Biology subjects

Marsat, G.

Publications and source records attributed to Marsat, G..

8 recordsLinked to original sources

bioRxiv2026

Adaptive spatiotemporal filtering of social electrosensory signals by cerebellar feedback

Sensory feedback can suppress predictable input, yet most research on this mechanism used simplified stimuli that do not capture the spatial and temporal structure of natural signals. We examined how cerebellum-like feedback, in brown ghost knifefish, shapes the encoding of realistic social electrosensory signals. These naturalistic signals replicated the spatial structure of social signals, spanned the range of typical AM beat frequencies, and incorporated movement-related contrast envelopes. Single-unit recordings were obtained from electrosensory lateral line lobe pyramidal cells while a conspecific-like signal was delivered. Responses were compared before and after pharmacological blockade of descending cerebellar feedback. As expected, feedback strongly attenuated responses to spatially-realistic low-frequency beats but did not alter beat-cycle coding at higher frequencies. However, feedback reduced the neural representation of movement-related contrast envelopes across all beat frequencies. Using information-theoretic tools, we showed that feedback strength adapts dynamically to the stimulus contrast over the past few hundred ms. Furthermore, we examined how the spatial coding by the pyramidal cell population is influenced by feedback. We show that feedback enhances localization cues. This improvement arose because feedback reduces weak background responses while not affecting the strongest responses, thereby increasing spatial contrast. These findings show that the same descending pathway jointly filters temporal and spatial features of the full range of natural signals, adapting to recent input statistics. This process exemplifies a general mechanism by which a predictive feedback can improve the efficiency of natural sensory representations.

neuroscience↗

bioRxiv2023

Spatial coding of conspecifics in subpopulations of hindbrain pyramidal cells of the gymnotiform electrosensory system

Localizing the source of a signal requires sophisticated neural mechanisms and we are still uncovering the coding principles that support accurate spatial processing. Weakly electric fish can detect and localize distant conspecifics, but the way this spatial information is encoded is unclear. Here, we investigate the spatial representation of conspecific signals in the hindbrain to determine how the properties of the heterogenous population of pyramidal cells affect the spatial coding accuracy of conspecific signals. We hypothesize that specific subsets of cells provide more accurate spatial information about conspecific location. We stimulated the fish with an artificial signal that replicates both the spatial and temporal structure of conspecific signals. We recorded from cells with various receptive field positions covering the entire body surface and analyzed the spike train with spike-train distance metrics to determine how accurately the location of the stimulus is encoded. We found that some pyramidal cells (such as ON-type, and those within the deep layer) encode the spatial information more accurately while other subgroups (OFF-type, and superficial layer) provide less accurate information. Our results help us understand how the heterogeneity of a population of cells allow the efficient processing of signals and suggest that a segregation of the spatial information stream starts earlier in the sensory pathway.

neuroscience↗

bioRxiv2023

Detection and localization of conspecifics in ghost knifefish are influenced by the relationship between the spatial organization of receptors and signals.

The detection and localization of signals rely on arrays of receptors, and their spatial organization plays a key role in determining the accuracy of the system. Weakly electric ghost knifefish rely on a distributed array of electroreceptors to detect spatially diffuse electric signals from conspecifics. While we know that spatial resolution for small objects, such as prey, is enhanced near the head due to a high receptor density, it is not clear how receptor organization influences the processing of global and diffuse signals from conspecifics. Using spatially realistic modeling, we quantified how receptor density influences detection and localization accuracy for conspecific signals across varying distances. Our main result demonstrates that receptor density markedly enhances detection accuracy in frontal regions at intermediate distances (35-50 cm) yet surprisingly contributes minimally to improving localization accuracy. This highlights a fundamental principle: receptor convergence primarily benefits signal detection when dealing with spatially diffuse stimuli, even though higher receptor density can enhance localization accuracy for spatially delineated signals. Our findings extend beyond the electrosensory modality, drawing parallels with other sensory systems, and offer broader insights into spatial processing principles.

neuroscience↗

bioRxiv2019

Characterizing neural coding performance for populations of sensory neurons: comparing a weighted spike distance metrics to other analytical methods.

The identity of sensory stimuli is encoded in the spatio-temporal patterns of responses of the encoding neural population. For stimuli to be discriminated reliably, differences in population responses must be accurately decoded by downstream networks. Several methods to compare patterns of responses have been used by neurophysiologists to characterize the accuracy of the sensory responses studied. Among the most widely used analysis, we note methods based on Euclidean distances or on spike metric distances. Methods based on artificial neural networks and machine learning that recognize and/or classify specific input patterns have also gained popularity. Here, we first compare these three strategies using datasets from three different model systems: the moth olfactory system, the electrosensory system of gymnotids, and leaky-integrate- and-fire (LIF) model responses. We show that the input-weighting procedure inherent to artificial neural networks allows the efficient extraction of information relevant to stimulus discrimination. To combine the convenience of methods such as spike metric distances but leverage the advantages of weighting the inputs, we propose a measure based on geometric distances where each dimension is weighted proportionally to how informative it is. We show that the result of this Weighted Euclidian Distance (WED) analysis performs as well or better than the artificial neural network we tested and outperforms the more traditional spike distance metrics. We applied information theoretic analysis to LIF responses and compare their encoding accuracy with the discrimination accuracy quantified through this WED analysis. We show a high degree of correlation between discrimination accuracy and information content and that our weighting procedure allowed the efficient use of information present to perform the discrimination task. We argue that our proposed measure provides the flexibility and ease of use sought by neurophysiologists while providing a more powerful way to extract relevant information than more traditional methods.

neuroscience↗

bioRxiv2019

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 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 pyramidal cells. 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 than in the centro-medial segment, the centro-lateral segment 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.

neuroscience↗

bioRxiv2018

Simplified neural encoding of social communication reflects lifestyle

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 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 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 do not exchange frequent chirps in non-breeding 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 central nervous system vary across species in a way that parallels the behavioral use of the sensory signals. SIGNIFICANCESender-receiver matching is a phenomenon commonly observed in the peripheral nervous system. It enables communication production and reception to evolve together so that conspecifics remain sensitive to important signals. In this manuscript we examine this phenomenon in the central nervous system of the weakly electric fish A. albifrons and compare its processing of communication signals to a closely related species (A. leptorhynchus). Although some differences across the two species can help tailor the system for processing species-specific signals, our data indicate that encoding of communication signals in A. albifrons is not as sensitive as in A. leptorhynchus for certain categories of signals. Our data support the idea that the extent of sender-receiver matching can vary as a function of behavioral needs.

neuroscience↗

bioRxiv2018

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 has 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 CB receptor agonist (i.e., {Delta}9-tetrahydrocannabinol, THC) in the weakly electric fish A. leptorhynchus. Using various behavioral paradigms involving social stimuli, we show that THC decreases locomotor behavior as in many species and influences the communication and social behavior. Across the different experiments we found that the propensity to emit communication signals (chirps) and to 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 familiar social and physical environments. THC-injected fish were less likely to chirp than control in familiar situation but not in novel ones. The tendency to be in close proximity was affected only in novel environments whith 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 weakly electric fish as a model.

neuroscience↗

bioRxiv2017

Task-specific sensory coding strategies matched to detection and discrimination behaviors in Apteronotus leptorhynchus

All sensory systems must reliably translate information about the environment into a neural code, mediating perception. 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. 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 produced in different contexts, 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 enough 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 different neural codes are utilized in the sensory system.\n\nSIGNIFICANCE STATEMENTResearch relating the structure of stimuli to the response of sensory neurons has left us with a detailed understanding of how different neural codes can represent information. Although various aspects of neural responses have been related to perceptual abilities, general principles relating behavioral tasks to sensory coding strategies are lacking. A major distinction can be made between signals that must simply be detected versus stimuli that must also be finely discriminated and evaluated. We show that these two different perceptual tasks are systematically matched by distinct neural coding strategies and we argue that our study identifies a general principle that is observed in various sensory systems.\n\nConflict of interest statementThe authors declare no competing financial interests.

neuroscience↗