Gary Marsat

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.

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.

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.

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.

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.

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.

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 neurons 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.

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.

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.

Signal cancellation and contrast invariance in electrosensory systems

When processing sensory input, it is of vital importance for the neural systems to be able to discriminate a novel stimulus from the background of redundant, unimportant signals. Neural mechanisms responsible for prediction and cancellation of redundant information could be an efficient way to achieve such discrimination. While the concrete mechanisms that the brain employs for this task are presently unknown, a network able to perform this cancellation is thought to exist in the electrosensory lateral line lobe (ELL) of weakly electric fish [1]. This fish emits a high-frequency (600-1000 Hz) sinusoidal electric organ discharge (EOD) into its environment to sense its surroundings and communicate to conspecifics. Small objects such as prey create spatially localized amplitude modulations (AMs) of the EOD, whereas tail bending or communication signals induce spatially global AMs [2]. These AMs are detected by electroreceptors that densely cover the body of the fish, and provide feedforward input to pyramidal cells in the ELL. It is known that a subpopulation of such pyramidal cells, the superficial pyramidal (SP) cells, remove low-frequency predictable global signals (i.e. tail bending) from their input to maximize detection of novel local stimuli (i.e. prey) [1]. This is presumably achieved using a feedback pathway involving the granule cell layer (a cerebellarlike structure known as EGp). These granule cells connect to SP cells via parallel fibers (PFs) which may be acting as delay lines segregated into frequency channels to destructively interfere with the global stimulus. Recent in vitro studies found a novel burst timingdependent learning rule which would be able to shape this feedback [3]. Following a previous work [4], we study the cancellation of low-frequency simple redundant signals, i.e. sine waves, in the ELL of the weakly electric fish. The study combines in vitro data, in vivo electrophysiology recordings from neurons in the ELL and numerical modeling to address this issue. More precisely, we model the neural network responsible for signal cancellation in the ELL of the fish, and compare our predictions with electrophysiology data recorded in vivo [4]. In the model, we assume the presence of: 1) stimulus-driven feedback to the SP neurons, 2) a large variety of temporal delays in the PFs transmitting such feedback, and 3) burstinduced long-term plasticity. We show that the modeled network is able to efficiently cancel global redundant signals by shaping the feedback as a negative image of the global signal arriving to the SP cells. Such negative image is generated via the burst-induced anti-Hebbian learning rule in the PF-SP cell synapses, while the full period of the signal is covered by the incoming feedback due to the wide range of PF delays present in the network. The cancellation is found to be in agreement with in vivo recordings, and it is strong for signals with frequencies up to 16 Hz, enabling a clearer background above which to detect relevant non-repetitive stimuli such as prey signals (and thus to better capture the prey). Due to the importance of the phase-relationship between the feedback and the stimulus, the mechanism is found to be frequency-specific, suggesting the presence of multiple frequency channels as observed in vivo [4]. Interestingly, our model predicts that the cancellation is maintained for signals with different AM strengths (i.e. contrasts). Such contrast-invariance is highly desirable since natural signals would display different contrasts depending, for instance, on the distance between the fish and the origin of the EOD perturbation. * Correspondence: jmejias@uottawa.ca Department of Physics, University of Ottawa, Ottawa, K1N 6N5 Ontario, Canada Full list of author information is available at the end of the article Mejias et al. BMC Neuroscience 2012, 13(Suppl 1):F2 http://www.biomedcentral.com/1471-2202/13/S1/F2