Feedback Inhibition Shapes Emergent Computational Properties of Cortical Microcircuit Motifs

Zeno Jonke, Robert Legenstein, Stefan Habenschuss, Wolfgang Maass

Research output: Contribution to journalArticleResearchpeer-review

Abstract

Cortical microcircuits are very complex networks, but they are composed of a relatively small number of stereotypical motifs. Hence, one strategy for throwing light on the computational function of cortical microcircuits is to analyze emergent computational properties of these stereotypical microcircuit motifs. We are addressing here the question how spike timing-dependent plasticity shapes the computational properties of one motif that has frequently been studied experimentally: interconnected populations of pyramidal cells and parvalbumin-positive inhibitory cells in layer 2/3. Experimental studies suggest that these inhibitory neurons exert some form of divisive inhibition on the pyramidal cells. We show that this data-based form of feedback inhibition, which is softer than that of winner-take-all models that are commonly considered in theoretical analyses, contributes to the emergence of an important computational function
through spike timing-dependent plasticity: The capability to disentangle superimposed firing patterns in upstream networks, and to represent their information content through a sparse assembly code.
Original languageEnglish
Pages (from-to)8511– 8523
Number of pages24
JournalThe journal of neuroscience
Volume37
Issue number35
DOIs
Publication statusPublished - 30 Aug 2017

Keywords

  • computational function
  • cortical microcircuits
  • divisive inhibition
  • feedback inhibition
  • synaptic plasticity
  • winner-take-all

Fields of Expertise

  • Information, Communication & Computing

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