A New Hypothesis for Sleep: Tuning for Criticality

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.

[1]  Jerome M. Siegel The incredible, shrinking sleep-learning connection , 2005 .

[2]  S. L. Lima,et al.  A phylogenetic analysis of the correlates of sleep in birds , 2006, Journal of sleep research.

[3]  Matthew P Walker,et al.  A refined model of sleep and the time course of memory formation. , 2005, The Behavioral and brain sciences.

[4]  T. Sejnowski,et al.  Why do we sleep? , 2000, Brain research.

[5]  G. Vogel,et al.  An alternative view of the neurobiology of dreaming. , 1978, The American journal of psychiatry.

[6]  N. Kleitman,et al.  Regularly occurring periods of eye motility, and concomitant phenomena, during sleep. , 1953, Science.

[7]  Terrence J. Sejnowski,et al.  Interactive reportWhy do we sleep?1 , 2000 .

[8]  E Greenfield,et al.  Mutual information in a dilute, asymmetric neural network model. , 2001, Physical review. E, Statistical, nonlinear, and soft matter physics.

[10]  Daniel Margoliash,et al.  Mammalian-like features of sleep structure in zebra finches , 2008, Proceedings of the National Academy of Sciences.

[11]  Dante R. Chialvo Critical brain networks , 2004 .

[12]  C. E. Ho,et al.  A procedure for an automated measurement of song similarity , 2000, Animal Behaviour.

[13]  A. M. Turing,et al.  Computing Machinery and Intelligence , 1950, The Philosophy of Artificial Intelligence.

[14]  G. Tononi,et al.  Extensive and Divergent Effects of Sleep and Wakefulness on Brain Gene Expression , 2004, Neuron.

[15]  Anna Wirz-Justice,et al.  Sleep deprivation in depression: what do we know, where do we go? , 1999, Biological Psychiatry.

[16]  Geoffrey E. Hinton,et al.  A Learning Algorithm for Boltzmann Machines , 1985, Cogn. Sci..

[17]  A. Destexhe,et al.  Are corticothalamic ‘up’ states fragments of wakefulness? , 2007, Trends in Neurosciences.

[18]  G. Tononi,et al.  Breakdown of Cortical Effective Connectivity During Sleep , 2005, Science.

[19]  J. Passchier,et al.  Interictal and Postictal Cognitive Changes in Migraine , 1999, Cephalalgia : an international journal of headache.

[20]  J. J. Hopfield,et al.  ‘Unlearning’ has a stabilizing effect in collective memories , 1983, Nature.

[21]  Geoffrey E. Hinton,et al.  The Helmholtz Machine , 1995, Neural Computation.

[22]  Anton M.L. Coenen Where is the classic interference theory for sleep and memory , 2005 .

[23]  G. Tononi,et al.  Differential Expression of Plasticity-Related Genes in Waking and Sleep and Their Regulation by the Noradrenergic System , 2000, The Journal of Neuroscience.

[24]  W. Fishbein,et al.  Paradoxical sleep and memory (I): Selective alterations following enriched and impoverished environmental rearing , 1980, Brain Research Bulletin.

[25]  R. Feynman Forces in Molecules , 1939 .

[26]  R. Stickgold,et al.  Practice with Sleep Makes Perfect Sleep-Dependent Motor Skill Learning , 2002, Neuron.

[27]  S. Murphy Brain and Intelligence in Vertebrates, Euan M. MacPhail. Oxford University Press, Oxford (1982), viii, +423. Price £20.00 hardback, £10.95 paperback , 1983 .

[28]  Hans Lüders,et al.  Epilepsy and Sleep: Physiological and Clinical Relationships , 2011 .

[29]  Dennis L. Murphy,et al.  REM sleep suppression induced by selective monoamine oxidase inhibitors , 2004, Psychopharmacology.

[30]  Geoffrey E. Hinton,et al.  Varieties of Helmholtz Machine , 1996, Neural Networks.

[31]  P Maquet,et al.  The Role of Sleep in Learning and Memory , 2001, Science.

[32]  L. Mukhametov Sleep in Marine Mammals , 1984 .

[33]  Nils Bertschinger,et al.  Real-Time Computation at the Edge of Chaos in Recurrent Neural Networks , 2004, Neural Computation.

[34]  Geoffrey E. Hinton Deterministic Boltzmann Learning Performs Steepest Descent in Weight-Space , 1989, Neural Computation.

[35]  Lyamin,et al.  Rest and activity states in a gray whale , 2000, Journal of sleep research.

[36]  J J Hopfield,et al.  What is a moment? Transient synchrony as a collective mechanism for spatiotemporal integration. , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[37]  Jürgen Schmidhuber,et al.  Long Short-Term Memory , 1997, Neural Computation.

[38]  A. M. Turing,et al.  Computing Machinery and Intelligence , 1950, The Philosophy of Artificial Intelligence.

[39]  B. Scharf,et al.  Localized pontine 1esion , 1984, Neurology.

[40]  G. Tononi,et al.  Sleep function and synaptic homeostasis. , 2006, Sleep medicine reviews.

[41]  R. Vertes,et al.  The case against memory consolidation in REM sleep. , 2000, The Behavioral and brain sciences.

[42]  Luís B. Almeida,et al.  A learning rule for asynchronous perceptrons with feedback in a combinatorial environment , 1990 .

[43]  L. Abbott,et al.  Cortical Development and Remapping through Spike Timing-Dependent Plasticity , 2001, Neuron.

[44]  G. Roth,et al.  Evolution of the brain and intelligence , 2005, Trends in Cognitive Sciences.

[45]  T. Sejnowski Neural Networks: Sleep and memory , 1995, Current Biology.

[46]  Geoffrey E. Hinton,et al.  The "wake-sleep" algorithm for unsupervised neural networks. , 1995, Science.

[47]  B Reisberg,et al.  First results on the effects of MAO inhibition on cognitive functioning in elderly depressed patients. , 1983, Archives of gerontology and geriatrics.

[48]  P. Mitra,et al.  How sleep affects the developmental learning of bird song , 2005, Nature.

[49]  Jerome M. Siegel,et al.  Do all animals sleep? , 2008, Trends in Neurosciences.

[50]  John M. Beggs,et al.  Neuronal Avalanches in Neocortical Circuits , 2003, The Journal of Neuroscience.

[51]  J. Born,et al.  Sleep forms memory for finger skills , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[52]  Stanley,et al.  Self-organized branching processes: Mean-field theory for avalanches. , 1995, Physical review letters.

[53]  L. Abbott,et al.  A simple growth model constructs critical avalanche networks. , 2007, Progress in brain research.

[54]  A. Gallup,et al.  Yawning as a Brain Cooling Mechanism: Nasal Breathing and Forehead Cooling Diminish the Incidence of Contagious Yawning , 2007 .

[55]  I Oswald,et al.  The effects of distorted visual input on sleep. , 1972, Psychophysiology.

[56]  A Meier-Koll,et al.  A biological oscillator system and the development of sleep-waking behavior during early infancy. , 1978, Chronobiologia.

[57]  Henry Markram,et al.  Real-Time Computing Without Stable States: A New Framework for Neural Computation Based on Perturbations , 2002, Neural Computation.

[58]  A. V. Ooyen,et al.  Activity-dependent outgrowth of neurons and overshoot phenomena in developing neural networks , 1994 .

[59]  Terrence J. Sejnowski,et al.  What is consolidated during sleep-dependent motor skill learning? , 2005 .

[60]  John M. Beggs,et al.  Neuronal Avalanches Are Diverse and Precise Activity Patterns That Are Stable for Many Hours in Cortical Slice Cultures , 2004, The Journal of Neuroscience.

[61]  Michael I. Jordan Attractor dynamics and parallelism in a connectionist sequential machine , 1990 .

[62]  Barak A. Pearlmutter Gradient calculations for dynamic recurrent neural networks: a survey , 1995, IEEE Trans. Neural Networks.

[63]  Amir F. Atiya,et al.  A Method for the Associative Storage of Analog Vectors , 1989, NIPS.

[64]  C. Koch,et al.  Constraints on cortical and thalamic projections: the no-strong-loops hypothesis , 1998, Nature.

[65]  M. Brazier,et al.  Brain mechanisms in memory and learning : from the single neuron to man , 1979 .

[66]  C. Elger,et al.  CAN EPILEPTIC SEIZURES BE PREDICTED? EVIDENCE FROM NONLINEAR TIME SERIES ANALYSIS OF BRAIN ELECTRICAL ACTIVITY , 1998 .

[67]  Pineda,et al.  Generalization of back-propagation to recurrent neural networks. , 1987, Physical review letters.

[68]  J. Siegel,et al.  Time for the sleep community to take a critical look at the purported role of sleep in memory processing. , 2005, Sleep.

[69]  T. Sejnowski,et al.  Sleep and Memory , 2022 .

[70]  E Hartmann,et al.  When is more or less sleep required? A study of variable sleepers. , 1976, Comprehensive psychiatry.

[71]  Patrice Y. Simard,et al.  Shaping the State Space Landscape in Recurrent Networks , 1990, NIPS.

[72]  David J. Foster,et al.  Reverse replay of behavioural sequences in hippocampal place cells during the awake state , 2006, Nature.

[73]  Francis Crick,et al.  The function of dream sleep , 1983, Nature.

[74]  J J ROSS,et al.  NEUROLOGICAL FINDINGS AFTER PROLONGED SLEEP DEPRIVATION. , 1965, Archives of neurology.

[75]  M. Silber,et al.  Epilepsy and Sleep: Physiological and Clinical Relationships , 2002 .

[76]  Jürgen-Christian Krieg,et al.  Sleep deprivation in depression , 2010, Expert review of neurotherapeutics.

[77]  W. Fishbein,et al.  Paradoxical sleep and memory storage processes. , 1977, Behavioral biology.

[78]  B. Ekstrand,et al.  Sleep and Memory , 1973, Science.

[79]  S. Renals,et al.  A study of network dynamics , 1990 .

[80]  K. Kaufman,et al.  Modafinil augmentation of antidepressant treatment in depression. , 2000, The Journal of clinical psychiatry.

[81]  Harald Haas,et al.  Harnessing Nonlinearity: Predicting Chaotic Systems and Saving Energy in Wireless Communication , 2004, Science.

[82]  C. Smith Sleep states and memory processes in humans: procedural versus declarative memory systems. , 2001, Sleep medicine reviews.

[83]  J. A. Horne,et al.  The consolidation hypothesis for REM sleep function: Stress and other confounding factors — A review , 1984, Biological Psychology.