The neural mechanisms that lead to sparse coding within the midbrain of weakly electric fish

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Animals must efficiently process behaviorally relevant stimuli in order to successfully interact with their environment. How neurons decode and then encode sensory information, and the ways in which neural strategies for coding change across successive brain areas, remains a central problem in neuroscience. Studies across sensory systems have shown that representations in higher order brain areas are more efficient because individual neurons respond selectively to specific features of sensory input (i.e. sparse coding). Yet, at the same time, robust recognition of a given feature of sensory input (e.g. a particular object, face) requires that neural responses become robust to transformations applied to that feature (e.g. rotation/translation resulting from looking at the object from different viewpoints). Such feature invariance somewhat opposes selectivity as it requires that neurons respond similarly to stimuli with very different spatiotemporal characteristics that belong to the same “category” (e.g. a car looked at from different viewpoints). The cellular and network mechanisms that mediate the tradeoff between response selectivity and feature invariance are however poorly understood in vertebrates. My proposal focuses on elucidating the mechanisms that enable electrosensory midbrain neurons in gymnotiform wave-type weakly electric fish to respond selectively but in an invariant manner to communication calls that occur during social interactions between conspecifics. These fish generate a quasi-sinusoidal electric field around their body and monitor perturbations of this field through an array of electroreceptor neurons scattered on their skin. During either agonistic or courtship behaviors, male fish tend to emit brief perturbations of their electric fields that consist of a transient increase in the electric field frequency and are commonly referred to as “chirps”. Previous studies have shown that fish will robustly respond to these chirps even when their stimulus waveforms display large heterogeneity. This result is even more surprising in light of electrophysiological studies showing that peripheral electrosensory neurons respond quite differentially to different stimulus waveforms resulting from chirps. Thus, an important question then is: how does the animal recognize these different waveforms as belonging to the same category (i.e. chirps)? Our preliminary data shows that some electrosensory midbrain neurons respond similarly to stimulus waveforms resulting from chirps but not at all to stimulus waveforms from other categories. Using a combination of in vivo patch clamp recordings, pharmacology, and mathematical modeling, I propose to uncover the cellular and network mechanisms that enable these neurons to display feature invariant yet at the same time selective responses to chirp stimuli. Because the electrosensory system shares many anatomical/physiological similarities with other eighth nerve systems (e.g. vestibular/auditory), it is very likely that the results from this research will be applicable to other systems.