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Spike-based neural computation and learning in the time domain: Applications to auditory and visual processing

Subject Area Cognitive, Systems and Behavioural Neurobiology
Term from 2008 to 2011
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 79296185
 
Understanding the role of action potential timing in neural information processing and learning has challenged brain researchers for over half a century. Despite advances in sensory system electrophysiology that have suggested that the precise timing of spikes can carry substantial information about eliciting stimuli, little understanding has been gained with respect to how downstream processing stages can decode such spike-timing based neuronal representations. Here we use our recently proposed spike-based synaptic learning rule, the tempotron, to study the function of spiking neural networks engaged in biologically realistic visual and auditory processing tasks. Using spiking models of the auditory periphery as well as electrophysiological recordings of retinal ganglion cell populations as input structures we ask three questions: 1. What is the functional role of specific cellular processes, such as conductance kinetics, short-term synaptic dynamics or dendritic compartments in spike-based neural processing? 2. What are optimal coding and readout strategies for early auditory and visual processing stages? 3. What are the computational principles underlying supervised spike-based learning rules in multi-layer neural networks engaged in demanding auditory processing of noisy connected speech? The present project will tie together spike-based neural computation from the perspectives of cellular biophysics, synaptic plasticity, and neural systems function.
DFG Programme Research Fellowships
International Connection Israel
 
 

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