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Graded persistent activity in entorhinal cortex neurons
KTH, Superseded Departments, Numerical Analysis and Computer Science, NADA.ORCID iD: 0000-0003-0281-9450
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2002 (English)In: Nature, ISSN 0028-0836, Vol. 420, no 6912, 173-178 p.Article in journal (Refereed) Published
Abstract [en]

Working memory represents the ability of the brain to hold externally or internally driven information for relatively short periods of time(1,2). Persistent neuronal activity is the elementary process underlying working memory but its cellular basis remains unknown. The most widely accepted hypothesis is that persistent activity is based on synaptic reverberations in recurrent circuits. The entorhinal cortex in the parahippocampal region is crucially involved in the acquisition, consolidation and retrieval of long-term memory traces for which working memory operations are essential(2). Here we show that individual neurons from layer V of the entorhinal cortex-which link the hippocampus to extensive cortical regions(3)-respond to consecutive stimuli with graded changes in firing frequency that remain stable after each stimulus presentation. In addition, the sustained levels of firing frequency can be either increased or decreased in an input-specific manner. This firing behaviour displays robustness to distractors; it is linked to cholinergic muscarinic receptor activation, and relies on activity-dependent changes of a Ca2+-sensitive cationic current. Such an intrinsic neuronal ability to generate graded persistent activity constitutes an elementary mechanism for working memory.

Place, publisher, year, edition, pages
2002. Vol. 420, no 6912, 173-178 p.
Keyword [en]
working-memory, parahippocampal region, cortical afferents, hippocampal, rat, connections, responses, channels, network, monkey
National Category
Neurosciences Bioinformatics (Computational Biology)
URN: urn:nbn:se:kth:diva-22041DOI: 10.1038/nature01171ISI: 000179200900045PubMedID: 12432392OAI: diva2:340739
QC 20100525 QC 20111229Available from: 2010-08-10 Created: 2010-08-10 Last updated: 2011-12-29Bibliographically approved

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Fransén, Erik
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Numerical Analysis and Computer Science, NADA
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