Theory of sequence memory in neocortex (Hawkins & Ahmad 2016)


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Accession:190610
"... First we show that a neuron with several thousand synapses segregated on active dendrites can recognize hundreds of independent patterns of cellular activity even in the presence of large amounts of noise and pattern variation. We then propose a neuron model where patterns detected on proximal dendrites lead to action potentials, defining the classic receptive field of the neuron, and patterns detected on basal and apical dendrites act as predictions by slightly depolarizing the neuron without generating an action potential. By this mechanism, a neuron can predict its activation in hundreds of independent contexts. We then present a network model based on neurons with these properties that learns time-based sequences. ..."
Reference:
1 . Hawkins J, Ahmad S (2016) Why Neurons Have Thousands of Synapses, a Theory of Sequence Memory in Neocortex. Front Neural Circuits 10:23 [PubMed]
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Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell; Realistic Network;
Brain Region(s)/Organism: Neocortex;
Cell Type(s): Neocortex V1 pyramidal intratelencephalic L2-5 cell; Neocortex V1 pyramidal corticothalamic L6 cell; Neocortex layer 4 pyramidal cell; Neocortex spiny stellate cell;
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Simulation Environment: Python (web link to model);
Model Concept(s): Action Potentials; Active Dendrites; Simplified Models;
Implementer(s): Ahmad, Subutai [sahmad at numenta.com];
Search NeuronDB for information about:  Neocortex V1 pyramidal corticothalamic L6 cell; Neocortex V1 pyramidal intratelencephalic L2-5 cell;
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