Neurocomputational models of time perception

Advances in Experimental Medicine and Biology

Volumn 829, Issue , 2014, Pages 49-71

  Hass, Joachim ^a   Durstewitz, Daniel ^a  

^a UNIVERSITY OF HEIDELBERG   (Germany)

Author keywords

Computational modeling; Ramping activity; Synfire chains; Weber s law

Indexed keywords

AFTER DEPOLARIZING CURRENT; AFTERHYPERPOLARIZATION; ARTIFICIAL NEURAL NETWORK; BIOPHYSICAL MODEL; CONTINGENT NEGATIVE VARIATION; DEPOLARIZATION; DYNAMIC ATTENDING THEORY; ELECTROPHYSIOLOGY; EXCITATORY POSTSYNAPTIC POTENTIAL; FIRING RATE; HUMAN; INFORMATION PROCESSING; INTERMETHOD COMPARISON; LINEAR PSYCHOPHYSICAL LAW; LONG TERM POTENTIATION; MATHEMATICAL MODEL; MODULATION BY NON TEMPORAL FACTOR; NEGATIVE FEEDBACK; NERVE CELL PLASTICITY; OSCILLATION; POSITIVE FEEDBACK; PRIORITY JOURNAL; PSYCHOLOGY; RAMPING ACTIVITY; SCALAR EXPECTANCY THEORY; SCALAR PROPERTY OF TIMING ERRORS; SPECTRAL TIMING; SPIKE; SPIKE TIMING DEPENDENT SYNAPTIC PLASTICITY; STATE SPACE TRAJECTORIES; STOCHASTIC DECAY OF MEMORY TRACE; STRIATAL BEAT MODEL; SYNFIRE CHAINS MODEL; TIME PERCEPTION; ANIMAL; BIOLOGICAL MODEL; MENTAL FUNCTION; NEUROPHYSIOLOGY; PHYSIOLOGY;

ANIMALS; HUMANS; MENTAL PROCESSES; MODELS, NEUROLOGICAL; NEUROPHYSIOLOGY; PSYCHOLOGY; TIME PERCEPTION;

EID: 84925581229     PISSN: 00652598     EISSN: 22148019     Source Type: Book Series    
DOI: 10.1007/978-1-4939-1782-2_4     Document Type: Chapter

References (117)

1. Lewis PA, Miall RC. Distinct systems for automatic and cognitively controlled time measurement: evidence from neuroimaging. Curr Opin Neurobiol. 2003;13:250-5.
2. Wearden JH, Lejeune H. Scalar properties in human timing: conformity and violations. Q J Exp Psychol. 2008;61:569-87.
3. Lejeune H, Wearden JH. Scalar properties in animal timing: conformity and violations. Q J Exp Psychol. 2006;59:1875-908.
4. Eisler H. Experiments on subjective duration 1868-1975: a collection of power function exponents. Psychol Bull. 1976;83(6):1154-71.
5. Grondin S. From physical time to the first and second moments of psychological time. Psychol Bull. 2001;127(1):22-44.
6. Gibbon J. Origins of scalar timing. Learn Motiv. 1991;22:3-38.
7. Gibbon J. Scalar expectancy theory and Weber's law in animal timing. Psychol Rev. 1977;84:279-325.
8. Seung HS, Lee DD, Reis BY, Tank DW. Stability of the memory of eye position in a recurrent network of conductance-based model neurons. Neuron. 2000;26 (1):259-71.
9. Taatgen NA, van Rijn H, Anderson J. An integrated theory of prospective time interval estimation: the role of cognition, attention, and learning. Psychol Rev. 2007;114(3):577.
10. Allan LG. The influence of the scalar timing model on human timing research. Behav Processes. 1998;444:101-17.
11. Creelman CD. Human discrimination of auditory duration. J Acoust Soc Am. 1962;34:582-93.
12. Eagleman D. Human time perception and its illusions. Curr Opin Neurobiol. 2008;18(2):131-6.
13. Buhusi CV, Meck WH. What makes us tick? Functional and neural mechanisms of interval timing. Nat Rev Neurosci. 2005;6:755-65.
14. Durstewitz D. Self-organizing neural integrator predicts interval times through climbing activity. J Neurosci. 2003;23(12):5342-53.
15. Hass J, Blaschke S, Rammsayer T, Herrmann JM. A neurocomputational model for optimal temporal processing. J Comput Neurosci. 2008;25:449-64.
16. Treisman M. Temporal discrimination and the indifference interval: Implications for a model of the "internal clock". Psychol Monogr. 1963;77 (13):1-31.
17. Jones MR. Time, our lost dimension: toward a new theory of perception, attention, and memory. Psychol Rev. 1976;83:323-55.
18. Jones MR, Boltz M. Dynamic attending and responses to time. Psychol Rev. 1989;96(3):459-91.
19. Jones MR. Attending to sound patterns and the role of entrainment. In: Nobre AC, Coull JT, editors. Attention and time. Oxford: Oxford University Press; 2010. p. 137-330.
20. Rumelhart DE McClelland JL. Parallel distributed processing: explorations in the microstructure of cognition. MIT Press; 1987.
21. Fujita M. Adaptive filter model of the cerebellum. Biol Cybern. 1982;45(3):195-206.
22. Desmond JE, Moore JW. Adaptive timing in neural networks: the conditioned response. Biol Cybern. 1988;58(6):405-15.
23. Grossberg S, Schmajuk NA. Neural dynamics of adaptive timing and temporal discrimination during associative learning. Neural Netw. 1989;2:79-102.
24. Carr CE, Konishi M. A circuit for detection of interaural time differences in the brain stem of the barn owl. J Neurosci. 1990;10(10):3227-46.
25. Church RM, Broadbent HA. Alternative representations of time, number, and rate. Cognition. 1990;37(1):55-81.
26. Miall C. The storage of time intervals using oscillating neurons. Neural Comput. 1989;1(3):359-71.
27. Buonomano DV, Mauk MD. Neural network model of the cerebellum: temporal discrimination and the timing of motor responses. Neural Comput. 1994;6 (1):38-55.
28. Buonomano DV, Merzenich MM. Temporal information transformed into a spatial code by a neural network with realistic properties. Science. 1995;267:1028-30.
29. Buonomano DV. Decoding temporal information: a model based on short-term synaptic plasticity. J Neurosci. 2000;20(3):1129-41.
30. Tieu KH, Keidel AL, McGann JP, Faulkner B, Brown TH. Perirhinal-amygdala circuit-level computational model of temporal encoding in fear conditioning. Psychobiology. 1999;27(1):1-25.
31. Matell MS, Meck WH. Cortico-striatal circuits and interval timing: coincidence detection of oscillatory processes. Cogn Brain Res. 2004;21:139-70.
32. Medina JF, Garcia KS, Nores WL, Taylor NM, Mauk MD. Timing mechanisms in the cerebellum: testing predictions of a large-scale computer simulation. J Neurosci. 2000;20(14):5516-25.
33. Yamazaki T, Tanaka S. Neural modeling of an internal clock. Neural Comput. 2006; 17:1032-58.
34. Simen P, Balci F, Cohen JD, Holmes P. A model of interval timing by neural integration. J Neurosci. 2011;31(25):9238-53.
35. Kitano K, Okamoto H, Fukai T. Time representing cortical activities: two models inspired by prefrontal persistent activity. Biol Cybern. 2003;88:387-94.
36. Hass J, Blaschke S, Rammsayer T, Herrmann JM. Detection of irregularities in auditory sequences: a neural-network approach to temporal processing. In: Mayor J, Ruh N, Plunkett K, editors. Proceedings of the NCPW11. World Scientific; 2009. p. 167-78.
37. Mauk MM, Buonomano DV. The neural basis of temporal processing. Annu Rev Neurosci. 2004;27:307-40.
38. Killeen PR, Fetterman JG. A behavioral theory of timing. Psychol Rev. 1988;95:274-95.
39. Staddon JER, Higa JJ. Time and memory: towards a pacemaker-free theory of interval timing. J Exp Anal Behav. 1999;71(2):215-51.
40. Karmarkar UR, Buonomano DV. Timing in the absence of clocks: encoding time in neural network states. Neuron. 2007;53(3):427-38.
41. Rammsayer TH. Neuropharmacological evidence for different timing mechanisms in humans. Q J Exp Psychol. 1999;52:273-86.
42. Meck WH. Affinity for the dopamine D2 receptor predicts neuroleptic potency in decreasing the speed of an internal clock. Pharmacol Biochem Behav. 1986;25:1185-9.
43. Gibbon J, Malapani C, Dale CL, Gallistel CR. Toward a neurobiology of temporal cognition: advances and challenges. Curr Opin Neurobiol. 1997;7:170-84.
44. Bizo LA, Chua JYM, Sanabria F, Killeen PR. The failure of Weber's law in time perception and production. Behav Processes. 2006;71:201-10.
45. Drake C, Botte MC. Tempo sensitivity in auditory sequences: evidence for a multiple-look model. Percept Psychophys. 1993;54(3):277-86.
46. Getty DJ. Counting processes in human timing. Percept Psychophys. 1976;20:191-7.
47. Allan LG. The perception of time. Percept Psychophys. 1979;26(5):340-54.
48. McDonnell MD, Abbott D. What is stochastic resonance? Definitions, misconceptions, debates, and its relevance to biology. PLoS Comput Biol. 2009;5(5): e1000348.
49. Garrett DD, Samanez-Larkin GR, MacDonald SWS, Lindenberger U, McIntosh A, Grady CL. Momentto- moment brain signal variability: a next frontier in human brain mapping? Neurosci Biobehav Rev. 2013;37(4):610-24.
50. Moss F, Ward LM, Sannita WG. Stochastic resonance and sensory information processing: a tutorial and review of applications. Clin Neurophysiol. 2004;115(2):267-81.
51. Durstewitz D, Deco G. Computational significance of transient dynamics in cortical networks. Eur J Neurosci. 2008;27(1):217-27.
52. Paninski L, Pillow JW, Simoncelli EP. Maximum likelihood estimation of a stochastic integrate-andfire neural encoding model. Neural Comput. 2004;16:2533-61.
53. Pouget A, Dayan P, Zemel RS. Inference and computation with population codes. Annu Rev Neurosci. 2003;26:381-410.
54. Hass J, Herrmann JM. The neural representation of time: an information-theoretic perspective. Neural Comput. 2012;24(6):1519-52.
55. Ahrens M, Sahani M. Inferring elapsed time from stochastic neural processes. In: Platt JC, Koller D, Singer Y, Roweis S, editors. NIPS 20. Cambridge: MIT Press; 2008. p. 1-8.
56. Almeida R, Ledberg A. A biologically plausible model of time-scale invariant interval timing. J Comput Neurosci. 2010;28:155-75.
57. Escola S, Eisele M, Miller K, Paninski L. Maximally reliable Markov chains under energy constraints. Neural Comput. 2009;21(7):1863-912.
58. Shapiro JL, Wearden J. Reinforcement learning and time perception - a model of animal experiments. In: Dietterich TG, Becker S, Ghahramani Z, editors. NIPS 14. Cambridge: MIT Press. p. 115-22.
59. Okamoto H, Fukai T. Neural mechanism for a cognitive timer. Phys Rev Lett. 2001;86(17):3919-22.
60. Reutimann J, Yakovlev V, Fusi S, Senn W. Climbing neuronal activity as an event-based cortical representation of time. J Neurosci. 2004;24(13):3295-303.
61. Durstewitz D. Neural representation of interval time. Neuroreport. 2004;15:745-9.
62. Lebedev MA, O'Doherty JE, Nicolelis MAL. Decoding of temporal intervals from cortical ensemble activity. J Neurophysiol. 2008;99:166-86.
63. Roux S, Coulmance M, Riehle A. Context-related representation of timing processes in monkey motor cortex. Eur J Neurosci. 2003;18:1011-6.
64. Leon MI, Shadlen MN. Representation of time by neurons in the posterior parietal cortex of the macaque. Neuron. 2003;38:317-27.
65. Mita A, Mushiake H, Shima K, Matsuzaka Y, Tanji J. Interval time coding by neurons in the presupplementary and supplementary motor areas. Nat Neurosci. 2009;12(4):502-7.
66. Niki H, Watanabe M. Prefrontal and cingulate unit activity during timing behavior in the monkey. Brain Res. 1979;171(2):213-24.
67. Brody C, Hernandez A, Zainos A, Romo R. Timing and neural encoding of somatosensory parametric working memory in macaque prefrontal cortex. Cereb Cortex. 2003;13(11):1196-207.
68. Rainer G, Rao CS, Miller EK. Prospective coding for objects in primate prefrontal cortex. J Neurosci. 1999;19(13):5493-505.
69. Quintana J, Fuster JM. From perception to action: temporal integrative functions of prefrontal and parietal neurons. Cereb Cortex. 1999;9(3):213-21.
70. Komura Y, Tamura R, Uwano T, Nishijo H, Kaga K, Ono T, et al. Retrospective and prospective coding for predicted reward in the sensory thalamus. Nature. 2001;412(6846):546-8.
71. Andrade R. Cell excitation enhances muscarinic cholinergic responses in rat association cortex. Brain Res. 1991;548(1):81-93.
72. Haj-Dahmane S, Andrade R. Muscarinic receptors regulate two different calcium-dependent nonselective cation currents in rat prefrontal cortex. Eur J Neurosci. 1999;11(6):1973-80.
73. Helmchen F, Imoto K, Sakmann B. Ca2+ buffering and action potential-evoked Ca2+ signal. Biophys J. 1996;70(2):1069-81.
74. Wang XJ. Synaptic reverberation underlying mnemonic persistent activity. Trends Neurosci. 2001;24 (8):455-63.
75. Machens CK, Romo R, Brody CD. Flexible control of mutual inhibition: a neural model of two-interval discrimination. Science. 2005;307(5712):1121-4.
76. Markram H, Lübke J, Frotscher M, Sakmann B. Regulation of synaptic efficacy by coincidence of postsynaptic APs and EPSPs. Science. 1997;275 (5297):213-5.
77. Bi GQ, Poo MM. Synaptic modification by correlated activity: Hebb's postulate revisited. Annu Rev Neurosci. 2001;24(1):139-66.
78. Hebb DO. The organization of behavior: a neuropsychological theory. New York: Wiley; 1949.
79. Buzsáki G, Draguhn A. Neuronal oscillations in cortical networks. Science. 2004;304(5679):1926-9.
80. Macar F, Vidal F, Casini L. The supplementary motor area in motor and sensory timing: evidence from slow brain potential changes. Exp Brain Res. 1999;125(3):271-80.
81. Macar F, Vidal F. Event-related potentials as indices of time processing: a review. J Psychophysiol. 2004;18:89-104.
82. Meck WH, Penney TB, Pouthas V. Cortico-striatal representation of time in animals and humans. Curr Opin Neurobiol. 2008;18:145-52.
83. Bal T, McCormick DA. Mechanisms of oscillatory activity in guinea-pig nucleus reticularis thalami in vitro: a mammalian pacemaker. J Physiol. 1993;468(1):669-91.
84. Egorov AV, Hamam BN, Fransén E, Hasselmo ME, Alonso AA. Graded persistent activity in entorhinal cortex neurons. Nature. 2002;420(6912): 173-8.
85. Fransén E, Tahvildari B, Egorov AV, Hasselmo ME, Alonso AA. Mechanism of graded persistent cellular activity of entorhinal cortex layer v neurons. Neuron. 2006;49(5):735-46.
86. Hass J, Farkhooi F, Durstewitz D. Dopaminergic modulation of time perception. Front Comput Neurosci. Conference Abstract: Bernstein Conference on Computational Neuroscience; 2010.
87. Buonomano DV. A learning rule for the emergence of stable dynamics and timing in recurrent networks. J Neurophysiol. 2005;94:2275-83.
88. Killeen PR, Taylor T. How the propagation of error through stochastic counters affects time discrimination and other psychophysical judgments. Psychol Rev. 2000;107:430-59.
89. Abeles M. Corticonics: neural circuits of the cerebral cortex. Cambridge: Cambridge University Press; 1991.
90. Herrmann JM, Hertz JA, Prügel-Bennet A. Analysis of synfire chains. Network Comput Neural. 1995;6:403-14.
91. Diesmann M, Gewaltig MO, Aertsen A. Stable propagation of synchronous spiking in cortical neural networks. Nature. 1999;402:529-33.
92. Riehle A, Grün S, Diesmann M, Aertsen A. Spike synchronization and rate modulation differentially involved in motor cortical function. Science. 1997;278(5345):1950-3.
93. Bienenstock E. A model of neocortex. Network Comput Neural. 1995;6:179-224.
94. Abeles M. Synfire chains. Scholarpedia. 2009;4 (7):1441.
95. Abeles M, Gat I. Detecting precise firing sequences in experimental data. J Neurosci Methods. 2001;107:141-54.
96. Grün S. Data-driven significance estimation for precise spike correlation. J Neurophysiol. 2009;101:1126-40.
97. Beggs J, Plenz D. Neuronal avalanches in neocortical circuits. J Neurosci. 2003;23:11167-77.
98. Izhikevich EM. Polychronization: computation with spikes. Neural Comput. 2006;18(2):245-82.
99. McLelland D, Paulsen O. Cortical songs revisited: a lesson in statistics. Neuron. 2007;53(3):413-25.
100. Yumoto N, Lu X, Henry TR, Miyachi S, Nambu A, Fukai T, et al. A neural correlate of the processing of multi-second time intervals in primate prefrontal cortex. PLoS One. 2011;6(4):e19168.
101. Matell MS, Shea-Brown E, Gooch C, Wilson AG, Rinzel J. A heterogeneous population code for elapsed time in rat medial agranular cortex. Behav Neurosci. 2011;125(1):54.
102. Jin DZ, Fujii N, Graybiel AM. Neural representation of time in cortico-basal ganglia circuits. Proc Natl Acad Sci U S A. 2009;106(45):19156-61.
103. Genovesio A, Tsujimoto S, Wise SP. Neuronal activity related to elapsed time in prefrontal cortex. J Neurophysiol. 2006;95:3281-5.
104. Matell MS, Meck WH, Nicolelis MAL. Interval timing and the encoding of signal duration by ensembles of cortical and striatal neurons. Behav Neurosci. 2003;117(4):760-73.
105. Maass W, Natschläger T, Markram H. Real-time computing without stable states: a new framework for neural computation based on perturbations. Neural Comput. 2002;14(11):2531-60.
106. Hyman JM, Ma L, Balaguer-Ballester E, Durstewitz D, Seamans JK. Contextual encoding by ensembles of medial prefrontal cortex neurons. Proc Natl Acad Sci U S A. 2012;109(13):5086-91.
107. BuzsákiG, da Silva FL. High frequency oscillations in the intact brain. Prog Neurobiol. 2012;98(3):241-9.
108. Klimesch W, Sauseng P, Hanslmayr S. EEG alpha oscillations: the inhibition-timing hypothesis. Brain Res Rev. 2007;53(1):63-88.
109. Steriade M. Grouping of brain rhythms in corticothalamic systems. Neuroscience. 2006;137 (4):1087-106.
110. Grondin S. Timing and time perception: a review of recent behavioral and neuroscience findings and theoretical directions. Atten Percept Psychophys. 2010;72(3):561-82.
111. Barnes R, Jones MR. Expectancy, attention, and time. Cogn Psychol. 2000;41(3):254-311.
112. Oprisan SA, Buhusi CV. Modeling pharmacological clock and memory patterns of interval timing in a striatal beat-frequency model with realistic, noisy neurons. Front Integr Neurosci. 2011;5:52.
113. Grossberg S. Adaptive resonance theory: how a brain learns to consciously attend, learn, and recognize a changing world. Neural Netw. 2012;37:1-47.
114. Hass J, Blaschke S, Herrmann JM. Cross-modal distortion of time perception: demerging the effects of observed and performed motion. PLoS One. 2012;7 (6):e38092.
115. Jazayeri M, Shadlen MN. Temporal context calibrates interval timing. Nat Neurosci. 2010;13 (8):1020-6.
116. Ley I, Haggard P, Yarrow K. Optimal integration of auditory and vibrotactile information for judgments of temporal order. J Exp Psychol Hum Percept Perform. 2009;35(4):1005.
117. Burr D, Banks MS, Morrone MC. Auditory dominance over vision in the perception of interval duration. Exp Brain Res. 2009;198(1):49-57.