arXiv subjects

W. Bialek

Publications and source records attributed to W. Bialek.

6 recordsLinked to original sources

arXiv2008

Combinatorial coding in neural populations

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 cortical population response. We have shown how a sensory stimulus could be estimated on a biologically-realistic time scale, given brief individual responses from a population of neurons with similar response properties. For neurons in extrastriate motion area MT, a combinatorial code, one that keeps track of the cell identity of action potentials and silences in individual neurons across the population, carries twice as much information about visual motion as does spike count averaged over the same group of cells. The combinatorial code is more informative because of the diverse firing rate dynamics of MT neurons in response to constant motion stimuli, and is robust to neuron-neuron correlations. We provide a theoretical motivation for these observations that challenges commonly held ideas about the nature of cortical coding at the level of single neurons and neural populations.

q-bio.NC↗

arXiv2003

Physical limits to biochemical signaling

Many crucial biological processes operate with surprisingly small numbers of molecules, and there is renewed interest in analyzing the impact of noise associated with these small numbers. Twenty--five years ago, Berg and Purcell showed that bacterial chemotaxis, where a single celled organism must respond to small changes in concentration of chemicals outside the cell, is limited directly by molecule counting noise, and that aspects of the bacteria's behavioral and computational strategies must be chosen to minimize the effects of this noise. Here we revisit and generalize their arguments to estimate the physical limits to signaling processes within the cell, and argue that recent experiments are consistent with performance approaching these limits.

physics.bio-ph↗

arXiv2001

Neural coding of naturalistic motion stimuli

We study a wide field motion sensitive neuron in the visual system of the blowfly {\em Calliphora vicina}. By rotating the fly on a stepper motor outside in a wooded area, and along an angular motion trajectory representative of natural flight, we stimulate the fly's visual system with input that approaches the natural situation. The neural response is analyzed in the framework of information theory, using methods that are free from assumptions. We demonstrate that information about the motion trajectory increases as the light level increases over a natural range. This indicates that the fly's brain utilizes the increase in photon flux to extract more information from the photoreceptor array, suggesting that imprecision in neural signals is dominated by photon shot noise in the physical input, rather than by noise generated within the nervous system itself.

physics.bio-ph↗

arXiv1999

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↗

arXiv1999

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↗

arXiv1998

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↗