Electrosensory interference in naturally occurring aggregates of a species of weakly electric fish, Eigenmannia virescens

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.

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.

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.

The complexity of high-frequency electric fields degrades electrosensory inputs: implications for the jamming avoidance response in weakly electric fish

Sensory systems encode environmental information that is necessary for adaptive behavioural choices, and thus greatly influence the evolution of animal behaviour and the underlying neural circuits. Here, we evaluate how the quality of sensory information impacts the jamming avoidance response (JAR) in weakly electric fish. To sense their environment, these fish generate an oscillating electric field: the electric organ discharge (EOD). Nearby fish with similar EOD frequencies perform the JAR to increase the difference between their EOD frequencies, i.e. their difference frequency (DF). The fish determines the sign of the DF: when it has a lower frequency (DF > 0), EOD frequency is decreased and vice versa. We study the sensory basis of the JAR in two species: Apteronotus leptorhynchus have a high frequency (ca 1000 Hz), spatio-temporally heterogeneous electric field, whereas Eigenmannia sp. have a low frequency (ca 300 Hz), spatially uniform field. We show that the increased complexity of the Apteronotus field decreases the reliability of sensory cues used to determine the DF. Interestingly, Apteronotus responds to all JAR stimuli by increasing EOD frequency, having lost the neural pathway that produces JAR-related decreases in EOD frequency. Our results suggest that electric field complexity may have influenced the evolution of the JAR by degrading the related sensory information.

Chirping and asymmetric jamming avoidance responses in the electric fish Distocyclus conirostris

Electrosensory systems of weakly electric fish must accommodate competing demands of sensing the environment (electrolocation) and receiving social information (electrocommunication). The jamming avoidance response (JAR) is a behavioral strategy thought to reduce electrosensory interference from conspecific signals close in frequency. We used playback experiments to characterize electric organ discharge frequency (EODf), chirping behavior and the JAR of Distocyclus conirostris, a gregarious electric fish species. EODs of D. conirostris had low frequencies (∼80-200 Hz) that shifted in response to playback stimuli. Fish consistently lowered EODf in response to higher-frequency stimuli but inconsistently raised or lowered EODf in response to lower-frequency stimuli. This led to jamming avoidance or anti-jamming avoidance, respectively. We compare these behaviors with those of closely related electric fish (Eigenmannia and Sternopygus) and suggest that the JAR may have additional social functions and may not solely minimize the deleterious effects of jamming, as its name suggests.

High-resolution behavioral mapping of electric fishes in Amazonian habitats

The study of animal behavior has been revolutionized by sophisticated methodologies that identify and track individuals in video recordings. Video recording of behavior, however, is challenging for many species and habitats including fishes that live in turbid water. Here we present a methodology for identifying and localizing weakly electric fishes on the centimeter scale with subsecond temporal resolution based solely on the electric signals generated by each individual. These signals are recorded with a grid of electrodes and analyzed using a two-part algorithm that identifies the signals from each individual fish and then estimates the position and orientation of each fish using Bayesian inference. Interestingly, because this system involves eavesdropping on electrocommunication signals, it permits monitoring of complex social and physical interactions in the wild. This approach has potential for large-scale non-invasive monitoring of aquatic habitats in the Amazon basin and other tropical freshwater systems.

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. Modulations of the fish's own electric field are sensed by these receptors and used in navigation, prey detection, and communication. We studied the neuronal representation of electric communication signals (called chirps) in the ampullary and the two tuberous pathways of Eigenmannia virescens. We first characterized different kinds of chirps observed in behavioral experiments. Since Eigenmannia chirps simultaneously drive all three types of receptors, we studied their responses in in vivo electrophysiological recordings. Our results demonstrate that different electroreceptor types encode different aspects of the stimuli and each appears best suited to convey information about a certain chirp type. A decoding analysis of single neurons and small populations shows that this specialization leads to a complementary representation of information in the tuberous and ampullary receptors. This suggests that a potential readout mechanism should combine information provided by the parallel processing streams to improve chirp detectability.

Perception and coding of envelopes in weakly electric fishes

Natural sensory stimuli have a rich spatiotemporal structure and can often be characterized as a high frequency signal that is independently modulated at lower frequencies. This lower frequency modulation is known as the envelope. Envelopes are commonly found in a variety of sensory signals, such as contrast modulations of visual stimuli and amplitude modulations of auditory stimuli. While psychophysical studies have shown that envelopes can carry information that is essential for perception, how envelope information is processed in the brain is poorly understood. Here we review the behavioral salience and neural mechanisms for the processing of envelopes in the electrosensory system of wave-type gymnotiform weakly electric fishes. These fish can generate envelope signals through movement, interactions of their electric fields in social groups or communication signals. The envelopes that result from the first two behavioral contexts differ in their frequency content, with movement envelopes typically being of lower frequency. Recent behavioral evidence has shown that weakly electric fish respond in robust and stereotypical ways to social envelopes to increase the envelope frequency. Finally, neurophysiological results show how envelopes are processed by peripheral and central electrosensory neurons. Peripheral electrosensory neurons respond to both stimulus and envelope signals. Neurons in the primary hindbrain recipient of these afferents, the electrosensory lateral line lobe (ELL), exhibit heterogeneities in their responses to stimulus and envelope signals. Complete segregation of stimulus and envelope information is achieved in neurons in the target of ELL efferents, the midbrain torus semicircularis (Ts).

Beyond the Jamming Avoidance Response: weakly electric fish respond to the envelope of social electrosensory signals

Recent studies have shown that central nervous system neurons in weakly electric fish respond to artificially constructed electrosensory envelopes, but the behavioral relevance of such stimuli is unclear. Here we investigate the possibility that social context creates envelopes that drive behavior. When Eigenmannia virescens are in groups of three or more, the interactions between their pseudo-sinusoidal electric fields can generate 'social envelopes'. We developed a simple mathematical prediction for how fish might respond to such social envelopes. To test this prediction, we measured the responses of E. virescens to stimuli consisting of two sinusoids, each outside the range of the Jamming Avoidance Response (JAR), that when added to the fish's own electric field produced low-frequency (below 10 Hz) social envelopes. Fish changed their electric organ discharge (EOD) frequency in response to these envelopes, which we have termed the Social Envelope Response (SER). In 99% of trials, the direction of the SER was consistent with the mathematical prediction. The SER was strongest in response to the lowest initial envelope frequency tested (2 Hz) and depended on stimulus amplitude. The SER generally resulted in an increase of the envelope frequency during the course of a trial, suggesting that this behavior may be a mechanism for avoiding low-frequency social envelopes. Importantly, the direction of the SER was not predicted by the superposition of two JAR responses: the SER was insensitive to the amplitude ratio between the sinusoids used to generate the envelope, but was instead predicted by the sign of the difference of difference frequencies.

Closed-loop stabilization of the jamming avoidance response reveals its locally unstable and globally nonlinear dynamics

The jamming avoidance response, or JAR, in the weakly electric fish has been analyzed at all levels of organization, from whole-organism behavior down to specific ion channels. Nevertheless, a parsimonious description of the JAR behavior in terms of a dynamical system model has not been achieved at least in part due to the fact that 'avoidance' behaviors are both intrinsically unstable and nonlinear. We overcame the instability of the JAR in Eigenmannia virescens by closing a feedback loop around the behavioral response of the animal. Specifically, the instantaneous frequency of a jamming stimulus was tied to the fish's own electrogenic frequency by a feedback law. Without feedback, the fish's own frequency diverges from the stimulus frequency, but appropriate feedback stabilizes the behavior. After stabilizing the system, we measured the responses in the fish's instantaneous frequency to various stimuli. A delayed first-order linear system model fit the behavior near the equilibrium. Coherence to white noise stimuli together with quantitative agreement across stimulus types supported this local linear model. Next, we examined the intrinsic nonlinearity of the behavior using clamped-frequency-difference experiments to extend the model beyond the neighborhood of the equilibrium. The resulting nonlinear model is composed of competing motor return and sensory escape terms. The model reproduces responses to step and ramp changes in the difference frequency (dF)and predicts a 'snap-through' bifurcation as a function of dF that we confirmed experimentally.

The spatial structure of stimuli shapes the timescale of correlations in population spiking activity

Throughout the central nervous system, the timescale over which pairs of neural spike trains are correlated is shaped by stimulus structure and behavioral context. Such shaping is thought to underlie important changes in the neural code, but the neural circuitry responsible is largely unknown. In this study, we investigate a stimulus-induced shaping of pairwise spike train correlations in the electrosensory system of weakly electric fish. Simultaneous single unit recordings of principal electrosensory cells show that an increase in the spatial extent of stimuli increases correlations at short () timescales while simultaneously reducing correlations at long () timescales. A spiking network model of the first two stages of electrosensory processing replicates this correlation shaping, under the assumptions that spatially broad stimuli both saturate feedforward afferent input and recruit an open-loop inhibitory feedback pathway. Our model predictions are experimentally verified using both the natural heterogeneity of the electrosensory system and pharmacological blockade of descending feedback projections. For weak stimuli, linear response analysis of the spiking network shows that the reduction of long timescale correlation for spatially broad stimuli is similar to correlation cancellation mechanisms previously suggested to be operative in mammalian cortex. The mechanism for correlation shaping supports population-level filtering of irrelevant distractor stimuli, thereby enhancing the population response to relevant prey and conspecific communication inputs.

The size of a stimulus that is sensed by the nervous system can control the activity of neurons in sensory areas. How neural wiring supports this dependence remains an open question. We explore this general phenomenon using weakly electric fish, which possess a sensory system that detects electric field modulations produced by the surrounding environment. In particular, these animals' nervous systems are tuned to detect the difference between spatially compact prey inputs and spatially broad communication calls from other fish. In experiment, we discover that these two classes of stimuli differentially control the synchrony between pairs of electrosensory neurons. Using a computational model, we predict that this modulation is related to feedforward and feedback neural pathways in the electrosensory system, and we verify this prediction with experiments. This architecture prevents low frequency distractor stimuli, such as the animal's own tail motion, from driving neural population responses. With our model, we demonstrate how a common neural architecture enables a population-level code for behaviorally relevant stimuli.

Active sensing via movement shapes spatiotemporal patterns of sensory feedback

Previous work has shown that animals alter their locomotor behavior to increase sensing volumes. However, an animal's own movement also determines the spatial and temporal dynamics of sensory feedback. Because each sensory modality has unique spatiotemporal properties, movement has differential and potentially independent effects on each sensory system. Here we show that weakly electric fish dramatically adjust their locomotor behavior in relation to changes of modality-specific information in a task in which increasing sensory volume is irrelevant. We varied sensory information during a refuge-tracking task by changing illumination (vision) and conductivity (electroreception). The gain between refuge movement stimuli and fish tracking responses was functionally identical across all sensory conditions. However, there was a significant increase in the tracking error in the dark (no visual cues). This was a result of spontaneous whole-body oscillations (0.1 to 1 Hz) produced by the fish. These movements were costly: in the dark, fish swam over three times further when tracking and produced more net positive mechanical work. The magnitudes of these oscillations increased as electrosensory salience was degraded via increases in conductivity. In addition, tail bending (1.5 to 2.35 Hz), which has been reported to enhance electrosensory perception, occurred only during trials in the dark. These data show that both categories of movements - whole-body oscillations and tail bends - actively shape the spatiotemporal dynamics of electrosensory feedback.

Coding conspecific identity and motion in the electric sense

Interactions among animals can result in complex sensory signals containing a variety of socially relevant information, including the number, identity, and relative motion of conspecifics. How the spatiotemporal properties of such evolving naturalistic signals are encoded is a key question in sensory neuroscience. Here, we present results from experiments and modeling that address this issue in the context of the electric sense, which combines the spatial aspects of vision and touch, with the temporal aspects of audition. Wave-type electric fish, such as the brown ghost knifefish, Apteronotus leptorhynchus, used in this study, are uniquely identified by the frequency of their electric organ discharge (EOD). Multiple beat frequencies arise from the superposition of the EODs of each fish. We record the natural electrical signals near the skin of a “receiving” fish that are produced by stationary and freely swimming conspecifics. Using spectral analysis, we find that the primary beats, and the secondary beats between them (“beats of beats”), can be greatly influenced by fish swimming; the resulting motion produces low-frequency envelopes that broaden all the beat peaks and reshape the “noise floor”. We assess the consequences of this motion on sensory coding using a model electroreceptor. We show that the primary and secondary beats are encoded in the afferent spike train, but that motion acts to degrade this encoding. We also simulate the response of a realistic population of receptors, and find that it can encode the motion envelope well, primarily due to the receptors with lower firing rates. We discuss the implications of our results for the identification of conspecifics through specific beat frequencies and its possible hindrance by active swimming.

Effectively processing information from a sensory scene is essential for animal survival. Motion in a sensory scene complicates this task by dynamically modifying signal properties. To address this general issue, we focus on weakly electric fish. Each fish produces a weak electrical carrier signal with a characteristic frequency. Electroreceptors on its skin encode the modulations of this carrier caused by nearby objects and other animals, enabling this fish to thrive in its nocturnal environment. Little is known about how swimming movements influence natural electrosensory scenes, specifically in the context of detection and identification of, and communication with conspecifics. Using recordings involving free-swimming fish, we characterize the amplitude modulations of the carrier signal arising from small groups of fish. The differences between individual frequencies (beats) are prominent features of these signals, with the number of beats reflecting the number of neighbours. We also find that the distance and motion of a free-swimming fish are represented in a slow modulation of the beat at the receiving fish. Modeling shows that these stimulus features can be effectively encoded in the activity of the electroreceptors, but that encoding quality of some features can be degraded by motion, suggesting that active swimming could hinder conspecific identification.

Sub- and suprathreshold adaptation currents have opposite effects on frequency tuning

Natural stimuli are often characterized by statistics that can vary over orders of magnitude. Experiments have shown that sensory neurons continuously adapt their responses to changes in these statistics, thereby optimizing information transmission. However, such adaptation can also alter the neuronal transfer function by attenuating if not eliminating responses to the low frequency components of time varying stimuli,which can create ambiguity in the neural code. We recorded from electrosensory pyramidal neurons before and after pharmacological inactivation of either calcium-activated (I(AHP)) or KCNQ voltage-gated potassium currents (I(M)). We found that blocking each current decreased adaptation in a similar fashion but led to opposite changes in the neuronal transfer function. Indeed, blocking I(AHP) increased while blocking I(M) instead decreased the response to low temporal frequencies. To understand this surprising result, we built a mathematical model incorporating each channel type. This model predicted that these differential effects could be accounted for by differential activation properties. Our results show that the mechanisms that mediate adaptation can either increase or decrease the response to low frequency stimuli. As such, they suggest that the nervous system resolves ambiguity resulting from adaptation through independent control of adaptation and the neuronal transfer function.

Routing the flow of sensory signals using plastic responses to bursts and isolated spikes: experiment and theory

Processing complex sensory environments efficiently requires a diverse array of neural coding strategies. Neural codes relying on specific temporal patterning of action potentials may offer advantages over using solely spike rate codes. In particular, stimulus-dependent burst firing may carry additional information that isolated spikes do not. We use the well characterized electrosensory system of weakly electric fish to address how stimulus-dependent burst firing can determine the flow of information in feedforward neural circuits with different forms of short-term synaptic plasticity. Pyramidal cells in the electrosensory lateral line lobe burst in response to low-frequency, local (prey) signals. We show that the ability of pyramidal cells to code for local signals in the presence of additional high-frequency, global (communication) stimuli is uncompromised, while burst firing is reduced. We developed a bursting neuron model to understand how these effects, in particular noise-induced burst suppression, arise from interplay between incoming sensory signals and intrinsic neuronal dynamics. Finally, we examined how postsynaptic target populations preferentially respond to one of the two sensory mixtures (local vs local plus global) depending on whether the populations are in receipt of facilitating or depressing synapses. This form of feedforward neural architecture may allow for efficient information flow in the same neural pathway via either isolated or burst spikes, where the mechanisms by which stimuli are encoded are adaptable and sensitive to a diverse array of stimulus and contextual mixtures.

Neural heterogeneities influence envelope and temporal coding at the sensory periphery

Peripheral sensory neurons respond to stimuli containing a wide range of spatio-temporal frequencies. We investigated electroreceptor neuron coding in the gymnotiform wave-type weakly electric fish Apteronotus leptorhynchus. Previous studies used low to mid temporal frequencies (<256 Hz) and showed that electroreceptor neuron responses to sensory stimuli could be almost exclusively accounted for by linear models, thereby implying a rate code. We instead used temporal frequencies up to 425 Hz, which is in the upper behaviorally relevant range for this species. We show that electroreceptors can: (A) respond up to the highest frequencies tested and (B) display strong nonlinearities in their responses to such stimuli. These nonlinearities were manifested by the fact that the responses to repeated presentations of the same stimulus were coherent at temporal frequencies outside of those contained in the stimulus waveform. Specifically, these consisted of low frequencies corresponding to the time varying contrast or envelope of the stimulus as well as higher harmonics of the frequencies contained in the stimulus. Heterogeneities in the afferent population influenced nonlinear coding as afferents with the lowest baseline firing rates tended to display the strongest nonlinear responses. To understand the link between afferent heterogeneity and nonlinear responsiveness, we used a phenomenological mathematical model of electrosensory afferents. Varying a single parameter in the model was sufficient to account for the variability seen in our experimental data and yielded a prediction: nonlinear responses to the envelope and at higher harmonics are both due to afferents with lower baseline firing rates displaying greater degrees of rectification in their responses. This prediction was verified experimentally as we found that the coherence between the half-wave rectified stimulus and the response resembled the coherence between the responses to repeated presentations of the stimulus in our dataset. This result shows that rectification cannot only give rise to responses to low frequency envelopes but also at frequencies that are higher than those contained in the stimulus. The latter result implies that information is contained in the fine temporal structure of electroreceptor afferent spike trains. Our results show that heterogeneities in peripheral neuronal populations can have dramatic consequences on the nature of the neural code.

Effects of restraint and immobilization on electrosensory behaviors of weakly electric fish

Weakly electric fishes have been an important model system in behavioral neuroscience for more than 40 years. These fishes use a specialized electric organ to produce an electric field that is typically below 1 volt/cm and serves in many behaviors including social communication and prey detection. Electrical behaviors are easy to study because inexpensive and widely available tools enable continuous monitoring of the electric field of individual or groups of interacting fish. Weakly electric fish have been routinely used in tightly controlled neurophysiological experiments in which the animal is immobilized using neuromuscular blockers (e.g., curare). Although experiments that involve immobilization are generally discouraged because it eliminates movement-based behavioral signs of pain and distress, many observable electrosensory behaviors in fish persist when the animal is immobilized. Weakly electric fish thus offer a unique opportunity to assess the effects of immobilization on behaviors including those that may reflect pain and distress. We investigated the effects of both immobilization and restraint on a variety of electrosensory behaviors in four species of weakly electric fishes and observed minor effects that were not consistent between the species tested or between particular behaviors. In general, we observed small increases and decreases in response magnitude to particular electrosensory stimuli. Stressful events such as asphyxiation and handling, however, resulted in significant changes in the fishes electrosensory behaviors. Signs of pain and distress include marked reductions in responses to electrosensory stimuli, inconsistent responses, and reductions in or complete cessation of the autogenous electric field.

Multivariate classification of animal communication signals: a simulation-based comparison of alternative signal processing procedures using electric fishes

Evolutionary studies of communication can benefit from classification procedures that allow individual animals to be assigned to groups (e.g. species) on the basis of high-dimension data representing their signals. Prior to classification, signals are usually transformed by a signal processing procedure into structural features. Applications of these signal processing procedures to animal communication have been largely restricted to the manual or semi-automated identification of landmark features from graphical representations of signals. Nonetheless, theory predicts that automated time-frequency-based digital signal processing (DSP) procedures can represent signals more efficiently (using fewer features) than can landmark procedures or frequency-based DSP - allowing more accurate classification. Moreover, DSP procedures are objective in that they require little previous knowledge of signal diversity, and are relatively free from potentially ungrounded assumptions of cross-taxon homology. Using a model data set of electric organ discharge waveforms from five sympatric species of the electric fish Gymnotus, we adopted an exhaustive simulation approach to investigate the classificatory performance of different signal processing procedures. We considered a landmark procedure, a frequency-based DSP procedure (the fast Fourier transform), and two kinds of time-frequency-based DSP procedures (a short-time Fourier transform, and several implementations of the discrete wavelet transform -DWT). The features derived from each of these signal processing procedures were then subjected to dimension reduction procedures to separate those features which permit the most effective discrimination among groups of signalers. We considered four alternative dimension reduction methods. Finally, each combination of reduced data was submitted to classification by linear discriminant analysis. Our results support theoretical predictions that time-frequency DSP procedures (especially DWT) permit more efficient discrimination of groups. The performance of signal processing was found to depend largely upon the dimension reduction procedure employed, and upon the number of resulting features. Because the best combinations of procedures are dataset-dependent and difficult to predict, we conclude that simulations of the kind described here, or at least simplified versions of them, should be routinely executed before classification of animal signals - especially unfamiliar ones.

Rooted in behaviour

Weakly electric fish have been one of the most successful systems in which to study the neural basis of behaviour. Currently, three avenues of research hold particular promise: the combination of field and laboratory studies to improve our understanding of natural electrosensory stimuli and their role in behaviour; the integration of research on natural electrosensory scenes and sensory processing; multidisciplinary approaches to address questions of sensory processing and motor control.

Temporal processing across multiple topographic maps in the electrosensory system

Multiple topographic representations of sensory space are common in the nervous system and presumably allow organisms to separately process particular features of incoming sensory stimuli that vary widely in their attributes. We compared the response properties of sensory neurons within three maps of the body surface that are arranged strictly in parallel to two classes of stimuli that mimic prey and conspecifics, respectively. We used information-theoretic approaches and measures of phase locking to quantify neuronal responses. Our results show that frequency tuning in one of the three maps does not depend on stimulus class. This map acts as a low-pass filter under both conditions. A previously described stimulus-class-dependent switch in frequency tuning is shown to occur in the other two maps. Only a fraction of the information encoded by all neurons could be recovered through a linear decoder. Particularly striking were low-pass neurons the information of which in the high-frequency range could not be decoded linearly. We then explored whether intrinsic cellular mechanisms could partially account for the differences in frequency tuning across maps. Injection of a Ca2+ chelator had no effect in the map with low-pass characteristics. However, injection of the same Ca2+ chelator in the other two maps switched the tuning of neurons from band-pass/high-pass to low-pass. These results show that Ca2+-dependent processes play an important part in determining the functional roles of different sensory maps and thus shed light on the evolution of this important feature of the vertebrate brain.

Synaptic plasticity can produce and enhance direction selectivity

The discrimination of the direction of movement of sensory images is critical to the control of many animal behaviors. We propose a parsimonious model of motion processing that generates direction selective responses using short-term synaptic depression and can reproduce salient features of direction selectivity found in a population of neurons in the midbrain of the weakly electric fish Eigenmannia virescens. The model achieves direction selectivity with an elementary Reichardt motion detector: information from spatially separated receptive fields converges onto a neuron via dynamically different pathways. In the model, these differences arise from convergence of information through distinct synapses that either exhibit or do not exhibit short-term synaptic depression—short-term depression produces phase-advances relative to nondepressing synapses. Short-term depression is modeled using two state-variables, a fast process with a time constant on the order of tens to hundreds of milliseconds, and a slow process with a time constant on the order of seconds to tens of seconds. These processes correspond to naturally occurring time constants observed at synapses that exhibit short-term depression. Inclusion of the fast process is sufficient for the generation of temporal disparities that are necessary for direction selectivity in the elementary Reichardt circuit. The addition of the slow process can enhance direction selectivity over time for stimuli that are sustained for periods of seconds or more. Transient (i.e., short-duration) stimuli do not evoke the slow process and therefore do not elicit enhanced direction selectivity. The addition of a sustained global, synchronous oscillation in the gamma frequency range can, however, drive the slow process and enhance direction selectivity to transient stimuli. This enhancement effect does not, however, occur for all combinations of model parameters. The ratio of depressing and nondepressing synapses determines the effects of the addition of the global synchronous oscillation on direction selectivity. These ingredients, short-term depression, spatial convergence, and gamma-band oscillations, are ubiquitous in sensory systems and may be used in Reichardt-style circuits for the generation and enhancement of a variety of biologically relevant spatiotemporal computations.

Short-term synaptic plasticity is ubiquitous in brain circuits, but its function in sensorimotor processing remains unclear. We propose a parsimonious model of motion processing using short-term depression to produce directionally selective responses. In the model circuit, information from two spatially separated receptive fields is combined after being asymmetrically processed by synapses that either exhibit short-term synaptic depression or do not. Motion in a preferred direction leads to a constructive interaction between the two channels; motion in the opposite direction does not. The model represents short-term synaptic depression as two processes with distinct time constants. The faster process alone suffices to generate direction selectivity in the circuit. The slow process, in contrast, can enhance direction selectivity to sustained stimuli. Therefore, the slow process mediates a form of attentional shift from alert, where the neuron responds more vigorously, to discriminating, where the neuron responds more selectively with fewer spikes. This explains a previously observed enhancement of direction selectivity in weakly electric fish in the presence of global synchronous gamma-band oscillations. These findings suggest a mechanistic connection between gamma-band oscillations and attention.

Interval coding. I. Burst interspike intervals as indicators of stimulus intensity

Short interspike intervals such as those that occur during burst firing are hypothesized to be distinct features of the neural code. Although a number of correlations between the occurrence of burst events and aspects of the stimulus have been identified, the relationship between burst characteristics and information transfer is uncertain. Pyramidal cells in the electrosensory lobe of the weakly electric fish, Apteronotus leptorhynchus, respond to dynamic broadband electrosensory stimuli with bursts and isolated spikes. In the present study, we mimic synaptic input during sensory stimulation by direct stimulation of electrosensory pyramidal cells with broadband current in vitro. The pyramidal cells respond to this stimulus with burst interspike intervals (ISIs) that are reliably and precisely correlated with the intensity of stimulus upstrokes. We found burst ISIs must differ by a minimum of 2 ms to discriminate, with low error, differences in stimulus intensity. Based on these results, we define and quantify a candidate interval code for the processing of sensory input. Finally, we demonstrate that interval coding is restricted to short ISIs such as those generated in burst events and that the proposed interval code is distinct from rate and timing codes.

Interval coding. II. Dendrite-dependent mechanisms

The rich temporal structure of neural spike trains provides multiple dimensions to code dynamic stimuli. Popular examples are spike trains from sensory cells where bursts and isolated spikes can serve distinct coding roles. In contrast to analyses of neural coding, the cellular mechanics of burst mechanisms are typically elucidated from the neural response to static input. Bridging the mechanics of bursting with coding of dynamic stimuli is an important step in establishing theories of neural coding. Electrosensory lateral line lobe (ELL) pyramidal neurons respond to static inputs with a complex dendrite-dependent burst mechanism. Here we show that in response to dynamic broadband stimuli, these bursts lack some of the electrophysiological characteristics observed in response to static inputs. A simple leaky integrate-and-fire (LIF)-style model with a dendrite-dependent depolarizing afterpotential (DAP) is sufficient to match both the output statistics and coding performance of experimental spike trains. We use this model to investigate a simplification of interval coding where the burst interspike interval (ISI) codes for the scale of a canonical upstroke rather than a multidimensional stimulus feature. Using this stimulus reduction, we compute a quantization of the burst ISIs and the upstroke scale to show that the mutual information rate of the interval code is maximized at a moderate DAP amplitude. The combination of a reduced description of ELL pyramidal cell bursting and a simplification of the interval code increases the generality of ELL burst codes to other sensory modalities.

Regulation of burst dynamics improves differential encoding of stimulus frequency by spike train segregation

Distinguishing between different signals conveyed in a single sensory modality presents a significant problem for sensory processing. The weakly electric fish Apteronotus leptorhynchus use electrosensory information to encode both low-frequency signals associated with environmental and prey signals and high-frequency communication signals between conspecifics. We identify a mechanism whereby the GABA(B) component of a feedback pathway to the electrosensory lobe is recruited to regulate the intrinsic burst dynamics and coding properties of pyramidal cells for these behaviorally relevant input signals. Through recordings in an in vitro slice preparation and a reduced model of pyramidal cells, we show that recruitment of dendritic GABA(B) currents can shift the timing of a backpropagating spike and its influence on an intrinsic burst mechanism. This regulation of burst firing alters the coding properties of pyramidal cells by improving the correlation of burst and tonic spikes with respect to low- or high-frequency components of complex stimuli. GABA(B) modulation of spike backpropagation thus improves the segregation of burst and tonic spikes evoked by simulated sensory input, allowing pyramidal cells to parcel the spike train into coding streams for the low- and high-frequency components. As the feedback pathway is predicted to be activated in circumstances where environmental and communication stimuli coexist, these data reveal a novel means by which inhibitory input can regulate spike backpropagation to improve signal segregation.

Neural strategies for optimal processing of sensory signals

The electrosensory system is used for both spatial navigation tasks and communication. An electric organ generates a sinusoidal electric field and cutaneous electroreceptors respond to this field. Objects such as prey or rocks cause a local low-frequency modulation of the electric field; this cue is used by electric fish for navigation and prey capture. The interference of the electric fields of conspecifics produces beats, often with high frequencies, that are also sensed by the electroreceptors; furthermore, these electric fish can transiently modulate their electric discharge as a communication signal. Thus these fish must therefore detect a variety of low-intensity signals that differ greatly in their spatial extent, frequency, and duration. Behavioral studies suggest that they are highly adapted to these tasks. Experimental and theoretical analyses of the neural circuitry for the electrosense has demonstrated many commonalities with the more common senses, e.g., topographic mapping and receptive fields with On or Off centers and surround inhibition. The integration of computational and experimental analyses has demonstrated novel mechanisms that appear to optimize weak signal detection in the electrosense including: noise shaping by correlations within single spike trains, induction of oscillations by delayed feedback inhibition, the requirement for maps with differing receptive field sizes tuned for different stimulus parameters, and the role of non-plastic feedback for adaptive cancellation of redundant signals. It is likely that these mechanisms will also be operative in other sensory systems.

Global Electrosensory Oscillations Enhance Directional Responses of Midbrain Neurons inEigenmannia

Eigenmannia, a genus of weakly electric fish, exhibits a specialized behavior known as the jamming avoidance response (JAR). The JAR results in a categorical difference between Eigenmannia that are in groups of conspecifics and those that are alone. Fish in groups exhibit the JAR behavior and thereby experience ongoing, global synchronous 20- to 50-Hz electrosensory oscillations, whereas solitary fish do not. Although previous work has shown that these ongoing signals do not significantly degrade electrosensory behavior, these oscillations nevertheless elicit short-term synaptic depression in midbrain circuits. Because short-term synaptic depression can have profound effects on the transmission of information through synapses, we examined the differences in intracellularly recorded responses of midbrain neurons in awake, behaving fish to moving electrosensory images under electrosensory conditions that mimic solitary fish and fish in groups. In solitary conditions, moving objects elicited Gaussian or sinusoidal postsynaptic potentials (PSPs) that commonly exhibited preferential responses to a direction of motion. Surprisingly, when the same stimulus was presented in the presence of the global oscillations, directional selectivity was increased in all neurons tested. The magnitudes of the differences in PSP amplitude for preferred and nonpreferred directions were correlated with a measure of short-term synaptic depression in both conditions. The electrosensory consequences of the JAR appear to result in an enhancement of the representation of direction of motion in midbrain neurons. The data also support a role for short-term synaptic depression in the generation and modulation of directional responses.

The cellular basis for parallel neural transmission of a high-frequency stimulus and its low-frequency envelope

Sensory stimuli often have rich temporal and spatial structure. One class of stimuli that are common to visual and auditory systems and, as we show, the electrosensory system are signals that contain power in a narrow range of temporal (or spatial) frequencies. Characteristic of this class of signals is a slower variation in their amplitude, otherwise known as an envelope. There is evidence suggesting that, in the visual cortex, both narrowband stimuli and their envelopes are coded for in separate and parallel streams. The implementation of this parallel transmission is not well understood at the cellular level. We have identified the cellular basis for the parallel transmission of signal and envelope in the electrosensory system: a two-cell network consisting of an interneuron connected to a pyramidal cell by means of a slow synapse. This circuit could, in principle, be implemented in the auditory or visual cortex by the previously identified biophysics of cortical interneurons.

The decoding of electrosensory systems

Progress in the study of electrosensory systems has been facilitated by the systematic use of behavior as a tool to probe the nervous system. Indeed, a specific behavior that is found in a subset of weakly electric fishes, the jamming avoidance response, was used to identify and characterize an entire suite of brain circuits, from sensory receptors to motor units, that are involved in control of this behavior. Recent progress has focused on a re-analysis of this circuit in relation to newly described electrosensory behaviors, including prey capture, social signaling and the tracking of electrosensory objects. This re-analysis has led to a re-evaluation of the broader functional relevance of specific neural solutions to computational problems that are related to the control of the jamming avoidance response. Some of the recent insights that have emerged from this work include descriptions of mechanisms underlying dynamic receptive field properties, descriptions of the neural activity related to simultaneously occurring sensory stimuli, and a greater understanding of the role of short-term synaptic plasticity in temporal processing.

Encoding and processing biologically relevant temporal information in electrosensory systems

Wave-type weakly electric fish are specialists in time-domain processing: behaviors in these animals are often tightly correlated with the temporal structure of electrosensory signals. Behavioral responses in these fish can be dependent on differences in the temporal structure of electrosensory signals alone. This feature has facilitated the study of temporal codes and processing in central nervous system circuits of these animals. The temporal encoding and mechanisms used to transform temporal codes in the brain have been identified and characterized in several species, including South American gymnotid species and in the African mormyrid genus Gymnarchus. These distantly related groups use similar strategies for neural computations of information on the order of microseconds, milliseconds, and seconds. Here, we describe a suite of mechanisms for behaviorally relevant computations of temporal information that have been elucidated in these systems. These results show the critical role that behavioral experiments continue to have in the study of the neural control of behavior and its evolution.