Study of sequential information processing in electroreception through modelling and closed-loop stimulation techniques

Tesis Doctoral inédita leída en la Universidad Autónoma de Madrid, Escuela Politécnica Superior, Departamento de Ingenieria Informática. Fecha de Lectura: 20-01-202

Temporal code-driven stimulation: definition and application to electric fish signaling

This Document is Protected by copyright and was first published by Frontiers. All rights reserved. it is reproduced with permissionClosed-loop activity-dependent stimulation is a powerful methodology to assess information processing in biological systems. In this context, the development of novel protocols, their implementation in bioinformatics toolboxes and their application to different description levels open up a wide range of possibilities in the study of biological systems. We developed a methodology for studying biological signals representing them as temporal sequences of binary events. A specific sequence of these events (code) is chosen to deliver a predefined stimulation in a closed-loop manner. The response to this code-driven stimulation can be used to characterize the system. This methodology was implemented in a real time toolbox and tested in the context of electric fish signaling. We show that while there are codes that evoke a response that cannot be distinguished from a control recording without stimulation, other codes evoke a characteristic distinct response. We also compare the code-driven response to open-loop stimulation. The discussed experiments validate the proposed methodology and the software toolbox.This work was funded by Spanish projects of Ministerio de Economia y Competitividad/FEDER TIN-2010-19607, TIN2014-54580-R, TIN-2012-30883, DPI2015 65833-P (http://www.mineco.gob.es/), ONRG grant N62909-14-1-N279, Brazilian Agency of Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (http://www.cnpq.br/) and Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (www.fapesp.br). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Modeling the sequential pattern variability of the electromotor command system of pulse electric fish

This study was supported by AEI/FEDER grants TIN2017-84452-R, PID2020-114867RB-I00, and PGC2018-095895-B-I0

Spatial processing of conspecific signals in weakly electric fish: from sensory image to neural population coding

In this dissertation, I examine how an animal’s nervous system encodes spatially realistic conspecific signals in their environment and how the encoding mechanisms support behavioral sensitivity. I begin by modeling changes in the electrosensory signals exchanged by weakly electric fish in a social context. During this behavior, I estimate how the spatial structure of conspecific stimuli influences sensory responses at the electroreceptive periphery. I then quantify how space is represented in the hindbrain, specifically in the primary sensory area called the electrosensory lateral line lobe. I show that behavioral sensitivity is influenced by the heterogeneous properties of the pyramidal cell population. I further demonstrate that this heterogeneity serves to start segregating spatial and temporal information early in the sensory pathway. Lastly, I characterize the accuracy of spatial coding in this network and predict the role of network elements, such as correlated noise and feedback, in shaping the spatial information. My research provides a comprehensive understanding of spatial coding in the first stages of sensory processing in this system and allows us to better understand how network dynamics shape coding accuracy

Amazon Nights II: Electric Boogaloo-Neural Adaptations for Communication in Three Species of Weakly Electric FIsh

Sensory systems have to extract useful information from environments awash in noise and confounding input. Studying how salient signals are encoded and filtered from these natural backgrounds is a key problem in neuroscience. Communication is a particularly tractable tool for studying this problem, as it is a ubiquitous task that all organisms must accomplish, easily compared across species, and is of significant ethological relevance. In this chapter I describe the current knowledge of what is both known and still unknown about how sensory systems are adapted for the challenges of encoding conspecific signals, particularly in environments complicated by conspecific-generated noise. The second half of this chapter describes why weakly electric fish are particularly suited to investigating how communication can shape the nervous system to accomplish this task

Insights into neural mechanisms and evolution of behaviour from electric fish.

Behaviour, although multifaceted and diverse, also seems to be convergent across taxa. Even distantly related organisms can show similar behaviours, involving sensory pattern recognition, locomotion and experiencedependent changes in sensory processing and motor output. In neuroscience, the prevalent use of particular systems as models for understanding the function of the human nervous system rests on this functional overlap and structural homology. However, we are only beginning to understand whether similarities in behaviour are paralleled by similarities in control mechanisms, neural circuitry and processing. This gap in knowledge is not surprising; the identification of the neural control of any particular behaviour or function can be a formidable challenge. As we learn more about how neural circuits control behaviour, we hope to gain a greater understanding of why particular solutions have developed 1 . Integration of information at these two levels will be essential for revealing the uniqueness of particular neural circuits 2 and mechanisms, as well as for understanding the roles of historical forces in determining the final architecture of neural circuits and processing. Electrosensory systems (BOX 1) are well suited to addressing these questions. In addition to their established utility for investigating receptor 3 and ion channel 4 function, electric fish have increasingly been used for studying the neural circuits that control behaviour 5 . Some fish are purely electroreceptive, whereas others can both sense and produce electric fields. Most species of the latter type continue to produce discharges of their electric organs (EODs, electric organ discharges) when prepared for in vivo neurophysiological recording. Furthermore, changes in these EODs produce a variety of electrosensory behaviours, permitting investigators to study the entire neural circuit for the control of these behaviours 5, Jamming avoidance responses Behaviour. Wave-type electric fish generate electric fields INSIGHTS INTO NEURAL MECHANISMS AND EVOLUTION OF BEHAVIOUR FROM ELECTRIC FISH Gary J. Rose Abstract | Both behaviour and its neural control can be studied at two levels. At the proximate level, we aim to identify the neural circuits that control behaviour and to understand how information is represented and processed in these circuits. Ultimately, however, we are faced with questions of why particular neural solutions have arisen, and what factors govern the ways in which neural circuits are modified during the evolution of new behaviours. Only by integrating these levels of analysis can we fully understand the neural control of behaviour. Recent studies of electrosensory systems show how this synthesis can benefit from the use of tractable systems and comparative studies

On the Role of Sensory Cancellation and Corollary Discharge in Neural Coding and Behavior

Studies of cerebellum-like circuits in fish have demonstrated that synaptic plasticity shapes the motor corollary discharge responses of granule cells into highly-specific predictions of self- generated sensory input. However, the functional significance of such predictions, known as negative images, has not been directly tested. Here we provide evidence for improvements in neural coding and behavioral detection of prey-like stimuli due to negative images. In addition, we find that manipulating synaptic plasticity leads to specific changes in circuit output that disrupt neural coding and detection of prey-like stimuli. These results link synaptic plasticity, neural coding, and behavior and also provide a circuit-level account of how combining external sensory input with internally-generated predictions enhances sensory processing. In addition, the mammalian dorsal cochlear nucleus (DCN) integrates auditory nerve input with a diverse array of sensory and motor signals processed within circuity similar to the cerebellum. Yet how the DCN contributes to early auditory processing has been a longstanding puzzle. Using electrophysiological recordings in mice during licking behavior we show that DCN neurons are largely unaffected by self-generated sounds while remaining sensitive to external acoustic stimuli. Recordings in deafened mice, together with neural activity manipulations, indicate that self-generated sounds are cancelled by non-auditory signals conveyed by mossy fibers. In addition, DCN neurons exhibit gradual reductions in their responses to acoustic stimuli that are temporally correlated with licking. Together, these findings suggest that DCN may act as an adaptive filter for cancelling self-generated sounds. Adaptive filtering has been established previously for cerebellum-like sensory structures in fish suggesting a conserved function for such structures across vertebrates

Stimulus Encoding and Feature Extraction by Multiple Sensory Neurons

Neighboring cells in topographical sensory maps may transmit similar information to the next higher level of processing. How information transmission by groups of nearby neurons compares with the performance of single cells is a very important question for understanding the functioning of the nervous system. To tackle this problem, we quantified stimulus-encoding and feature extraction performance by pairs of simultaneously recorded electrosensory pyramidal cells in the hindbrain of weakly electric fish. These cells constitute the output neurons of the first central nervous stage of electrosensory processing. Using random amplitude modulations (RAMs) of a mimic of the fish’s own electric field within behaviorally relevant frequency bands, we found that pyramidal cells with overlapping receptive fields exhibit strong stimulus-induced correlations. To quantify the encoding of the RAM time course, we estimated the stimuli from simultaneously recorded spike trains and found significant improvements over single spike trains. The quality of stimulus reconstruction, however, was still inferior to the one measured for single primary sensory afferents. In an analysis of feature extraction, we found that spikes of pyramidal cell pairs coinciding within a time window of a few milliseconds performed significantly better at detecting upstrokes and downstrokes of the stimulus compared with isolated spikes and even spike bursts of single cells. Coincident spikes can thus be considered “distributed bursts.” Our results suggest that stimulus encoding by primary sensory afferents is transformed into feature extraction at the next processing stage. There, stimulus-induced coincident activity can improve the extraction of behaviorally relevant features from the stimulus

Peripheral and Central Mechanisms of Temporal Pattern Recognition

Encoding information into the timing patterns of action potentials, or spikes, is a strategy used broadly in neural circuits. This type of coding scheme requires downstream neurons to be sensitive to the temporal patterns of presynaptic inputs. Indeed, neurons with temporal filtering properties have been found in a wide range of sensory pathways. However, how such response properties arise was previously not well understood. The goal of my dissertation research has been to elucidate how temporal filtering by single neurons contributes to the behavioral ability to recognize timing patterns in communication signals. I have addressed this question using mormyrid weakly electric fish, which vary the time intervals between successive electric pulses to communicate. Fish detect these signals with sensory receptors in their skin. In the majority of species, these receptors fire a single spike in response to each electric pulse. Spiking receptors faithfully encode the interpulse intervals in communication signals into interspike intervals, which are then decoded by interval-selective midbrain neurons. Using in vivo intracellular recordings from awake fish during sensory stimulation, I found that short-term depression and temporal summation play important roles in establishing single-neuron interval selectivity. Moreover, the combination of short-term depression and temporal summation in the circuit resulted in greater diversity of interval tuning properties across the population of neurons, which would increase the population’s ability to detect temporally patterned communication signals. Indeed, I found that the responses of single interval-selective neurons were sensitive to subtle variation in the timing patterns of a specific communication display produced by different individuals. A subset of mormyrid species has sensory receptors that produce spontaneously oscillating potentials. How the electrosensory system of these species established sensitivity to temporally patterned communication signals was completely unknown. Using in vivo extracellular recordings, I demonstrated that these receptors encode sensory stimuli into phase resets, which is the first clear instance of information coding by oscillatory phase reset. Furthermore, the ongoing oscillations conferred enhanced sensitivity to fast temporal patterns that are only found in the communication signals of a large group of fish. Behavioral playback experiments provided further support for the hypothesis that oscillating receptors are specialized for detecting communication signals produced by a group of conspecifics, which is a novel role for a sensory receptor. These findings demonstrate that temporal pattern sensitivity, which was previously thought to be a central processing problem, can also arise from peripheral filtering through a novel oscillatory phase reset mechanism

Bursts and Isolated Spikes Code for Opposite Movement Directions in Midbrain Electrosensory Neurons

Directional selectivity, in which neurons respond strongly to an object moving in a given direction but weakly or not at all to the same object moving in the opposite direction, is a crucial computation that is thought to provide a neural correlate of motion perception. However, directional selectivity has been traditionally quantified by using the full spike train, which does not take into account particular action potential patterns. We investigated how different action potential patterns, namely bursts (i.e. packets of action potentials followed by quiescence) and isolated spikes, contribute to movement direction coding in a mathematical model of midbrain electrosensory neurons. We found that bursts and isolated spikes could be selectively elicited when the same object moved in opposite directions. In particular, it was possible to find parameter values for which our model neuron did not display directional selectivity when the full spike train was considered but displayed strong directional selectivity when bursts or isolated spikes were instead considered. Further analysis of our model revealed that an intrinsic burst mechanism based on subthreshold T-type calcium channels was not required to observe parameter regimes for which bursts and isolated spikes code for opposite movement directions. However, this burst mechanism enhanced the range of parameter values for which such regimes were observed. Experimental recordings from midbrain neurons confirmed our modeling prediction that bursts and isolated spikes can indeed code for opposite movement directions. Finally, we quantified the performance of a plausible neural circuit and found that it could respond more or less selectively to isolated spikes for a wide range of parameter values when compared with an interspike interval threshold. Our results thus show for the first time that different action potential patterns can differentially encode movement and that traditional measures of directional selectivity need to be revised in such cases