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

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 …

Information is carried in the brain by the joint activity patterns of large groups of neurons.
Understanding the structure and function of population neural codes is challenging because of …

Entropy and information provide natural measures of correlation among elements in a
network. We construct here the information theoretic analog of connected correlation functions: …

In retina and in cortical slice the collective response of spiking neural populations is well
described by “maximum-entropy” models in which only pairs of neurons interact. We asked, …

The firing reliability and precision of an isopotential membrane patch consisting of a realistically
large number of ion channels is investigated using a stochastic Hodgkin-Huxley (HH) …

A key issue in understanding the neural code for an ensemble of neurons is the nature and
strength of correlations between neurons and how these correlations are related to the …

We have explored the manner in which the population of retinal ganglion cells collectively
represent the visual world. Ganglion cells in the salamander were recorded simultaneously …

10.7554/eLife.00759.001 Social behavior in mammals is often studied in pairs under artificial
conditions, yet groups may rely on more complicated social structures. Here, we use a …

In vision, two mixtures, each containing an independent set of many different wavelengths,
may produce a common color percept termed “white.” In audition, two mixtures, each …