SearcharxivSearch

arXiv subjects

N. Brenner

Publications and source records attributed to N. Brenner.

3 recordsLinked to original sources

Symbols and synergy in a neural code

Understanding a neural code requires knowledge both of the elementary symbols that transmit information and of the algorithm for translating these symbols into sensory signals or motor actions. We show that these questions can be separated: the information carried by any candidate symbol in the code--- a pattern of spikes across time or across a population of cells---can be measured, independent of assumptions about what these patterns might represent. By comparing the information carried by a compound pattern with the information carried independently by its parts, we measure directly the synergy among these parts. We illustrate the use of these methods by applying them to experiments on the motion sensitive neuron H1 of the fly's visual system, where we confirm that two spikes close together in time carry far more than twice the information carried by a single spike. We analyze the sources of this synergy, and provide evidence that pairs of spikes close together in time may be special symbols in the code of H1.

physics.bio-ph

Statistical properties of spike trains: universal and stimulus-dependent aspects

Statistical properties of spike trains measured from a sensory neuron in-vivo are studied experimentally and theoretically. Experiments are performed on an identified neuron in the visual system of the blowfly. It is shown that the spike trains exhibit universal behavior over short time, modulated by a stimulus-dependent envelope over long time. A model of the neuron as a nonlinear oscillator driven by noise and an external stimulus, is suggested to account for these results. The model enables a theoretic distinction of the effects of internal neuronal properties from effects of external stimulus properties, and their identification in the measured spike trains. The universal regime is characterized by one dimensionless parameter, representing the internal degree of irregularity, which is determined both by the sensitivity of the neuron and by the properties of the noise. The envelope is related in a simple way to properties of the input stimulus as seen through nonlinearity of the neural response. Explicit formulas are derived for different statistical properties in both the universal and the stimulus-dependent regimes. These formulas are in very good agreement with the data in both regimes.

physics.bio-ph

Universal Statistical Behavior of Neural Spike Trains

We construct a model that predicts the statistical properties of spike trains generated by a sensory neuron. The model describes the combined effects of the neuron's intrinsic properties, the noise in the surrounding, and the external driving stimulus. We show that the spike trains exhibit universal statistical behavior over short times, modulated by a strongly stimulus-dependent behavior over long times. These predictions are confirmed in experiments on H1, a motion-sensitive neuron in the fly visual system.

physics.bio-ph