A framework for a low-cost system of automated gate control in assays of spatial cognition in fishes.

Automation of experimental setups is a promising direction in behavioral research because it can facilitate the acquisition of data while increasing its repeatability and reliability. For example, research in spatial cognition can benefit from automated control by systematic manipulation of sensory cues and more efficient execution of training procedures. However, commercial solutions are often costly, restricted to specific platforms, and mainly focused on the automation of data acquisition, stimulus presentation, and reward delivery. Animal welfare considerations as well as experimental demands may require automating the access of an animal or animals to the experimental arena. Here, we provide and test a low-cost, versatile Raspberry Pi-based solution for such use cases. We provide four application scenarios of varying complexities, based on our research of spatial orientation and navigation in weakly electric fish, with step-by-step protocols for the control of gates in the experimental setups. This easy-to-implement, platform-independent approach can be adapted to various experimental needs, including closed-loop as well as field experiments. As such, it can contribute to the optimization and standardization of experiments in a variety of species, thereby enhancing the comparability of data.

Gene and Allele-Specific Expression Underlying the Electric Signal Divergence in African Weakly Electric Fish.

In the African weakly electric fish genus Campylomormyrus, electric organ discharge signals are strikingly different in shape and duration among closely related species, contribute to prezygotic isolation, and may have triggered an adaptive radiation. We performed mRNA sequencing on electric organs and skeletal muscles (from which the electric organs derive) from 3 species with short (0.4 ms), medium (5 ms), and long (40 ms) electric organ discharges and 2 different cross-species hybrids. We identified 1,444 upregulated genes in electric organ shared by all 5 species/hybrid cohorts, rendering them candidate genes for electric organ-specific properties in Campylomormyrus. We further identified several candidate genes, including KCNJ2 and KLF5, and their upregulation may contribute to increased electric organ discharge duration. Hybrids between a short (Campylomormyrus compressirostris) and a long (Campylomormyrus rhynchophorus) discharging species exhibit electric organ discharges of intermediate duration and showed imbalanced expression of KCNJ2 alleles, pointing toward a cis-regulatory difference at this locus, relative to electric organ discharge duration. KLF5 is a transcription factor potentially balancing potassium channel gene expression, a crucial process for the formation of an electric organ discharge. Unraveling the genetic basis of the species-specific modulation of the electric organ discharge in Campylomormyrus is crucial for understanding the adaptive radiation of this emerging model taxon of ecological (perhaps even sympatric) speciation.

Diet in phenotypically divergent sympatric species of African weakly electric fish (genus: Campylomormyrus)-A hybrid capture/HTS metabarcoding approach.

Ecological speciation within the mormyrid genus Campylomormyrus resulted in sympatric species exhibiting divergence in their feeding apparatus and electric organ discharge (EOD). This study documents the overall diet of the genus Campylomormyrus and examines the hypothesis that the Campylomormyrus radiation is caused by adaptation to different food sources. We performed diet assessment of five sympatric Campylomormyrus species (C. alces, C. compressirostris, C. curvirostris, C. tshokwe, C. numenius) and their sister taxon Gnathonemus petersii with markedly different snout morphologies and EODs using hybrid capture/HTS DNA metabarcoding of their stomach contents. Our approach allowed for high taxonomic resolution of prey items, including benthic invertebrates, allochthonous invertebrates and vegetation. Comparisons of the diet compositions using quantitative measures and diet overlap indices revealed that all species are able to exploit multiple food niches in their habitats, that is fauna at the bottom, the water surface and the water column. A major part of the diet is larvae of aquatic insects, such as dipterans, coleopterans and trichopterans, known to occur in holes and interstitial spaces of the substrate. The results indicate that different snout morphologies and the associated divergence in the EOD could translate into different prey spectra. This suggests that the diversification in EOD and/or morphology of the feeding apparatus could be under functional adaptation.

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.

Serotonin increases population coding of behaviorally relevant stimuli by enhancing responses of ON but not OFF-type sensory neurons.

How neural populations encode sensory input to generate behavioral responses remains a central problem in systems neuroscience. Here we investigated how neuromodulation influences population coding of behaviorally relevant stimuli to give rise to behavior in the electrosensory system of the weakly electric fish Apteronotus leptorhynchus. We performed multi-unit recordings from ON and OFF sensory pyramidal cells in response to stimuli whose amplitude (i.e., envelope) varied in time, before and after electrical stimulation of the raphe nuclei. Overall, raphe stimulation increased population coding by ON- but not by OFF-type cells, despite both cell types showing similar sensitivities to the stimulus at the single neuron level. Surprisingly, only changes in population coding by ON-type cells were correlated with changes in behavioral responses. Taken together, our results show that neuromodulation differentially affects ON vs. OFF-type cells in order to enhance perception of behaviorally relevant sensory input.

Spike timing-dependent plasticity alters electrosensory neuron synaptic strength in vitro but does not consistently predict changes in sensory tuning in vivo.

How do sensory systems optimize detection of behaviorally relevant stimuli when the sensory environment is constantly changing? We addressed the role of spike timing-dependent plasticity (STDP) in driving changes in synaptic strength in a sensory pathway and whether those changes in synaptic strength could alter sensory tuning. It is challenging to precisely control temporal patterns of synaptic activity in vivo and replicate those patterns in vitro in behaviorally relevant ways. This makes it difficult to make connections between STDP-induced changes in synaptic physiology and plasticity in sensory systems. Using the mormyrid species Brevimyrus niger and Brienomyrus brachyistius, which produce electric organ discharges for electrolocation and communication, we can precisely control the timing of synaptic input in vivo and replicate these same temporal patterns of synaptic input in vitro. In central electrosensory neurons in the electric communication pathway, using whole cell intracellular recordings in vitro, we paired presynaptic input with postsynaptic spiking at different delays. Using whole cell intracellular recordings in awake, behaving fish, we paired sensory stimulation with postsynaptic spiking using the same delays. We found that Hebbian STDP predictably alters sensory tuning in vitro and is mediated by NMDA receptors. However, the change in synaptic responses induced by sensory stimulation in vivo did not adhere to the direction predicted by the STDP observed in vitro. Further analysis suggests that this difference is influenced by polysynaptic activity, including inhibitory interneurons. Our findings suggest that STDP rules operating at identified synapses may not drive predictable changes in sensory responses at the circuit level.NEW & NOTEWORTHY We replicated behaviorally relevant temporal patterns of synaptic activity in vitro and used the same patterns during sensory stimulation in vivo. There was a Hebbian spike timing-dependent plasticity (STDP) pattern in vitro, but sensory responses in vivo did not shift according to STDP predictions. Analysis suggests that this disparity is influenced by differences in polysynaptic activity, including inhibitory interneurons. These results suggest that STDP rules at synapses in vitro do not necessarily apply to circuits in vivo.

Ketamine disrupts locomotion and electrolocation in a novel model of schizophrenia, Gnathonemus petersii fish.

The present study aimed to examine a weakly electric fish Gnathonemus petersii (G. petersii) as a candidate model organism of glutamatergic theory of schizophrenia. The idea of G. petersii elevating the modeling of schizophrenia symptoms is based on the fish's electrolocation and electrocommunication abilities. Fish were exposed to the NMDA antagonist ketamine in two distinct series differing in the dose of ketamine. The main finding revealed ketamine-induced disruption of the relationship between electric signaling and behavior indicating impairment of fish navigation. Moreover, lower doses of ketamine significantly increased locomotion and erratic movement and higher doses of ketamine reduced the number of electric organ discharges indicating successful induction of positive schizophrenia-like symptoms and disruption of fish navigation. Additionally, a low dose of haloperidol was used to test the normalization of the positive symptoms to suggest a predictive validity of the model. However, although successfully induced, positive symptoms were not normalized using the low dose of haloperidol; hence, more doses of the typical antipsychotic haloperidol and probably also of a representative of atypical antipsychotic drugs need to be examined to confirm the predictive validity of the model.

Computational modeling predicts regulation of central pattern generator oscillations by size and density of the underlying heterogenous network.

Central pattern generators are characterized by a heterogeneous cellular composition, with different cell types playing distinct roles in the production and transmission of rhythmic signals. However, little is known about the functional implications of individual variation in the relative distributions of cells and their connectivity patterns. Here, we addressed this question through a combination of morphological data analysis and computational modeling, using the pacemaker nucleus of the weakly electric fish Apteronotus leptorhynchus as case study. A neural network comprised of 60-110 interconnected pacemaker cells and 15-30 relay cells conveying its output to electromotoneurons in the spinal cord, this nucleus continuously generates neural signals at frequencies of up to 1 kHz with high temporal precision. We systematically explored the impact of network size and density on oscillation frequencies and their variation within and across cells. To accurately determine effect sizes, we minimized the likelihood of complex dynamics using a simplified setup precluding differential delays. To identify natural constraints, parameter ranges were extended beyond experimentally recorded numbers of cells and connections. Simulations revealed that pacemaker cells have higher frequencies and lower within-population variability than relay cells. Within-cell precision and between-cells frequency synchronization increased with the number of pacemaker cells and of connections of either type, and decreased with relay cell count in both populations. Network-level frequency-synchronized oscillations occurred in roughly half of simulations, with maximized likelihood and firing precision within biologically observed parameter ranges. These findings suggest the structure of the biological pacemaker nucleus is optimized for generating synchronized sustained oscillations.

Mormyrid fish as models for investigating sensory-motor integration: A behavioural perspective.

Animals possess senses which gather information from their environment. They can tune into important aspects of this information and decide on the most appropriate response, requiring coordination of their sensory and motor systems. This interaction is bidirectional. Animals can actively shape their perception with self-driven motion, altering sensory flow to maximise the environmental information they are able to extract. Mormyrid fish are excellent candidates for studying sensory-motor interactions, because they possess a unique sensory system (the active electric sense) and exhibit notable behaviours that seem to be associated with electrosensing. This review will take a behavioural approach to unpicking this relationship, using active electrolocation as an example where body movements and sensing capabilities are highly related and can be assessed in tandem. Active electrolocation is the process where individuals will generate and detect low-voltage electric fields to locate and recognise nearby objects. We will focus on research in the mormyrid Gnathonemus petersii (G. petersii), given the extensive study of this species, particularly its object recognition abilities. By studying object detection and recognition, we can assess the potential benefits of self-driven movements to enhance selection of biologically relevant information. Finally, these findings are highly relevant to understanding the involvement of movement in shaping the sensory experience of animals that use other sensory modalities. Understanding the overlap between sensory and motor systems will give insight into how different species have become adapted to their environments.

Finding food in the dark: how trajectories of a gymnotiform fish change with spatial learning.

We analyzed the trajectories of freely foraging Gymnotus sp., a pulse-type gymnotiform weakly electric fish, swimming in a dark arena. For each fish, we compared the its initial behavior as it learned the relative location of landmarks and food with its behavior after learning was complete, i.e. after time/distance to locate food had reached a minimal asymptotic level. During initial exploration when the fish did not know the arena layout, trajectories included many sharp angle head turns that occurred at nearly completely random intervals. After spatial learning was complete, head turns became far smoother. Interestingly, the fish still did not take a stereotyped direct route to the food but instead took smooth but variable curved trajectories. We also measured the fish's heading angle error (heading angle - heading angle towards food). After spatial learning, the fish's initial heading angle errors were strongly biased to zero, i.e. the fish mostly turned towards the food. As the fish approached closer to the food, they switched to a random search strategy with a more uniform distribution of heading angle errors.

A dynamic spike threshold with correlated noise predicts observed patterns of negative interval correlations in neuronal spike trains.

Negative correlations in the sequential evolution of interspike intervals (ISIs) are a signature of memory in neuronal spike-trains. They provide coding benefits including firing-rate stabilization, improved detectability of weak sensory signals, and enhanced transmission of information by improving signal-to-noise ratio. Primary electrosensory afferent spike-trains in weakly electric fish fall into two categories based on the pattern of ISI correlations: non-bursting units have negative correlations which remain negative but decay to zero with increasing lags (Type I ISI correlations), and bursting units have oscillatory (alternating sign) correlation which damp to zero with increasing lags (Type II ISI correlations). Here, we predict and match observed ISI correlations in these afferents using a stochastic dynamic threshold model. We determine the ISI correlation function as a function of an arbitrary discrete noise correlation function [Formula: see text], where k is a multiple of the mean ISI. The function permits forward and inverse calculations of the correlation function. Both types of correlation functions can be generated by adding colored noise to the spike threshold with Type I correlations generated with slow noise and Type II correlations generated with fast noise. A first-order autoregressive (AR) process with a single parameter is sufficient to predict and accurately match both types of afferent ISI correlation functions, with the type being determined by the sign of the AR parameter. The predicted and experimentally observed correlations are in geometric progression. The theory predicts that the limiting sum of ISI correlations is [Formula: see text] yielding a perfect DC-block in the power spectrum of the spike train. Observed ISI correlations from afferents have a limiting sum that is slightly larger at [Formula: see text] ([Formula: see text]). We conclude that the underlying process for generating ISIs may be a simple combination of low-order AR and moving average processes and discuss the results from the perspective of optimal coding.

Electric-field-coupled oscillators for collective electrochemical perception in biohybrid robotics.

This work explores the application of nonlinear oscillators coupled by an electric field in water, inspired by weakly electric fish. Such coupled oscillators operate in clear and colloidal (mud, bottom silt) water and represent a collective electrochemical sensor that is sensitive to global environmental parameters, the geometry of the common electric field and spatial dynamics of autonomous underwater vehicles (AUVs). Implemented in hardware and software, this approach can be used to create global awareness in a group of robots, which possess limited sensing and communication capabilities. Using oscillators from different AUVs enables extension of the range limitations related to the electric dipole of a single AUV. Applications of this technique are demonstrated for detecting the number of AUVs, distances between them, perception of dielectric objects and synchronization of behavior. Recognizing self-/nonself-generated signals by electric fish is re-embodied in a technological way through an 'electrical mirror' for discrimination between 'collective self' and 'collective nonself'. These approaches have been implemented in several research projects with bioinspired/biohybrid systems in fresh and salt water, and electrochemical sensing in fluidic media.

Minimal sensor arrays for localizing objects using an electric sense.

Weakly electric fish encode perturbations in a self-generated electric field to sense their environment. Localizing objects using this electric sense requires that distance be decoded from a two-dimensionalelectric imageof the field perturbations on their skin. Many studies of object localization by weakly electric fish, and by electric sensing in a generic context, have focused on extracting location information from different features of the electric image. Some of these studies have also considered the additional information gained from sampling the electric image at different times, and from different viewpoints. Here, we take a different perspective and instead consider the information available at asinglepoint in space (i.e. a single sensor or receptor) at a single point in time (i.e. constant field). By combining the information from multiple receptors, we show that an object's distance can be unambiguously encoded by as few as four receptors at specific locations on a sensing surface in a manner that is relatively robust to environmental noise. This provides a lower bound on the information (i.e. receptor array size) required to decode the three-dimensional location of an object using an electric sense.

Convergent mosaic brain evolution is associated with the evolution of novel electrosensory systems in teleost fishes.

Brain region size generally scales allometrically with brain size, but mosaic shifts in brain region size independent of brain size have been found in several lineages and may be related to the evolution of behavioral novelty. African weakly electric fishes (Mormyroidea) evolved a mosaically enlarged cerebellum and hindbrain, yet the relationship to their behaviorally novel electrosensory system remains unclear. We addressed this by studying South American weakly electric fishes (Gymnotiformes) and weakly electric catfishes (Synodontis spp.), which evolved varying aspects of electrosensory systems, independent of mormyroids. If the mormyroid mosaic increases are related to evolving an electrosensory system, we should find similar mosaic shifts in gymnotiforms and Synodontis. Using micro-computed tomography scans, we quantified brain region scaling for multiple electrogenic, electroreceptive, and non-electrosensing species. We found mosaic increases in cerebellum in all three electrogenic lineages relative to non-electric lineages and mosaic increases in torus semicircularis and hindbrain associated with the evolution of electrogenesis and electroreceptor type. These results show that evolving novel electrosensory systems is repeatedly and independently associated with changes in the sizes of individual major brain regions independent of brain size, suggesting that selection can impact structural brain composition to favor specific regions involved in novel behaviors.

Larger animals tend to have larger brains and smaller animals tend to have smaller ones. However, some species do not fit the pattern that would be expected based on their body size. This variation between species can also apply to individual brain regions. This may be due to evolutionary forces shaping the brain when favouring particular behaviours. However, it is difficult to directly link changes in species behaviour and variations in brain structure. One way to understand the impact of evolutionary adaptations is to study species that have developed new behaviours and compare them to related ones that lack such a behaviour. An opportunity to do this lies in the ability of several species of fish to produce and sense electric fields in water. While this system is not found in most fish, it has evolved multiple times independently in distantly-related lineages. Schumacher and Carlson examined whether differences in the size of brains and individual regions between species were associated with the evolution of electric field generation and sensing. Micro-computed tomography, or µCT, scans of the brains of multiple fish species revealed that the species that can produce electricity ­ also known as 'electrogenic' species' ­ have more similar brain structures to each other than to their close relatives that lack this ability. The brain regions involved in producing and detecting electrical charges were larger in these electrogenic fish. This similarity was apparent despite variations in how total brain size has evolved with body size across species. These results demonstrate how evolutionary forces acting on particular behaviours can lead to predictable changes in brain structure. Understanding how and why brains evolve will allow researchers to better predict how species' brains and behaviours may adapt as human activities alter their environments.

Communication with self, friends and foes in active-sensing animals.

Animals that rely on electrolocation and echolocation for navigation and prey detection benefit from sensory systems that can operate in the dark, allowing them to exploit sensory niches with few competitors. Active sensing has been characterized as a highly specialized form of communication, whereby an echolocating or electrolocating animal serves as both the sender and receiver of sensory information. This characterization inspires a framework to explore the functions of sensory channels that communicate information with the self and with others. Overlapping communication functions create challenges for signal privacy and fidelity by leaving active-sensing animals vulnerable to eavesdropping, jamming and masking. Here, we present an overview of active-sensing systems used by weakly electric fish, bats and odontocetes, and consider their susceptibility to heterospecific and conspecific jamming signals and eavesdropping. Susceptibility to interference from signals produced by both conspecifics and prey animals reduces the fidelity of electrolocation and echolocation for prey capture and foraging. Likewise, active-sensing signals may be eavesdropped, increasing the risk of alerting prey to the threat of predation or the risk of predation to the sender, or drawing competition to productive foraging sites. The evolutionary success of electrolocating and echolocating animals suggests that they effectively counter the costs of active sensing through rich and diverse adaptive behaviors that allow them to mitigate the effects of competition for signal space and the exploitation of their signals.

Salience of multisensory feedback regulates behavioral variability.

Many animal behaviors are robust to dramatic variations in morphophysiological features, both across and within individuals. The control strategies that animals use to achieve such robust behavioral performances are not known. Recent evidence suggests that animals rely on sensory feedback rather than precise tuning of neural controllers for robust control. Here we examine the structure of sensory feedback, including multisensory feedback, for robust control of animal behavior. We re-examined two recent datasets of refuge tracking responses ofEigenmannia virescens, a species of weakly electric fish.Eigenmanniarely on both the visual and electrosensory cues to track the position of a moving refuge. The datasets include experiments that varied the strength of visual and electrosensory signals. Our analyses show that increasing the salience (perceptibility) of visual or electrosensory signals resulted in more robust and precise behavioral responses. Further, we find that robust performance was enhanced by multisensory integration of simultaneous visual and electrosensory cues. These findings suggest that engineers may achieve better system performance by improving the salience of multisensory feedback rather than solely focusing on precisely tuned controllers.

Reconstruction of Electric Discharge Patterns and Electrogenesis Mechanism in African Sharptooth Catfish Clarias gariepinus (Clariidae, Siluriformes).

Electrical discharges (EDs) in the African sharptooth catfish Clarias gariepinus were studied. Irregular monopolar EDs, lasting for 8-10 ms and longer, and more complex EDs, lasting for 20-50 ms and characterized by specific indentation of the discharge pattern, were recorded in pairs of individuals exhibiting both aggressive and defensive behavior. The pattern of long discharges was reconstructed by adding short EDs with different latencies and amplitudes. The conditions for the formation of long EDs with asynchronous activity of electromotor neurons and the possibility of coordinated operation of the electric generator and electroreceptor systems in catfish were considered, since an increase in the duration of EDs lowers the threshold of their perception.

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.

Motion parallax for object localization in electric fields.

Parallax, as a visual effect, is used for depth perception of objects. But is there also the effect of parallax in the context of electric field imagery? In this work, the example of weakly electric fish is used to investigate how the self-generated electric field that these fish utilize for orientation and communication alike, may be used as a template to define electric parallax. The skin of the electric fish possesses a vast amount of electroreceptors that detect the self-emitted dipole-like electric field. In this work, the weakly electric fish is abstracted as an electric dipole with a sensor line in between the two emitters. With an analytical description of the object distortion for a uniform electric field, the distortion in a dipole-like field is simplified and simulated. On the basis of this simulation, the parallax effect could be demonstrated in electric field images i.e. by closer inspection of voltage profiles on the sensor line. Therefore, electric parallax can be defined as the relative movement of a signal feature of the voltage profile (here, the maximum or peak of the voltage profile) that travels along the sensor line peak trace (PT). The PT width correlates with the object's vertical distance to the sensor line, as close objects create a large PT and distant objects a small PT, comparable with the effect of visual motion parallax.

Electric signal synchronization as a behavioural strategy to generate social attention in small groups of mormyrid weakly electric fish and a mobile fish robot.

African weakly electric fish communicate at night by constantly emitting and perceiving brief electrical signals (electric organ discharges, EOD) at variable inter-discharge intervals (IDI). While the waveform of single EODs contains information about the sender's identity, the variable IDI patterns convey information about its current motivational and behavioural state. Pairs of fish can synchronize their EODs to each other via echo responses, and we have previously formulated a 'social attention hypothesis' stating that fish use echo responses to address specific individuals and establish brief dyadic communication frameworks within a group. Here, we employed a mobile fish robot to investigate the behaviour of small groups of up to four Mormyrus rume and characterized the social situations during which synchronizations occurred. An EOD-emitting robot reliably evoked social following behaviour, which was strongest in smaller groups and declined with increasing group size. We did not find significant differences in motor behaviour of M. rume with either an interactive playback (echo response) or a random control playback by the robot. Still, the robot reliably elicited mutual synchronizations with other fish. Synchronizations mostly occurred during relatively close social interactions, usually when the fish that initiated synchronization approached either the robot or another fish from a distance. The results support our social attention hypothesis and suggest that electric signal synchronization might facilitate the exchange of social information during a wide range of social behaviours from aggressive territorial displays to shoaling and even cooperative hunting in some mormyrids.