2017/05/22 by Zeno Jonke, Robert Legenstein, Jonke, Zeno +5
Neuroscience · Engineering · #Neural dynamics and brain function #Advanced Memory and Neural Computing #Neuroscience and Neural Engineering
paper · pdf · doi:10.48550/arxiv.1705.07614
Cortical microcircuits are very complex networks, but they are composed of a\nrelatively small number of stereotypical motifs. Hence one strategy for\nthrowing light on the computational function of cortical microcircuits is to\nanalyze emergent computational properties of these stereotypical microcircuit\nmotifs. We are addressing here the question how spike-timing dependent\nplasticity (STDP) shapes the computational properties of one motif that has\nfrequently been studied experimentally: interconnected populations of pyramidal\ncells and parvalbumin-positive inhibitory cells in layer 2/3. Experimental\nstudies suggest that these inhibitory neurons exert some form of divisive\ninhibition on the pyramidal cells. We show that this data-based form of\nfeedback inhibition, which is softer than that of winner-take-all models that\nare commonly considered in theoretical analyses, contributes to the emergence\nof an important computational function through STDP: The capability to\ndisentangle superimposed firing patterns in upstream networks, and to represent\ntheir information content through a sparse assembly code.\n