Wake-sleep transition as a noisy bifurcation

被引:13
|
作者
Yang, Dong-Ping [1 ,2 ]
McKenzie-Sell, Lauren [1 ]
Karanjai, Angela [1 ]
Robinson, P. A. [1 ,2 ]
机构
[1] Univ Sydney, Sch Phys, Sydney, NSW 2006, Australia
[2] Univ Sydney, Ctr Integrat Brain Funct, Sydney, NSW 2006, Australia
基金
澳大利亚研究理事会;
关键词
ASCENDING AROUSAL SYSTEM; MATHEMATICAL-MODELS; QUANTITATIVE MODEL; SLOWING-DOWN; DEPRIVATION; WAKEFULNESS; PRECURSOR; NETWORKS; DYNAMICS; FATIGUE;
D O I
10.1103/PhysRevE.94.022412
中图分类号
O35 [流体力学]; O53 [等离子体物理学];
学科分类号
070204 ; 080103 ; 080704 ;
摘要
A recent physiologically based model of the ascending arousal system is used to analyze the dynamics near the transition from wake to sleep, which corresponds to a saddle-node bifurcation at a critical point. A normal form is derived by approximating the dynamics by those of a particle in a parabolic potential well with dissipation. This mechanical analog is used to calculate the power spectrum of fluctuations in response to a white noise drive, and the scalings of fluctuation variance and spectral width are derived versus distance from the critical point. The predicted scalings are quantitatively confirmed by numerical simulations, which show that the variance increases and the spectrum undergoes critical slowing, both in accord with theory. These signals can thus serve as potential precursors to indicate imminent wake-sleep transition, with potential application to safety-critical occupations in transport, air-traffic control, medicine, and heavy industry.
引用
收藏
页数:10
相关论文
共 50 条
  • [1] The Wake-Sleep 'Phase Transition' at the Gate to Consciousness
    Hepp, K.
    JOURNAL OF STATISTICAL PHYSICS, 2018, 172 (02) : 562 - 568
  • [2] Differences of ERPs during the wake-sleep transition
    Ganten, P
    Basar-Eroglu, C
    Miener, M
    Struber, D
    Stadler, M
    JOURNAL OF PSYCHOPHYSIOLOGY, 1998, 12 (01) : 102 - 102
  • [3] Wake-sleep PCA
    Choi, Seungjin
    2007 IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-6, 2007, : 2431 - 2434
  • [4] Convergence of the Wake-Sleep algorithm
    Ikeda, S
    Amari, S
    Nakahara, H
    ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 11, 1999, 11 : 239 - 245
  • [5] Wake-sleep circuitry: an overview
    Saper, Clifford B.
    Fuller, Patrick M.
    CURRENT OPINION IN NEUROBIOLOGY, 2017, 44 : 186 - 192
  • [6] Wake-Sleep Consolidated Learning
    Sorrenti, Amelia
    Bellitto, Giovanni
    Salanitri, Federica Proietto
    Pennisi, Matteo
    Palazzo, Simone
    Spampinato, Concetto
    IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2024,
  • [7] A NONINVASIVE ECG RECORDING IN INTACT MICE DURING SLEEP AND WAKE-SLEEP TRANSITION
    Sato, S.
    Kanbayashi, T.
    Imanishi, A.
    Tsutsui, K.
    Shimizu, T.
    SLEEP, 2017, 40 : A41 - A41
  • [8] A measure of ventilatory variability at wake-sleep transition predicts sleep apnea severity
    Ibrahim, Lamia H.
    Patel, Sanjay R.
    Modarres, Mohammad
    Johnson, Nathan L.
    Mehra, Reena
    Kirchner, H. Lester
    Redline, Susan
    CHEST, 2008, 134 (01) : 73 - 78
  • [9] Natural Reweighted Wake-Sleep
    Varady, Csongor
    Volpi, Riccardo
    Malago, Luigi
    Ay, Nihat
    NEURAL NETWORKS, 2022, 155 : 574 - 591
  • [10] Dynamic detection of wake-sleep transition with reaction time-magnitude
    Gao, Chuang
    Chen, Bin
    Wei, Wei
    NEURAL REGENERATION RESEARCH, 2009, 4 (07) : 552 - 560