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. In the context of courtship, we observed large quantities of electrocommunication signals. Echo responses, acknowledgment signals, and their synchronizing role in spawning demonstrated the behavioral relevance of these signals. In both courtship and aggressive contexts, we observed robust behavioral responses in stimulus regimes that have so far been neglected in electrophysiological studies of this well characterized sensory system and that are well beyond the range of known best frequency and amplitude tuning of the electroreceptor afferents' firing rate modulation. Our results emphasize the importance of quantifying sensory scenes derived from freely behaving animals in their natural habitats for understanding the function and evolution of neural systems. The processing mechanisms of sensory systems have evolved in the context of the natural lives of organisms. To understand the functioning of sensory systems therefore requires probing them in the stimulus regimes in which they evolved. We took advantage of the continuously generated electric fields of weakly electric fish to explore electrosensory stimulus statistics in their natural Neotropical habitat. Unexpectedly, many of the electrocommunication signals recorded during courtship, spawning, and aggression had much smaller amplitudes or higher frequencies than stimuli used so far in neurophysiological characterizations of the electrosensory system. Our results demonstrate that quantifying sensory scenes derived from freely behaving animals in their natural habitats is essential to avoid biases in the choice of stimuli used to probe brain function.

No abstract

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. Here, we propose a simple format, the “open metaData Markup Language” (odML), for collecting and exchanging metadata in an automated, computer-based fashion. In odML arbitrary metadata information is stored as extended key–value pairs in a hierarchical structure. Central to odML is a clear separation of format and content, i.e., neither keys nor values are defined by the format. This makes odML flexible enough for storing all available metadata instantly without the necessity to submit new keys to an ontology or controlled terminology. Common standard keys can be defined in odML-terminologies for guaranteeing interoperability. We started to define such terminologies for neurophysiological data, but aim at a community driven extension and refinement of the proposed definitions. By customized terminologies that map to these standard terminologies, metadata can be named and organized as required or preferred without softening the standard. Together with the respective libraries provided for common programming languages, the odML format can be integrated into the laboratory workflow, facilitating automated collection of metadata information where it becomes available. The flexibility of odML also encourages a community driven collection and definition of terms used for annotating data in the neurosciences.

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. Here we experimentally test the theoretical predictions by quantifying and comparing neuronal response properties in tuberous and ampullary electroreceptor afferents of the weakly electric fish Apteronotus leptorhynchus. These related systems show similar levels of synchronous activity, but only in the more irregularly firing tuberous afferents a synchrony code is established, whereas in the more regularly firing ampullary afferents it is not. The mere existence of synchronous activity is thus not sufficient for a synchrony code. Single-cell features such as the irregularity of spiking and the frequency dependence of the neuron's transfer function determine whether synchronous spikes possess a distinct meaning for the encoding of time-dependent signals. Because of the strong nonlinearity of the spiking threshold, neural noise can be beneficial by improving the representation of stimuli in populations of spiking neurons (3-7). Noise reduces the precision with which spikes lock to the stimulus (1). In populations of neurons that share a common input, for example by having overlapping receptive fields, noise as well as population heterogeneity has the advantage to decorrelate the responses (8, 9). That is, only those stimulus features that drive the population strongest could synchronize the response across neurons and thereby signal the presence of a particularly important stimulus.The role of synchronous activity in the cortex is widely discussed (6, 10-12), e.g., as a possible solution for the binding problem (for review see, e.g., refs. 13 and 14), as a separate information channel to relay visual information from thalamus to visual cortex (15), as a mechanism for gain control in visual cortex (16), or as a code for odor categories in zebrafish olfactory bulb (17).A synchrony code requires that asynchronously firing populations are synchronized or, vice versa, synchronization is escaped under certain conditions or by specific stimuli. In weakly electric fish, changes in the level of synchronization are considered an important cue for the detection of communication signals on the level of the receptor afferents (18-21) and subsequent processing in hind-and midbrain neurons (22,23). Middleton et al. (24) demonstrated that reading out population activity of electrosensory neurons with either integrators or coincidence detectors results in two distinct representations of sensory stimuli. Integrators encode low stimulus frequencies, approximately matching frequencies characteristic of prey detection and navigation. Coincidence detectors discard low-frequency information and encode predominantly higher frequencies matching the ones of c...