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

Supervised learning algorithm for analysis of communication signals in the weakly electric fish Apteronotus leptorhynchus

Signal analysis plays a preeminent role in neuroethological research. Traditionally, signal identification has been based on pre-defined signal (sub-)types, thus being subject to the investigator's bias. To address this deficiency, we have developed a supervised learning algorithm for the detection of subtypes of chirps-frequency/amplitude modulations of the electric organ discharge that are generated predominantly during electric interactions of individuals of the weakly electric fish Apteronotus leptorhynchus. This machine learning paradigm can learn, from a 'ground truth' data set, a function that assigns proper outputs (here: time instances of chirps and associated chirp types) to inputs (here: time-series frequency and amplitude data). By employing this artificial intelligence approach, we have validated previous classifications of chirps into different types and shown that further differentiation into subtypes is possible. This demonstration of its superiority compared to traditional methods might serve as proof-of-principle of the suitability of the supervised machine learning paradigm for a broad range of signals to be analyzed in neuroethology.

Environmental experiences shape sexually dimorphic neuronal circuits and behaviour

Dimorphic traits, shaped by both natural and sexual selection, ensure optimal fitness and survival of the organism. This includes neuronal circuits that are largely affected by different experiences and environmental conditions. Recent evidence suggests that sexual dimorphism of neuronal circuits extends to different levels such as neuronal activity, connectivity and molecular topography that manifest in response to various experiences, including chemical exposures, starvation and stress. In this review, we propose some common principles that govern experience-dependent sexually dimorphic circuits in both vertebrate and invertebrate organisms. While sexually dimorphic neuronal circuits are predetermined, they have to maintain a certain level of fluidity to be adaptive to different experiences. The first layer of dimorphism is at the level of the neuronal circuit, which appears to be dictated by sex-biased transcription factors. This could subsequently lead to differences in the second layer of regulation namely connectivity and synaptic properties. The third regulator of experience-dependent responses is the receptor level, where dimorphic expression patterns determine the primary sensory encoding. We also highlight missing pieces in this field and propose future directions that can shed light onto novel aspects of sexual dimorphism with potential benefits to sex-specific therapeutic approaches. Thus, sexual identity and experience simultaneously determine behaviours that ultimately result in the maximal survival success.

Detecting a periodic signal by a population of spiking neurons in the weakly nonlinear response regime

Motivated by experimental observations, we investigate a variant of the cocktail party problem: the detection of a weak periodic stimulus in the presence of fluctuations and another periodic stimulus which is stronger than the periodic signal to be detected. Specifically, we study the response of a population of stochastic leaky integrate-and-fire (LIF) neurons to two periodic signals and focus in particular on the question, whether the presence of one of the stimuli can be detected from the population activity. As a detection criterion, we use a simple threshold-crossing of the population activity over a certain time window. We show by means of the receiver operating characteristics (ROC) that the detectability depends only weakly on the time window of observation but rather strongly on the stimulus amplitude. Counterintuitively, the detection of the weak periodic signal can be facilitated by the presence of a strong periodic input current depending on the frequencies of the two signals and on the dynamical regime in which the neurons operate. Beside numerical simulations of the model, we present an analytical approximation for the ROC curve that is based on the weakly nonlinear response theory for a stochastic LIF neuron.

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. Here we analyze the consequences of population size and axonal conduction delays on the stimulus encoding performance in the electrosensory system of the electric fish Apteronotus leptorhynchus. We experimentally locate p-type electroreceptor afferents along the rostro-caudal body axis and relate locations to neurophysiological response properties. In an information-theoretical approach we analyze the coding performance in homogeneous and heterogeneous populations. As expected, the amount of information increases with population size and, on average, heterogeneous populations encode better than the average same-size homogeneous population, if conduction delays are compensated for. The spread of neuronal conduction delays within a receptive field strongly degrades encoding of high-frequency stimulus components. Receptive field sizes typically found in the electrosensory lateral line lobe of A. leptorhynchus appear to be a good compromise between the spread of conduction delays and encoding performance. The limitations imposed by finite axonal conduction velocity are relevant for any converging network as is shown by model populations of LIF neurons. The bandwidth of natural stimuli and the maximum meaningful population sizes are constrained by conduction delays and may thus impact the optimal design of nervous systems.

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 Apteronotus rostratus showed the behavioral relevance of very high difference frequencies. Contrary to expectations from previous studies, our electrophysiological data show strong responses of p-type electroreceptor afferents whenever the difference frequency approaches integer multiples (mistuned octaves) of the fish's own electric field frequency (carrier). Mathematical reasoning and simulations show that common approaches to extract amplitude modulations, such as Hilbert transform or half-wave rectification, are not sufficient to explain the responses at carrier octaves. Instead, half-wave rectification needs to be smoothed out, for example by a cubic function. Because electroreceptive afferents share many properties with auditory nerve fibers, these mechanisms may underly the human perception of beats at mistuned octaves as described by Ohm and Helmholtz.

Advances in non-invasive tracking of wave-type electric fish in natural and laboratory settings

Recent technological advances greatly improved the possibility to study freely behaving animals in natural conditions. However, many systems still rely on animal-mounted devices, which can already bias behavioral observations. Alternatively, animal behaviors can be detected and tracked in recordings of stationary sensors, e.g., video cameras. While these approaches circumvent the influence of animal-mounted devices, identification of individuals is much more challenging. We take advantage of the individual-specific electric fields electric fish generate by discharging their electric organ (EOD) to record and track their movement and communication behaviors without interfering with the animals themselves. EODs of complete groups of fish can be recorded with electrode arrays submerged in the water and then be tracked for individual fish. Here, we present an improved algorithm for tracking electric signals of wave-type electric fish. Our algorithm benefits from combining and refining previous approaches of tracking individual specific EOD frequencies and spatial electric field properties. In this process, the similarity of signal pairs in extended data windows determines their tracking order, making the algorithm more robust against detection losses and intersections. We quantify the performance of the algorithm and show its application for a data set recorded with an array of 64 electrodes distributed over a 12 m² section of a stream in the Llanos, Colombia, where we managed, for the first time, to track Apteronotus leptorhynchus over many days. These technological advances make electric fish a unique model system for a detailed analysis of social and communication behaviors, with strong implications for our research on sensory coding.

A Spark in the Dark: Uncovering Natural Activity Patterns of Mormyrid Weakly Electric Fish

To understand animal ecology, observation of wildlife in the natural habitat is essential, but particularly challenging in the underwater realm. Weakly electric fishes provide an excellent opportunity to overcome some of these challenges because they generate electric organ discharges (EODs) to sense their environment and to communicate, which can be detected non-invasively. We tracked the EOD and swimming activity of two species of mormyrid weakly electric fishes (Marcusenius victoriae and Petrocephalus degeni) over diel cycles in the laboratory, and we recorded EODs and environmental dissolved oxygen (DO) concentration and temperature over several months in a naturally hypoxic habitat in Uganda. Under laboratory conditions, both species showed increases of activity and exploration behavior that were closely synchronized to the onset of the dark phase. In the wild, fish preferred structurally complex habitats during the day, but dispersed toward open areas at night, presumably to forage and interact. Nocturnal increase of movement range coincided with diel declines in DO concentration to extremely low levels. The fact that fish showed pronounced nocturnal activity patterns in the laboratory and in the open areas of their habitat, but not under floating vegetation, indicates that light intensity exerts a direct effect on their activity. We hypothesize that being dark-active and tolerant to hypoxia increases the resistance of these fish against predators. This study establishes a new technology to record EODs in the field and provides a window into the largely unknown behavior of mormyrids in their natural habitat.

Electrocommunication signals and aggressive behavior vary among male morphs in an apteronotid fish, Compsaraia samueli

Within-species variation in male morphology is common among vertebrates and is often characterized by dramatic differences in behavior and hormonal profiles. Males with divergent morphs also often use communication signals in a status-dependent way. Weakly electric knifefish are an excellent system for studying variation in male morphology and communication and its hormonal control. Knifefish transiently modulate the frequency of their electric organ discharge (EOD) during social encounters to produce chirps and rises. In the knifefish Compsaraia samueli, males vary extensively in jaw length. EODs and their modulations (chirps and rises) have never been investigated in this species, so it is unclear whether jaw length is related to the function of these signals. We used three behavioral assays to analyze EOD modulations in male C. samueli: (1) artificial playbacks, (2) relatively brief, live agonistic dyadic encounters, and (3) long-term overnight recordings. We also measured circulating levels of two androgens, 11-ketotestosterone and testosterone. Chirp structure varied within and across individuals in response to artificial playback, but was unrelated to jaw length. Males with longer jaws were more often dominant in dyadic interactions. Chirps and rises were correlated with and preceded attacks regardless of status, suggesting these signals function in aggression. In longer-term interactions, chirp rate declined after one week of pairing, but was unrelated to male morphology. Levels of circulating androgens were low and not predictive of jaw length or EOD signal parameters. These results suggest that communication signals and variation in male morphology are linked to outcomes of non-breeding agonistic contests.

Mixed selectivity coding of sensory and motor social signals in the thalamus of a weakly electric fish

High-level neural activity often exhibits mixed selectivity to multivariate signals. How such representations arise and modulate natural behavior is poorly understood. We addressed this question in weakly electric fish, whose social behavior is relatively low dimensional and can be easily reproduced in the laboratory. We report that the preglomerular complex, a thalamic region exclusively connecting midbrain with pallium, implements a mixed selectivity strategy to encode interactions related to courtship and rivalry. We discuss how this code enables the pallial recurrent networks to control social behavior, including dominance in male-male competition and female mate selection. Notably, response latency analysis and computational modeling suggest that corollary discharge from premotor regions is implicated in flagging outgoing communications and thereby disambiguating self- versus non-self-generated signals. These findings provide new insights into the neural substrates of social behavior, multi-dimensional neural representation, and its role in perception and decision making.

The Use of Supervised Learning Models in Studying Agonistic Behavior and Communication in Weakly Electric Fish

Despite considerable advances, studying electrocommunication of weakly electric fish, particularly in pulse-type species, is challenging as very short signal epochs at variable intervals from a few hertz up to more than 100 Hz need to be assigned to individuals. In this study, we show that supervised learning approaches offer a promising tool to automate or semiautomate the workflow, and thereby allowing the analysis of much longer episodes of behavior in a reasonable amount of time. We provide a detailed workflow mainly based on open resource software. We demonstrate the usefulness by applying the approach to the analysis of dyadic interactions of Gnathonemus petersii. Coupling of the proposed methods with a boundary element modeling approach, we are thereby able to model the information gained and provided during agonistic encounters. The data indicate that the passive electrosensory input, in particular, provides sufficient information to localize a contender during the pre-contest phase, fish did not use or rely on the theoretically also available sensory information of the contest outcome-determining size difference between contenders before engaging in agonistic behavior.

Electrocommunication signals indicate motivation to compete during dyadic interactions of an electric fish

Animals across species compete for limited resources. Whereas in some species competition behavior is solely based on the individual's own abilities, other species assess their opponents to facilitate these interactions. Using cues and communication signals, contestants gather information about their opponent, adjust their behavior accordingly, and can thereby avoid high costs of escalating fights. We tracked electrocommunication signals known as ‘rises’ and agonistic behaviors of the gymnotiform electric fish Apteronotus leptorhynchus in staged competition experiments. A larger body size relative to the opponent was the sole significant predictor for winners. Sex and the frequency of the continuously emitted electric field only mildly influenced competition outcome. In males, correlations of body size and winning were stronger than in females and, especially when losing against females, communication and agonistic interactions were enhanced, suggesting that males are more motivated to compete. Fish that lost competitions emitted the majority of rises, but their quantity depended on the competitors’ relative size and sex. The emission of a rise could be costly since it provoked ritualized biting or chase behaviors by the other fish. Despite winners being accurately predictable based on the number of rises after the initial 25 min, losers continued to emit rises. The number of rises emitted by losers and the duration of chase behaviors depended in similar ways on physical attributes of contestants. Detailed evaluation of these correlations suggests that A. leptorhynchus adjusts its competition behavior according to mutual assessment, where rises could signal a loser's motivation to continue assessment through ritualized fighting.

Summary: Electric fish adjust their competition behavior according to mutual assessment, where electrocommunication with so-called ‘rises’ could signal a loser's motivation to continue assessment through ritualized fighting.

Vocal and Electric Fish: Revisiting a Comparison of Two Teleost Models in the Neuroethology of Social Behavior

The communication behaviors of vocal fish and electric fish are among the vertebrate social behaviors best understood at the level of neural circuits. Both forms of signaling rely on midbrain inputs to hindbrain pattern generators that activate peripheral effectors (sonic muscles and electrocytes) to produce pulsatile signals that are modulated by frequency/repetition rate, amplitude and call duration. To generate signals that vary by sex, male phenotype, and social context, these circuits are responsive to a wide range of hormones and neuromodulators acting on different timescales at multiple loci. Bass and Zakon (2005) reviewed the behavioral neuroendocrinology of these two teleost groups, comparing how the regulation of their communication systems have both converged and diverged during their parallel evolution. Here, we revisit this comparison and review the complementary developments over the past 16 years. We (a) summarize recent work that expands our knowledge of the neural circuits underlying these two communication systems, (b) review parallel studies on the action of neuromodulators (e.g., serotonin, AVT, melatonin), brain steroidogenesis (via aromatase), and social stimuli on the output of these circuits, (c) highlight recent transcriptomic studies that illustrate how contemporary molecular methods have elucidated the genetic regulation of social behavior in these fish, and (d) describe recent studies of mochokid catfish, which use both vocal and electric communication, and that use both vocal and electric communication and consider how these two systems are spliced together in the same species. Finally, we offer avenues for future research to further probe how similarities and differences between these two communication systems emerge over ontogeny and evolution.

Leptinergic Regulation of Vertebrate Communication Signals

Animal communication signals are regulated by multiple hormonal axes that ensure appropriate signal targeting, timing, and information content. The regulatory roles of steroid hormones and many peptide hormones are well understood and documented across a wide range of vertebrate taxa. Two recent studies have reported a novel function for leptin, a peptide hormone central to energy balance regulation: regulating communication signals of weakly electric fish and singing mice. With only limited evidence available at this time, a key question is just how widespread leptinergic regulation of communication signals is within and across taxa. A second important question is what features of communication signals are subject to leptinergic regulation. Here we consider the functional significance of leptinergic regulation of animal communication signals in the context of both direct and indirect signal metabolic costs. Direct costs arise from metabolic investment in signal production, while indirect costs arise from the predation and social conflict consequences of the signal's information content. We propose a preliminary conceptual framework for predicting which species will exhibit leptinergic regulation of their communication signals and which signal features leptin will regulate. This framework suggests a number of directly testable predictions within and across taxa. Accounting for additional factors such as life history and the potential co-regulation of communication signals by leptin and glucocorticoids will likely require modification or elaboration of this model.

Neurobiology: The power of pauses in electrocommunication

A new study of social communication behavior in weakly electric fish identifies neural mechanisms that may account for the significance of silent pauses in communication.

Synergistic population coding of natural communication stimuli by hindbrain electrosensory neurons

Understanding how neural populations encode natural stimuli with complex spatiotemporal structure to give rise to perception remains a central problem in neuroscience. Here we investigated population coding of natural communication stimuli by hindbrain neurons within the electrosensory system of weakly electric fish Apteronotus leptorhynchus. Overall, we found that simultaneously recorded neural activities were correlated: signal but not noise correlations were variable depending on the stimulus waveform as well as the distance between neurons. Combining the neural activities using an equal-weight sum gave rise to discrimination performance between different stimulus waveforms that was limited by redundancy introduced by noise correlations. However, using an evolutionary algorithm to assign different weights to individual neurons before combining their activities (i.e., a weighted sum) gave rise to increased discrimination performance by revealing synergistic interactions between neural activities. Our results thus demonstrate that correlations between the neural activities of hindbrain electrosensory neurons can enhance information about the structure of natural communication stimuli that allow for reliable discrimination between different waveforms by downstream brain areas.

Population Coding of Natural Electrosensory Stimuli by Midbrain Neurons

Natural stimuli display spatiotemporal characteristics that typically vary over orders of magnitude, and their encoding by sensory neurons remains poorly understood. We investigated population coding of highly heterogeneous natural electrocommunication stimuli in Apteronotus leptorhynchus of either sex. Neuronal activities were positively correlated with one another in the absence of stimulation, and correlation magnitude decayed with increasing distance between recording sites. Under stimulation, we found that correlations between trial-averaged neuronal responses (i.e., signal correlations) were positive and higher in magnitude for neurons located close to another, but that correlations between the trial-to-trial variability (i.e., noise correlations) were independent of physical distance. Overall, signal and noise correlations were independent of stimulus waveform as well as of one another. To investigate how neuronal populations encoded natural electrocommunication stimuli, we considered a nonlinear decoder for which the activities were combined. Decoding performance was best for a timescale of 6 ms, indicating that midbrain neurons transmit information via precise spike timing. A simple summation of neuronal activities (equally weighted sum) revealed that noise correlations limited decoding performance by introducing redundancy. Using an evolution algorithm to optimize performance when considering instead unequally weighted sums of neuronal activities revealed much greater performance values, indicating that midbrain neuron populations transmit information that reliably enable discrimination between different stimulus waveforms. Interestingly, we found that different weight combinations gave rise to similar discriminability, suggesting robustness. Our results have important implications for understanding how natural stimuli are integrated by downstream brain areas to give rise to behavioral responses.SIGNIFICANCE STATEMENT We show that midbrain electrosensory neurons display correlations between their activities and that these can significantly impact performance of decoders. While noise correlations limited discrimination performance by introducing redundancy, considering unequally weighted sums of neuronal activities gave rise to much improved performance and mitigated the deleterious effects of noise correlations. Further analysis revealed that increased discriminability was achieved by making trial-averaged responses more separable, as well as by reducing trial-to-trial variability by eliminating noise correlations. We further found that multiple combinations of weights could give rise to similar discrimination performances, which suggests that such combinatorial codes could be achieved in the brain. We conclude that the activities of midbrain neuronal populations can be used to reliably discriminate between highly heterogeneous stimulus waveforms.

Spooky Interaction at a Distance in Cave and Surface Dwelling Electric Fishes

Glass knifefish (Eigenmannia) are a group of weakly electric fishes found throughout the Amazon basin. Their electric organ discharges (EODs) are energetically costly adaptations used in social communication and for localizing conspecifics and other objects including prey at night and in turbid water. Interestingly, a troglobitic population of blind cavefish Eigenmannia vicentespelea survives in complete darkness in a cave system in central Brazil. We examined the effects of troglobitic conditions, which includes a complete loss of visual cues and potentially reduced food sources, by comparing the behavior and movement of freely behaving cavefish to a nearby epigean (surface) population (Eigenmannia trilineata). We found that the strengths of electric discharges in cavefish were greater than in surface fish, which may result from increased reliance on electrosensory perception, larger size, and sufficient food resources. Surface fish were recorded while feeding at night and did not show evidence of territoriality, whereas cavefish appeared to maintain territories. Surprisingly, we routinely found both surface and cavefish with sustained differences in EOD frequencies that were below 10 Hz despite being within close proximity of about 50 cm. A half century of analysis of electrosocial interactions in laboratory tanks suggest that these small differences in EOD frequencies should have triggered the "jamming avoidance response," a behavior in which fish change their EOD frequencies to increase the difference between individuals. Pairs of fish also showed significant interactions between EOD frequencies and relative movements at large distances, over 1.5 m, and at high differences in frequencies, often >50 Hz. These interactions are likely "envelope" responses in which fish alter their EOD frequency in relation to higher order features, specifically changes in the depth of modulation, of electrosocial signals.

Serotonergic Modulation of Sensory Neuron Activity and Behavior in Apteronotus albifrons

Organisms must constantly adapt to changes in their environment to survive. It is thought that neuromodulators such as serotonin enable sensory neurons to better process input encountered during different behavioral contexts. Here, we investigated how serotonergic innervation affects neural and behavioral responses to behaviorally relevant envelope stimuli in the weakly electric fish species Apteronotus albifrons. Under baseline conditions, we found that exogenous serotonin application within the electrosensory lateral line lobe increased sensory neuron excitability, thereby promoting burst firing. We found that serotonin enhanced the responses to envelope stimuli of pyramidal cells within the lateral segment of the electrosensory lateral line lobe (ELL) by increasing sensitivity, with the increase more pronounced for stimuli with higher temporal frequencies (i.e., >0.2 Hz). Such increases in neural sensitivity were due to increased burst firing. At the organismal level, bilateral serotonin application within the ELL lateral segment enhanced behavioral responses to sensory input through increases in sensitivity. Similar to what was observed for neural responses, increases in behavioral sensitivity were more pronounced for higher (i.e., >0.2 Hz) temporal frequencies. Surprisingly, a comparison between our results and previous ones obtained in the closely related species A. leptorhynchus revealed that, while serotonin application gave rise to similar effects on neural excitability and responses to sensory input, serotonin application also gave rise to marked differences in behavior. Specifically, behavioral responses in A. leptorhynchus were increased primarily for lower (i.e., ≤0.2 Hz) rather than for higher temporal frequencies. Thus, our results strongly suggest that there are marked differences in how sensory neural responses are processed downstream to give rise to behavior across both species. This is even though previous results have shown that the behavioral responses of both species to envelope stimuli were identical when serotonin is not applied.

Defining "active sensing" through an analysis of sensing energetics: homeoactive and alloactive sensing

The term "active sensing" has been defined in multiple ways. Most strictly, the term refers to sensing that uses self-generated energy to sample the environment (e.g., echolocation). More broadly, the definition includes all sensing that occurs when the sensor is moving (e.g., tactile stimuli obtained by an immobile versus moving fingertip) and, broader still, includes all sensing guided by attention or intent (e.g., purposeful eye movements). The present work offers a framework to help disambiguate aspects of the "active sensing" terminology and reveals properties of tactile sensing unique among all modalities. The framework begins with the well-described "sensorimotor loop," which expresses the perceptual process as a cycle involving four subsystems: environment, sensor, nervous system, and actuator. Using system dynamics, we examine how information flows through the loop. This "sensory-energetic loop" reveals two distinct sensing mechanisms that subdivide active sensing into homeoactive and alloactive sensing. In homeoactive sensing, the animal can change the state of the environment, while in alloactive sensing the animal can alter only the sensor's configurational parameters and thus the mapping between input and output. Given these new definitions, examination of the sensory-energetic loop helps identify two unique characteristics of tactile sensing: 1) in tactile systems, alloactive and homeoactive sensing merge to a mutually controlled sensing mechanism, and 2) tactile sensing may require fundamentally different predictions to anticipate reafferent input. We expect this framework may help resolve ambiguities in the active sensing community and form a basis for future theoretical and experimental work regarding alloactive and homeoactive sensing.

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 Apteronotus leptorhynchus (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. We identify key elements necessary for locking to multiple frequencies, study its limits, and provide concise mathematical models reproducing our main findings. Our findings provide another example of how rate and temporal codes can coexist and complement each other in single neurons and demonstrate that sensory coding in p-type electroreceptor afferents provides a much richer representation of the sensory environment than commonly assumed. Since the underlying mechanisms are not specific to the electrosensory system, our results could provide the basis for studying multiple frequency locking in other systems.NEW & NOTEWORTHY Locking of neuronal spikes to external and internal signals is a ubiquitous neurophysiological mechanism that has been extensively studied in several brain areas and species. Using experimental data from the electrosensory system and concise mathematical models, we analyze how a single neuron can simultaneously lock to multiple frequencies. Our findings demonstrate how temporal and rate codes can complement each other and lead to rich neuronal representations of sensory signals.

Tracking activity patterns of a multispecies community of gymnotiform weakly electric fish in their neotropical habitat without tagging

Field studies on freely behaving animals commonly require tagging and often are focused on single species. Weakly electric fish generate a species- and individual-specific electric organ discharge (EOD) and therefore provide a unique opportunity for individual tracking without tagging. Here, we present and test tracking algorithms based on recordings with submerged electrode arrays. Harmonic structures extracted from power spectra provide fish identity. Localization of fish based on weighted averages of their EOD amplitudes is found to be more robust than fitting a dipole model. We apply these techniques to monitor a community of three species, Apteronotus rostratus, Eigenmannia humboldtii and Sternopygus dariensis, in their natural habitat in Darién, Panama. We found consistent upstream movements after sunset followed by downstream movements in the second half of the night. Extrapolations of these movements and estimates of fish density obtained from additional transect data suggest that some fish cover at least several hundreds of meters of the stream per night. Most fish, including E. humboldtii, were traversing the electrode array solitarily. From in situ measurements of the decay of the EOD amplitude with distance of individual animals, we estimated that fish can detect conspecifics at distances of up to 2 m. Our recordings also emphasize the complexity of natural electrosensory scenes resulting from the interactions of the EODs of different species. Electrode arrays thus provide an unprecedented window into the so-far hidden nocturnal activities of multispecies communities of weakly electric fish at an unmatched level of detail.

Neural Synchrony Gives Rise to Amplitude- and Duration-Invariant Encoding Consistent With Perception of Natural Communication Stimuli

When confronted with a highly variable environment, it remains poorly understood how neural populations encode and classify natural stimuli to give rise to appropriate and consistent behavioral responses. Here we investigated population coding of natural communication signals with different attributes (i.e., amplitude and duration) in the electrosensory system of the weakly electric fish Apteronotus leptorhynchus. Our results show that, while single peripheral neurons encode the detailed timecourse of different stimulus waveforms, measures of population synchrony are effectively unchanged because of coordinated increases and decreases in activity. A phenomenological mathematical model reproduced this invariance and shows that this can be explained by considering homogeneous populations whose responses are solely determined by single neuron firing properties. Moreover, recordings from downstream central neurons reveal that synchronous afferent activity is actually decoded and thus most likely transmitted to higher brain areas. Finally, we demonstrate that the associated behavioral responses at the organism level are invariant. Our results provide a mechanism by which amplitude- and duration-invariant coding of behaviorally relevant sensory input emerges across successive brain areas thereby presumably giving rise to invariant behavioral responses. Such mechanisms are likely to be found in other systems that share anatomical and functional features with the electrosensory system (e.g., auditory, visual, vestibular).

Descending pathways mediate adaptive optimized coding of natural stimuli in weakly electric fish

Biological systems must be flexible to environmental changes to survive. This is exemplified by the fact that sensory systems continuously adapt to changes in the environment to optimize coding and behavioral responses. However, the nature of the underlying mechanisms remains poorly understood in general. Here, we investigated the mechanisms mediating adaptive optimized coding of naturalistic stimuli with varying statistics depending on the animal's velocity during movement. We found that central neurons adapted their responses to stimuli with different power spectral densities such as to optimally encode them, thereby ensuring that behavioral responses are, in turn, better matched to the new stimulus statistics. Sensory adaptation further required descending inputs from the forebrain as well as the raphe nuclei. Our findings thus reveal a previously unknown functional role for descending pathways in mediating adaptive optimized coding of natural stimuli that is likely generally applicable across sensory systems and species.

Encoding and Perception of Electro-communication Signals in Apteronotus leptorhynchus

Animal communication plays an essential role in triggering diverse behaviors. It is believed in this regard that signal production by a sender and its perception by a receiver is co-evolving in order to have beneficial effects such as to ensure that conspecifics remain sensitive to these signals. However, in order to give appropriate responses to a communication signal, the receiver has to first detect and interpret it in a meaningful way. The detection of communication signals can be limited under some circumstances, for example when the signal is masked by the background noise in which it occurs (e.g., the cocktail-party problem). Moreover, some signals are very alike despite having different meanings making it hard to discriminate between them. How the central nervous system copes with these tasks and problems is a central question in systems neuroscience. Gymnotiform weakly electric fish pose an interesting system to answer these questions for various reasons: (1) they use a variety of communication signals called “chirps” during different behavioral encounters; (2) the central physiology of the electrosensory system is well known; and (3) most importantly, these fish give reliable behavioral responses to artificial stimuli that resemble natural communication signals, making it possible to uncover the neural mechanisms that lead to the observed behaviors.

Electrosensory Contrast Signals for Interacting Weakly Electric Fish

Active sensory systems have evolved to properly encode natural stimuli including those created by conspecifics, yet little is known about the properties of such stimuli. We consider the electrosensory signal at the skin of a fixed weakly electric fish in the presence of a swimming conspecific. The dipole recordings are obtained in parallel with video tracking of the position of the animals. This enables the quantification of the relationships between the recording dipole and the positions of the head, midbody and tail of the freely swimming fish. The contrast of the signal at the skin is shown to be well-fitted by a decreasing exponential function of distance. It is thus anti-correlated with distance; it is also correlated with the second envelope (i.e., the envelope of the envelope) of the raw recorded signal. The variance of the contrast signal is highest at short range. However, the coefficient of variation (CV) of this signal increases with distance. We find a range of position and associated contrast patterns under quasi-2D swimming conditions. This is quantified using global measures of the visit times of the free fish within measurable range, with each visit causing a bump in contrast. The durations of these bumps as well as the times between these bumps are well reproduced by a doubly stochastic process formed by a dichotomous (two-state) noise with Poisson statistics multiplying a colored noise [Ornstein-Uhlenbeck (OU) process]. Certain rapid body movements such as bending or turning are seen to produce contrast drops that may be part of cloaking strategies.

Dominance in Habitat Preference and Diurnal Explorative Behavior of the Weakly Electric Fish Apteronotus leptorhynchus

Electrocommunication and -localization behaviors of weakly electric fish have been studied extensively in the lab, mostly by means of short-term observations on constrained fish. Far less is known about their behaviors in more natural-like settings, where fish are less constrained in space and time. We tracked individual fish in a population of fourteen brown ghost knifefish (Apteronotus leptorhynchus) housed in a large 2 m³ indoor tank based on their electric organ discharges (EOD). The tank contained four different natural-like microhabitats (gravel, plants, isolated stones, stacked stones). In particular during the day individual fish showed preferences for specific habitats which provided appropriate shelter. Male fish with higher EOD frequencies spent more time in their preferred habitat during the day, moved more often between habitats during the night, and less often during the day in comparison to low-frequency males. Our data thus revealed a link between dominance indicated by higher EOD frequency, territoriality, and a more explorative personality in male A. leptorhynchus. In females, movement activity during both day and night correlated positively with EOD frequency. In the night, fish of either sex moved to another habitat after about 6 s on average. During the day, the average transition time was also very short at about 20 s. However, these activity phases were interrupted by phases of inactivity that lasted on average about 20 min during the day, but only 3 min in the night. The individual preference for daytime retreat sites did not reflect the frequent explorative movements at night.

Neural Processing of Communication Signals: The Extent of Sender-Receiver Matching Varies across Species of Apteronotus

As communication signal properties change, through genetic drift or selective pressure, the sensory systems that receive these signals must also adapt to maintain sensitivity and adaptability in an array of contexts. Shedding light on this process helps us to understand how sensory codes are tailored to specific tasks. In a species of weakly electric fish, Apteronotus albifrons, we examined the unique neurophysiological properties that support the encoding of electrosensory communication signals that the animal encounters in social exchanges. We compare our findings to the known coding properties of the closely related species Apteronotus leptorhynchus to establish how these animals differ in their ability to encode their distinctive communication signals. While there are many similarities between these two species, we found notable differences leading to relatively poor coding of the details of chirp structure occurring on high-frequency background beats. As a result, small differences in chirp properties are poorly resolved by the nervous system. We performed behavioral tests to relate A. albifrons chirp coding strategies to its use of chirps during social encounters. Our results suggest that A. albifrons does not exchange frequent chirps in a nonbreeding condition, particularly when the beat frequency is high. These findings parallel the mediocre chirp coding accuracy in that they both point to a reduced reliance on frequent and rich exchange of information through chirps during these social interactions. Therefore, our study suggests that neural coding strategies in the CNS vary across species in a way that parallels the behavioral use of the sensory signals.

Population Coding and Correlated Variability in Electrosensory Pathways

The fact that perception and behavior depend on the simultaneous and coordinated activity of neural populations is well established. Understanding encoding through neuronal population activity is however complicated by the statistical dependencies between the activities of neurons, which can be present in terms of both their mean (signal correlations) and their response variability (noise correlations). Here, we review the state of knowledge regarding population coding and the influence of correlated variability in the electrosensory pathways of the weakly electric fish Apteronotus leptorhynchus. We summarize known population coding strategies at the peripheral level, which are largely unaffected by noise correlations. We then move on to the hindbrain, where existing data from the electrosensory lateral line lobe (ELL) shows the presence of noise correlations. We summarize the current knowledge regarding the mechanistic origins of noise correlations and known mechanisms of stimulus dependent correlation shaping in ELL. We finish by considering future directions for understanding population coding in the electrosensory pathways of weakly electric fish, highlighting the benefits of this model system for understanding the origins and impact of noise correlations on population coding.