.at/record/1701
https://research-explorer.app.ist.ac.at/record/1701.json
26330611
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.