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M J Chacron

Publications and source records attributed to M J Chacron.

3 recordsLinked to original sources

Firing statistics of a neuron model driven by long-range correlated noise.

We study the statistics of the firing patterns of a perfect integrate and fire neuron model driven by additive long-range correlated Ornstein-Uhlenbeck noise. Using a quasistatic weak noise approximation we obtain expressions for the interspike interval (ISI) probability density, the power spectral density, and the spike count Fano factor. We find unimodal, long-tailed ISI densities, Lorenzian power spectra at low frequencies, and a minimum in the Fano factor as a function of counting time. The implications of these results for signal detection are discussed.

Action Potentials↗

Negative interspike interval correlations increase the neuronal capacity for encoding time-dependent stimuli.

Accurate detection of sensory input is essential for the survival of a species. Weakly electric fish use amplitude modulations of their self-generated electric field to probe their environment. P-type electroreceptors convert these modulations into trains of action potentials. Cumulative relative refractoriness in these afferents leads to negatively correlated successive interspike intervals (ISIs). We use simple and accurate models of P-unit firing to show that these refractory effects lead to a substantial increase in the animal's ability to detect sensory stimuli. This assessment is based on two approaches, signal detection theory and information theory. The former is appropriate for low-frequency stimuli, and the latter for high-frequency stimuli. For low frequencies, we find that signal detection is dependent on differences in mean firing rate and is optimal for a counting time at which spike train variability is minimal. Furthermore, we demonstrate that this minimum arises from the presence of negative ISI correlations at short lags and of positive ISI correlations that extend out to long lags. Although ISI correlations might be expected to reduce information transfer, in fact we find that they improve information transmission about time-varying stimuli. This is attributable to the differential effect that these correlations have on the noise and baseline entropies. Furthermore, the gain in information transmission rate attributable to correlations exhibits a resonance as a function of stimulus bandwidth; the maximum occurs when the inverse of the cutoff frequency of the stimulus is of the order of the decay time constant of refractory effects. Finally, we show that the loss of potential information caused by a decrease in spike-timing resolution is smaller for low stimulus cutoff frequencies than for high ones. This suggests that a rate code is used for the encoding of low-frequency stimuli, whereas spike timing is important for the encoding of high-frequency stimuli.

Action Potentials↗

Suprathreshold stochastic firing dynamics with memory in P-type electroreceptors.

Weakly electric fish generate a periodic electric field as a carrier signal for active location and communication tasks. Highly sensitive P-type receptors on their surface fire in response to carrier amplitude modulations (AM's) in a noisy phase locked fashion. A simple generic model of receptor activity and signal encoding is presented. Its suprathreshold dynamics, memory and receptor noise reproduce observed firing interval distributions and correlations. The model ultimately explains how smooth responses to AM's are compatible with its nonlinear phase locking properties, and reveals how receptor noise can sometimes enhance the encoding of small yet suprathreshold AM's.

Animals↗