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

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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.

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

References (41)

  • G.J. Hupé et al.

    Electrocommunication signals in free swimming brown ghost knifefish, Apteronotus leptorhynchus

    J Exp Biol

    (2008)
  • M.E. Nelson et al.

    Characterization and modeling of P-type electrosensory afferent responses to amplitude modulations in a wave-type electric fish

    J Comp Physiol A

    (1997)
  • L. Maler

    Receptive field organization across multiple electrosensory maps. II. Computational analysis of the effects of receptive field size on prey localization

    J Comp Neurol

    (2009)
  • L. Maler

    Receptive field organization across multiple electrosensory maps. I. Columnar organization and estimation of receptive field size

    J Comp Neurol

    (2009)
  • G. Marsat et al.

    Transient signals trigger synchronous bursts in an identified population of neurons

    J Neurophysiol

    (2009)
  • R. Krahe et al.

    Burst firing in sensory systems

    Nat Rev Neurosci

    (2004)
  • G. Marsat et al.

    A behavioral role for feature detection by sensory bursts

    J Neurosci

    (2006)
  • G. Schwartz et al.

    Sophisticated temporal pattern recognition in retinal ganglion cells

    J Neurophysiol

    (2008)
  • N.A. Lesica et al.

    Dynamic encoding of natural luminance sequences by LGN bursts

    PLoS Biol

    (2006)
  • A.M.M. Oswald et al.

    Interval coding. I. Burst interspike intervals as indicators of stimulus intensity

    J Neurophysiol

    (2007)
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