Continual Learning in a Multi-Layer Network of an Electric Fish.

Distributing learning across multiple layers has proven extremely powerful in artificial neural networks. However, little is known about how multi-layer learning is implemented in the brain. Here, we provide an account of learning across multiple processing layers in the electrosensory lobe (ELL) of mormyrid fish and report how it solves problems well known from machine learning. Because the ELL operates and learns continuously, it must reconcile learning and signaling functions without switching its mode of operation. We show that this is accomplished through a functional compartmentalization within intermediate layer neurons in which inputs driving learning differentially affect dendritic and axonal spikes. We also find that connectivity based on learning rather than sensory response selectivity assures that plasticity at synapses onto intermediate-layer neurons is matched to the requirements of output neurons. The mechanisms we uncover have relevance to learning in the cerebellum, hippocampus, and cerebral cortex, as well as in artificial systems.

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.

Advancing human disease research with fish evolutionary mutant models.

Model organism research is essential to understand disease mechanisms. However, laboratory-induced genetic models can lack genetic variation and often fail to mimic the spectrum of disease severity. Evolutionary mutant models (EMMs) are species with evolved phenotypes that mimic human disease. EMMs complement traditional laboratory models by providing unique avenues to study gene-by-environment interactions, modular mutations in noncoding regions, and their evolved compensations. EMMs have improved our understanding of complex diseases, including cancer, diabetes, and aging, and illuminated mechanisms in many organs. Rapid advancements of sequencing and genome-editing technologies have catapulted the utility of EMMs, particularly in fish. Fish are the most diverse group of vertebrates, exhibiting a kaleidoscope of specialized phenotypes, many that would be pathogenic in humans but are adaptive in the species' specialized habitat. Importantly, evolved compensations can suggest avenues for novel disease therapies. This review summarizes current research using fish EMMs to advance our understanding of human disease.

Neuroendocrine mechanisms contributing to the coevolution of sociality and communication.

Communication is inherently social, so signaling systems should evolve with social systems. The 'social complexity hypothesis' posits that social complexity necessitates communicative complexity and is generally supported in vocalizing mammals. This hypothesis, however, has seldom been tested outside the acoustic modality, and comparisons across studies are confounded by varying definitions of complexity. Moreover, proximate mechanisms underlying coevolution of sociality and communication remain largely unexamined. In this review, we argue that to uncover how sociality and communication coevolve, we need to examine variation in the neuroendocrine mechanisms that coregulate social behavior and signal production and perception. Specifically, we focus on steroid hormones, monoamines, and nonapeptides, which modulate both social behavior and sensorimotor circuits and are likely targets of selection during social evolution. Lastly, we highlight weakly electric fishes as an ideal system in which to comparatively address the proximate mechanisms underlying relationships between social and signal diversity in a novel modality.

A review of the reproductive biology of mormyroid fishes: An emerging model for biomedical research.

Mormyroidea is a superfamily of weakly electric African fishes with great potential as a model in a variety of biomedical research areas including systems neuroscience, muscle cell and craniofacial development, ion channel biophysics, and flagellar/ciliary biology. However, they are currently difficult to breed in the laboratory setting, which is essential for any tractable model organism. As such, there is a need to better understand the reproductive biology of mormyroids to breed them more reliably in the laboratory to effectively use them as a biomedical research model. This review seeks to (1) briefly highlight the biomedically relevant phenotypes of mormyroids and (2) compile information about mormyroid reproduction including sex differences, breeding season, sexual maturity, gonads, gametes, and courtship/spawning behaviors. We also highlight areas of mormyroid reproductive biology that are currently unexplored and/or have the potential for further investigation that may provide insights into more successful mormyroid laboratory breeding methods.

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.

Model organisms and systems in neuroethology: one hundred years of history and a look into the future.

The Journal of Comparative Physiology lived up to its name in the last 100 years by including more than 1500 different taxa in almost 10,000 publications. Seventeen phyla of the animal kingdom were represented. The honeybee (Apis mellifera) is the taxon with most publications, followed by locust (Locusta migratoria), crayfishes (Cambarus spp.), and fruitfly (Drosophila melanogaster). The representation of species in this journal in the past, thus, differs much from the 13 model systems as named by the National Institutes of Health (USA). We mention major accomplishments of research on species with specific adaptations, specialist animals, for example, the quantitative description of the processes underlying the axon potential in squid (Loligo forbesii) and the isolation of the first receptor channel in the electric eel (Electrophorus electricus) and electric ray (Torpedo spp.). Future neuroethological work should make the recent genetic and technological developments available for specialist animals. There are many research questions left that may be answered with high yield in specialists and some questions that can only be answered in specialists. Moreover, the adaptations of animals that occupy specific ecological niches often lend themselves to biomimetic applications. We go into some depth in explaining our thoughts in the research of motion vision in insects, sound localization in barn owls, and electroreception in weakly electric fish.

Vasotocin but not isotocin is involved in the emergence of the dominant-subordinate status in males of the weakly electric fish, Gymnotus omarorum.

The establishment of the dominant-subordinate status implies a clear behavioral asymmetry between contenders that arises immediately after the resolution of the agonistic encounter and persists during the maintenance of stable dominance hierarchies. Changes in the activity of the brain social behavior network (SBN) are postulated to be responsible for the establishment and maintenance of the dominant-subordinate status. The hypothalamic nonapeptides of the vasopressin (AVP) and oxytocin (OT) families are known to modulate the activity of the SBN in a context-dependent manner across vertebrates, including status-dependent modulations. We searched for status-dependent asymmetries in AVP-like (vasotocin, AVT) and OT-like (isotocin, IT) cell number and activation immediately after the establishment of dominance in males of the weakly electric fish, Gymnotus omarorum, which displays the best understood example of non-breeding territorial aggression among teleosts. We used immunolabeling (FOS, AVT, and IT) of preoptic area (POA) neurons after dyadic agonistic encounters. This study is among the first to show in teleosts that AVT, but not IT, is involved in the establishment of the dominant-subordinate status. We also found status-dependent subregion-specific changes of AVT cell number and activation. These results confirm the involvement of AVT in the establishment of dominance and support the speculation that AVT is released from dominants' AVT neurons.

Species variation in steroid hormone-related gene expression contributes to species diversity in sexually dimorphic communication in electric fishes.

Sexually dimorphic behaviors are often regulated by gonadal steroid hormones. Species diversity in behavioral sex differences may arise as expression of genes mediating steroid action in brain regions controlling these behaviors evolves. The electric communication signals of apteronotid knifefishes are an excellent model for comparatively studying neuroendocrine regulation of sexually dimorphic behavior. These fish produce and detect weak electric organ discharges (EODs) for electrolocation and communication. EOD frequency (EODf), controlled by the medullary pacemaker nucleus (Pn), is sexually dimorphic and regulated by androgens and estrogens in some species, but is sexually monomorphic and unaffected by hormones in other species. We quantified expression of genes for steroid receptors, metabolizing enzymes, and cofactors in the Pn of two species with sexually dimorphic EODf (Apteronotus albifrons and Apteronotus leptorhynchus) and two species with sexually monomorphic EODf ("Apteronotus" bonapartii and Parapteronotus hasemani). The "A." bonapartii Pn expressed lower levels of androgen receptor (AR) genes than the Pn of species with sexually dimorphic EODf. In contrast, the P. hasemani Pn robustly expressed AR genes, but expressed lower levels of genes for 5α-reductases, which convert androgens to more potent metabolites, and higher levels of genes for 17ß-hydroxysteroid dehydrogenases that oxidize androgens and estrogens to less potent forms. These findings suggest that sexual monomorphism of EODf arose convergently via two different mechanisms. In "A." bonapartii, reduced Pn expression of ARs likely results in insensitivity of EODf to androgens, whereas in P. hasemani, gonadal steroids may be metabolically inactivated in the Pn, reducing their potential to influence EODf.

Differential expression of steroid-related genes across electrosensory brain regions in two sexually dimorphic species of electric knifefish.

The production of communication signals can be modulated by hormones acting on the brain regions that regulate these signals. However, less is known about how signal perception is regulated by hormones. The electrocommunication signals of weakly electric fishes are sexually dimorphic, sensitive to hormones, and vary across species. The neural circuits that regulate the production and perception of these signals are also well-characterized, and electric fishes are thus an excellent model to examine the neuroendocrine regulation of sensorimotor mechanisms of communication. We investigated (1) whether steroid-related genes are expressed in sensory brain regions that process communication signals; and (2) whether this expression differs across sexes and species that have different patterns of sexual dimorphism in their signals. Apteronotus leptorhynchus and Apteronotus albifrons produce continuous electric organ discharges (EODs) that are used for communication. Two brain regions, the electrosensory lateral line lobe (ELL) and the dorsal torus semicircularis (TSd), process inputs from electroreceptors to allow fish to detect and discriminate electrocommunication signals. We used qPCR to quantify the expression of genes for two androgen receptors (ar1, ar2), two estrogen receptors (esr1, esr2b), and aromatase (cyp19a1b). Four out of five steroid-related genes were expressed in both sensory brain regions, and their expression often varied between sexes and species. These results suggest that expression of steroid-related genes in the brain may differentially influence how EOD signals are encoded across species and sexes, and that gonadal steroids may coordinately regulate central circuits that control both the production and perception of EODs.

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.

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.

Neuroethology in South America: past, present and future.

South America is a vast continent endowed with extraordinary biodiversity that offers abundant opportunities for neuroethological research. Although neuroethology is still emerging in the region, the number of research groups studying South American species to unveil the neural organization of natural behaviors has grown considerably during the last decade. In this Perspective, we provide an account of the roots and strategies that led to the present state of neuroethology in the Southern Cone of America, with a forward-looking vision of its role in education and its international recognition. Hopefully, our Perspective will serve to further promote the study of natural behaviors across South America, as well as in other scarcely explored regions of the world.

Time-Comparator Neural Circuits of Gymnotiform Electric Fishes.

Weakly electric fish possess electrosensory neural systems that are dedicated to detect microsecond time differences between sensory signals. Many features of this timing system, such as electroreceptor encoding, time-locked responses, and time-comparator neural circuit, are shared by closely related as well as distantly related electric fishes. The appearance and location of the time-comparator neural structures, however, are different among species. The timing systems of different electric fish species are compared.

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.

EEOA: Cost and Energy Efficient Task Scheduling in a Cloud-Fog Framework.

Cloud-fog computing is a wide range of service environments created to provide quick, flexible services to customers, and the phenomenal growth of the Internet of Things (IoT) has produced an immense amount of data on a daily basis. To complete tasks and meet service-level agreement (SLA) commitments, the provider assigns appropriate resources and employs scheduling techniques to efficiently manage the execution of received IoT tasks in fog or cloud systems. The effectiveness of cloud services is directly impacted by some other important criteria, such as energy usage and cost, which are not taken into account by many of the existing methodologies. To resolve the aforementioned problems, an effective scheduling algorithm is required to schedule the heterogeneous workload and enhance the quality of service (QoS). Therefore, a nature-inspired multi-objective task scheduling algorithm called the electric earthworm optimization algorithm (EEOA) is proposed in this paper for IoT requests in a cloud-fog framework. This method was created using the combination of the earthworm optimization algorithm (EOA) and the electric fish optimization algorithm (EFO) to improve EFO's potential to be exploited while looking for the best solution to the problem at hand. Concerning execution time, cost, makespan, and energy consumption, the suggested scheduling technique's performance was assessed using significant instances of real-world workloads such as CEA-CURIE and HPC2N. Based on simulation results, our proposed approach improves efficiency by 89%, energy consumption by 94%, and total cost by 87% over existing algorithms for the scenarios considered using different benchmarks. Detailed simulations demonstrate that the suggested approach provides a superior scheduling scheme with better results than the existing scheduling techniques.

Visualization of electric fields and associated behavior in fish and other aquatic animals.

In some fish lineages, evolution has led to unique sensory adaptations that provide information which is not available to terrestrial animals. These sensory systems include, among others, electroreception, which together with the ability of fish to generate electric discharges plays a role in social communication and object location. Most studies on electric phenomena in aquatic animals are dedicated to selected groups of electric fishes that regularly generate electric signals (Mormyriformes, Gymnotiformes). There exist, however, several species (hitherto described as non-electric) which, though able to perceive electric signals, have now been found to also generate them. In this article, we introduce a tool that we have designed to investigate such electric activity. This required significant adaptations of the equipment used in fish with regular discharge generation. The necessary improvements were realized by using a multielectrode registration setup allowing simultaneous visualization and quantification of behavior and associated electric activity of fish, alone or in groups, with combined electro-video clips. Precise synchronization of locomotor and electric behaviors made it possible to determine the electrically active fish in a group, and also the location of the electrogenic structure inside the fish's body. Our simple registration procedure, together with data presentation, should attract a broad audience of scientists taking up the challenge of uncovering electric phenomena in aquatic animals currently treated as electrically inactive.

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.