Differences in Sodium Channel Densities in the Apical Dendrites of Pyramidal Cells of the Electrosensory Lateral Line Lobe.

Heterogeneity of neural properties within a given neural class is ubiquitous in the nervous system and permits different sub-classes of neurons to specialize for specific purposes. This principle has been thoroughly investigated in the hindbrain of the weakly electric fish A. leptorhynchus in the primary electrosensory area, the Electrosensory Lateral Line lobe (ELL). The pyramidal cells (PCs) that receive inputs from tuberous electroreceptors are organized in three maps in distinct segments of the ELL. The properties of these cells vary greatly across maps due to differences in connectivity, receptor expression, and ion channel composition. These cells are a seminal example of bursting neurons and their bursting dynamic relies on the presence of voltage-gated Na+ channels in the extensive apical dendrites of the superficial PCs. Other ion channels can affect burst generation and their expression varies across ELL neurons and segments. For example, SK channels cause hyperpolarizing after-potentials decreasing the likelihood of bursting, yet bursting propensity is similar across segments. We question whether the depolarizing mechanism that generates the bursts presents quantitative differences across segments that could counterbalance other differences having the opposite effect. Although their presence and role are established, the distribution and density of the apical dendrites' Na+ channels have not been quantified and compared across ELL maps. Therefore, we test the hypothesis that Na+ channel density varies across segment by quantifying their distribution in the apical dendrites of immunolabeled ELL sections. We found the Na+ channels to be two-fold denser in the lateral segment (LS) than in the centro-medial segment (CMS), the centro-lateral segment (CLS) being intermediate. Our results imply that this differential expression of voltage-gated Na+ channels could counterbalance or interact with other aspects of neuronal physiology that vary across segments (e.g., SK channels). We argue that burst coding of sensory signals, and the way the network regulates bursting, should be influenced by these variations in Na+ channel density.

Behavioral and neural aspects of the spatial processing of conspecifics signals in the electrosensory system.

Localizing the source of a signal is often as important as deciphering the signal's message. Localization mechanisms must cope with the challenges of representing the spatial information of weak, noisy signals. Comparing these strategies across modalities and model systems allows a broader understanding of the general principles shaping spatial processing. In this review we focus on the electrosensory system of knifefish and provide an overview of our current understanding of spatial processing in this system, in particular, localization of conspecific signals. We argue that many mechanisms observed in other sensory systems, such as the visual or auditory systems, have comparable implementations in the electrosensory system. Our review therefore describes a field of research with unique opportunities to provide new insights into the principles underlying spatial processing. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Neural Processing of Communication Signals: The Extent of Sender-Receiver Matching Varies across Species of Apteronotus.

As communication signal properties change, through genetic drift or selective pressure, the sensory systems that receive these signals must also adapt to maintain sensitivity and adaptability in an array of contexts. Shedding light on this process helps us to understand how sensory codes are tailored to specific tasks. In a species of weakly electric fish, Apteronotus albifrons, we examined the unique neurophysiological properties that support the encoding of electrosensory communication signals that the animal encounters in social exchanges. We compare our findings to the known coding properties of the closely related species Apteronotus leptorhynchus to establish how these animals differ in their ability to encode their distinctive communication signals. While there are many similarities between these two species, we found notable differences leading to relatively poor coding of the details of chirp structure occurring on high-frequency background beats. As a result, small differences in chirp properties are poorly resolved by the nervous system. We performed behavioral tests to relate A. albifrons chirp coding strategies to its use of chirps during social encounters. Our results suggest that A. albifrons does not exchange frequent chirps in a nonbreeding condition, particularly when the beat frequency is high. These findings parallel the mediocre chirp coding accuracy in that they both point to a reduced reliance on frequent and rich exchange of information through chirps during these social interactions. Therefore, our study suggests that neural coding strategies in the CNS vary across species in a way that parallels the behavioral use of the sensory signals.

Systematic Analysis of Transmitter Coexpression Reveals Organizing Principles of Local Interneuron Heterogeneity.

Broad neuronal classes are surprisingly heterogeneous across many parameters, and subclasses often exhibit partially overlapping traits including transmitter coexpression. However, the extent to which transmitter coexpression occurs in predictable, consistent patterns is unknown. Here, we demonstrate that pairwise coexpression of GABA and multiple neuropeptide families by olfactory local interneurons (LNs) of the moth Manduca sexta is highly heterogeneous, with a single LN capable of expressing neuropeptides from at least four peptide families and few instances in which neuropeptides are consistently coexpressed. Using computational modeling, we demonstrate that observed coexpression patterns cannot be explained by independent probabilities of expression of each neuropeptide. Our analyses point to three organizing principles that, once taken into consideration, allow replication of overall coexpression structure: (1) peptidergic neurons are highly likely to coexpress GABA; (2) expression probability of allatotropin depends on myoinhibitory peptide expression; and (3) the all-or-none coexpression patterns of tachykinin neurons with several other neuropeptides. For other peptide pairs, the presence of one peptide was not predictive of the presence of the other, and coexpression probability could be replicated by independent probabilities. The stochastic nature of these coexpression patterns highlights the heterogeneity of transmitter content among LNs and argues against clear-cut definition of subpopulation types based on the presence of single neuropeptides. Furthermore, the receptors for all neuropeptides and GABA were expressed within each population of principal neuron type in the antennal lobe (AL). Thus, activation of any given LN results in a dynamic cocktail of modulators that have the potential to influence every level of olfactory processing within the AL.

Selective and Context-Dependent Social and Behavioral Effects of Δ9-Tetrahydrocannabinol in Weakly Electric Fish.

Cannabinoid (CB) receptors are widespread in the nervous system and influence a variety of behaviors. Weakly electric fish have been a useful model system in the study of the neural basis of behavior, but we know nothing of the role played by the CB system. Here, we determine the overall behavioral effect of a nonselective CB receptor agonist, namely Δ9-tetrahydrocannabinol (THC), in the weakly electric fish Apte-ronotus leptorhynchus. Using various behavioral paradigms involving social stimuli, we show that THC decreases locomotor behavior, as in many species, and influences communication and social behavior. Across the different experiments, we found that the propensity to emit communication signals (chirps) and seek social interactions was affected in a context-dependent manner. We explicitly tested this hypothesis by comparing the behavioral effects of THC injection in fish placed in a novel versus a familiar social and physical environment. THC-injected fish were less likely to chirp than control fish in familiar situations but not in novel ones. The tendency to be in close proximity to other fish was affected only in novel environments, with control fish clustering more than THC-injected ones. By identifying behaviors affected by CB agonists, our study can guide further comparative and neurophysiological studies of the role of the CB system using a weakly electric fish as a model.

Task-specific sensory coding strategies are matched to detection and discrimination performance.

The acquisition of sensory information is limited by the neural encoding method used, constraining perceptual abilities. The most relevant aspects of stimuli may change as behavioral context changes, making efficient encoding of information more challenging. Sensory systems must balance rapid detection of a stimulus with perception of fine details that enable discrimination between similar stimuli. Here, we show that in a species of weakly electric fish, Apteronotus leptorhynchus, two coding strategies are employed for these separate behavioral tasks. Using communication signals, we demonstrate a strong correlation between neural coding strategies and behavioral performance on a discrimination task. Extracellular recordings of pyramidal cells within the electrosensory lateral line lobe of alert fish show two distinct response patterns, either burst discharges with little variation between different signals of the same category, or a graded, heterogeneous response that contains sufficient information to discriminate between signals with slight variations. When faced with a discrimination-based task, the behavioral performance of the fish closely matches predictions based on coding strategy. Comparisons of these results with neural and behavioral responses observed in other model systems suggest that our study highlights a general principle in the way sensory systems utilize different neural codes.

Variable synaptic strengths controls the firing rate distribution in feedforward neural networks.

Heterogeneity of firing rate statistics is known to have severe consequences on neural coding. Recent experimental recordings in weakly electric fish indicate that the distribution-width of superficial pyramidal cell firing rates (trial- and time-averaged) in the electrosensory lateral line lobe (ELL) depends on the stimulus, and also that network inputs can mediate changes in the firing rate distribution across the population. We previously developed theoretical methods to understand how two attributes (synaptic and intrinsic heterogeneity) interact and alter the firing rate distribution in a population of integrate-and-fire neurons with random recurrent coupling. Inspired by our experimental data, we extend these theoretical results to a delayed feedforward spiking network that qualitatively capture the changes of firing rate heterogeneity observed in in-vivo recordings. We demonstrate how heterogeneous neural attributes alter firing rate heterogeneity, accounting for the effect with various sensory stimuli. The model predicts how the strength of the effective network connectivity is related to intrinsic heterogeneity in such delayed feedforward networks: the strength of the feedforward input is positively correlated with excitability (threshold value for spiking) when firing rate heterogeneity is low and is negatively correlated with excitability with high firing rate heterogeneity. We also show how our theory can be used to predict effective neural architecture. We demonstrate that neural attributes do not interact in a simple manner but rather in a complex stimulus-dependent fashion to control neural heterogeneity and discuss how it can ultimately shape population codes.

Co-adaptation of electric organ discharges and chirps in South American ghost knifefishes (Apteronotidae).

Animal communication signals that simultaneously share the same sensory channel are likely to co-evolve to maximize the transmission of each signal component. Weakly electric fish continuously produce a weak electric field that functions in communication. Fish modulate the electric organ discharge (EOD) on short timescales to produce context-specific signals called chirps. EODs and chirps are simultaneously detected by electroreceptors and processed in the electrosensory system. We analyzed these signals, first to explore whether EOD waveform is encoded in the signal received by electroreceptors and then to examine how EODs and chirps interact to influence conspicuousness. Our findings show that gross discrimination of sinusoidal from complex EOD waveforms is feasible for all species, but fine discrimination of waveform may be possible only for species with waveforms of intermediate complexity. The degree of chirp frequency modulation and chirp relative decay strongly influenced chirp conspicuousness, but other chirp parameters were less influential. The frequency difference between the interacting EODs also strongly impacted chirp conspicuousness. Finally, we developed a method for creating hybrid chirp/EOD combinations to independently analyze the impact of chirp species, EOD species, and EOD difference frequency on chirp conspicuousness. All three components and their interactions strongly influenced chirp conspicuousness, which suggests that evolutionary changes in parameters of either chirps or EODs are likely to influence chirp detection. Examining other environmental factors such as noise created by fish movement and species-typical patterns of sociality may enrich our understanding of how interacting EODs affect the detection and discrimination of chirps across species.

Learning contrast-invariant cancellation of redundant signals in neural systems.

Cancellation of redundant information is a highly desirable feature of sensory systems, since it would potentially lead to a more efficient detection of novel information. However, biologically plausible mechanisms responsible for such selective cancellation, and especially those robust to realistic variations in the intensity of the redundant signals, are mostly unknown. In this work, we study, via in vivo experimental recordings and computational models, the behavior of a cerebellar-like circuit in the weakly electric fish which is known to perform cancellation of redundant stimuli. We experimentally observe contrast invariance in the cancellation of spatially and temporally redundant stimuli in such a system. Our model, which incorporates heterogeneously-delayed feedback, bursting dynamics and burst-induced STDP, is in agreement with our in vivo observations. In addition, the model gives insight on the activity of granule cells and parallel fibers involved in the feedback pathway, and provides a strong prediction on the parallel fiber potentiation time scale. Finally, our model predicts the existence of an optimal learning contrast around 15% contrast levels, which are commonly experienced by interacting fish.

Bursting neurons and ultrasound avoidance in crickets.

Decision making in invertebrates often relies on simple neural circuits composed of only a few identified neurons. The relative simplicity of these circuits makes it possible to identify the key computation and neural properties underlying decisions. In this review, we summarize recent research on the neural basis of ultrasound avoidance in crickets, a response that allows escape from echolocating bats. The key neural property shaping behavioral output is high-frequency bursting of an identified interneuron, AN2, which carries information about ultrasound stimuli from receptor neurons to the brain. AN2's spike train consists of clusters of spikes - bursts - that may be interspersed with isolated, non-burst spikes. AN2 firing is necessary and sufficient to trigger avoidance steering but only high-rate firing, such as occurs in bursts, evokes this response. AN2 bursts are therefore at the core of the computation involved in deciding whether or not to steer away from ultrasound. Bursts in AN2 are triggered by synaptic input from nearly synchronous bursts in ultrasound receptors. Thus the population response at the very first stage of sensory processing - the auditory receptor - already differentiates the features of the stimulus that will trigger a behavioral response from those that will not. Adaptation, both intrinsic to AN2 and within ultrasound receptors, scales the burst-generating features according to the stimulus statistics, thus filtering out background noise and ensuring that bursts occur selectively in response to salient peaks in ultrasound intensity. Furthermore AN2's sensitivity to ultrasound varies adaptively with predation pressure, through both developmental and evolutionary mechanisms. We discuss how this key relationship between bursting and the triggering of avoidance behavior is also observed in other invertebrate systems such as the avoidance of looming visual stimuli in locusts or heat avoidance in beetles.

Cellular and circuit properties supporting different sensory coding strategies in electric fish and other systems.

Neural codes often seem tailored to the type of information they must carry. Here we contrast the encoding strategies for two different communication signals in electric fish and describe the underlying cellular and network properties that implement them. We compare an aggressive signal that needs to be quickly detected, to a courtship signal whose quality needs to be evaluated. The aggressive signal is encoded by synchronized bursts and a predictive feedback input is crucial in separating background noise from the communication signal. The courtship signal is accurately encoded through a heterogenous population response allowing the discrimination of signal differences. Most importantly we show that the same strategies are used in other systems arguing that they evolved similar solutions because they faced similar tasks.

Preparing for the unpredictable: adaptive feedback enhances the response to unexpected communication signals.

To interact with the environment efficiently, the nervous system must generate expectations about redundant sensory signals and detect unexpected ones. Neural circuits can, for example, compare a prediction of the sensory signal that was generated by the nervous system with the incoming sensory input, to generate a response selective to novel stimuli. In the first-order electrosensory neurons of a gymnotiform electric fish, a negative image of low-frequency redundant communication signals is subtracted from the neural response via feedback, allowing unpredictable signals to be extracted. Here we show that the cancelling feedback not only suppresses the predictable signal but also actively enhances the response to the unpredictable communication signal. A transient mismatch between the predictive feedback and incoming sensory input causes both to be positive: the soma is suddenly depolarized by the unpredictable input, whereas the neuron's apical dendrites remain depolarized by the lagging cancelling feedback. The apical dendrites allow the backpropagation of somatic spikes. We show that backpropagation is enhanced when the dendrites are depolarized, causing the unpredictable excitatory input to evoke spike bursts. As a consequence, the feedback driven by a predictable low-frequency signal not only suppresses the response to a redundant stimulus but also induces a bursting response triggered by unpredictable communication signals.

Frequency-tuned cerebellar channels and burst-induced LTD lead to the cancellation of redundant sensory inputs.

For optimal sensory processing, neural circuits must extract novel, unpredictable signals from the redundant sensory input in which they are embedded, but the detailed cellular and network mechanisms that implement such selective cancellation are presently unknown. Using a combination of modeling and experiment, we characterize in detail a cerebellar circuit in weakly electric fish, showing how it can carry out this computation. We use a model incorporating the wide range of experimentally estimated parallel fiber feedback delays and a burst-induced LTD rule derived from in vitro experiments to explain the precise cancellation of redundant signals observed in vivo. Our model demonstrates how the backpropagation-dependent burst dynamics adjusts the temporal pairing width of the plasticity mechanism to precisely match the frequency of the redundant signal. The model also makes the prediction that this cerebellar feedback pathway must be composed of frequency-tuned channels; this prediction is subsequently verified in vivo, highlighting a novel and general capability of cerebellar circuitry.

Neural heterogeneity and efficient population codes for communication signals.

Efficient sensory coding implies that populations of neurons should represent information-rich aspects of a signal with little redundancy. Recent studies have shown that neural heterogeneity in higher brain areas enhances the efficiency of encoding by reducing redundancy across the population. Here, we study how neural heterogeneity in the early stages of sensory processing influences the efficiency of population codes. Through the analysis of in vivo recordings, we contrast the encoding of two types of communication signals of electric fishes in the most peripheral sensory area of the CNS, the electrosensory lateral line lobe (ELL). We show that communication signals used during courtship (big chirps) and during aggressive encounters (small chirps) are encoded by different populations of ELL pyramidal cells, namely I-cells and E-cells, respectively. Most importantly, we show that the encoding strategy differs for the two signals and we argue that these differences allow these cell types to encode specifically information-rich features of the signals. Small chirps are detected, and their timing is accurately signaled through stereotyped spike bursts, whereas the shape of big chirps is accurately represented by variable increases in firing rate. Furthermore, we show that the heterogeneity across I-cells enhances the efficiency of the population code and thus permits the accurate discrimination of different quality courtship signals. Our study shows the importance of neural heterogeneity early in a sensory system and that it initiates the sparsification of sensory representation thereby contributing to the efficiency of the neural code.

The structure and size of sensory bursts encode stimulus information but only size affects behavior.

Cricket ultrasound avoidance is a classic model system for neuroethology. Avoidance steering is triggered by high-firing-rate bursts of spikes in the auditory command neuron AN2. Although bursting is common among sensory neurons, and although the detailed structure of bursts may encode information about the stimulus, it is as yet unclear whether this information is decoded. We address this question in two ways: from an information coding point of view, by showing the relationship between stimulus and burst structure; and also from a functional point of view by showing the relationship between burst structure and behavior. We conclude that the burst structure carries detailed temporal information about the stimulus but that this has little impact on the behavioral response, which is affected mainly by burst size.

Transient signals trigger synchronous bursts in an identified population of neurons.

It is an important task in neuroscience to find general principles that relate neural codes to the structure of the signals they encode. The structure of sensory signals can be described in many ways, but one important categorization distinguishes continuous from transient signals. We used the communication signals of the weakly electric fish to reveal how transient signals (chirps) can be easily distinguished from the continuous signal they disrupt. These communication signals-low-frequency sinusoids interrupted by high-frequency transients-were presented to pyramidal cells of the electrosensory lateral line lobe (ELL) during in vivo recordings. We show that a specific population of electrosensory neurons encodes the occurrence of the transient signal by synchronously producing a burst of spikes, whereas bursting was neither common nor synchronous in response to the continuous signal. We also confirmed that burst can be triggered by low-frequency modulations typical of prey signals. However, these bursts are more common in a different segment of the ELL and during spatially localized stimulation. These localized stimuli will elicit synchronized bursting only in a restricted number of cells the receptive fields of which overlap the spatial extent of the stimulus. Therefore the number of cells simultaneously producing a burst and the ELL segment responding most strongly may carry the information required to disambiguate chirps from prey signals. Finally we show that the burst response to chirps is due to a biophysical mechanism previously characterized by in vitro studies of electrosensory neurons. We conclude that bursting and synchrony across cells are important mechanisms used by sensory neurons to carry the information about behaviorally relevant but transient signals.

A behavioral role for feature detection by sensory bursts.

Brief episodes of high-frequency firing of sensory neurons, or bursts, occur in many systems, including mammalian auditory and visual systems, and are believed to signal the occurrence of particularly important stimulus features, i.e., to function as feature detectors. However, the behavioral relevance of sensory bursts has not been established in any system. Here, we show that bursts in an identified auditory interneuron of crickets reliably signal salient stimulus features and reliably predict behavioral responses. Our results thus demonstrate the close link between sensory bursts and behavior.

Effect of the temporal pattern of contralateral inhibition on sound localization cues.

We studied the temporal coding properties of identified interneurons in the auditory system of crickets, using information theory as an analytical tool. The ascending neuron 1 (AN1), which is tuned to the dominant carrier frequency (CF) of cricket songs, selectively codes the limited range of amplitude modulation (AM) frequencies that occur in these signals. AN2, which is most sensitive to the ultrasonic frequencies that occur in echolocation calls of insectivorous bats, codes a broader range of AM frequencies, as occur in bat calls. A third neuron, omega neuron 1 (ON1), which is dually tuned to both ranges of carrier frequency, was shown previously to have CF-specific coding properties, allowing it to represent accurately the differing temporal structures of both cricket songs and bat calls. ON1 is a source of contralateral inhibition to AN1 and AN2, enhancing binaural contrast and facilitating sound localization. We used dichotic stimulation to examine the importance of the temporal structure of contralateral inhibition for enhancing binaural contrast. Contralateral inhibition degrades the coding of temporal pattern by AN1 and AN2, but only if the temporal pattern of inhibitory input matches that of excitation. Firing rate is also decreased most strongly by temporally matched contralateral inhibition. This is apparent for AN1 in its mean firing rate; for AN2, high-frequency firing is selectively suppressed. Our results show that the CF-specific coding properties of ON1 allow this single neuron to enhance effectively localization cues for both cricket-like and bat-like acoustic signals.