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

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Understanding how natural stimuli are encoded by peripheral sensory neurons and subsequently decoded by higher structures, the neural code, is a central problem in neuroscience. The long-term goals of the proposed research program are to understand the cellular and network mechanisms that make sensory neurons more selective in their responses to natural sensory input. It is generally agreed that peripheral sensory neurons employ dense neural codes (i.e. codes in which neurons respond to a wide range of stimuli) and that neurons in higher areas employ sparse neural codes (i.e. codes in which neurons respond selectively to the sparsely distributed informative components of natural stimuli). These sparse codes have now been widely observed across animal taxa, including the human hippocampus, monkey visual cortex, locust olfactory system, and songbird forebrain. It is argued that such sparse codes are more efficient because individual neurons detect specific features of sensory input and are metabolically less costly than dense codes. At the same time, recognition of a given stimulus feature (e.g. a particular object, face) requires that neural responses become robust to the sometimes very different inputs associated with this feature (e.g. the same object observed from different viewpoints).