Synchronization and fractal scaling as foundations for cognitive control

Abstract This article investigates the degree to which the intrinsic propensity for entrainment in oscillatory systems serves as a plausible foundation for understanding the assembly and flexibility of cognitive systems. Three experiments tested for the strength of performance entrainment to oscillations inserted into event timing and stimulus properties of cognitive tasks. In the first temporal estimation experiment, attractor strength analyses revealed participants spontaneously entrained to sinusoidal changes in the duration of inter-trial intervals. A second simple reaction time task introduced oscillatory changes to the inter-stimulus interval durations across trials, and attractor strength analyses revealed weaker but reliable entrainment to the input signals. A third dyadic temporal estimation task revealed oscillatory entrainment that was distributed across pairs of participants. The experimental results were evaluated in terms of coupled oscillator dynamics and short-term perceptual lags. The entrainment hypothesis was most successful in explaining the empirical patterns, suggesting that cognitive performance relies on coordinative activity. Together, the three studies demonstrated coordinative activity over a range of temporal scales and distributed across individuals comprising the dyads. The simple reaction time study illustrated within-trial coordinative dynamics; individual temporal estimation illustrated across-trial coordination, and dyadic temporal estimation illustrated person-to-person coordinative dynamics. The findings underscore the role environmental constraints impose on cognitive activity and demonstrate how seemingly disparate features of distinct cognitive tasks can be assimilated in terms of synchronization principles.

[1]  John G Holden,et al.  Fractal 1/ƒ dynamics suggest entanglement of measurement and human performance. , 2011, Journal of experimental psychology. Human perception and performance.

[2]  G. V. van Orden,et al.  Dispersion of response times reveals cognitive dynamics. , 2009, Psychological review.

[3]  Didier Delignières,et al.  Complexity matching in side-by-side walking. , 2017, Human movement science.

[4]  E. Wagenmakers,et al.  Theories and models for 1/f(beta) noise in human movement science. , 2009, Human movement science.

[5]  Fred Hasselman,et al.  1/f scaling in movement time changes with practice in precision aiming. , 2009, Nonlinear dynamics, psychology, and life sciences.

[6]  W. Tschacher,et al.  The dynamical systems approach to cognition : concepts and empirical paradigms based on self-organization, embodiment, and coordination dynamics , 2003 .

[7]  D. Gilden Cognitive emissions of 1/f noise. , 2001, Psychological review.

[8]  J. Kelso,et al.  The Metastable Brain , 2014, Neuron.

[9]  G. Orden,et al.  LIVING IN THE PINK: INTENTIONALITY, WELLBEING, AND COMPLEXITY , 2011 .

[10]  Didier Delignières,et al.  Multifractal signatures of complexity matching , 2016, Experimental Brain Research.

[11]  Sebastian Wallot,et al.  The Blue-Collar Brain , 2012, Front. Physio..

[12]  Simon Grondin,et al.  Overloading temporal memory. , 2005, Journal of experimental psychology. Human perception and performance.

[13]  David L. Gilden,et al.  Global Model Analysis of Cognitive Variability , 2009, Cogn. Sci..

[14]  R. Ratcliff,et al.  Estimation and interpretation of 1/fα noise in human cognition , 2004 .

[15]  S. Matsumoto,et al.  Synchronization and scaling of relaxationally coupled integrate-and-fire oscillators , 2003 .

[16]  R. Church,et al.  Alternative representations of time, number, and rate , 1990, Cognition.

[17]  R. F. A. Cox,et al.  A Trade-Off Study Revealing Nested Timescales of Constraint , 2012, Front. Physio..

[18]  J. Kelso,et al.  Cortical coordination dynamics and cognition , 2001, Trends in Cognitive Sciences.

[19]  Eugene M. Izhikevich,et al.  Dynamical Systems in Neuroscience: The Geometry of Excitability and Bursting , 2006 .

[20]  G. V. van Orden,et al.  Human cognition and 1/f scaling. , 2005, Journal of experimental psychology. General.

[21]  Michael J. Richardson,et al.  Measuring group synchrony: a cluster-phase method for analyzing multivariate movement time-series , 2012, Front. Physio..

[22]  William H. Press,et al.  The Art of Scientific Computing Second Edition , 1998 .

[23]  T. Järvilehto,et al.  The theory of the organism-environment system: I. Description of the theory , 1998, Integrative physiological and behavioral science : the official journal of the Pavlovian Society.

[24]  Derek H. Arnold,et al.  Spatially Localized Distortions of Event Time , 2006, Current Biology.

[25]  Manuel Varlet,et al.  Predicting the biological variability of environmental rhythms: Weak or strong anticipation for sensorimotor synchronization? , 2013, Brain and Cognition.

[26]  A. Opstal Dynamic Patterns: The Self-Organization of Brain and Behavior , 1995 .

[27]  C. Torrence,et al.  A Practical Guide to Wavelet Analysis. , 1998 .

[28]  H. Haken,et al.  A theoretical model of phase transitions in human hand movements , 2004, Biological Cybernetics.

[29]  Linda B. Smith,et al.  A Dynamic Systems Approach to the Development of Cognition and Action , 2007, Journal of Cognitive Neuroscience.

[30]  Shi Kai,et al.  Self-Organized Criticality: Emergent Complex Behavior in PM , 2015 .

[31]  D. Lewkowicz,et al.  A dynamic systems approach to the development of cognition and action. , 2007, Journal of cognitive neuroscience.

[32]  R. Gibbs Embodiment and Cognitive Science: Concepts , 2005 .

[33]  C. Miniussi,et al.  The Functional Importance of Rhythmic Activity in the Brain , 2012, Current Biology.

[34]  Christopher T. Kello,et al.  Complexity matching in dyadic conversation. , 2014, Journal of experimental psychology. General.

[35]  Michael T. Turvey,et al.  On strong anticipation , 2010, Cognitive Systems Research.

[36]  Michael T. Turvey,et al.  Frequency detuning of the phase entrainment dynamics of visually coupled rhythmic movements , 1995, Biological Cybernetics.

[37]  M. J. Amon Examining Coordination and Emergence During Individual and Distributed Cognitive Tasks , 2016 .

[38]  A. Winfree The geometry of biological time , 1991 .

[39]  P. N. Kugler,et al.  Information, Natural Law, and the Self-Assembly of Rhythmic Movement , 2015 .

[40]  R. Knight,et al.  Oscillatory Dynamics of Prefrontal Cognitive Control , 2016, Trends in Cognitive Sciences.

[41]  Steven H. Strogatz,et al.  Sync: The Emerging Science of Spontaneous Order , 2003 .

[42]  Mikhail Belkin,et al.  The Geometry and Dynamics of Lifelogs: Discovering the Organizational Principles of Human Experience , 2014, PloS one.

[43]  Isidoros Doxas,et al.  The Episodic Nature of Experience: A Dynamical Systems Analysis , 2017, Cogn. Sci..

[44]  Henry D. I. Abarbanel,et al.  Analysis of Observed Chaotic Data , 1995 .

[45]  H. Haken,et al.  A stochastic theory of phase transitions in human hand movement , 1986, Biological Cybernetics.

[46]  Michael T. Turvey,et al.  Strong anticipation: Sensitivity to long-range correlations in synchronization behavior , 2008 .

[47]  Michael J Richardson,et al.  Fractal coordination in adults' attention to hierarchical visual patterns. , 2015, Nonlinear dynamics, psychology, and life sciences.

[48]  Rolf Weitkunat,et al.  Interval timing routines for the IBM PC/XT/AT microcomputer family , 1987 .

[49]  G. V. van Orden,et al.  Situated Behavior and the Place of Measurement in Psychological Theory , 2010 .

[50]  R. Duncan Luce,et al.  Response Times: Their Role in Inferring Elementary Mental Organization , 1986 .

[51]  O. Sporns Networks of the Brain , 2010 .

[52]  Fred Hasselman,et al.  Classifying acoustic signals into phoneme categories: average and dyslexic readers make use of complex dynamical patterns and multifractal scaling properties of the speech signal , 2014, PeerJ.

[53]  Christopher T. Kello,et al.  Scaling laws in cognitive sciences , 2010, Trends in Cognitive Sciences.

[54]  G. Buzsáki,et al.  Neuronal Oscillations in Cortical Networks , 2004, Science.

[55]  A. Giuliani,et al.  Detecting deterministic signals in exceptionally noisy environments using cross-recurrence quantification , 1998 .

[56]  M. Turvey Action and perception at the level of synergies. , 2007, Human movement science.

[57]  S. Grondin Timing and time perception: A review of recent behavioral and neuroscience findings and theoretical directions , 2010, Attention, perception & psychophysics.

[58]  Adam W. Kiefer,et al.  Walking changes the dynamics of cognitive estimates of time intervals. , 2009, Journal of experimental psychology. Human perception and performance.

[59]  Michael T. Turvey,et al.  Concurrent Cognitive Task Modulates Coordination Dynamics , 2005, Cogn. Sci..

[60]  John M. Flach,et al.  Control Theory for Humans: Quantitative Approaches To Modeling Performance , 2002 .

[61]  A. Kristofferson,et al.  Response delays and the timing of discrete motor responses , 1973 .

[62]  Schreiber,et al.  Improved Surrogate Data for Nonlinearity Tests. , 1996, Physical review letters.

[63]  G. V. van Orden,et al.  Self-organization of cognitive performance. , 2003, Journal of experimental psychology. General.

[64]  Lawrence M. Ward,et al.  Dynamical Cognitive Science , 2001 .

[65]  G. Buzsáki Rhythms of the brain , 2006 .

[66]  Scott W. Brown,et al.  Attentional processes in time perception: effects of mental workload and event structure. , 2002, Journal of experimental psychology. Human perception and performance.

[67]  Michael J. Spivey,et al.  Spectral convergence in tapping and physiological fluctuations: coupling and independence of 1/f noise in the central and autonomic nervous systems , 2014, Front. Hum. Neurosci..

[68]  Maarten L. Wijnants,et al.  A Review of Theoretical Perspectives in Cognitive Science on the Presence of Scaling in Coordinated Physiological and Cognitive Processes , 2014 .

[69]  Mary Jean Amon,et al.  Fractal Scaling and Implicit Bias: A Conceptual Replication of Correll (2008) , 2016, CogSci.

[70]  Michael J. Richardson,et al.  Distinguishing the noise and attractor strength of coordinated limb movements using recurrence analysis , 2007, Biological Cybernetics.

[71]  Christopher T. Kello,et al.  The emergent coordination of cognitive function. , 2007, Journal of experimental psychology. General.

[72]  L. Glass Synchronization and rhythmic processes in physiology , 2001, Nature.

[73]  G. Schöner Timing, Clocks, and Dynamical Systems , 2002, Brain and Cognition.

[74]  Michael J. Spivey,et al.  The Continuity Of Mind , 2008 .

[75]  P. Fries Rhythms for Cognition: Communication through Coherence , 2015, Neuron.

[76]  J. Flach Control With an Eye for Perception: Precursors to an Active Psychophysics , 1990 .

[77]  Ramesh Balasubramaniam,et al.  Trajectory Formation in Timed Repetitive Movements , 2006 .

[78]  D L Gilden,et al.  1/f noise in human cognition. , 1995, Science.

[79]  G. Ermentrout Dynamic patterns: The self-organization of brain and behavior , 1997 .

[80]  Bruce J. West,et al.  Maximizing information exchange between complex networks , 2008 .

[81]  James L. McClelland,et al.  Enlarging the scope: grasping brain complexity , 2013, Front. Syst. Neurosci..

[82]  John G. Holden,et al.  The Self-Organization of a Spoken Word , 2012, Front. Psychology.

[83]  Damian G. Stephen,et al.  The role of fractality in perceptual learning: exploration in dynamic touch. , 2010, Journal of experimental psychology. Human perception and performance.

[84]  Dirk Vorberg,et al.  Linear phase-correction in synchronization: predictions, parameter estimation, and simulations , 2002 .

[85]  J. Holden,et al.  Dynamics of cognition. , 2012, Wiley interdisciplinary reviews. Cognitive science.

[86]  O. Sporns Discovering the Human Connectome , 2012 .

[87]  R. Ratcliff,et al.  Human cognition and a pile of sand: a discussion on serial correlations and self-organized criticality. , 2005, Journal of experimental psychology. General.

[88]  D. Delignières,et al.  Strong anticipation: complexity matching in interpersonal coordination , 2012, Experimental Brain Research.