Active sensing associated with spatial learning reveals memory-based attention in an electric fish

Social behavior in South American electric fishes: Linking neuroendocrine regulation, signal plasticity, and reproductive strategies

Cross-species analysis can provide valuable insights into the neural and hormonal mechanisms underlying behavior. South American weakly electric fishes (order Gymnotiformes) are ideal models due to their well-characterized electric signals, which convey important social information. These signals are quantifiable and traceable to specific brain and peripheral substrates. This review focuses on social electric signaling in two nocturnal gymnotiform species found syntopically in Uruguay: Gymnotus omarorum and Brachyhypopomus gauderio. We examine the influence of sex, social context, and neuromodulators on signal flexibility across day/night and seasonal cycles. Common features include a nocturnal increase in basal electric rate mediated by melatonin, enhancing awareness and social engagement; androgen-mediated seasonal protection of electric signals against high summer temperatures; and the production of social electric signals, such as chirps and interruptions, during social interactions, modulated by vasotocinergic and serotonergic systems. Key differences lie in neuromodulator involvement and signal plasticity: B. gauderio exhibits greater signal flexibility, with sex- and context-dependent waveform changes and a broader repertoire of transient social signals used in dyadic interactions, supported by distinct neural mechanisms. These differences likely reflect species-specific reproductive strategies and their associated costs, such as predation pressure. This review underscores the value of studying electric behavior to understand the integration of internal states with environmental and social cues, offering insights into mechanisms underlying behavioral responses to natural challenges.

The sensory-effector cycle, contributions from a native species

The analysis of the action-perception cycle in Gymnotus omarorum has proven that this native species is an excellent model system to study the dynamics of this loop and the implementation mechanisms of its different stages. This analysis provided insight into cell and synaptic function, plasticity, circuitry ensemble, and neural codes. This research has also contributed to the development of Neuroscience that led to the foundation of the Sociedad Uruguaya de Neurociencias which anniversary this issue celebrates. This article first considers the features that these fish offer to the conceptual analysis of reafferent systems. Second, it focuses on some of the stages involved in the sensory effector cycle. This includes the analysis of: a) how the electromotor system contributes to the understanding of central pattern generators of rhythms and action patterns; b) how electric images are formed, peripherally encoded, and contribute to the understanding of how imaging molds perception; c) how sensory detection and behavioral responses to novel events may be used for describing the dynamics of the cycle; d) how the pulsed imaging strategy illustrates the importance of using a code of packeted well timed spikes for fast detection of sensory features; and e) how the interactions between electro- and skeletomotor control using the Mauthner initiated escape response serve as a useful neuroethological case study. We conclude by considering some still open questions and research perspectives that, together with the exceptional advantages offered by electric fish, provide promising advances in the general understanding of the neural basis of the sensory-motor loop.

Shortcutting from self-motion signals reveals a cognitive map in mice

Animals navigate by learning the spatial layout of their environment. We investigated spatial learning of mice in an open maze where food was hidden in one of a hundred holes. Mice leaving from a stable entrance learned to efficiently navigate to the food without the need for landmarks. We developed a quantitative framework to reveal how the mice estimate the food location based on analyses of trajectories and active hole checks. After learning, the computed 'target estimation vector' (TEV) closely approximated the mice's route and its hole check distribution. The TEV required learning both the direction and distance of the start to food vector, and our data suggests that different learning dynamics underlie these estimates. We propose that the TEV can be precisely connected to the properties of hippocampal place cells. Finally, we provide the first demonstration that, after learning the location of two food sites, the mice took a shortcut between the sites, demonstrating that they had generated a cognitive map.

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.

Lessons in cognition: A review of maze designs and procedures used to measure spatial learning in fish

The use of different mazes to assess spatial learning has become more common in fish behavior studies in recent decades. This increase in fish cognition research has opened the door to numerous possibilities for exciting and diverse questions, such as identifying ecological drivers of spatial cognition and understanding the role individual variation plays in navigational abilities. There are many different types of mazes, each with its own specific considerations, making it challenging to determine exactly which spatial test is the most relevant and appropriate for a particular experiment. Many spatial mazes, such as the T-maze and Y-maze, have been successfully adapted from rodent studies, particularly with respect to zebrafish, a widely accepted non-mammalian model in biomedical studies. Standardization across studies is increasing with these easily accessible maze designs, validating them for use in fish; however, variations in design (e.g., length of arms and scale) and procedure still exist, and the impact of these variations on results is largely unknown. The efforts to standardize mazes outside zebrafish work are also more limited. Other mazes have been developed specifically for use on fish, with design modifications varying widely, making it difficult to draw comparisons. In this review, we have highlighted the many design and procedural elements that should be considered for the acquisition of reliable behavioral data, with the goal of drawing readers' attention to aspects of experimentation that are often not given the careful consideration that they deserve. We then argue that additional focused research and reporting is needed to produce more reliable methods in spatial learning research across a broader range of subjects.

Understanding daily rhythms in weakly electric fish: the role of melatonin on the electric behavior of Brachyhypopomus gauderio

Living organisms display molecular, physiological and behavioral rhythms synchronized with natural environmental cycles. Understanding the interaction between environment, physiology and behavior requires taking into account the complexity of natural habitats and the diversity of behavioral and physiological adaptations. Brachyhypopomus gauderio is characterized by the emission of electric organ discharges (EOD), with a very stable rate modulated by social and environmental cues. The nocturnal arousal in B. gauderio coincides with a melatonin-dependent EOD rate increase. Here, we first show a daily cycle in both the EOD basal rate (EOD-BR) and EOD-BR variability of B. gauderio in nature. We approached the understanding of the role of melatonin in this natural behavior through both behavioral pharmacology and in vitro assays. We report, for the first time in gymnotiformes, a direct effect of melatonin on the pacemaker nucleus (PN) in in vitro preparation. Melatonin treatment lowered EOD-BR in freely moving fish and PN basal rate, while increasing the variability of both. These results show that melatonin plays a key role in modulating the electric behavior of B. gauderio through its effect on rate and variability, both of which must be under a tight temporal regulation to prepare the animal for the challenging nocturnal environment.

The sensory effects of light on the electric organ discharge rate of Gymnotus omarorum

Gymnotiformes are nocturnal fishes inhabiting the root mats of floating plants. They use their electric organ discharge (EOD) to explore the environment and to communicate. Here, we show and describe tonic and phasic sensory-electromotor responses to light distinct from indirect effects depending on the light-induced endogenous circadian rhythm. In the dark, principally during the night, inter-EOD interval histograms are bimodal: the main peak corresponds to the basal rate and a secondary peak corresponds to high-frequency bouts. Light causes a twofold tonic but opposing effect on the EOD histogram: (i) decreasing the main mode and (ii) blocking the high-frequency bouts and consequently increasing the main peak at the expense of removal of the secondary one. Additionally, light evokes phasic responses whose amplitude increases with intensity but whose slow time course and poor adaptation differentiate from the so-called novelty responses evoked by abrupt changes in sensory stimuli of other modalities. We confirmed that Gymnotus omarorum tends to escape from light, suggesting that these phasic responses are probably part of a global 'light-avoidance response'. We interpret the data within an ecological context. Fish rest under the shade of aquatic plants during the day and light spots due to the sun's relative movement alert the fish to hide in shady zones to avoid macroptic predators and facilitate tracking the movement of floating plant islands by wind and/or water currents.

An internal model for canceling self-generated sensory input in freely behaving electric fish

Internal models that predict the sensory consequences of motor actions are vital for sensory, motor, and cognitive functions. However, the relationship between motor action and sensory input is complex, often varying from one moment to another depending on the state of the animal and the environment. The neural mechanisms for generating predictions under such challenging, real-world conditions remain largely unknown. Using novel methods for underwater neural recording, a quantitative analysis of unconstrained behavior, and computational modeling, we provide evidence for an unexpectedly sophisticated internal model at the first stage of active electrosensory processing in mormyrid fish. Closed-loop manipulations reveal that electrosensory lobe neurons are capable of simultaneously learning and storing multiple predictions of the sensory consequences of motor commands specific to different sensory states. These results provide mechanistic insights into how internal motor signals and information about the sensory environment are combined within a cerebellum-like circuitry to predict the sensory consequences of natural behavior.

Computational cross-species views of the hippocampal formation

The discovery of place cells and head direction cells in the hippocampal formation of freely foraging rodents has led to an emphasis of its role in encoding allocentric spatial relationships. In contrast, studies in head-fixed primates have additionally found representations of spatial views. We review recent experiments in freely moving monkeys that expand upon these findings and show that postural variables such as eye/head movements strongly influence neural activity in the hippocampal formation, suggesting that the function of the hippocampus depends on where the animal looks. We interpret these results in the light of recent studies in humans performing challenging navigation tasks which suggest that depending on the context, eye/head movements serve one of two roles-gathering information about the structure of the environment (active sensing) or externalizing the contents of internal beliefs/deliberation (embodied cognition). These findings prompt future experimental investigations into the information carried by signals flowing between the hippocampal formation and the brain regions controlling postural variables, and constitute a basis for updating computational theories of the hippocampal system to accommodate the influence of eye/head movements.

A brainstem integrator for self-location memory and positional homeostasis in zebrafish

To track and control self-location, animals integrate their movements through space. Representations of self-location are observed in the mammalian hippocampal formation, but it is unknown if positional representations exist in more ancient brain regions, how they arise from integrated self-motion, and by what pathways they control locomotion. Here, in a head-fixed, fictive-swimming, virtual-reality preparation, we exposed larval zebrafish to a variety of involuntary displacements. They tracked these displacements and, many seconds later, moved toward their earlier location through corrective swimming ("positional homeostasis"). Whole-brain functional imaging revealed a network in the medulla that stores a memory of location and induces an error signal in the inferior olive to drive future corrective swimming. Optogenetically manipulating medullary integrator cells evoked displacement-memory behavior. Ablating them, or downstream olivary neurons, abolished displacement corrections. These results reveal a multiregional hindbrain circuit in vertebrates that integrates self-motion and stores self-location to control locomotor behavior.

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.

Eye movements reveal spatiotemporal dynamics of visually-informed planning in navigation

Goal-oriented navigation is widely understood to depend upon internal maps. Although this may be the case in many settings, humans tend to rely on vision in complex, unfamiliar environments. To study the nature of gaze during visually-guided navigation, we tasked humans to navigate to transiently visible goals in virtual mazes of varying levels of difficulty, observing that they took near-optimal trajectories in all arenas. By analyzing participants' eye movements, we gained insights into how they performed visually-informed planning. The spatial distribution of gaze revealed that environmental complexity mediated a striking trade-off in the extent to which attention was directed towards two complimentary aspects of the world model: the reward location and task-relevant transitions. The temporal evolution of gaze revealed rapid, sequential prospection of the future path, evocative of neural replay. These findings suggest that the spatiotemporal characteristics of gaze during navigation are significantly shaped by the unique cognitive computations underlying real-world, sequential decision making.

The Geometric World of Fishes: A Synthesis on Spatial Reorientation in Teleosts

Fishes navigate through underwater environments with remarkable spatial precision and memory. Freshwater and seawater species make use of several orientation strategies for adaptative behavior that is on par with terrestrial organisms, and research on cognitive mapping and landmark use in fish have shown that relational and associative spatial learning guide goal-directed navigation not only in terrestrial but also in aquatic habitats. In the past thirty years, researchers explored spatial cognition in fishes in relation to the use of environmental geometry, perhaps because of the scientific value to compare them with land-dwelling animals. Geometric navigation involves the encoding of macrostructural characteristics of space, which are based on the Euclidean concepts of "points", "surfaces", and "boundaries". The current review aims to inspect the extant literature on navigation by geometry in fishes, emphasizing both the recruitment of visual/extra-visual strategies and the nature of the behavioral task on orientation performance.

Social ascent changes cognition, behaviour and physiology in a highly social cichlid fish

When an individual ascends in dominance status within their social community, they often undergo a suite of behavioural, physiological and neuromolecular changes. While these changes have been extensively characterized across a number of species, we know much less about the degree to which these changes in turn influence cognitive processes like associative learning, memory and spatial navigation. Here, we assessed male Astatotilapia burtoni, an African cichlid fish known for its dynamic social dominance hierarchies, in a set of cognitive tasks both before and after a community perturbation in which some individuals ascended in dominance status. We assayed steroid hormone (cortisol, testosterone) levels before and after the community experienced a social perturbation. We found that ascending males changed their physiology and novel object recognition preference during the perturbation, and they subsequently differed in social competence from non-ascenders. Additionally, using a principal component analysis we were able to identify specific cognitive and physiological attributes that appear to predispose certain individuals to ascend in social status once a perturbation occurs. These previously undiscovered relationships between social ascent and cognition further emphasize the broad influence of social dominance on animal decision-making. This article is part of the theme issue 'The centennial of the pecking order: current state and future prospects for the study of dominance hierarchies'.

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.

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

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

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

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

Linking active sensing and spatial learning in weakly electric fish

Weakly electric fish can learn the spatial layout of their environment using only their short-range electric sense. During spatial learning, active sensing motions are used to memorize landmark locations so that they can serve as anchors for idiothetic-based navigation. A hindbrain feedback circuit selectively amplifies the electrosensory input arising from these motions. The ascending electrolocation pathway preferentially transmits this information to the pallial regions involved in spatial learning and navigation. Similarities in both behavioral patterns and hindbrain circuitry of gymnotiform and mormyrid fish, two families that independently evolved their electrosense, suggest that amplification and transmission of active sensing motion inputs are fundamental mechanisms for spatial memory acquisition.

Spatial Cognition in Teleost Fish: Strategies and Mechanisms

Teleost fish have been traditionally considered primitive vertebrates compared to mammals and birds in regard to brain complexity and behavioral functions. However, an increasing amount of evidence suggests that teleosts show advanced cognitive capabilities including spatial navigation skills that parallel those of land vertebrates. Teleost fish rely on a multiplicity of sensory cues and can use a variety of spatial strategies for navigation, ranging from relatively simple body-centered orientation responses to allocentric or "external world-centered" navigation, likely based on map-like relational memory representations of the environment. These distinct spatial strategies are based on separate brain mechanisms. For example, a crucial brain center for egocentric orientation in teleost fish is the optic tectum, which can be considered an essential hub in a wider brain network responsible for the generation of egocentrically referenced actions in space. In contrast, other brain centers, such as the dorsolateral telencephalic pallium of teleost fish, considered homologue to the hippocampal pallium of land vertebrates, seem to be crucial for allocentric navigation based on map-like spatial memory. Such hypothetical relational memory representations endow fish's spatial behavior with considerable navigational flexibility, allowing them, for example, to perform shortcuts and detours.

Glutamatergic control of a pattern-generating central nucleus in a gymnotiform fish

The activity of central pattern-generating networks (CPGs) may change under the control exerted by various neurotransmitters and modulators to adapt its behavioral outputs to different environmental demands. Although the mechanisms underlying this control have been well established in invertebrates, most of their synaptic and cellular bases are not yet well understood in vertebrates. Gymnotus omarorum, a pulse-type gymnotiform electric fish, provides a well-suited vertebrate model to investigate these mechanisms. G. omarorum emits rhythmic and stereotyped electric organ discharges (EODs), which function in both perception and communication, under the command of an electromotor CPG. This nucleus is composed of electrotonically coupled intrinsic pacemaker cells, which pace the rhythm, and bulbospinal projecting relay cells that contribute to organize the pattern of the muscle-derived effector activation that produce the EOD. Descending influences target CPG neurons to produce adaptive behavioral electromotor responses to different environmental challenges. We used electrophysiological and pharmacological techniques in brainstem slices of G. omarorum to investigate the underpinnings of the fast transmitter control of its electromotor CPG. We demonstrate that pacemaker, but not relay cells, are endowed with ionotropic and metabotropic glutamate receptor subtypes. We also show that glutamatergic control of the CPG likely involves two types of synapses contacting pacemaker cells, one type containing both α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) and N-methyl-d-aspartate (NMDA) receptors and the other one only-NMDA receptor. Fast neurotransmitter control of vertebrate CPGs seems to exploit the kinetics of the involved postsynaptic receptors to command different behavioral outputs. The prospect of common neural designs to control CPG activity in vertebrates is discussed.NEW & NOTEWORTHY Underpinnings of neuromodulation of central pattern-generating networks (CPG) have been well characterized in many species. The effects of fast neurotransmitter systems remain, however, poorly understood. This research uses in vitro electrophysiological and pharmacological techniques to show that the neurotransmitter control of a vertebrate CPG in gymnotiform fish involves the convergence of only-NMDA and AMPA-NMDA glutamatergic synapses onto neurons that pace the rhythm. These inputs may organize different behavioral outputs according to their distinct functional properties.

Equal performance but distinct behaviors: sex differences in a novel object recognition task and spatial maze in a highly social cichlid fish

Sex differences in behavior and cognition can be driven by differential selection pressures from the environment and in the underlying neuromolecular mechanisms of decision-making. The highly social cichlid fish Astatotilapia burtoni exhibits dynamic and complex social hierarchies, yet explicit cognitive testing (outside of social contexts) and investigations of sex differences in cognition have yet to be fully explored. Here we assessed male and female A. burtoni in two cognitive tasks: a novel object recognition task and a spatial task. We hypothesized that males outperform females in a spatial learning task and exhibit more neophilic/exploratory behavior across both tasks. In the present study we find that both sexes prefer the familiar object in a novel object recognition task, but the time at which they exhibit this preference differs between the sexes. Females more frequently learned the spatial task, exhibiting longer decision latencies and quicker error correction, suggesting a potential speed-accuracy tradeoff. Furthermore, the sexes differ in space use in both tasks and in a principal component analysis of the spatial task. A model selection analysis finds that preference, approach, and interaction duration in the novel object recognition task reach a threshold of importance averaged across all models. This work highlights the need to explicitly test for sex differences in cognition to better understand how individuals navigate dynamic social environments.

Distribution of the cholinergic nuclei in the brain of the weakly electric fish, Apteronotus leptorhynchus: Implications for sensory processing

Acetylcholine acts as a neurotransmitter/neuromodulator of many central nervous system processes such as learning and memory, attention, motor control, and sensory processing. The present study describes the spatial distribution of cholinergic neurons throughout the brain of the weakly electric fish, Apteronotus leptorhynchus, using in situ hybridization of choline acetyltransferase mRNA. Distinct groups of cholinergic cells were observed in the telencephalon, diencephalon, mesencephalon, and hindbrain. These included cholinergic cell groups typically identified in other vertebrate brains, for example, motor neurons. Using both in vitro and ex vivo neuronal tracing methods, we identified two new cholinergic connections leading to novel hypotheses on their functional significance. Projections to the nucleus praeeminentialis (nP) arise from isthmic nuclei, possibly including the nucleus lateralis valvulae (nLV) and the isthmic nucleus (nI). The nP is a central component of all electrosensory feedback pathways to the electrosensory lateral line lobe (ELL). We have previously shown that some neurons in nP, TS, and tectum express muscarinic receptors. We hypothesize that, based on nLV/nI cell responses in other teleosts and isthmic connectivity in A. leptorhynchus, the isthmic connections to nP, TS, and tectum modulate responses to electrosensory and/or visual motion and, in particular, to looming/receding stimuli. In addition, we found that the octavolateral efferent (OE) nucleus is the likely source of cholinergic fibers innervating the ELL. In other teleosts, OE inhibits octavolateral hair cells during locomotion. In gymnotiform fish, OE may also act on the first central processing stage and, we hypothesize, implement corollary discharge modulation of electrosensory processing during locomotion.

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.

Task-Related Sensorimotor Adjustments Increase the Sensory Range in Electrolocation

Perception and motor control traditionally are studied separately. However, motor activity can serve as a scaffold to shape the sensory flow. This tight link between motor actions and sensing is particularly evident in active sensory systems. Here, we investigate how the weakly electric mormyrid fish Gnathonemus petersii of undetermined sex structure their sensing and motor behavior while learning a perceptual task. We find systematic adjustments of the motor behavior that correlate with an increased performance. Using a model to compute the electrosensory input, we show that these behavioral adjustments improve the sensory input. As we find low neuronal detection thresholds at the level of medullary electrosensory neurons, it seems that the behavior-driven improvements of the sensory input are highly suitable to overcome the sensory limitations, thereby increasing the sensory range. Our results show that motor control is an active component of sensory learning, demonstrating that a detailed understanding of contribution of motor actions to sensing is needed to understand even seemingly simple behaviors.SIGNIFICANCE STATEMENT Motor-guided sensation and perception are intertwined, with motor behavior serving as a scaffold to shape the sensory input. We characterized how the weakly electric mormyrid fish Gnathonemus petersii, as it learns a perceptual task, restructures its sensorimotor behavior. We find that systematic adjustments of the motor behavior correlate with increased performance and a shift of the sensory attention of the animal. Analyzing the afferent electrosensory input shows that a significant gain in information results from these sensorimotor adjustments. Our results show that motor control can be an active component of sensory learning. Researching the sensory corollaries of motor control thus can be crucial to understand sensory sensation and perception under naturalistic conditions.

Cellular and Network Mechanisms May Generate Sparse Coding of Sequential Object Encounters in Hippocampal-Like Circuits

The localization of distinct landmarks plays a crucial role in encoding new spatial memories. In mammals, this function is performed by hippocampal neurons that sparsely encode an animal’s location relative to surrounding objects. Similarly, the dorsolateral pallium (DL) is essential for spatial learning in teleost fish. The DL of weakly electric gymnotiform fish receives both electrosensory and visual input from the preglomerular nucleus (PG), which has been hypothesized to encode the temporal sequence of electrosensory or visual landmark/food encounters. Here, we show that DL neurons in the Apteronotid fish and in the Carassius auratus (goldfish) have a hyperpolarized resting membrane potential (RMP) combined with a high and dynamic spike threshold that increases following each spike. Current-evoked spikes in DL cells are followed by a strong small-conductance calcium-activated potassium channel (SK)-mediated after-hyperpolarizing potential (AHP). Together, these properties prevent high frequency and continuous spiking. The resulting sparseness of discharge and dynamic threshold suggest that DL neurons meet theoretical requirements for generating spatial memory engrams by decoding the landmark/food encounter sequences encoded by PG neurons. Thus, DL neurons in teleost fish may provide a promising, simple system to study the core cell and network mechanisms underlying spatial memory.

Data-driven inference for stationary jump-diffusion processes with application to membrane voltage fluctuations in pyramidal neurons

The emergent activity of biological systems can often be represented as low-dimensional, Langevin-type stochastic differential equations. In certain systems, however, large and abrupt events occur and violate the assumptions of this approach. We address this situation here by providing a novel method that reconstructs a jump-diffusion stochastic process based solely on the statistics of the original data. Our method assumes that these data are stationary, that diffusive noise is additive, and that jumps are Poisson. We use threshold-crossing of the increments to detect jumps in the time series. This is followed by an iterative scheme that compensates for the presence of diffusive fluctuations that are falsely detected as jumps. Our approach is based on probabilistic calculations associated with these fluctuations and on the use of the Fokker-Planck and the differential Chapman-Kolmogorov equations. After some validation cases, we apply this method to recordings of membrane noise in pyramidal neurons of the electrosensory lateral line lobe of weakly electric fish. These recordings display large, jump-like depolarization events that occur at random times, the biophysics of which is unknown. We find that some pyramidal cells increase their jump rate and noise intensity as the membrane potential approaches spike threshold, while their drift function and jump amplitude distribution remain unchanged. As our method is fully data-driven, it provides a valuable means to further investigate the functional role of these jump-like events without relying on unconstrained biophysical models.

Sensory Cues Modulate Smooth Pursuit and Active Sensing Movements

Animals routinely use autogenous movement to regulate the information encoded by their sensory systems. Weakly electric fish use fore-aft movements to regulate visual and electrosensory feedback as they maintain position within a moving refuge. During refuge tracking, fish produce two categories of movements: smooth pursuit that is approximately linear in its relation to the movement of the refuge and ancillary active sensing movements that are nonlinear. We identified four categories of nonlinear movements which we termed scanning, wiggle, drift, and reset. To examine the relations between sensory cues and production of both linear smooth pursuit and nonlinear active sensing movements, we altered visual and electrosensory cues for refuge tracking and measured the fore-aft movements of the fish. Specifically, we altered the length and structure of the refuge and performed experiments with light and in complete darkness. Linear measures of tracking performance were better for shorter refuges (less than a body length) than longer ones (>1.5 body lengths). The magnitude of nonlinear active sensing movements was strongly modulated by light cues but also increased as a function of both longer refuge length and decreased features. Specifically, fish shifted swimming movements from smooth pursuit to scanning when tracking in dark conditions. Finally, fish appear to use nonlinear movements as an alternate tracking strategy in longer refuges: the fish may use more drifts and resets to avoid exiting the ends of the refuge.

Neural activity in a hippocampus-like region of the teleost pallium is associated with active sensing and navigation

Most vertebrates use active sensing strategies for perception, cognition and control of motor activity. These strategies include directed body/sensor movements or increases in discrete sensory sampling events. The weakly electric fish, Gymnotus sp., uses its active electric sense during navigation in the dark. Electric organ discharge rate undergoes transient increases during navigation to increase electrosensory sampling. Gymnotus also use stereotyped backward swimming as an important form of active sensing that brings objects toward the electroreceptor dense fovea-like head region. We wirelessly recorded neural activity from the pallium of freely swimming Gymnotus. Spiking activity was sparse and occurred only during swimming. Notably, most units tended to fire during backward swims and their activity was on average coupled to increases in sensory sampling. Our results provide the first characterization of neural activity in a hippocampal (CA3)-like region of a teleost fish brain and connects it to active sensing of spatial environmental features.

Closed-Loop Control of Active Sensing Movements Regulates Sensory Slip

Active sensing involves the production of motor signals for the purpose of acquiring sensory information [1-3]. The most common form of active sensing, found across animal taxa and behaviors, involves the generation of movements-e.g., whisking [4-6], touching [7, 8], sniffing [9, 10], and eye movements [11]. Active sensing movements profoundly affect the information carried by sensory feedback pathways [12-15] and are modulated by both top-down goals (e.g., measuring weight versus texture [1, 16]) and bottom-up stimuli (e.g., lights on or off [12]), but it remains unclear whether and how these movements are controlled in relation to the ongoing feedback they generate. To investigate the control of movements for active sensing, we created an experimental apparatus for freely swimming weakly electric fish, Eigenmannia virescens, that modulates the gain of reafferent feedback by adjusting the position of a refuge based on real-time videographic measurements of fish position. We discovered that fish robustly regulate sensory slip via closed-loop control of active sensing movements. Specifically, as fish performed the task of maintaining position inside the refuge [17-22], they dramatically up- or downregulated fore-aft active sensing movements in relation to a 4-fold change of experimentally modulated reafferent gain. These changes in swimming movements served to maintain a constant magnitude of sensory slip. The magnitude of sensory slip depended on the presence or absence of visual cues. These results indicate that fish use two controllers: one that controls the acquisition of information by regulating feedback from active sensing movements and another that maintains position in the refuge, a control structure that may be ubiquitous in animals [23, 24].

A time-stamp mechanism may provide temporal information necessary for egocentric to allocentric spatial transformations

Learning the spatial organization of the environment is essential for most animals’ survival. This requires the animal to derive allocentric spatial information from egocentric sensory and motor experience. The neural mechanisms underlying this transformation are mostly unknown. We addressed this problem in electric fish, which can precisely navigate in complete darkness and whose brain circuitry is relatively simple. We conducted the first neural recordings in the preglomerular complex, the thalamic region exclusively connecting the optic tectum with the spatial learning circuits in the dorsolateral pallium. While tectal topographic information was mostly eliminated in preglomerular neurons, the time-intervals between object encounters were precisely encoded. We show that this reliable temporal information, combined with a speed signal, can permit accurate estimation of the distance between encounters, a necessary component of path-integration that enables computing allocentric spatial relations. Our results suggest that similar mechanisms are involved in sequential spatial learning in all vertebrates.

Finding their way around is an essential part of survival for many animals and helps them to locate food, mates and shelter. Animals have evolved the ability to form a 'map' or representation of their surroundings. For example, the electric fish Apteronotus leptorhynchus, is able to precisely learn the location of food and navigate there. It can do this in complete darkness by generating a weak electric field. As it swims, every object it encounters generates an ‘electric image’ that is detected on the skin and processed in the brain.

However, all the cues the fish comes across are from its own point of view – the information about its environment is processed with respect to its location. And yet, the map that it generates needs to be independent of the fish’s position – it has to work regardless of where the animal is. The way animals translate ‘self-centered’ experiences to form a general representation of their surroundings is not yet fully understood.

Now, Wallach et al. studied how internal brain maps are generated in A. leptorhynchus. Information about the fish's environment passes through a structure in the brain called the preglomerular complex. Measuring the activity of this region revealed that the preglomerular complex does not process much self-centered information. Instead, whenever the fish passed any object – regardless of where it was in relation to the fish – the event triggered a brief burst of preglomerular activity. The intensity of the activity depended on how recently the fish had encountered another object. This information, combined with the dynamics of the fish's movement, could be what allows the fish to convert a sequence of encounters into a general spatial map.

These findings could help to inform research on learning and navigation. Further research could also reveal whether other species, including humans, generate their mental maps in a similar way. This may be relevant for people suffering from diseases such as Alzheimer’s, in which a sense of orientation has become impaired.

Sensory Flow as a Basis for a Novel Distance Cue in Freely Behaving Electric Fish

The sensory input that an animal receives is directly linked to its motor activity. Behavior thus enables animals to influence their sensory input, a concept referred to as active sensing. How such behavior can serve as a scaffold for generating sensory information is of general scientific interest. In this article, we investigate how behavior can shape sensory information by using some unique features of the sensorimotor system of the weakly electric fish. Based on quantitative behavioral characterizations and computational reconstruction of sensory input, we show how electrosensory flow is actively created during highly patterned, spontaneous behavior in Gnathonemus petersii. The spatiotemporal structure of the sensory input provides information for the computation of a novel distance cue, which allows for a continuous estimation of distance. This has significant advantages over previously known nondynamic distance estimators as determined from electric image blur. Our investigation of the sensorimotor interactions in pulsatile electrolocation shows, for the first time, that the electrosensory flow contains behaviorally relevant information accessible only through active behavior. As patterned sensory behaviors are a shared feature of (active) sensory systems, our results have general implications for the understanding of (active) sensing, with the proposed sensory flow-based measure being potentially pertinent to a broad range of sensory modalities.

SIGNIFICANCE STATEMENT

Acquisition of sensory information depends on motion, as either an animal or its sensors move. Behavior can thus actively influence the sensory flow; and in this way, behavior can be seen as a manifestation of the brain's integrative functions. The properties of the active pulsatile electrolocation system in Gnathonemus petersii allow for the sensory input to be computationally reconstructed, enabling us to link the informational content of spatiotemporal sensory dynamics to behavior. Our study reveals a novel sensory cue for estimating depth that is actively generated by the fishes' behavior. The physical and behavioral similarities between electrolocation and other active sensory systems suggest that this may be a mechanism shared by (active) sensory systems.

Weakly electric fish learn both visual and electrosensory cues in a multisensory object discrimination task

Weakly electric fish use electrosensory, visual, olfactory and lateral line information to guide foraging and navigation behaviors. In many cases they preferentially rely on electrosensory cues. Do fish also memorize non-electrosensory cues? Here, we trained individuals of gymnotiform weakly electric fish Apteronotus albifrons in an object discrimination task. Objects were combinations of differently conductive materials covered with differently colored cotton hoods. By setting visual and electrosensory cues in conflict we analyzed the sensory hierarchy among the electrosensory and the visual sense in object discrimination. Our experiments show that: (i) black ghost knifefish can be trained to solve discrimination tasks similarly to the mormyrid fish; (ii) fish preferentially rely on electrosensory cues for object discrimination; (iii) despite the dominance of the electrosense they still learn the visual cue and use it when electrosensory information is not available; (iv) fish prefer the trained combination of rewarded cues over combinations that match only in a single feature and also memorize the non-rewarded combination.

Hippocampal-like circuitry in the pallium of an electric fish: Possible substrates for recursive pattern separation and completion

Teleost fish are capable of complex behaviors, including social and spatial learning; lesion studies show that these abilities require dorsal telencephalon (pallium). The teleost telencephalon has subpallial and pallial components. The subpallium is well described and highly conserved. In contrast, the teleost pallium is not well understood and its relation to that of other vertebrates remains controversial. Here we analyze the connectivity of the subdivisions of dorsal pallium (DD) of an electric gymnotiform fish, Apteronotus leptorhynchus: superficial (DDs), intermediate (DDi) and magnocellular (DDmg) components. The major pathways are recursive: the dorsolateral pallium (DL) projects strongly to DDi, with lesser inputs to DDs and DDmg. DDi in turn projects strongly to DDmg, which then feeds back diffusely to DL. Our quantitative analysis of DDi connectivity demonstrates that it is a global recurrent network. In addition, we show that the DD subnuclei have complex reciprocal connections with subpallial regions. Specifically, both DDi and DDmg are reciprocally connected to pallial interneurons within the misnamed rostral entopeduncular nucleus (Er). Based on DD connectivity, we illustrate the close similarity, and possible homology, between hippocampal and DD/DL circuitry. We hypothesize that DD/DL circuitry can implement the same pattern separation and completion computations ascribed to the hippocampal dentate gyrus and CA3 fields. We further contend that the DL to DDi to DDmg to DL feedback loop makes the pattern separation/completion operations recursive. We discuss our results with respect to recent studies on fear avoidance conditioning in zebrafish and attention and spatial learning in a pulse gymnotiform fish. J. Comp. Neurol. 525:8-46, 2017. © 2016 Wiley Periodicals, Inc.