Impact and sources of neuronal variability in the fly's motion vision pathway.

Nervous systems encode information about dynamically changing sensory input by changes in neuronal activity. Neuronal activity changes, however, also arise from noise sources within and outside the nervous system or from changes of the animal's behavioral state. The resulting variability of neuronal responses in representing sensory stimuli limits the reliability with which animals can respond to stimuli and may thus even affect the chances for survival in certain situations.

Relating neuronal to behavioral performance: variability of optomotor responses in the blowfly.

Behavioral responses of an animal vary even when they are elicited by the same stimulus. This variability is due to stochastic processes within the nervous system and to the changing internal states of the animal. To what extent does the variability of neuronal responses account for the overall variability at the behavioral level? To address this question we evaluate the neuronal variability at the output stage of the blowfly's (Calliphora vicina) visual system by recording from motion-sensitive interneurons mediating head optomotor responses.

Open-loop speed discrimination performance of ocular following response and perception.

So far, it remains largely unresolved to what extent neuronal noise affects behavioral responses. Here, we investigate, where in the human visual motion pathway noise originates that limits the performance of the entire system. In particular, we ask whether perception and eye movements are limited by a common noise source, or whether processing stages after the separation into different streams limit their performance.

Ocular following response to sampled motion.

We investigate the impact of monitor frame rate on the human ocular following response (OFR) and find that the response latency considerably depends on the frame rate in the range of 80-160 Hz, which is far above the flicker fusion limit. From the lowest to the highest frame rate the latency declines by roughly 10 ms. Moreover, the relationship between response latency and stimulus speed is affected by the frame rate, compensating and even inverting the effect at lower frame rates.

Information and discriminability as measures of reliability of sensory coding.

Response variability is a fundamental issue in neural coding because it limits all information processing. The reliability of neuronal coding is quantified by various approaches in different studies. In most cases it is largely unclear to what extent the conclusions depend on the applied reliability measure, making a comparison across studies almost impossible.

Implications of functionally different synaptic inputs for neuronal gain and computational properties of fly visual interneurons.

Neurons embedded in networks are thought to receive synaptic inputs that do not drive them on their own, but modulate the responsiveness to driving input. Although studies on brain slices have led to detailed knowledge of how nondriving input affects dendritic integration, its origin and functional implications remain unclear. We tackle this issue using an ensemble of fly wide-field visual interneurons.

Impact of photon noise on the reliability of a motion-sensitive neuron in the fly's visual system.

Variable behavioral responses to identical visual stimuli can, in part, be traced back to variable neuronal signals that provide unreliable information about the outside world. This unreliability in encoding of visual information is caused by several noise sources such as photon noise, synaptic noise, or the stochastic nature of ion channels. Neurons of the fly's visual motion pathway have been claimed to represent perfect encoders, with photon noise as the main noise source limiting their performance.

Variability of postsynaptic responses depends non-linearly on the number of synaptic inputs.

A conductance-based model for synaptic transmission and postsynaptic integration reveals how postsynaptic responses and their variability depend on the number of synaptic inputs. With increasing number of balanced stochastic excitatory and inhibitory inputs, the postsynaptic responses and their variance first increase and then decrease again. This non-linearity can be attributed to an anti-correlation between the total excitatory and inhibitory currents.

Neural encoding of behaviourally relevant visual-motion information in the fly.

Information processing in visual systems is constrained by the spatial and temporal characteristics of the sensory input and by the biophysical properties of the neuronal circuits. Hence, to understand how visual systems encode behaviourally relevant information, we need to know about both the computational capabilities of the nervous system and the natural conditions under which animals normally operate. By combining behavioural, neurophysiological and computational approaches, it is now possible in the fly to assess adaptations that process visual-motion information under the constraints of its natural input.