Searching for collective behavior in a large network of sensory neurons.
Maximum entropy models are the least structured probability distributions that exactly reproduce a chosen set of statistics measured in an interacting network. Here we use this principle to construct probabilistic models which describe the correlated spiking activity of populations of up to 120 neur...
Saved in:
| Main Authors: | Gašper Tkačik, Olivier Marre, Dario Amodei, Elad Schneidman, William Bialek, Michael J Berry |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2014-01-01
|
| Series: | PLoS Computational Biology |
| Online Access: | https://doi.org/10.1371/journal.pcbi.1003408 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
High Accuracy Decoding of Dynamical Motion from a Large Retinal Population.
by: Olivier Marre, et al.
Published: (2015-07-01) -
Error-Robust Modes of the Retinal Population Code.
by: Jason S Prentice, et al.
Published: (2016-11-01) -
Exactly solvable statistical physics models for large neuronal populations
by: Christopher W. Lynn, et al.
Published: (2025-05-01) -
Homeostatic synaptic normalization optimizes learning in network models of neural population codes
by: Jonathan Mayzel, et al.
Published: (2024-12-01) -
Social and spatial predictors of collective search behaviors
by: Marion Hoffman, et al.
Published: (2025-05-01)