activity
19992008
most citedIsing models for networks of real neurons

104 citations · 375 across the 17 of their papers we have counts for

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Showing q-bio.NCShow all

8 papers · 1 filter

q-bio.NC20082 cited

Combinatorial coding in neural populations

L. C. Osborne, S. E. Palmer, S. G. Lisberger +1

To evaluate the nature of the neural code in the cerebral cortex, we have used a combination of theory and experiment to assess how information is represented in a realistic cortic…

q-bio.NC20071 cited

Efficient representation as a design principle for neural coding and computation

William Bialek, Rob R. de Ruyter van Steveninck, Naftali Tishby

Does the brain construct an efficient representation of the sensory world? We review progress on this question, focusing on a series of experiments in the last decade which use fly…

q-bio.NC20062 cited

Neural coding of a natural stimulus ensemble: Uncovering information at sub-millisecond resolution

Ilya Nemenman, Geoffrey D. Lewen, William Bialek +1

Our knowledge of the sensory world is encoded by neurons in sequences of discrete, identical pulses termed action potentials or spikes. There is persistent controversy about the ex…

q-bio.NC2006104 cited

Ising models for networks of real neurons

Gasper Tkacik, Elad Schneidman, Michael J Berry +1

Ising models with pairwise interactions are the least structured, or maximum-entropy, probability distributions that exactly reproduce measured pairwise correlations between spins.…

q-bio.NC20065 cited

Synergy from Silence in a Combinatorial Neural Code

Elad Schneidman, Jason L. Puchalla, Ronen Segev +3

The manner in which groups of neurons represent events in the external world is fundamental to neuroscience. Here, we analyze the population code of the retina during naturalistic…

q-bio.NC2005

Weak pairwise correlations imply strongly correlated network states in a neural population

Elad Schneidman, Michael J. Berry, Ronen Segev +1

Biological networks have so many possible states that exhaustive sampling is impossible. Successful analysis thus depends on simplifying hypotheses, but experiments on many systems…