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A Cortical Attractor Network with Martinotti Cells Driven by Facilitating Synapses
KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
2012 (English)In: PLoS ONE, ISSN 1932-6203, Vol. 7, no 4, e30752- p.Article in journal (Refereed) Published
Abstract [en]

The population of pyramidal cells significantly outnumbers the inhibitory interneurons in the neocortex, while at the same time the diversity of interneuron types is much more pronounced. One acknowledged key role of inhibition is to control the rate and patterning of pyramidal cell firing via negative feedback, but most likely the diversity of inhibitory pathways is matched by a corresponding diversity of functional roles. An important distinguishing feature of cortical interneurons is the variability of the short-term plasticity properties of synapses received from pyramidal cells. The Martinotti cell type has recently come under scrutiny due to the distinctly facilitating nature of the synapses they receive from pyramidal cells. This distinguishes these neurons from basket cells and other inhibitory interneurons typically targeted by depressing synapses. A key aspect of the work reported here has been to pinpoint the role of this variability. We first set out to reproduce quantitatively based on in vitro data the di-synaptic inhibitory microcircuit connecting two pyramidal cells via one or a few Martinotti cells. In a second step, we embedded this microcircuit in a previously developed attractor memory network model of neocortical layers 2/3. This model network demonstrated that basket cells with their characteristic depressing synapses are the first to discharge when the network enters an attractor state and that Martinotti cells respond with a delay, thereby shifting the excitation-inhibition balance and acting to terminate the attractor state. A parameter sensitivity analysis suggested that Martinotti cells might, in fact, play a dominant role in setting the attractor dwell time and thus cortical speed of processing, with cellular adaptation and synaptic depression having a less prominent role than previously thought.

Place, publisher, year, edition, pages
2012. Vol. 7, no 4, e30752- p.
Keyword [en]
adaptation, article, artificial neural network, cell activation, cell function, cell interaction, cell type, controlled study, long term depression, Martinotti cell, mathematical model, nerve cell inhibition, nerve cell membrane potential, nerve cell plasticity, nerve cell stimulation, postsynaptic inhibition, presynaptic inhibition, pyramidal nerve cell, spike wave, synaptic efficacy
National Category
Bioinformatics (Computational Biology)
URN: urn:nbn:se:kth:diva-98613DOI: 10.1371/journal.pone.0030752ISI: 000305345000002ScopusID: 2-s2.0-84859820450OAI: diva2:537987
Swedish Research Council, VR-621-2004-3807EU, European Research Council, FP6-2004-IST-FETPI-015879Swedish e‐Science Research Center

QC 20120628

Available from: 2012-06-28 Created: 2012-06-28 Last updated: 2013-04-08Bibliographically approved

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Krishnamurthy, PradeepLansner, Anders
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