Oscillatory neurocomputing with ring attractors: a network architecture for mapping locations in space onto patterns of neural synchrony

Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences
Hugh T BlairJason Cong

Abstract

Theories of neural coding seek to explain how states of the world are mapped onto states of the brain. Here, we compare how an animal's location in space can be encoded by two different kinds of brain states: population vectors stored by patterns of neural firing rates, versus synchronization vectors stored by patterns of synchrony among neural oscillators. It has previously been shown that a population code stored by spatially tuned 'grid cells' can exhibit desirable properties such as high storage capacity and strong fault tolerance; here it is shown that similar properties are attainable with a synchronization code stored by rhythmically bursting 'theta cells' that lack spatial tuning. Simulations of a ring attractor network composed from theta cells suggest how a synchronization code might be implemented using fewer neurons and synapses than a population code with similar storage capacity. It is conjectured that reciprocal connections between grid and theta cells might control phase noise to correct two kinds of errors that can arise in the code: path integration and teleportation errors. Based upon these analyses, it is proposed that a primary function of spatially tuned neurons might be to couple the phases of neural osci...Continue Reading

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Citations

Apr 4, 2014·The Journal of Neuroscience : the Official Journal of the Society for Neuroscience·Daniel Bush, Neil Burgess
May 3, 2014·The Journal of Neuroscience : the Official Journal of the Society for Neuroscience·Christopher P Burgess, Neil Burgess
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Dec 25, 2013·Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences·Tom HartleyJohn O'Keefe
Dec 25, 2013·Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences·Michael E Hasselmo
Mar 20, 2015·Hippocampus·Michael E Hasselmo, Chantal E Stern
Jan 22, 2020·Annual Review of Neuroscience·John B IssaDaniel A Dombeck
Jan 27, 2019·PLoS Computational Biology·Joseph D MonacoKechen Zhang
Feb 18, 2020·Hippocampus·Daniel Bush, Neil Burgess

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