Effect of burst spikes on linear and nonlinear signal transmission in spiking neurons.

We study the impact of bursts on spike statistics and neural signal transmission. We propose a stochastic burst algorithm that is applied to a burst-free spike train and adds a random number of temporally-jittered burst spikes to each spike. This simple algorithm ignores any possible stimulus-dependence of bursting but allows to relate spectra and signal-transmission characteristics of burst-free and burst-endowed spike trains.

Receptive field sizes and neuronal encoding bandwidth are constrained by axonal conduction delays.

Studies on population coding implicitly assume that spikes from the presynaptic cells arrive simultaneously at the integrating neuron. In natural neuronal populations, this is usually not the case-neuronal signaling takes time and populations cover a certain space. The spread of spike arrival times depends on population size, cell density and axonal conduction velocity.

Beat encoding at mistuned octaves within single electrosensory neurons.

Beats are slow periodic amplitude modulations resulting from the superposition of two spectrally close periodic signals. The difference frequency between the signals sets the frequency of the beat. A field study in the electric fish showed the behavioral relevance of very high difference frequencies.

Simultaneous spike-time locking to multiple frequencies.

Locking of neural firing is ubiquitously observed in the brain and occurs when neurons fire at a particular phase or in synchronization with an external signal. Here we study in detail the locking of single neurons to multiple distinct frequencies at the example of p-type electroreceptor afferents in the electrosensory system of the weakly electric fish (brown ghost knifefish). We find that electrosensory afferents and pyramidal cells in the electrosensory lateral line lobe (ELL) lock to multiple frequencies, including the electric organ discharge (EOD) frequency, beat, and stimulus itself.

odMLtables: A User-Friendly Approach for Managing Metadata of Neurophysiological Experiments.

An essential aspect of scientific reproducibility is a coherent and complete acquisition of metadata along with the actual data of an experiment. The high degree of complexity and heterogeneity of neuroscience experiments requires a rigorous management of the associated metadata. The odML framework represents a solution to organize and store complex metadata digitally in a hierarchical format that is both human and machine readable.

Statistics of Natural Communication Signals Observed in the Wild Identify Important Yet Neglected Stimulus Regimes in Weakly Electric Fish.

Sensory systems evolve in the ecological niches that each species is occupying. Accordingly, encoding of natural stimuli by sensory neurons is expected to be adapted to the statistics of these stimuli. For a direct quantification of sensory scenes, we tracked natural communication behavior of male and female weakly electric fish, , in their Neotropical rainforest habitat with high spatiotemporal resolution over several days.

Synchronous spikes are necessary but not sufficient for a synchrony code in populations of spiking neurons.

Synchronous activity in populations of neurons potentially encodes special stimulus features. Selective readout of either synchronous or asynchronous activity allows formation of two streams of information processing. Theoretical work predicts that such a synchrony code is a fundamental feature of populations of spiking neurons if they operate in specific noise and stimulus regimes.

Weakly electric fish learn both visual and electrosensory cues in a multisensory object discrimination task.

Weakly electric fish use electrosensory, visual, olfactory and lateral line information to guide foraging and navigation behaviors. In many cases they preferentially rely on electrosensory cues. Do fish also memorize non-electrosensory cues? Here, we trained individuals of gymnotiform weakly electric fish Apteronotus albifrons in an object discrimination task.

Handling Metadata in a Neurophysiology Laboratory.

To date, non-reproducibility of neurophysiological research is a matter of intense discussion in the scientific community. A crucial component to enhance reproducibility is to comprehensively collect and store metadata, that is, all information about the experiment, the data, and the applied preprocessing steps on the data, such that they can be accessed and shared in a consistent and simple manner. However, the complexity of experiments, the highly specialized analysis workflows and a lack of knowledge on how to make use of supporting software tools often overburden researchers to perform such a detailed documentation.

Encoding of social signals in all three electrosensory pathways of Eigenmannia virescens.

Extracting complementary features in parallel pathways is a widely used strategy for a robust representation of sensory signals. Weakly electric fish offer the rare opportunity to study complementary encoding of social signals in all of its electrosensory pathways. Electrosensory information is conveyed in three parallel pathways: two receptor types of the tuberous (active) system and one receptor type of the ampullary (passive) system.

Static frequency tuning accounts for changes in neural synchrony evoked by transient communication signals.

Although communication signals often vary continuously on the underlying signal parameter, they are perceived as distinct categories. We here report the opposite case where an electrocommunication signal is encoded in four distinct regimes, although the behavior described to date does not show distinct categories. In particular, we studied the encoding of chirps by P-unit afferents in the weakly electric fish Apteronotus leptorhynchus.

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.

A Bottom-up Approach to Data Annotation in Neurophysiology.

Metadata providing information about the stimulus, data acquisition, and experimental conditions are indispensable for the analysis and management of experimental data within a lab. However, only rarely are metadata available in a structured, comprehensive, and machine-readable form. This poses a severe problem for finding and retrieving data, both in the laboratory and on the various emerging public data bases.

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.