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Spike-Timing Theory of Working Memory

Overview of attention for article published in PLoS Computational Biology, August 2010
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Title
Spike-Timing Theory of Working Memory
Published in
PLoS Computational Biology, August 2010
DOI 10.1371/journal.pcbi.1000879
Pubmed ID
Authors

Botond Szatmáry, Eugene M. Izhikevich

Abstract

Working memory (WM) is the part of the brain's memory system that provides temporary storage and manipulation of information necessary for cognition. Although WM has limited capacity at any given time, it has vast memory content in the sense that it acts on the brain's nearly infinite repertoire of lifetime long-term memories. Using simulations, we show that large memory content and WM functionality emerge spontaneously if we take the spike-timing nature of neuronal processing into account. Here, memories are represented by extensively overlapping groups of neurons that exhibit stereotypical time-locked spatiotemporal spike-timing patterns, called polychronous patterns; and synapses forming such polychronous neuronal groups (PNGs) are subject to associative synaptic plasticity in the form of both long-term and short-term spike-timing dependent plasticity. While long-term potentiation is essential in PNG formation, we show how short-term plasticity can temporarily strengthen the synapses of selected PNGs and lead to an increase in the spontaneous reactivation rate of these PNGs. This increased reactivation rate, consistent with in vivo recordings during WM tasks, results in high interspike interval variability and irregular, yet systematically changing, elevated firing rate profiles within the neurons of the selected PNGs. Additionally, our theory explains the relationship between such slowly changing firing rates and precisely timed spikes, and it reveals a novel relationship between WM and the perception of time on the order of seconds.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 468 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 20 4%
Germany 14 3%
United Kingdom 9 2%
Switzerland 5 1%
Brazil 4 <1%
Japan 4 <1%
Netherlands 3 <1%
France 3 <1%
Canada 3 <1%
Other 21 4%
Unknown 382 82%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 129 28%
Researcher 109 23%
Student > Master 72 15%
Professor > Associate Professor 23 5%
Professor 20 4%
Other 74 16%
Unknown 41 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 98 21%
Computer Science 84 18%
Neuroscience 57 12%
Engineering 56 12%
Physics and Astronomy 41 9%
Other 79 17%
Unknown 53 11%