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    A New Hypothesis for Sleep: Tuning for Criticality


    Pearlmutter, Barak A. and Conor J. Houghton, Conor J. (2009) A New Hypothesis for Sleep: Tuning for Criticality. Neural Computation, 21 (6). pp. 1622-1641. ISSN 1530-888X

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    Official URL: http://www.mitpressjournals.org/doi/pdf/10.1162/ne...


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    Abstract

    We propose that the critical function of sleep is to prevent uncontrolled neuronal feedback while allowing rapid responses and prolonged retention of short-term memories. Through learning, the brain is tuned to react optimally to environmental challenges. Optimal behavior often requires rapid responses and the prolonged retention of short-term memories. At a neuronal level, these correspond to recurrent activity in local networks. Unfortunately, when a network exhibits recurrent activity, small changes in the parameters or conditions can lead to runaway oscillations. Thus, the very changes that improve the processing performance of the network can put it at risk of runaway oscillation. To prevent this, stimulus-dependent network changes should be permitted only when there is a margin of safety around the current network parameters. We propose that the essential role of sleep is to establish this margin by exposing the network to a variety of inputs, monitoring for erratic behavior, and adjusting the parameters. When sleep is not possible, an emergency mechanism must come into play, preventing runaway behavior at the expense of processing efficiency. This is tiredness.

    Item Type: Article
    Additional Information: Copyright Notice "©2009 Massachusetts Institute of Technology. Originally publsihed in Neural Computation." The original publication is available at http://www.mitpressjournals.org/doi/pdf/10.1162/neco.2009.05-08-787
    Keywords: New hypothesis for sleep; Sleep deprivation; Cetaceans and unihemispherical sleep; Hamilton Institute sleep.
    Academic Unit: Faculty of Science and Engineering > Biology
    Faculty of Science and Engineering > Computer Science
    Faculty of Science and Engineering > Research Institutes > Hamilton Institute
    Faculty of Science and Engineering > Mathematics and Statistics
    Item ID: 1653
    Identification Number: https://doi.org/10.1162/neco.2009.05-08-787
    Depositing User: Hamilton Editor
    Date Deposited: 10 Nov 2009 11:10
    Journal or Publication Title: Neural Computation
    Publisher: MIT Press
    Refereed: Yes
    URI:
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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