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Contribution to a conference proceedings/Contribution to a book | FZJ-2019-04247 |
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2019
ACM Press New York, New York, USA
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Please use a persistent id in citations: http://hdl.handle.net/2128/24492 doi:10.1145/3354265.3354281
Abstract: Sequence processing has been proposed to be the universal computation performed by the neocortex. The Hierarchical Temporal Memory (HTM) model provides a mechanistic implementation of this form of processing. While the model accounts for a number of neocortical features, it is based on networks of highly abstract neuron and synapse models updated in discrete time. Here, we reformulate the model in terms of a network of spiking neurons with continuous-time dynamics to investigate how neuronal parameters such as cell-intrinsic time constants and synaptic weights constrain the sequence-processing speed.
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