Parallel processing in electrosensory maps: from neuronal encoding to spatial learning.

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The aim of the project is to understand the process of electrosensory object representation and recognition in context to natural behaviors. On the one hand we focus on sensory bottom-up processes, which are characterized by a parallel processing of stimuli. On the other hand, higher brain areas linked to active electroreception are analyzed with respect to top-down associative processes.We will examine how electric images of real objects are represented and neuronally encoded within two parallel neural maps of the ELL. The hypothesis underlying the experiments is that parallel processing leads to efficient extraction of behaviorally relevant features and that this is reflected in differences in spatial coding between the maps.Using anatomical approaches we will investigate how information that has been processes separately in the ELL is conveyed and eventually converges in higher brain areas. Through the combination of anatomical and neurophysiological approaches we expect to derive generalizable information about efficient sensory processing that will have an impact beyond the specific model system of electric fishes. This knowledge then could be integrated with modeling studies on sensor-fusion issues and technical implementations of biological sensing principles.These studies, with their focus on bottom-up processes, will be complemented by studies of higher cognitive capabilities and their neuronal basis. The influence of associative processes on the higher electrosensory processing areas - especially the Cerebellum and the Telencephalon - will be characterized for the first time. Therefore we will study the expression of immediate early genes. Combining this with behavioral studies on spatial learning, we strive to map those higher brain regions devoted to electrosensory spatial learning. These behavioral experiments will enable us to shed new light on homologies of learning processes and the underlying neural structures in vertebrates.In summary, our application addresses both fundamental research questions specific to a well-established model organism and research questions that of broad relevance in sensory processing. Further our results will connect to application-oriented implementations of efficient sensory processing based on bio-inspired approaches.