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Division of labor among distinct subtypes of inhibitory neurons in a cortical microcircuit of working memory
Center for Complex Systems, Brandeis University, Waltham, MA 02254, United States.
Linköping University, The Institute of Technology. Linköping University, Department of Physics, Chemistry and Biology, Computational Biology .
Section of Neurobiology, Yale University School of Medicine, 333 Cedar Street, New Haven, CT 06510, United States, Wake Forest Univ. School of Medicine, Dept. of Neurobiology and Anatomy, Winston-Salem, NC 27157-1010, United States.
Section of Neurobiology, Yale University School of Medicine, 333 Cedar Street, New Haven, CT 06510, United States.
2004 (English)In: Proceedings of the National Academy of Sciences of the United States of America, ISSN 0027-8424, E-ISSN 1091-6490, Vol. 101, no 5, p. 1368-1373Article in journal (Refereed) Published
Abstract [en]

A conspicuous feature of cortical organization is the wide diversity of inhibitory interneurons, their differential computational functions remain unclear. Here we propose a local cortical circuit in which three major subtypes of interneurons play distinct roles. In a model designed for spatial working memory, stimulus tuning of persistent activity arises from the concerted action of widespread inhibition mediated by perisoma-targeting (parvalbumin-containing) interneurons and localized disinhibition of pyramidal cells via interneuron-targeting (calretinin-containing) interneurons. Moreover, resistance against distracting stimuli (a fundamental property of working memory) is dynamically controlled by dendrite-targeting (calbindin-containing) interneurons. The experimental observation of inverted tuning curves of monkey prefrontal neurons recorded during working memory supports a key model prediction. This work suggests a framework for understanding the division of labor and cooperation among different inhibitory cell types in a recurrent cortical circuit.

Place, publisher, year, edition, pages
2004. Vol. 101, no 5, p. 1368-1373
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:liu:diva-45823DOI: 10.1073/pnas.0305337101OAI: oai:DiVA.org:liu-45823DiVA, id: diva2:266719
Available from: 2009-10-11 Created: 2009-10-11 Last updated: 2017-12-13

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Tegnér, Jesper

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