Cellular and circuit properties supporting different sensory coding strategies in electric fish and other systems
Highlights
► Electric fish detect aggressive communication signals via synchronized bursts. ► Courtship signals are well described by heterogeneous population responses. ► Different neural properties support these two different forms of population coding. ► These same coding strategies are implemented across a wide range of systems.
Introduction
An important question in neuroscience is to understand how a neural code is matched to the characteristics of the natural signals. Some sensory signals are quickly detected by the nervous system, such as a noxious stimulus or an alarm call, causing rapid avoidance or an escape reflex. The nervous system must extract these signals from the background noise and, past a certain signal-to-noise ratio, trigger a behavioral response. Other signals carry information on a range of time scales and their local temporal details are important. These signals must be encoded by the nervous system in a way that enables downstream neurons to extract relevant information on multiple time scales. In this review we describe principles underlying the coding of these two types of stimuli in the context of communication signals in electric fish. We show how the circuitry and the cellular properties are matched to the respective signal properties to produce an efficient behaviorally relevant encoding. We further argue for their applicability to sensory processing in a wide range of organisms and modalities.
We first focus on an aggressive signal (Figure 1a) and describe how the cellular and network properties are linked to a spike burst code that allows sensitive detection of the signal. We discuss how feedback influences the burst-generating mechanism to permit efficient stimulus extraction in the presence of competing signals. We then look at the accurate encoding of courtship signals (Figure 1b) by a population of electrosensory neurons, allowing fine discrimination of stimuli attributes. The heterogeneity of the cells’ responses, due to a diversity in their cellular and synaptic properties, plays a crucial role by increasing the amount of information carried by the population.
Section snippets
Electrocommunication and electroreception
Electric fish produce a weak electric field around their body to navigate, find prey and communicate with one another [1]. Gymnotiform wave-type electric fish have an electrical organ that continuously discharges at a constant rate. The summation of the electric fields from two interacting fish cause amplitude modulations called beats. Interacting fish are thus constantly exposed to these background beat modulations. The most common type of communication signals, chirps, consist of transient
Bursting and detection of small chirps
The ELL is divided in three topographic maps. Its output cells are organized in several layers and come in two intermingled types: the E-cells respond to increases in EOD amplitude and I-cells to decreases. Depending on the map, layer and cell type, the cellular, network and response properties of the cells vary greatly [7, 8] although they are embedded in a common local microcircuit. When presented with small chirps, superficial E-cells of the lateral map respond most strongly by emitting
Neural heterogeneity and discrimination of big chirps
Courtship signals can carry information about male quality. When courting females, males often produce big chirps which are categorically different from aggression-associated small chirps (Figure 1; [34]). Big chirps evoke graded and diverse increases in the firing rate of ELL I-cells (Figure 2d; [20••]). The E-cells responding to small chirps provide little information about the big chips. The diverse big chirp-evoked responses from individual I-cells combine into a noise-free, invariant,
Conclusion
We have contrasted the processing of two different communication signals and described some of the network and cellular properties involved (see Figure 2 for a graphical summary). In one case, a bursting response allows the reliable detection of the stimulus. The interplay between the bursting dynamics and predictive feedback input allows for both filtering out background signals and extracting unexpected signals. In the other case heterogeneity allows a courtship signal to be efficiently
References and recommended reading
Papers of particular interest, published within the period of review, have been highlighted as:
• of special interest
•• of outstanding interest
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Cited by (57)
Neuroendocrine mechanisms contributing to the coevolution of sociality and communication
2023, Frontiers in NeuroendocrinologyMixed selectivity coding of sensory and motor social signals in the thalamus of a weakly electric fish
2022, Current BiologyCitation Excerpt :The electrocommunication signals associated with social behavior are low dimensional, are easy to record and mimic, and have been described in laboratory settings3–9 and in the fish’s natural environment.10 The motor pathways that generate electrocommunication signals11 and the responses of electroreceptors and medullary and midbrain electrosensory neurons to such signals12–15 have been characterized. Certain South American gymnotiform fish (apteronotids and Eigenmannia) emit quasi-sinusoidal8,16 electric organ discharges (EODs) and have electroreceptors tuned to this discharge, enabling them to navigate and communicate in the dark.12,13,15,17
Lower Baseline Variability Gives Rise to Lower Detection Thresholds in Midbrain than Hindbrain Electrosensory Neurons
2020, NeuroscienceCitation Excerpt :When two conspecifics are located in close proximity to one another, interference between their EODs gives rise to a sinusoidal amplitude modulation (i.e., a beat or first-order) whose frequency is given by the difference between the two EOD frequencies and whose amplitude (i.e., envelope or second-order) is inversely proportional to the distance between both animals (Yu et al., 2012). The tuning properties of electrosensory neurons that respond to both first- and second-order stimulus attributes have been extensively studied and reviewed (Chacron et al., 2003b, 2011; Marsat et al., 2012; Krahe and Maler, 2014; Clarke et al., 2015; Huang and Chacron, 2017; Metzen and Chacron, 2019). Recent studies have started uncovering the mechanisms that enable electrosensory neurons to respond to second-order attributes (Metzen and Chacron, 2015, 2019; Huang and Chacron, 2016; Huang et al., 2016, 2018, 2019; Metzen et al., 2018).
7.18 - Parallel Coding in the Electrosensory Medulla: Physiological Heterogeneity Facilitates the Processing of Diverse Stimulus Classes
2020, The Senses: A Comprehensive Reference: Volume 1-7, Second Edition