A novel channel of information transmission in the brain: correlations between the activities of medullary neurons encode behaviorally relevant stimuli in weakly electric fish

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We rely on our senses in almost every aspect of our everyday live, yet our understanding of how the brain processes sensory stimuli in order to generate reliable behavior is very limited. As the activity of the single neuron typically displays substantial variability, the generation of robust behavioral responses is thought to be achieved by combining the activities of neural populations (i.e. population coding). To investigate population coding, scientists have recorded from many neurons simultaneously which revealed that the activities of neurons are often correlated, both in terms of their average response to a stimulus (i.e. signal correlations) as well in terms of their variabilities (i.e. noise correlations). While it is generally agreed that correlations impact coding, whether they are beneficial or detrimental is still focus of intense debates within the scientific community. Understanding how correlated activity affects coding is furthermore complicated by the fact that correlations are not fixed but change depending on sensory and behavioral context or the internal state of the brain. This plasticity however allows for the interesting hypothesis that correlations themselves could convey information about sensory input and constitute an additional channel of information transmission in the brain that works independent of single neuron attributes (e.g. firing rate). However, to this day this theory remains experimentally untested. During my research fellowship, I will test this hypothesis in the electrosensory system of the weakly electric fish Apteronotus leptorhynchus, a South-American Gymnotid species that navigates and communicates by means of an electric field that is actively generated and constantly surrounds its body. Electrosensory neurons within the medulla are known to display strong correlations. Based on my preliminary data, I hypothesize that noise correlations gradually encode behaviorally relevant stimulus attributes and thus providing an additional channel of information transmission in the brain. After a thorough characterization, I will then elucidate the nature of the neural circuits that enable this novel coding mechanism.Previous work has shown that many scientific breakthroughs were achieved by working on model animals with a relatively simple and well described nervous system and well-characterized natural stimuli, which all apply to Apteronotus leptorhynchus. Furthermore, the functional principles and molecular machinery of this nervous system are similar to those found in higher vertebrates including humans. Consequently, I expect that my findings will have a broad applicability to other model systems and brain areas and will be transformative towards understanding of how correlated activity impacts population coding.