1/f noise in human cognition: Is it ubiquitous, and what does it mean?

Farrell, Simon; Wagenmakers, Eric‐Jan; Ratcliff, Roger

doi:10.3758/bf03193989

Cited by 80 publications

(78 citation statements)

References 26 publications

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“…When the optimal strategy in a task is to provide a series of independent and identically distributed responses, people often perform sub-optimally. Long-range autocorrelations have been observed, where responses depend on earlier events that occurred quite a long time previously (e.g., Gilden, 2001; Thornton & Gilden, 2005;Van Orden, Holden, & Turvey, 2003, although not all authors agree on the meaning of the phenomena (e.g., Farrell, Wagenmakers, & Ratcliff, 2006;Wagenmakers, Farrell, & Ratcliff, 2004. The same criticism applies to dynamical systems research as to the Gambler's Fallacy-tasks requiring long sequences of stationary and conditionally random responses have questionable ecological validity.…”

Section: Introductionmentioning

confidence: 90%

Detecting and predicting changes

Brown

Steyvers

2009

Cognitive Psychology

108

127

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Section: Introductionmentioning

confidence: 90%

Detecting and predicting changes

Brown

Steyvers

2009

Cognitive Psychology

108

127

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“…1 The serial dependence is ubiquitous in human cognitive performance and has been suggested to reflect an internal representational structure within the cognitive system (Farrell, Wagenmakers, & Ratcliff, 2006;Gilden, Thornton, & Mallon, 1995). In particular, this self-dependency in RT implies that there is an association between the memory state of the previous and current stimulus (Verstynen et al, 2012).…”

Section: Discussionmentioning

confidence: 99%

New insights into statistical learning and chunk learning in implicit sequence acquisition

Clark

2016

Psychon Bull Rev

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Implicit sequence learning is ubiquitous in our daily life. However, it is unclear whether the initial acquisition of sequences results from learning to chunk items (i.e., chunk learning) or learning the underlying statistical regularities (i.e., statistical learning). By grouping responses with or without a distinct chunk or statistical structure into segments and comparing these responses, previous studies have demonstrated both chunk and statistical learning. However, few studies have considered the response sequence as a whole and examined the temporal dependency of the entire sequence, where the temporal dependencies could disclose the internal representations of chunk and statistical learning. Participants performed a serial reaction time (SRT) task under different stimulus interval conditions. We found that sequence learning reflected by reaction time (RT) rather than motor improvements represented by movement time (MT). The temporal dependency of RT and MT revealed that both RT and MT displayed recursive patterns caused by biomechanical effects of response locations and foot transitions. Chunking was noticeable only in the presence of the recurring RT or MT but vanished after the recursive component was removed, implying that chunk formation may result from biomechanical constraints rather than learning itself. In addition, we observed notable first-order autocorrelations in RT. This trial-to-trial association enhanced as learning progressed regardless of stimulus intervals, reflecting the internal cognitive representation of the first-order stimulus contingencies. Our results suggest that initial acquisition of implicit sequences may arise from first-order statistical learning rather than chunk learning.

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“…98,102,103 The bulk of that initial skepticism was answered, however. 44,104 The empirical patterns held up to rigorous statistical scrutiny, and fractal scaling, in one form or another, has emerged as the most representative and most likely description of the empirical reports.…”

Section: Advanced Reviewmentioning

confidence: 99%

Dynamics of cognition

Riley

Holden

2012

WIRES Cognitive Science

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The application of dynamical systems methods and concepts to cognitive phenomena has broadened the range of testable hypotheses and theoretical narratives available to cognitive scientists. Most research in cognitive dynamics tests the degree to which observed cognitive performance is consistent with one or another core phenomena associated with complex dynamical systems, such as tests for phase transitions, coupling among processes, or scaling laws. Early applications of dynamical systems theory to perceptual-motor performance and developmental psychology paved the way for more recent applications of dynamical systems analyses, models, and theoretical concepts in areas such as learning, memory, speech perception, decision making, problem solving, and reading, among others. Reviews of the empirical results of both foundational and contemporary cognitive dynamics are provided. © 2012 John Wiley & Sons, Ltd. How to cite this article:WIREs Cogn Sci 2012, 3:593-606. doi: 10.1002/wcs.1200 INTRODUCTION Adynamical system is simply one that changes over time (see Box 1). It is apparent that many of the processes cognitive scientists study-development, learning, the spread of activation in a semantic network, changing patterns of cortical activity, motor behavior, and so on-are intrinsically dynamical. Dynamical systems theory supplies new tools and concepts for understanding these and other cognitive phenomena. The theory offers a full complement of analytical methods (e.g., nonlinear time series analyses) and modeling strategies (e.g., differential equations). Most importantly, it motivates novel theoretical and empirical questions: One may explore the relative stability of a cognitive activity, test for meta-or multi-stability, or test for empirical patterns consistent with scaling behavior, emergence, and self-organization.These kinds of questions complement those posed by mainstream cognitive science-which traditionally has emphasized static properties of mind such as symbolic representations or structural mechanisms of information processing-by focusing explicitly on change 1-9 (see, e.g., Elman 10 for a dynamical interpretation of connectionist models). Much work in cognitive dynamics was inspired by parallel * Correspondence to: michael.riley@uc.edu Center for Cognition, Action, & Perception, Department of Psychology, University of Cincinnati, Cincinnati, OH, USA efforts to understand the dynamics of perceptionaction. [11][12][13][14][15] Early and significant progress emerged in the domain of motor coordination, where the behavioral phenomena were more obviously dynamical and high-resolution measurement technologies were more readily available. 16 The dynamical account of interlimb rhythmic coordination 12,14 is an example of an early success.Research in cognitive dynamics is often allied with some version of embodiment. [17][18][19][20][21] Dynamical systems were sometimes framed as replacements for computational-representational accounts, 8,19 as distinct but complementary, 22 or even as consistent with inform...

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1/f noise in human cognition: Is it ubiquitous, and what does it mean?

Abstract: Researchers in psychology are paying increasing attention to temporal correlations in performance on cognitive tasks. Recently, Thornton and Gilden (2005)

Cited by 80 publications

References 26 publications

Detecting and predicting changes

Detecting and predicting changes

New insights into statistical learning and chunk learning in implicit sequence acquisition

Dynamics of cognition

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