Urban stressors: Interactive effects of noise, light regime and fluoxetine on zebrafish behavior

Chemical, noise and light pollution are pervasive anthropogenic stressors. These stressors have been investigated individually; however, to our knowledge no one has investigated interactions between the three or their impacts on fish. The current study investigated the effects of chronic exposure to a common environmental pollutant, fluoxetine (3 and 300 ng/L), light pollution (artificial light at night), and acute environmental noise (motorboat engine) on the behavioral responses of zebrafish (Danio rerio). The effects of these treatments on zebrafish boldness, anxiety, time to feed, habitat preference in the presence of a visual predation cue (bird), and shoaling behavior in the presence of a conspecific alarm chemical and a visual predation cue were measured. Fluoxetine alone decreased zebrafish boldness, although effects were dose-, sex-, and noise-order-dependent. Zebrafish exposed to artificial light at night showed higher activity levels and were bolder than fish that were raised in an environment with a normal 12 h light-12 h dark photoperiod. Noise exposure often resulted in increased activity. However, we also observed interactions between the three factors. In several experiments, fluoxetine suppressed the effects artificial light at night, suggesting an antagonistic interaction. Fluoxetine also reduced behavioral responses to sudden noise in several experiments. The visual predation cue caused significant reductions in activity, but all three factors affected responses to predation, leading to behaviors that may increase zebrafish vulnerability. The order in which fish were exposed to noise pollution was also important. Fish that were tested with noise first often reacted more strongly than those that were initially tested without noise, suggesting that noise increased the stress of adaption to a new environment. Environmental stressors often co-exist in the real world and the limited number of studies in this area underscores the need for more comprehensive research.

Soft Materials and Devices Enabling Sensorimotor Functions in Soft Robots

Sensorimotor functions, the seamless integration of sensing, decision-making, and actuation, are fundamental for robots to interact with their environments. Inspired by biological systems, the incorporation of soft materials and devices into robotics holds significant promise for enhancing these functions. However, current robotics systems often lack the autonomy and intelligence observed in nature due to limited sensorimotor integration, particularly in flexible sensing and actuation. As the field progresses toward soft, flexible, and stretchable materials, developing such materials and devices becomes increasingly critical for advanced robotics. Despite rapid advancements individually in soft materials and flexible devices, their combined applications to enable sensorimotor capabilities in robots are emerging. This review addresses this emerging field by providing a comprehensive overview of soft materials and devices that enable sensorimotor functions in robots. We delve into the latest development in soft sensing technologies, actuation mechanism, structural designs, and fabrication techniques. Additionally, we explore strategies for sensorimotor control, the integration of artificial intelligence (AI), and practical application across various domains such as healthcare, augmented and virtual reality, and exploration. By drawing parallels with biological systems, this review aims to guide future research and development in soft robots, ultimately enhancing the autonomy and adaptability of robots in unstructured environments.

Fixational eye movements and their associated evoked potentials during natural vision are altered in schizophrenia

Background

Visual exploration is abnormal in schizophrenia; however, few studies have investigated the physiological responses during selecting objectives in more ecological scenarios. This study aimed to demonstrate that people with schizophrenia have difficulties observing the prominent elements of an image due to a deficit mechanism of sensory modulation (active sensing) during natural vision.

Methods

An electroencephalogram recording with eye tracking data was collected on 18 healthy individuals and 18 people affected by schizophrenia while looking at natural images. These had a prominent color element and blinking produced by changes in image luminance.

Results

We found fewer fixations when all images were scanned, late focus on prominent image areas, decreased amplitude in the eye-fixation-related potential, and decreased intertrial coherence in the SCZ group.

Conclusions

The decrease in the visual attention response evoked by the prominence of visual stimuli in patients affected by schizophrenia is generated by a reduction in endogenous attention mechanisms to initiate and maintain visual exploration. Further work is required to explain the relationship of this decrease with clinical indicators.

Controlling the input: How one-year-old infants sustain visual attention

Traditionally, the exogenous control of gaze by external saliencies and the endogenous control of gaze by knowledge and context have been viewed as competing systems, with late infancy seen as a period of strengthening top-down control over the vagaries of the input. Here we found that one-year-old infants control sustained attention through head movements that increase the visibility of the attended object. Freely moving one-year-old infants (n = 45) wore head-mounted eye trackers and head motion sensors while exploring sets of toys of the same physical size. The visual size of the objects, a well-documented salience, varied naturally with the infant's moment-to-moment posture and head movements. Sustained attention to an object was characterized by the tight control of head movements that created and then stabilized a visual size advantage for the attended object for sustained attention. The findings show collaboration between exogenous and endogenous attentional systems and suggest new hypotheses about the development of sustained visual attention.

Active oscillations in microscale navigation

Living organisms routinely navigate their surroundings in search of better conditions, more food, or to avoid predators. Typically, animals do so by integrating sensory cues from the environment with their locomotor apparatuses. For single cells or small organisms that possess motility, fundamental physical constraints imposed by their small size have led to alternative navigation strategies that are specific to the microscopic world. Intriguingly, underlying these myriad exploratory behaviours or sensory functions is the onset of periodic activity at multiple scales, such as the undulations of cilia and flagella, the vibrations of hair cells, or the oscillatory shape modes of migrating neutrophils. Here, I explore oscillatory dynamics in basal microeukaryotes and hypothesize that these active oscillations play a critical role in enhancing the fidelity of adaptive sensorimotor integration.

Autogenous cerebral processes: an invitation to look at the brain from inside out

While external stimulation can reliably trigger neuronal activity, cerebral processes can operate independently from the environment. In this study, we conceptualize autogenous cerebral processes (ACPs) as intrinsic operations of the brain that exist on multiple scales and can influence or shape stimulus responses, behavior, homeostasis, and the physiological state of an organism. We further propose that the field should consider exploring to what extent perception, arousal, behavior, or movement, as well as other cognitive functions previously investigated mainly regarding their stimulus-response dynamics, are ACP-driven.

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.

Scene saliencies in egocentric vision and their creation by parents and infants

Across the lifespan, humans are biased to look first at what is easy to see, with a handful of well-documented visual saliences shaping our attention (e.g., Itti & Koch, 2001). These attentional biases may emerge from the contexts in which moment-tomoment attention occurs, where perceivers and their social partners actively shape bottom-up saliences, moving their bodies and objects to make targets of interest more salient. The goal of the present study was to determine the bottom-up saliences present in infant egocentric images and to provide evidence on the role that infants and their mature social partners play in highlighting targets of interest via these saliences. We examined 968 unique scenes in which an object had purposefully been placed in the infant's egocentric view, drawn from videos created by one-year-old infants wearing a head camera during toy-play with a parent. To understand which saliences mattered in these scenes, we conducted a visual search task, asking participants (n = 156) to find objects in the egocentric images. To connect this to the behaviors of perceivers, we then characterized the saliences of objects placed by infants or parents compared to objects that were otherwise present in the scenes. Our results show that body-centric properties, such as increases in the centering and visual size of the object, as well as decreases in the number of competing objects immediately surrounding it, both predicted faster search time and distinguished placed and unplaced objects. The present results suggest that the bottom-up saliences that can be readily controlled by perceivers and their social partners may most strongly impact our attention. This finding has implications for the functional role of saliences in human vision, their origin, the social structure of perceptual environments, and how the relation between bottom-up and top-down control of attention in these environments may support infant learning.

Latency shortening with enhanced sparseness and responsiveness in V1 during active visual sensing

In natural vision, neuronal responses to visual stimuli occur due to self-initiated eye movements. Here, we compare single-unit activity in the primary visual cortex (V1) of non-human primates to flashed natural scenes (passive vision condition) to when they freely explore the images by self-initiated eye movements (active vision condition). Active vision enhances the number of neurons responding, and the response latencies become shorter and less variable across neurons. The increased responsiveness and shortened latency during active vision were not explained by increased visual contrast. While the neuronal activities in all layers of V1 show enhanced responsiveness and shortened latency, a significant increase in lifetime sparseness during active vision is observed only in the supragranular layer. These findings demonstrate that the neuronal responses become more distinct in active vision than passive vision, interpreted as consequences of top-down predictive mechanisms.

Neuromorphic Engineering Needs Closed-Loop Benchmarks

Neuromorphic engineering aims to build (autonomous) systems by mimicking biological systems. It is motivated by the observation that biological organisms—from algae to primates—excel in sensing their environment, reacting promptly to their perils and opportunities. Furthermore, they do so more resiliently than our most advanced machines, at a fraction of the power consumption. It follows that the performance of neuromorphic systems should be evaluated in terms of real-time operation, power consumption, and resiliency to real-world perturbations and noise using task-relevant evaluation metrics. Yet, following in the footsteps of conventional machine learning, most neuromorphic benchmarks rely on recorded datasets that foster sensing accuracy as the primary measure for performance. Sensing accuracy is but an arbitrary proxy for the actual system's goal—taking a good decision in a timely manner. Moreover, static datasets hinder our ability to study and compare closed-loop sensing and control strategies that are central to survival for biological organisms. This article makes the case for a renewed focus on closed-loop benchmarks involving real-world tasks. Such benchmarks will be crucial in developing and progressing neuromorphic Intelligence. The shift towards dynamic real-world benchmarking tasks should usher in richer, more resilient, and robust artificially intelligent systems in the future.

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.

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

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

Hidden species diversity in Marcusenius moorii (Teleostei: Mormyridae) from the Congo Basin

New collections from the Yangambi Biosphere Reserve (YBR) and Okapi Wildlife Reserve (OWR) revealed the presence of two groups of specimens similar to, but different from Marcusenius moorii. To study both these groups, an integrated morphological and genetic (mtDNA, cytb) approach was used. This study revealed that one of the two groups is conspecific with Marcusenius lambouri, a junior synonym of M. moorii, which is herein revalidated, with M. moorii longulus as its junior synonym. Marcusenius lambouri differs from M. moorii by a higher number of lateral line scales (44-46 vs. 40-43), a shorter pectoral-fin length (14.6-19.9 vs. 20.3-25.2% standard length; L_S ) and a more elongated body due to a usually shallower middle body depth (19.8-26.5 vs. 26.3-35.9% L_S ). The other group revealed to be a new species for science, Marcusenius verheyenorum, which can be distinguished from its congeners with eight circumpeduncular scales by the following unique combination of characters: a rounded head with a terminal mouth; a short and deep caudal peduncle (middle caudal-peduncle depth, 44.9-54.6% caudal-peduncle length; L_CP ), a deep body (middle body depth, 27.7-34.2% L_S ), 38-43 scales on the lateral line, 40-41 vertebrae, 20-21 dorsal-fin rays and 26 anal-fin rays. Some specimens previously attributed to M. moorii were examined and reassigned to M. lambouri or M. verheyenorum. As a result, M. moorii and M. lambouri occur in sympatry in the middle Congo Basin, with the distribution area of M. moorii still further extending into the lower Congo Basin. Instead, the distribution of M. verheyenorum is limited to some right bank tributaries of the upstream part of the middle Congo Basin. Two museum records from the Lilanda River (YBR), collected in the 1950s and previously identified as M. moorii, were re-identified as belonging to the new species, M. verheyenorum. However, the species now seems locally extinct in that region, which reflects the significant anthropogenic effects even within this reserve.

Active Sensing: Constancy Requires Change

We constantly generate movements in order to enhance our ability to perceive the external environment. New research on electric fish has used augmented reality to demonstrate that animals dynamically regulate their movements to maintain variability in their sensory input.

Segregating signal from noise through movement in echolocating bats

Segregating signal from noise is one of the most fundamental problems shared by all biological and human-engineered sensory systems. In echolocating bats that search for small objects such as tiny insects in the presence of large obstacles (e.g., vegetation), this task can pose serious challenges as the echoes reflected from the background might be several times louder than the desired signal. Bats’ ability to adjust their sensing, specifically their echolocation signal and sequence design has been deeply studied. In this study, we show that in addition to adjusting their sensing, bats also use movement in order to segregate desired echoes from background noise. Bats responded to an acoustically echoic background by adjusting their angle of attack. Specifically, the bats in our experiment used movement and not adaptation of sensory acquisition in order to overcome a sensory challenge. They approached the target at a smaller angle of attack, which results in weaker echoes from the background as was also confirmed by measuring the echoes of the setup from the bat’s point of view. Our study demonstrates the importance of movement in active sensing.

Strategies of locomotion composition

This review aims to highlight the importance of saccades during locomotion as a strategy to reduce sensory information loss while the subject is moving. Acquiring sensory data from the environment during movement results in a temporal flow of information, as the sensory precept changes with the position of the observer. Accordingly, the movement pattern shapes the sensory flow. Therefore, the requirements of locomotion and sensation have to be balanced in the behaviour of the organism. Insect vision provides deep insight into the interplay between action and perception. Insects can shape their optic flow by reducing their rotational movements to fast and short saccades. This generates prolonged phases of translations which provide depth information. Extensive behavioural and physiological studies on insects show how shaping the optic flow facilitates the coding of motion vision. Indeed the saccadic strategy provides an elegant solution to optimise sensory flow. Complementary studies in other taxa reported similar locomotion strategies emphasising the crucial influence of sensory flow on locomotion.

Novel Functions of Feedback in Electrosensory Processing

Environmental signals act as input and are processed across successive stages in the brain to generate a meaningful behavioral output. However, a ubiquitous observation is that descending feedback projections from more central to more peripheral brain areas vastly outnumber ascending feedforward projections. Such projections generally act to modify how sensory neurons respond to afferent signals. Recent studies in the electrosensory system of weakly electric fish have revealed novel functions for feedback pathways in that their transformation of the afferent input generates neural firing rate responses to sensory signals mediating perception and behavior. In this review, we focus on summarizing these novel and recently uncovered functions and put them into context by describing the more "classical" functions of feedback in the electrosensory system. We further highlight the parallels between the electrosensory system and other systems as well as outline interesting future directions.

Learning active sensing strategies using a sensory brain-machine interface

Diverse organisms, from insects to humans, actively seek out sensory information that best informs goal-directed actions. Efficient active sensing requires congruity between sensor properties and motor strategies, as typically honed through evolution. However, it has been difficult to study whether active sensing strategies are also modified with experience. Here, we used a sensory brain-machine interface paradigm, permitting both free behavior and experimental manipulation of sensory feedback, to study learning of active sensing strategies. Rats performed a searching task in a water maze in which the only task-relevant sensory feedback was provided by intracortical microstimulation (ICMS) encoding egocentric bearing to the hidden goal location. The rats learned to use the artificial goal direction sense to find the platform with the same proficiency as natural vision. Manipulation of the acuity of the ICMS feedback revealed distinct search strategy adaptations. Using an optimization model, the different strategies were found to minimize the effort required to extract the most salient task-relevant information. The results demonstrate that animals can adjust motor strategies to match novel sensor properties for efficient goal-directed behavior.

The Cognitive Ecology of Stimulus Ambiguity: A Predator-Prey Perspective

Organisms face the cognitive challenge of making decisions based on imperfect information. Predators and prey, in particular, are confronted with ambiguous stimuli when foraging and avoiding attacks. These challenges are accentuated by variation imposed by environmental, physiological, and cognitive factors. While the cognitive factors influencing perceived ambiguity are often assumed to be fixed, contemporary findings reveal that perceived ambiguity is instead the dynamic outcome of interactive cognitive processes. Here, we present a framework that integrates recent advances in neurophysiology and sensory ecology with a classic decision-making model, signal detection theory (SDT), to understand the cognitive mechanisms that shape perceived stimulus ambiguity in predators and prey. Since stimulus ambiguity is pervasive, the framework discussed here provides insights that extend into nonforaging contexts.

Representation of object's shape by multiple electric images in electrolocation

Weakly electric fish generate an electric field by discharging an electric organ located on the tail region. An object near the fish modulates the self-generated electric field. The modulated field enables the fish to perceive objects even in complete darkness. The ability to perceive objects is provided by the electrosensory system of the fish. Electroreceptors distributed on the fish's skin surface can sense the modulated field, on the basis of transdermal voltage across the skin surface, called electric images. The fish can extract object's features such as lateral distance, size, shape, and electric property from an electric image. Although previous studies have demonstrated the relationship between electric-image features and object's distance and size, it remains unclear what features of an electric image represent the object's shape. We make here a hypothesis that shape information is not represented by a single image but by multiple images caused by the object's rotation or fish movement around the object. To test the hypothesis, we develop a computational model that can predict electric images produced by the rotation of differently shaped objects. We used five different shapes of resistive objects: a circle, a square, an equilateral triangle, a rectangle, and an ellipsoid. We show that differently shaped objects of a fixed arrangement generate similar Gaussian electric images, irrespective of their shapes. We also show that the features of an electric image such as the peak amplitude, half-maximum width, and peak position exhibit the angle-dependent variations characteristic to object rotation, depending on object shapes and lateral distances. Furthermore, we demonstrate that an integration effect of the peak amplitude and half-maximum width could be an invariant measure of object shape. These results suggest that the fish could perceive an object shape by combining those image features produced during exploratory behaviors around the object.

Timing Is of the Essence: Improvement in Perception During Active Sensing

Active sensing refers to the concept of animals perceiving their environment while involving self-initiated motor acts. As a consequence of these motor acts, this activity produces direct and timely changes in the sensory surface. Is the brain able to take advantage of the precise time-locking that occurs during active sensing? Is the intrinsic predictability present during active sensing, impacting the sensory processes? We conjecture that if stimuli presentation is evoked by a self-initiated motor act, sensory discrimination and timing accuracy would improve. We studied this phenomenon when rats had to locate the position of a brief light stimulus, either when it was elicited by a warning light [passive condition (PC)] or when it was generated by a lever press [active condition (AC)]. We found that during the PC, rats had 66% of correct responses, vs. a significantly higher 77% of correct responses in AC. Furthermore, reaction times reduced from 1,181 ms during AC to 816 ms during PC For the latter condition, the probability of detecting the side of the light stimulus was negatively correlated with the time lag between the motor act and the evoked light and with a 38% reduction on performance per second of delay. These experiment shows that the mechanism that underlies sensory improvement during active behaviors have a constrained time dynamic, where the peak performances occur during the motor act, decreasing proportionally to the lag between the motor act and the stimulus presentation. This result is consistent with the evidence already found in humans, of a precise time dynamic of the improvement of sensory acuity after a motor act and reveals an equivalent process in rodents. Our results support the idea that perception and action are precisely coordinated in the brain.

Adaptations in the call emission pattern of frugivorous bats when orienting under challenging conditions

Echolocating bats emit biosonar calls and use echoes arising from call reflections, for orientation. They often pattern their calls into groups which increases the rate of sensory feedback. Insectivorous bats emit call groups at a higher rate when orienting in cluttered compared to uncluttered environments. Frugivorous bats increase the rate of call group emission when they echolocate in noisy environments. In frugivorous bats, it remains unclear if call group emission represents an exclusive adaptation to avoid acoustic interference by signals of conspecifics or if it represents an adaptation that allows to orient under demanding environmental conditions. Here, we compared the emission pattern of the frugivorous bat Carolliaperspicillata when the bats were flying in narrow versus wide or cluttered versus non-cluttered corridors. The bats emitted larger call groups and they increased the call rate within call groups when navigating in narrow or cluttered environments. These adaptations resemble the ones shown when the bats navigate in noisy environments. Thus, call group emission represents an adaptive behavior when the bats orient in complex environments.

Population Coding and Correlated Variability in Electrosensory Pathways

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

Serotonin Selectively Increases Detectability of Motion Stimuli in the Electrosensory System

Serotonergic innervation of sensory areas is found ubiquitously across the central nervous system of vertebrates. Here, we used a system's level approach to investigate the role of serotonin on processing motion stimuli in the electrosensory system of the weakly electric fish Apteronotus albifrons. We found that exogenous serotonin application increased the firing activity of pyramidal neural responses to both looming and receding motion. Separating spikes belonging to bursts from those that were isolated revealed that this effect was primarily due to increased burst firing. Moreover, when investigating whether firing activity during stimulation could be discriminated from baseline (i.e., in the absence of stimulation), we found that serotonin increased stimulus discriminability only for some stimuli. This is because increased burst firing was most prominent for these. Further, the effects of serotonin were highly heterogeneous, with some neurons displaying large while others instead displaying minimal changes in responsiveness following serotonin application. Further analysis revealed that serotonin application had the greatest effect on neurons with low baseline firing rates and little to no effect on neurons with high baseline firing rates. Finally, the effects of serotonin on sensory neuron responses were largely independent of object velocity. Our results therefore reveal a novel function for the serotonergic system in selectively enhancing discriminability for motion stimuli.

Local cortical activity of distant brain areas can phase-lock to the olfactory bulb's respiratory rhythm in the freely behaving rat

An important unresolved question about neural processing is the mechanism by which distant brain areas coordinate their activities and relate their local processing to global neural events. A potential candidate for the local-global integration are slow rhythms such as respiration. In this study, we asked if there are modulations of local cortical processing that are phase-locked to (peripheral) sensory-motor exploratory rhythms. We studied rats on an elevated platform where they would spontaneously display exploratory and rest behaviors. Concurrent with behavior, we monitored whisking through electromyography and the respiratory rhythm from the olfactory bulb (OB) local field potential (LFP). We also recorded LFPs from dorsal hippocampus, primary motor cortex, primary somatosensory cortex, and primary visual cortex. We defined exploration as simultaneous whisking and sniffing above 5 Hz and found that this activity peaked at ~8 Hz. We considered rest as the absence of whisking and sniffing, and in this case, respiration occurred at ~3 Hz. We found a consistent shift across all areas toward these rhythm peaks accompanying behavioral changes. We also found, across areas, that LFP gamma (70-100 Hz) amplitude could phase-lock to the animal's OB respiratory rhythm, a finding indicative of respiration-locked changes in local processing. In a subset of animals, we also recorded the hippocampal theta activity and found that occurred at frequencies overlapped with respiration but was not spectrally coherent with it, suggesting a different oscillator. Our results are consistent with the notion of respiration as a binder or integrator of activity between brain regions.

Vibration-guided mate searching in treehoppers: directional accuracy and sampling strategies in a complex sensory environment

Animal movement decisions involve an action-perception cycle in which sensory flow influences motor output. Key aspects of the action-perception cycle involved in movement decisions can be identified by integrating path information with measurement of environmental cues. We studied mate searching in insects for which the primary sensory cues are mechanical vibrations traveling through the tissues of living plants. We mapped search paths of male thornbug treehoppers locating stationary females through an exchange of vibrational signals. At each of the males' sampling locations, we used two-dimensional laser vibrometry to measure stem motion produced by female vibrational signals. We related properties of the vibrational signals to the males' movement direction, inter-sample distance and accuracy. Males experienced gradients in signal amplitude and in the whirling motion of the plant stem, and these gradients were influenced to varying degrees by source distance and local stem properties. Males changed their sampling behavior during the search, making longer inter-sample movements farther from the source, where uncertainty is higher. The primary directional cue used by searching males was the direction of wave propagation, and males made more accurate decisions when signal amplitude was higher, when time delays were longer between the front and back legs, and when female responses were short in duration. The whirling motion of plant stems, including both the eccentricity and the major axes of motion, is a fundamental feature of vibrational environments on living plants, and we show for the first time that it has important influences on the decisions of vibrationally homing insects.

Motion parallax in electric sensing

A crucial step in forming spatial representations of the environment involves the estimation of relative distance. Active sampling through specific movements is considered essential for optimizing the sensory flow that enables the extraction of distance cues. However, in electric sensing, direct evidence for the generation and exploitation of sensory flow is lacking. Weakly electric fish rely on a self-generated electric field to navigate and capture prey in the dark. This electric sense provides a blurred representation of the environment, making the exquisite sensory abilities of electric fish enigmatic. Stereotyped back-and-forth swimming patterns reminiscent of visual peering movements are suggestive of the active generation of sensory flow, but how motion contributes to the disambiguation of the electrosensory world remains unclear. Here, we show that a dipole-like electric field geometry coupled to motion provides the physical basis for a nonvisual parallax. We then show in a behavioral assay that this cue is used for electrosensory distance perception across phylogenetically distant taxa of weakly electric fish. Notably, these species electrically sample the environment in temporally distinct ways (using discrete pulses or quasisinusoidal waves), suggesting a ubiquitous role for parallax in electric sensing. Our results demonstrate that electrosensory information is extracted from sensory flow and used in a behaviorally relevant context. A better understanding of motion-based electric sensing will provide insight into the sensorimotor coordination required for active sensing in general and may lead to improved electric field-based imaging applications in a variety of contexts.

Social interactions between live and artificial weakly electric fish: Electrocommunication and locomotor behavior of Mormyrus rume proboscirostris towards a mobile dummy fish

Mormyrid weakly electric fish produce short, pulse-type electric organ discharges for actively probing their environment and to communicate with conspecifics. Animals emit sequences of pulse-trains that vary in overall frequency and temporal patterning and can lead to time-locked interactions with the discharge activity of other individuals. Both active electrolocation and electrocommunication are additionally accompanied by stereotypical locomotor patterns. However, the concrete roles of electrical and locomotor patterns during social interactions in mormyrids are not well understood. Here we used a mobile fish dummy that was emitting different types of electrical playback sequences to study following behavior and interaction patterns (electrical and locomotor) between individuals of weakly electric fish. We confronted single individuals of Mormyrus rume proboscirostris with a mobile dummy fish designed to attract fish from a shelter and recruit them into an open area by emitting electrical playbacks of natural discharge sequences. We found that fish were reliably recruited by the mobile dummy if it emitted electrical signals and followed it largely independently of the presented playback patterns. While following the dummy, fish interacted with it spatially by displaying stereotypical motor patterns, as well as electrically, e.g. through discharge regularizations and by synchronizing their own discharge activity to the playback. However, the overall emission frequencies of the dummy were not adopted by the following fish. Instead, social signals based on different temporal patterns were emitted depending on the type of playback. In particular, double pulses were displayed in response to electrical signaling of the dummy and their expression was positively correlated with an animals' rank in the dominance hierarchy. Based on additional analysis of swimming trajectories and stereotypical locomotor behavior patterns, we conclude that the reception and emission of electrical communication signals play a crucial role in mediating social interactions in mormyrid weakly electric fish.

Optic flow-based collision-free strategies: From insects to robots

Flying insects are able to fly smartly in an unpredictable environment. It has been found that flying insects have smart neurons inside their tiny brains that are sensitive to visual motion also called optic flow. Consequently, flying insects rely mainly on visual motion during their flight maneuvers such as: takeoff or landing, terrain following, tunnel crossing, lateral and frontal obstacle avoidance, and adjusting flight speed in a cluttered environment. Optic flow can be defined as the vector field of the apparent motion of objects, surfaces, and edges in a visual scene generated by the relative motion between an observer (an eye or a camera) and the scene. Translational optic flow is particularly interesting for short-range navigation because it depends on the ratio between (i) the relative linear speed of the visual scene with respect to the observer and (ii) the distance of the observer from obstacles in the surrounding environment without any direct measurement of either speed or distance. In flying insects, roll stabilization reflex and yaw saccades attenuate any rotation at the eye level in roll and yaw respectively (i.e. to cancel any rotational optic flow) in order to ensure pure translational optic flow between two successive saccades. Our survey focuses on feedback-loops which use the translational optic flow that insects employ for collision-free navigation. Optic flow is likely, over the next decade to be one of the most important visual cues that can explain flying insects' behaviors for short-range navigation maneuvers in complex tunnels. Conversely, the biorobotic approach can therefore help to develop innovative flight control systems for flying robots with the aim of mimicking flying insects' abilities and better understanding their flight.

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.

Object discrimination through active electrolocation: Shape recognition and the influence of electrical noise

The weakly electric fish Gnathonemus petersii can recognise objects using active electrolocation. Here, we tested two aspects of object recognition; first whether shape recognition might be influenced by movement of the fish, and second whether object discrimination is affected by the presence of electrical noise from conspecifics. (i) Unlike other object features, such as size or volume, no parameter within a single electrical image has been found that encodes object shape. We investigated whether shape recognition might be facilitated by movement-induced modulations (MIM) of the set of electrical images that are created as a fish swims past an object. Fish were trained to discriminate between pairs of objects that either created similar or dissimilar levels of MIM of the electrical images. As predicted, the fish were able to discriminate between objects up to a longer distance if there was a large difference in MIM between the objects than if there was a small difference. This supports an involvement of MIMs in shape recognition but the use of other cues cannot be excluded. (ii) Electrical noise might impair object recognition if the noise signals overlap with the EODs of an electrolocating fish. To avoid jamming, we predicted that fish might employ pulsing strategies to prevent overlaps. To investigate the influence of electrical noise on discrimination performance, two fish were tested either in the presence of a conspecific or of playback signals and the electric signals were recorded during the experiments. The fish were surprisingly immune to jamming by conspecifics: While the discrimination performance of one fish dropped to chance level when more than 22% of its EODs overlapped with the noise signals, the performance of the other fish was not impaired even when all its EODs overlapped. Neither of the fish changed their pulsing behaviour, suggesting that they did not use any kind of jamming avoidance strategy.

Passive and active electroreception during agonistic encounters in the weakly electric fish Gymnotus omarorum

Agonistic behaviour related to territorial defence is likely to be costly in terms of energy loss and risk of injury. Hence information about the fighting ability of a potential opponent could influence the outcome of the contest. We here study electric images of the territorial and aggressive weakly electric fish Gymnotus omarorum in the context of agonistic behaviour. We show that passive and active electric images may drive the approach towards an opponent. The likelihood of first attacks can be predicted in these fish based on electric image information, suggesting that aggressive interactions may in fact be triggered through the passive electrosensory information.

Modeling latency code processing in the electric sense: from the biological template to its VLSI implementation

Understanding the coding of sensory information under the temporal constraints of natural behavior is not yet well resolved. There is a growing consensus that spike timing or latency coding can maximally exploit the timing of neural events to make fast computing elements and that such mechanisms are essential to information processing functions in the brain. The electric sense of mormyrid fish provides a convenient biological model where this coding scheme can be studied. The sensory input is a physically ordered spatial pattern of current densities, which is coded in the precise timing of primary afferent spikes. The neural circuits of the processing pathway are well known and the system exhibits the best known illustration of corollary discharge, which provides the reference to decoding the sensory afferent latency pattern. A theoretical model has been constructed from available electrophysiological and neuroanatomical data to integrate the principal traits of the neural processing structure and to study sensory interaction with motor-command-driven corollary discharge signals. This has been used to explore neural coding strategies at successive stages in the network and to examine the simulated network capacity to reproduce output neuron responses. The model shows that the network has the ability to resolve primary afferent spike timing differences in the sub-millisecond range, and that this depends on the coincidence of sensory and corollary discharge-driven gating signals. In the integrative and output stages of the network, corollary discharge sets up a proactive background filter, providing temporally structured excitation and inhibition within the network whose balance is then modulated locally by sensory input. This complements the initial gating mechanism and contributes to amplification of the input pattern of latencies, conferring network hyperacuity. These mechanisms give the system a robust capacity to extract behaviorally meaningful features of the electric image with high sensitivity over a broad working range. Since the network largely depends on spike timing, we finally discuss its suitability for implementation in robotic applications based on neuromorphic hardware.

Finding and identifying simple objects underwater with active electrosense

Active electrosense is used by some fish for the sensing of nearby objects by means of the perturbations the objects induce in a self-generated electric field. As with echolocation (sensing via perturbations of an emitted acoustic field) active electrosense is particularly useful in environments where darkness, clutter or turbidity makes vision ineffective. Work on engineered variants of active electrosense is motivated by the need for sensors in underwater systems that function well at short range and where vision-based approaches can be problematic, as well as to aid in understanding the computational principles of biological active electrosense. Prior work in robotic active electrosense has focused on tracking and localization of spherical objects. In this study, we present an algorithm for estimating the size, shape, orientation, and location of ellipsoidal objects, along with experimental results. The algorithm is implemented in a robotic active electrosense system whose basic approach is similar to biological active electrosense systems, including the use of movement as part of sensing. At a range up to ≈20 cm, or about half the length of the robot, the algorithm localizes spheroids that are one-tenth the length of the robot with accuracy of better than 1 cm for position and 5° in orientation. The algorithm estimates object size and length-to-width ratio with an accuracy of around 10%.

Computational modeling of electric imaging in weakly electric fish: insights for physiology, behavior and evolution

Weakly electric fish can sense electric signals produced by other animals whether they are conspecifics, preys or predators. These signals, sensed by passive electroreception, sustain electrocommunication, mating and agonistic behavior. Weakly electric fish can also generate a weak electrical discharge with which they can actively sense the animate and inanimate objects in their surroundings. Understanding both sensory modalities depends on our knowledge of how pre-receptorial electric images are formed and how movements modify them during behavior. The inability of effectively measuring pre-receptorial fields at the level of the skin contrasts with the amount of knowledge on electric fields and the availability of computational methods for estimating them. In this work we review past work on modeling of electric organ discharge and electric images, showing the usefulness of these methods to calculate the field and providing a brief explanation of their principles. In addition, we focus on recent work demonstrating the potential of electric image modeling and what the method has to offer for experimentalists studying sensory physiology, behavior and evolution.

Motor patterns during active electrosensory acquisition

Motor patterns displayed during active electrosensory acquisition of information seem to be an essential part of a sensory strategy by which weakly electric fish actively generate and shape sensory flow. These active sensing strategies are expected to adaptively optimize ongoing behavior with respect to either motor efficiency or sensory information gained. The tight link between the motor domain and sensory perception in active electrolocation make weakly electric fish like Gnathonemus petersii an ideal system for studying sensory-motor interactions in the form of active sensing strategies. Analyzing the movements and electric signals of solitary fish during unrestrained exploration of objects in the dark, we here present the first formal quantification of motor patterns used by fish during electrolocation. Based on a cluster analysis of the kinematic values we categorized the basic units of motion. These were then analyzed for their associative grouping to identify and extract short coherent chains of behavior. This enabled the description of sensory behavior on different levels of complexity: from single movements, over short behaviors to more complex behavioral sequences during which the kinematics alter between different behaviors. We present detailed data for three classified patterns and provide evidence that these can be considered as motor components of active sensing strategies. In accordance with the idea of active sensing strategies, we found categorical motor patterns to be modified by the sensory context. In addition these motor patterns were linked with changes in the temporal sampling in form of differing electric organ discharge frequencies and differing spatial distributions. The ability to detect such strategies quantitatively will allow future research to investigate the impact of such behaviors on sensing.

Using a classic paper by Bell as a platform for discussing the role of corollary discharge-like signals in sensory perception and movement control

Decades of behavioral observations have shown that invertebrate and vertebrate species have the ability to distinguish between self-generated afferent inputs versus those that are generated externally. In the present article, I describe activities focused around the discussion of a classic American Physiological Society paper by Curtis C. Bell that lays the foundation for students to investigate the neural substrate underlying this ability. Students will leave this activity being able to 1) describe the technical aspects and limitations of an electric fish preparation commonly used to acquire single unit (extracellular) neurophysiological data, 2) provide physiological evidence showing that the activity of principal cells in the posterior lateral line lobe of the electric fish brain reflects that of a reafference comparator that could be used in dissociating self-generated versus externally generated sensory signals, and 3) knowledgeably discuss hypotheses concerning the role of corollary discharge and cerebellar-like structures in vertebrate and invertebrate species. The skills and background knowledge gained in this activity lay the platform for advanced study of scientific investigations into sensory, motor, and cognitive processes in undergraduate, graduate, or medical school curricula.

Statistics of the electrosensory input in the freely swimming weakly electric fish Apteronotus leptorhynchus

The neural computations underlying sensory-guided behaviors can best be understood in view of the sensory stimuli to be processed under natural conditions. This input is often actively shaped by the movements of the animal and its sensory receptors. Little is known about natural sensory scene statistics taking into account the concomitant movement of sensory receptors in freely moving animals. South American weakly electric fish use a self-generated quasi-sinusoidal electric field for electrolocation and electrocommunication. Thousands of cutaneous electroreceptors detect changes in the transdermal potential (TDP) as the fish interact with conspecifics and the environment. Despite substantial knowledge about the circuitry and physiology of the electrosensory system, the statistical properties of the electrosensory input evoked by natural swimming movements have never been measured directly. Using underwater wireless telemetry, we recorded the TDP of Apteronotus leptorhynchus as they swam freely by themselves and during interaction with a conspecific. Swimming movements caused low-frequency TDP amplitude modulations (AMs). Interacting with a conspecific caused additional AMs around the difference frequency of their electric fields, with the amplitude of the AMs (envelope) varying at low frequencies due to mutual movements. Both AMs and envelopes showed a power-law relationship with frequency, indicating spectral scale invariance. Combining a computational model of the electric field with video tracking of movements, we show that specific swimming patterns cause characteristic spatiotemporal sensory input correlations that contain information that may be used by the brain to guide behavior.