Timescale invariance in the pacemaker-accumulator family of timing models

Pacemaker-accumulator (PA) systems have been the most popular kind of timing model in the half-century since their introduction by Treisman (1963). Many alternative timing models have been designed predicated on different assumptions, though the dominant PA model during this period — Gibbon and Church’s Scalar Expectancy Theory (SET) — invokes most of them. As in Treisman, SET’s implementation assumes a fixed-rate clock-pulse generator and encodes durations by storing average pulse counts; unlike Treisman’s model, SET’s decision process invokes Weber’s law of magnitude-comparison to account for timescale-invariant temporal precision in animal behavior. This is one way to deal with the ‘Poisson timing’ issue, in which relative temporal precision increases for longer durations, contrafactually, in a simplified version of Treisman’s model. First, we review the fact that this problem does not afflict Treisman’s model itself due to a key assumption not shared by SET. Second, we develop a contrasting PA model, an extension of Killeen and Fetterman’s Behavioral Theory of Timing that accumulates Poisson pulses up to a fixed criterion level, with pulse rates adapting to time different intervals. Like Treisman’s model, this time-adaptive, opponent Poisson, drift–diffusion model accounts for timescale invariance without first assuming Weber’s law. It also makes new predictions about response times and learning speed and connects interval timing to the popular drift–diffusion model of perceptual decision making. With at least three different routes to timescale invariance, the PA model family can provide a more compelling account of timed behavior than may be generally appreciated.

[1]  A. Einstein Über die von der molekularkinetischen Theorie der Wärme geforderte Bewegung von in ruhenden Flüssigkeiten suspendierten Teilchen [AdP 17, 549 (1905)] , 2005, Annalen der Physik.

[2]  J. Wolfowitz,et al.  Optimum Character of the Sequential Probability Ratio Test , 1948 .

[3]  William Feller,et al.  An Introduction to Probability Theory and Its Applications , 1951 .

[4]  M. Stone Models for choice-reaction time , 1960 .

[5]  M. Treisman Temporal discrimination and the indifference interval. Implications for a model of the "internal clock". , 1963, Psychological monographs.

[6]  M TREISMAN,et al.  NOISE AND WEBER'S LAW: THE DISCRIMINATION OF BRIGHTNESS AND OTHER DIMENSIONS. , 1964, Psychological review.

[7]  Micheal Treisman,et al.  A statistical decision model for sensory discrimination which predicts Weber’s law and other sensory laws: Some results of a computer simulation , 1966 .

[8]  Donald Laming,et al.  Information theory of choice-reaction times , 1968 .

[9]  R. Church,et al.  Bisection of temporal intervals. , 1977, Journal of experimental psychology. Animal behavior processes.

[10]  J. Gibbon Scalar expectancy theory and Weber's law in animal timing. , 1977 .

[11]  Roger Ratcliff,et al.  A Theory of Memory Retrieval. , 1978 .

[12]  S. Roberts,et al.  Isolation of an internal clock. , 1981, Journal of experimental psychology. Animal behavior processes.

[13]  M. Treisman Temporal Rhythms and Cerebral Rhythms a , 1984, Annals of the New York Academy of Sciences.

[14]  R M Church,et al.  Scalar Timing in Memory , 1984, Annals of the New York Academy of Sciences.

[15]  R. Ratcliff Theoretical interpretations of the speed and accuracy of positive and negative responses. , 1985, Psychological review.

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

[17]  P R Killeen,et al.  Optimal timing and the Weber function. , 1987, Psychological review.

[18]  P. Killeen,et al.  A behavioral theory of timing. , 1988, Psychological review.

[19]  J. Leroy Folks,et al.  The Inverse Gaussian Distribution: Theory: Methodology, and Applications , 1988 .

[20]  Stephen Grossberg,et al.  Neural dynamics of adaptive timing and temporal discrimination during associative learning , 1989, Neural Networks.

[21]  Christopher Miall,et al.  The Storage of Time Intervals Using Oscillating Neurons , 1989, Neural Computation.

[22]  M. Treisman,et al.  The Internal Clock: Evidence for a Temporal Oscillator Underlying Time Perception with Some Estimates of its Characteristic Frequency , 1990, Perception.

[23]  R. Church,et al.  Representation of time , 1990, Cognition.

[24]  J. Gibbon,et al.  Human bisection at the geometric mean , 1991 .

[25]  John Gibbon,et al.  Ubiquity of scalar timing with Poisson clock , 1992 .

[26]  M. Treisman,et al.  The Internal Clock: Electroencephalographic Evidence for Oscillatory Processes Underlying Time Perception , 1994, The Quarterly journal of experimental psychology. A, Human experimental psychology.

[27]  R. Church,et al.  Application of scalar timing theory to individual trials. , 1994, Journal of experimental psychology. Animal behavior processes.

[28]  John E. R. Staddon,et al.  MULTIPLE TIME SCALES IN SIMPLE HABITUATION , 1996 .

[29]  W. Meck Neuropharmacology of timing and time perception. , 1996, Brain research. Cognitive brain research.

[30]  H S Seung,et al.  How the brain keeps the eyes still. , 1996, Proceedings of the National Academy of Sciences of the United States of America.

[31]  A. Machado Learning the temporal dynamics of behavior. , 1997, Psychological review.

[32]  Lewis A. Bizo,et al.  Time's causes , 1997 .

[33]  C. Gallistel,et al.  Toward a neurobiology of temporal cognition: advances and challenges , 1997, Current Opinion in Neurobiology.

[34]  Lewis A. Bizo,et al.  Chapter 3 Time's causes , 1997 .

[35]  B W Connors,et al.  Layer‐Specific Pathways for the Horizontal Propagation of Epileptiform Discharges in Neocortex , 1998, Epilepsia.

[36]  Jeffrey N. Rouder,et al.  Modeling Response Times for Two-Choice Decisions , 1998 .

[37]  R. Church,et al.  Temporal search as a function of the variability of interfood intervals. , 1998, Journal of experimental psychology. Animal behavior processes.

[38]  The choose-short effect and trace models of timing. , 1999, Journal of the experimental analysis of behavior.

[39]  J. Staddon,et al.  Time and memory: towards a pacemaker-free theory of interval timing. , 1999, Journal of the experimental analysis of behavior.

[40]  Jeffrey N. Rouder,et al.  A diffusion model account of masking in two-choice letter identification. , 2000, Journal of experimental psychology. Human perception and performance.

[41]  C. Gallistel,et al.  Time, rate, and conditioning. , 2000, Psychological review.

[42]  Desmond J. Higham,et al.  An Algorithmic Introduction to Numerical Simulation of Stochastic Differential Equations , 2001, SIAM Rev..

[43]  James L. McClelland,et al.  The time course of perceptual choice: the leaky, competing accumulator model. , 2001, Psychological review.

[44]  J H Wearden,et al.  Scalar timing without reference memory? Episodic temporal generalization and bisection in humans , 2001, The Quarterly journal of experimental psychology. B, Comparative and physiological psychology.

[45]  J. Staddon,et al.  A tuned-trace theory of interval-timing dynamics. , 2002, Journal of the experimental analysis of behavior.

[46]  Xiao-Jing Wang,et al.  Probabilistic Decision Making by Slow Reverberation in Cortical Circuits , 2002, Neuron.

[47]  R. Ratcliff,et al.  A comparison of macaque behavior and superior colliculus neuronal activity to predictions from models of two-choice decisions. , 2003, Journal of neurophysiology.

[48]  F. Tuerlinckx The efficient computation of the cumulative distribution and probability density functions in the diffusion model , 2004, Behavior research methods, instruments, & computers : a journal of the Psychonomic Society, Inc.

[49]  Philip L. Smith,et al.  Psychology and neurobiology of simple decisions , 2004, Trends in Neurosciences.

[50]  W. Meck,et al.  Cortico-striatal circuits and interval timing: coincidence detection of oscillatory processes. , 2004, Brain research. Cognitive brain research.

[51]  C. Gallistel,et al.  Sources of variability and systematic error in mouse timing behavior. , 2004, Journal of experimental psychology. Animal behavior processes.

[52]  W. Meck Neuroanatomical localization of an internal clock: A functional link between mesolimbic, nigrostriatal, and mesocortical dopaminergic systems , 2006, Brain Research.

[53]  Werner Ehm,et al.  The dual klepsydra model of internal time representation and time reproduction. , 2006, Journal of theoretical biology.

[54]  A Neurocomputational Model of Impaired Imitation , 2006 .

[55]  Josey Y. M. Chu,et al.  The failure of Weber's law in time perception and production , 2006, Behavioural Processes.

[56]  J. Gold,et al.  The neural basis of decision making. , 2007, Annual review of neuroscience.

[57]  U. Karmarkar,et al.  Timing in the Absence of Clocks: Encoding Time in Neural Network States , 2007, Neuron.

[58]  R. Church,et al.  A modular theory of learning and performance , 2007, Psychonomic bulletin & review.

[59]  Joachim Haß,et al.  A neurocomputational model for optimal temporal processing , 2008, Journal of Computational Neuroscience.

[60]  Richard S. Sutton,et al.  Stimulus Representation and the Timing of Reward-Prediction Errors in Models of the Dopamine System , 2008, Neural Computation.

[61]  Scott D. Brown,et al.  The simplest complete model of choice response time: Linear ballistic accumulation , 2008, Cognitive Psychology.

[62]  J. Staddon,et al.  The behavioral economics of choice and interval timing. , 2009, Psychological review.

[63]  Rita Almeida,et al.  A biologically plausible model of time-scale invariant interval timing , 2009, Journal of Computational Neuroscience.

[64]  C. Gallistel,et al.  Acquisition of peak responding: What is learned? , 2009, Behavioural Processes.

[65]  Roger Ratcliff,et al.  Perceptual discrimination in static and dynamic noise: the temporal relation between perceptual encoding and decision making. , 2010, Journal of experimental psychology. General.

[66]  C. Gallistel,et al.  Time and Associative Learning. , 2010, Comparative cognition & behavior reviews.

[67]  Jonathan D. Cohen,et al.  A Model of Interval Timing by Neural Integration , 2011, The Journal of Neuroscience.

[68]  Jonathan D. Cohen,et al.  Interval Timing by Long-Range Temporal Integration , 2011, Front. Integr. Neurosci..

[69]  M. Sahani,et al.  Observers Exploit Stochastic Models of Sensory Change to Help Judge the Passage of Time , 2011, Current Biology.

[70]  Jonathan D. Cohen,et al.  Optimal Temporal Risk Assessment , 2011, Front. Integr. Neurosci..

[71]  Martin Wiener,et al.  Temporal Discrimination of Sub- and Suprasecond Time Intervals: A Voxel-Based Lesion Mapping Analysis , 2011, Front. Integr. Neurosci..

[72]  Guan-Yu Chen,et al.  Three-Dimensional Reconstruction of Brain-wide Wiring Networks in Drosophila at Single-Cell Resolution , 2011, Current Biology.

[73]  Yoshua Bengio,et al.  Adaptive Drift-Diffusion Process to Learn Time Intervals , 2011, 1103.2382.

[74]  Marc W. Howard,et al.  A Scale-Invariant Internal Representation of Time , 2012, Neural Computation.

[75]  Peter R. Killeen,et al.  Absent without leave; a neuroenergetic theory of mind wandering , 2013, Front. Psychol..

[76]  Andre Luzardo,et al.  An adaptive drift-diffusion model of interval timing dynamics , 2013, Behavioural Processes.

[77]  H. Terrace,et al.  Sources of Variance in an Information Processing Theory of Timing , 2014 .

[78]  J. Staddon The New Behaviorism , 2021, The New Behaviorism.