Biomedical subjects

J Kretzberg

Publications and source records attributed to J Kretzberg.

4 recordsLinked to original sources

PubMed2000

Reliability of a fly motion-sensitive neuron depends on stimulus parameters.

The variability of responses of sensory neurons constrains how reliably animals can respond to stimuli in the outside world. We show for a motion-sensitive visual interneuron of the fly that the variability of spike trains depends on the properties of the motion stimulus, although differently for different stimulus parameters. (1) The spike count variances of responses to constant and to dynamic stimuli lie in the same range. (2) With increasing stimulus size, the variance may slightly decrease. (3) Increasing pattern contrast reduces the variance considerably. For all stimulus conditions, the spike count variance is much smaller than the mean spike count and does not depend much on the mean activity apart from very low activities. Using a model of spike generation, we analyzed how the spike count variance depends on the membrane potential noise and the deterministic membrane potential fluctuations at the spike initiation zone of the neuron. In a physiologically plausible range, the variance is affected only weakly by changes in the dynamics or the amplitude of the deterministic membrane potential fluctuations. In contrast, the amplitude and dynamics of the membrane potential noise strongly influence the spike count variance. The membrane potential noise underlying the variability of the spike responses in the motion-sensitive neuron is concluded to be affected considerably by the contrast of the stimulus but by neither its dynamics nor its size.

Action Potentials↗

PubMed1998

Temporal precision of the encoding of motion information by visual interneurons.

BACKGROUND: There is much controversy about the timescale on which neurons process and transmit information. On the one hand, a vast amount of information can be processed by the nervous system if the precise timing of individual spikes on a millisecond timescale is important. On the other hand, neuronal responses to identical stimuli often vary considerably and stochastic response fluctuations can exceed the mean response amplitude. Here, we examined the timescale on which neural responses could be locked to visual motion stimuli. RESULTS: Spikes of motion-sensitive neurons in the visual system of the blowfly are time-locked to visual motion with a precision in the range of several tens of milliseconds. Nevertheless, different motion-sensitive neurons with largely overlapping receptive fields generate a large proportion of spikes almost synchronously. This precision is brought about by stochastic rather than by motion-induced membrane-potential fluctuations elicited by the common peripheral input. The stochastic membrane-potential fluctuations contain more power at frequencies above 30-40 Hz than the motion-induced potential changes. A model of spike generation indicates that such fast membrane-potential changes are a major determinant of the precise timing of spikes. CONCLUSIONS: The timing of spikes in neurons of the motion pathway of the blowfly is controlled on a millisecond timescale by fast membrane-potential fluctuations. Despite this precision, spikes do not lock to motion stimuli on this timescale because visual motion does not induce sufficiently rapid changes in the membrane potential.

Action Potentials↗

PubMedDate not supplied

Membrane potential fluctuations determine the precision of spike timing and synchronous activity: a model study.

It is much debated on what time scale information is encoded by neuronal spike activity. With a phenomenological model that transforms time-dependent membrane potential fluctuations into spike trains, we investigate constraints for the timing of spikes and for synchronous activity of neurons with common input. The model of spike generation has a variable threshold that depends on the time elapsed since the previous action potential and on the preceding membrane potential changes. To ensure that the model operates in a biologically meaningful range, the model was adjusted to fit the responses of a fly visual interneuron to motion stimuli. The dependence of spike timing on the membrane potential dynamics was analyzed. Fast membrane potential fluctuations are needed to trigger spikes with a high temporal precision. Slow fluctuations lead to spike activity with a rate about proportional to the membrane potential. Thus, for a given level of stochastic input, the frequency range of membrane potential fluctuations induced by a stimulus determines whether a neuron can use a rate code or a temporal code. The relationship between the steepness of membrane potential fluctuations and the timing of spikes has also implications for synchronous activity in neurons with common input. Fast membrane potential changes must be shared by the neurons to produce synchronous activity.

Action Potentials↗

PubMedDate not supplied

Neural coding with graded membrane potential changes and spikes.

The neural encoding of sensory stimuli is usually investigated for spike responses, although many neurons are known to convey information by graded membrane potential changes. We compare by model simulations how well different dynamical stimuli can be discriminated on the basis of spiking or graded responses. Although a continuously varying membrane potential contains more information than binary spike trains, we find situations where different stimuli can be better discriminated on the basis of spike responses than on the basis of graded responses. Spikes can be superior to graded membrane potential fluctuations if spikes sharpen the temporal structure of neuronal responses by amplifying fast transients of the membrane potential. Such fast membrane potential changes can be induced deterministically by the stimulus or can be due to membrane potential noise that is influenced in its statistical properties by the stimulus. The graded response mode is superior for discrimination between stimuli on a fine time scale.

Action Potentials↗