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What the Rat's Whiskers Tell the Rat's Brain

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If you have a question about this talk, please contact Guillaume Hennequin.

The whisker system is beautifully organised and its microcircuitry is perhaps the best understood of any mammalian sensory system, making it an attractive model system for investigations in systems and computational neuroscience. The focus of my group’s work is the basic question of how spike trains represent sensory events (‘neural coding’).

In any sensory system, the primary afferents constitute the first level of sensory representation and fundamentally constrain all subsequent information processing. We have determined that neural coding in this system is based on action potentials that are timed with remarkable (sub-millisecond) precision. We have also determined that the spike timing, reliability and stimulus selectivity of primary afferents can be accurately described by a simple Generalised Linear Model, consisting of linear stimulus filtering combined with spike feedback. The model accurately predicts not only the response of primary afferents to white noise whisker motion (median correlation coefficient 0.92) but also to naturalistic, texture-induced whisker motion. A 2 -dimensional filter subspace, corresponding to different mixtures of position and velocity sensitivity, captured 94% of the variance in the stimulus selectivity of the model. Our results suggest that the first stage of the whisker system approximately tile a low-dimensional (2-3D) feature space.

This talk is part of the Computational Neuroscience series.

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