Spike-timing theory of working memory
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1
The Neurosciences Institute, United States
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2
Brain Corporation, United States
Working memory (WM) is 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 memories. Existing models, however, fail to explain how WM functionality emerges in the brain’s vast memory content. We show that large memory content and WM functionality emerge spontaneously if we take the spike-timing nature of neuronal processing into account. This is in contrast with previously suggested mechanisms of WM, where spike-timing is ignored and the models’ explanatory power is limited to systems having small repertoires of long-term memories represented by, e.g., carefully selected non-overlapping populations of neurons. In our model, memories are represented by extensively overlapping groups of neurons that exhibit stereotypical time-locked spatio-temporal spike-timing patterns, called polychronous patterns. This mechanism, for example, allows for a set of neurons with two distinct patterns of synaptic connections with appropriate axonal conduction delays to form two distinct polychronous neuronal groups (PNGs). In other words, PNGs are defined by distinct sets of synapses, and not by the neurons per se, which allows neurons to take part in multiple PNGs and enables the same set of neurons to generate several different distinct stereotypical precise spatio-temporal spike-timing patterns. PNGs arise spontaneously in simulated realistic cortical spiking networks shaped by spike-timing dependent plasticity (STDP). In our model, these polychronous patterns are the basis for the large memory content, and the activation of a PNG is the underlying currency of information. Activation of PNGs in spiking networks happens spontaneously due to stochastic synaptic noise. These reactivations, however, can be biased by short-term changes in synaptic efficacies, which, in our model, are implemented in the form of short-term STDP, where short-term synaptic changes depend on the conjunction of pre- and post-synaptic activity. Using simulations, we show how such associative synaptic plasticity can select externally cued PNGs into WM by temporarily strengthening the synapses of the selected PNGs: This strengthening increases the spontaneous reactivation frequency of the selected PNGs, resulting in irregular, yet systematically changing elevated firing activity patterns of intra-PNG neurons, consistent with those recorded in vivo during WM tasks. Note that despite the fact that PNGs share neurons amongst each other, activity of one PNG does not spread to the others, therefore, frequent reactivation of a selected PNG does not initiate uncontrollable activity in the network. Hence, our WM mechanism can work in a network with large memory content. Our theory explains the relationship between precise spikes and slowly changing firing rates of neurons engaged in active maintenance of WM, and it points to the connection between WM and perception of elapsed time on the order of seconds. It also predicts that polychronous structures are essential for cognitive functions like WM, and such structures may be the basis for memory replays involving, for example, prefrontal cortex, visual cortex, and hippocampus.
Conference:
Computational and Systems Neuroscience 2010, Salt Lake City, UT, United States, 25 Feb - 2 Mar, 2010.
Presentation Type:
Poster Presentation
Topic:
Poster session III
Citation:
Szatmáry
B and
Izhikevich
E
(2010). Spike-timing theory of working memory.
Front. Neurosci.
Conference Abstract:
Computational and Systems Neuroscience 2010.
doi: 10.3389/conf.fnins.2010.03.00191
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Received:
03 Mar 2010;
Published Online:
03 Mar 2010.
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Correspondence:
Botond Szatmáry, The Neurosciences Institute, San Diego, United States, botond.szatmary@braincorporation.com