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Neuroimaging of interval timing
Cognitive Brain Research 21 (2004) 133 – 137 www.elsevier.com/locate/cogbrainres
Editorial
Neuroimaging of interval timing
Abstract Exactly how the brain is able to measure the durations of events lasting from seconds to minutes while maintaining time-scale invariance remains largely a mystery. Neuroimaging studies are only now beginning to unravel the nature of interval timing and reveal whether different timing mechanisms are required for the perception and production of sub- and supra-second intervals that can be defined by different stimulus modalities. We here review the impact that neuroimaging studies have had on the field of timing and time perception and outline the major challenges that remain to be addressed before a physiologically realistic theory of interval timing can be established involving cortico-striatal circuits. D 2004 Elsevier B.V. All rights reserved. Theme: Neural Basis of Behavior Topic: Cognition Keywords: Timing; Time perception; Cerebral cortex; Basal ganglia; Caudate; Putamen; Cerebellum; fMRI
1. Introduction to special issue on the dneuroimaging of interval timingT Interval-timing studies using modern neuroimaging techniques such as positron emission tomography (PET), eventrelated functional magnetic resonance imaging (fMRI), electroencephalography (EEG) with its associated eventrelated potentials (ERP), and magnetoencephalography (MEG) have produced a variety of intriguing, but sometimes conflicting results [4,6,13,22–24,48,49,51]. Many studies have focused on motor timing, making it difficult to identify whether activation in systems traditionally associated with motor control, such as the basal ganglia and cerebellum, relates to more cognitively oriented domains of interval timing [19–21,32,49]. A few studies that used PET specifically examined time perception [19,21,35]. Unfortunately, the time scale of PET scanning is limited to blockedtrial designs that cannot disentangle processing associated with encoding an interval from processing associated with decision making and implementing a response. More recent studies using fMRI in humans and ensemble recording techniques in animals have provided clear evidence for the interdependency of cortical and sub-cortical structures such as the basal ganglia in timing and time perception [5,8,14,16,18,37,38,40,41,43,44,54,55,57, 58,60,61]. A common feature of many of these neuroimaging studies is the explicit attempt to dissect the contribution of 0926-6410/$ - see front matter D 2004 Elsevier B.V. All rights reserved. doi:10.1016/j.cogbrainres.2004.07.010
different timing components (e.g., clock, memory, and decision stages) as described by Gibbon et al. [11]. For example, by employing an innovative experimental design, Coull et al. [5] were able to isolate a functional anatomical network for perceptual (non-motor) timing in which linear increases in task performance were accompanied by corresponding increases in brain activity. The study made use of dynamically changing visual stimulus attributes (e.g., color and duration) that could be differentially attended to by the participants. Increasing attentional allocation to the temporal integration of stimulus duration selectively increased activity in a cortico-striatal network that included the pre-supplementary motor area, the right frontal operculum, and the right putamen. Conversely, increasing attention to the integration of the temporal variation in the color of the stimulus (rather than its duration) selectively increased activity in visual area V4. Thus, by parametrically increasing the attentional demands of the psychophysical task these researchers were able to identify the neural substrates of time and color perception. In another influential study, the within-trial evolution of interval timing was examined by Rao et al. [55] who reported that activation in the basal ganglia (right putamen and caudate) occurred early in the trial, and was uniquely associated with encoding time intervals, whereas cerebellar activation unfolded later, suggesting an involvement of processes other than explicit timing. Early cortical activation
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associated with encoding of time intervals was observed in the right inferior parietal cortex and bilateral premotor cortex, implicating these systems in attention and temporary maintenance of intervals. Later activation in the right dorsolateral prefrontal cortex emerged during comparison of time intervals. The authors claim their results illustrate a dynamic network of cortical–subcortical activation associated with different components of temporal information processing. However, there are several potential shortcomings concerning this study. First, the dynamics of brain activation patterns were studied for rather short delay periods (up to 4 s). Clearly, these delay periods should be extended to directly distinguish brain systems involved in encoding and short- and/or long-term maintenance of time intervals. Moreover, besides basal ganglia activation being observed early on in the course of temporal integration, multiple brain structures (including the basal ganglia) were equally activated during later stages suggesting that no clear conclusion could be made on the sole basis of the subtraction techniques used to identify activated areas. Nonetheless, the aforementioned studies constitute seminal contributions to the field of interval-timing research and demonstrate the important role that emerging neuroimaging technologies can play in dissecting cognitive functions of the normal and diseased brain. In a number of these neuroimaging studies, striatal activation has been strongly associated with the encoding of time intervals [5,8,14, 24,44,55]. These findings corroborate studies in Parkinson’s disease (PD) showing that dopaminergic treatment improves both motor timing [44–47] and time perception [33]. Pharmacological challenges in humans and other animals also indicate that dopaminergic antagonists and agonists, respectively, slow down and speed up interval-timing processes [2,27,39,41,53]. Contrary to one proposal [7,17,22,53], these and other studies show that the basal ganglia are involved in timing a wide range of intervals, from hundreds of milliseconds (e.g., 300 ms) to tens of seconds (e.g., 20 s) or longer ([12,15]—see also Ref. [32]). Consistent with these fMRI results is the recent discovery of the dopaminergic influence on both encoding and retrieval of temporal memories in PD [34,31,33], processes otherwise separable in their functional and neural correlates [12,28,36,54,55]. Collectively, these results implicate basal ganglia circuitry as well as dopaminergic neurotransmission within striatal and/or cortical sites in timing and time perception that affect cognitive functions as diverse as attention, counting, language, learning, and memory [1,2,9,25,28, 27,41,46,50]. The papers included in this special issue of Cognitive Brain Research are aimed at extending our current state of knowledge concerning the neuroanatomy of interval timing by addressing key questions that remain unanswered [29]. Do perception and production timing tasks activate similar brain areas in the same individual? What are the effects, if any, of timing across a wide range of durations, i.e., are different neural mechanisms involved in
the timing of short (ms to s) and long (min to h) durations? To what extent is interval timing modality specific and dependent upon attentional time sharing? Does the type of feedback and delay between learning and retrieval affect temporal processing? Are analog counting and timing subserved by the same type of integration mechanism? How does timing develop in the infant brain? Is there evidence for chronotopy in the basal ganglia or cortex? How is the scalar property (i.e., time-scale invariance) of interval timing implemented by the relevant neural substrates? Does differential brain activation within or across striatal–corticocerebellar circuits (in location, extent, or intensity) account for the observation of age-specific timing errors? Answers to all of these questions are still required to clarify the nature of the time-sense that distinguishes the intact brain from the diseased brain.
Fig. 1. Group data obtained from a fMRI experiment in which the time course of the hemodynamic response associated with the participant’s active production of a btimedQ response at either 11 or 17 s after signal onset (top panel) was compared with a passive, buntimedQ response triggered by a stimulus presentation at either 11 or 17 s after signal onset (bottom panel). The data have been normalized and replotted on a relative time scale after being adjusted for the obtained peaks (T*) in the hemodynamic response. See Hinton [14] for additional procedural details.
Editorial
2. Illustrations of the scalar property of interval timing using fMRI The scalar property is one of the major hallmarks of interval timing and reflects the observation that the variability associated with the precision of the binternal clockQ grows in proportion to the length of the interval being timed [3,11,30]. Multiplicative sources of variance (in either the clock or memory) contribute to time scale invariance where time is like a brubberbandQ that can be stretched to accommodate the relative signal durations experienced in any particular situation [10]. Consequently, it is important to determine which brain areas serve as scalar timekeepers and exhibit anticipation of the time of occurrence of future events [12]. In a pioneering fMRI study using a peak-interval timing procedure with 7- and 11-s signal durations, Hinton [14] reported that the putamen was the only brain region in which the time course of the hemodynamic response associated with interval timing preceded the activation due to a motor-control condition. This pattern of activation reflected anticipation of the response rather than its immediate preparation or execution. Other brain regions (e.g., primary motor cortex and supplementary motor area) did not exhibit differential activation between the interval-timing and the motor-control conditions. Furthermore, these brain regions showed much greater activation in the hemisphere contra-lateral to the hand used to make the simple reaction-time response. In contrast, the right putamen was more active than the left putamen under all timing conditions regardless of the hand used. This is a rather surprising result and lends considerable support to the finding of lateralization of interval timing to the right putamen [8]. When the normalized percent change in the hemodynamic response is plotted as a function of time since signal onset on a relative time scale the activation associated with producing a response at 11 or 17 s should superimpose if that brain region is directly involved in the timekeeping process. In contrast, if the hemodynamic response displays a constant (rather than a multiplicative) source of variability then the 17-s response function should be considerably sharper than the 11-s response function when plotted on a relative time scale. Each of these outcomes is illustrated in Fig. 1 which displays the type of interval-timing and motorcontrol data reported by Hinton [14]. The fMRI data have been normalized and replotted on a relative time scale after being adjusted for the obtained peaks (T*) in the hemodynamic response. These data clearly indicate that the scalar property of interval timing is observed in the activation pattern of the right putamen when it is associated with an interval-timing condition in which the production of a motor response must be timed and that a non-scalar pattern of activation is associated with the execution of a simple (i.e., non-timed) motor response. The scalar property of the hemodynamic response was not observed in any other brain region nor did any other brain region exhibit a differential time course of activation for the interval-timing versus the motor-control condition [14].
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3. Summary Neuroimaging techniques are essential in identifying brain areas whose activation correlates tightly with specific dimensions of the participants’ behavioral repertoire [14,26]. A tight correlation between cerebral activity and behavior underlies the logic of all brain-imaging experiments. If the logic of neuroimaging is correct, however, it should also be possible to reverse this sequence of operations. Once we understand the function of a given brain area or network of areas, it should be possible to use on-line activation measurements to infer what kind of psychological process the participant was performing. Reanalysis of imaging data for individual participants using correlation patterns of brain activity during single trials (see Refs. [3,11,12,52]) should open up new possibilities in understanding cognitive competence and its neural correlates. All of the papers contained in this special issue present the view that interval timing can be isolated from other cognitive processes using the appropriate experimental designs and neuroimaging techniques. The ultimate goal is to develop physiologically realistic models of interval timing that can be related to the activation of striatal–cortico-cerebellar circuits [5,8,28,29,34,33,36–38,40,42,48,51,54–60]. References [1] E.M. Brannon, J.D. Roitman, Nonverbal representations of time and number in animals and human infants, in: W.H. Meck (Ed.), Functional and Neural Mechanisms of Interval Timing, CRC Press, Boca Raton, FL, 2003, pp. 143 – 182. [2] C.V. Buhusi, Dopaminergic mechanisms of interval timing and attention, in: W.H. Meck (Ed.), Functional and Neural Mechanisms of Interval Timing, CRC Press, Boca Raton, FL, 2003, pp. 317 – 338. [3] R.M. Church, W.H. Meck, J. Gibbon, Application of scalar timing theory to individual trials, Journal of Experimental Psychology: Animal Behavior Processes 20 (1994) 135 – 155. [4] J.T. Coull, A.C. Nobre, Where and when to pay attention: the neural systems for directing attention to spatial locations and to time intervals as revealed by both PET and fMRI, Journal of Neuroscience 18 (1998) 7426 – 7435. [5] J.T. Coull, F. Vidal, B. Nazarian, F. Macar, Functional anatomy of the attentional modulation of time estimation, Science 303 (2004) 1506 – 1508. [6] C. Dale, G. Gratton, J. Gibbon, Event-related brain potentials isolate the motor component in a tapping task, NeuroReport 12 (2001) 3015 – 3018. [7] J. Diedrichsen, R.B. Ivry, J. Pressing, Cerebellar and basal ganglia contributions to interval timing, in: W.H. Meck (Ed.), Functional and Neural Mechanisms of Interval Timing, CRC Press, Boca Raton, FL, 2003, pp. 457 – 483. [8] A.M. Ferrandez, L. Hugueville, S. Lehe´ricy, J.B. Poline, C. Marsault, V. Pouthas, Basal ganglia and supplementary motor area subtend duration perception: an fMRI study, NeuroImage 19 (2003) 1532 – 1544. [9] C. Fortin, Attentional time-sharing in interval timing, in: W.H. Meck (Ed.), Functional and Neural Mechanisms of Interval Timing, CRC Press, Boca Raton, FL, 2003, pp. 235 – 260. [10] J. Gibbon, R.M. Church, Representation of time, Cognition 37 (1990) 23 – 54. [11] J. Gibbon, R.M. Church, W.H. Meck, Scalar timing in memory, Annals of The New York Academy of Sciences 423 (1984) 52 – 77.
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[12] J. Gibbon, C. Malapani, C.L. Dale, C.R. Gallistel, Toward a neurobiology of temporal cognition: advances and challenges, Current Opinion in Neurobiology 7 (1997) 170 – 184. [13] D.L. Harrington, K.Y. Haaland, Neural underpinnings of temporal processing, Reviews in the Neuroscience 10 (1999) 91 – 116. [14] S.C. Hinton, Neuroimaging approaches to the study of interval timing, in: W.H. Meck (Ed.), Functional and Neural Mechanisms of Interval Timing, CRC Press, Boca Raton, FL, 2003, pp. 419 – 438. [15] S.H. Hinton, W.H. Meck, The binternal clocksQ of circadian and interval timing, Endeavour 21 (1997) 82 – 87. [16] S.C. Hinton, W.H. Meck, J.R. MacFall, Peak-interval timing in humans activates frontal–striatal loops, NeuroImage 3 (1996) S224. [17] R. Ivry, The representation of temporal information in perception and motor control, Current Opinion in Neurobiology 6 (1996) 851 – 857. [18] P. Janata, S.T. Grafton, Swinging in the brain: shared neural substrates for behaviors related to sequencing and music, Nature Neuroscience 6 (2003) 682 – 687. [19] M. Jueptner, M. Rijntjes, C. Weiller, J.H. Faiss, Localization of a cerebellar timing process using PET, Neurology 45 (1995) 1540 – 1545. [20] J. Larsson, B. Gulyas, P.E. Roland, Cortical representation of selfpaced finger movement, NeuroReport 7 (1996) 463 – 468. [21] H. Lejeune, P. Maquet, M. Bonnet, L. Casini, A. Ferrara, F. Macar, V. Pouthas, M. Timsit-Berthier, F. Vidal, The basic pattern of activation in motor and sensory temporal tasks: positron emission tomography data, Neuroscience Letters 235 (1997) 21 – 24. [22] P.A. Lewis, R.C. Miall, Brain activation patterns during measurement of sub- and supra-second intervals, Neuropsychologia 41 (2003) 1583 – 1592. [23] P.A. Lewis, R.C. Miall, Distinct systems for automatic and cognitively controlled time measurement: evidence from neuroimaging, Current Opinion in Neurobiology 13 (2003) 250 – 255. [24] P.A. Lewis, R.C. Miall, Overview: an image of human neural timing, in: W.H. Meck (Ed.), Functional and Neural Mechanisms of Interval Timing, CRC Press, Boca Raton, FL, 2003, pp. 515 – 532. [25] C. Lustig, Grandfather’s clock: attention and interval timing in older adults, in: W.H. Meck (Ed.), Functional and Neural Mechanisms of Interval Timing, CRC Press, Boca Raton, FL, 2003, pp. 261 – 293. [26] C. Lustig, R.L. Buckner, Preserved neural correlates of priming in old age and dementia, Neuron 42 (2004) 865 – 875. [27] C. Lustig, W.H. Meck, Chronic treatment with haloperidol induces deficits in working memory and feedback effects of interval timing, Brain and Cognition (2004) (in press). [28] C. Lustig, M.S. Matell, W.H. Meck, Not bjustQ a coincidence: frontal– striatal synchronization in working memory and interval timing, Memory (2004) (in press). [29] F. Macar, Timing in the new millennium: where are we now? in: W.H. Meck (Ed.), Functional and Neural Mechanisms of Interval Timing, CRC Press, Boca Raton, FL, 2003, pp. 533 – 540. [30] C. Malapani, S. Fairhurst, Scalar timing in animals and humans, Learning and Motivation 33 (2002) 156 – 176. [31] C. Malapani, B.C. Rakitin, Interval timing in the dopamine-depleted basal ganglia: from empirical data to timing theory, in: W.H. Meck (Ed.), Functional and Neural Mechanisms of Interval Timing, CRC Press, Boca Raton, FL, 2003, pp. 485 – 514. [32] C. Malapani, B. Dubois, G. Rancurel, J. Gibbon, Cerebellar dysfunctions of temporal processing in the seconds range in humans, NeuroReport 9 (1998) 3907 – 3912. [33] C. Malapani, B. Rakitin, R. Levy, W.H. Meck, B. Deweer, B. Dubois, J. Gibbon, Coupled temporal memories in Parkinson’s disease: a dopamine-related dysfunction, Journal of Cognitive Neuroscience 10 (1998) 316 – 331. [34] C. Malapani, B. Deweer, J. Gibbon, Separating storage from retrieval dysfunction of temporal memory in Parkinson’s disease, Journal of Cognitive Neuroscience 14 (2002) 311 – 322.
[35] P. Maquet, H. Lejeune, V. Pouthas, M. Bonnet, L. Casini, F. Macar, M. Timsit-Berthier, F. Vidal, A. Ferrara, C. Degueldre, L. Quaglia, G. Delfiore, A. Luxen, R. Woods, J.C. Mazziotta, D. Comar, Brain activation induced by estimation of duration: a PET study, NeuroImage 3 (1996) 119 – 126. [36] M.S. Matell, W.H. Meck, Neuropsychological mechanisms of interval timing behavior, BioEssays 22 (2000) 94 – 103. [37] M.S. Matell, W.H. Meck, M.A.L. Nicolelis, Integration of behavior and timing: anatomically separate systems or distributed processing? in: W.H. Meck (Ed.), Functional and Neural Mechanisms of Interval Timing, CRC Press, Boca Raton, FL, 2003, pp. 371 – 391. [38] M.S. Matell, W.H. Meck, M.A.L. Nicolelis, Interval timing and the encoding of signal duration by ensembles of cortical and striatal neurons, Behavioral Neuroscience 117 (2003) 760 – 773. [39] W.H. Meck, Neuropharmacology of timing and time perception, Cognitive Brain Research 3 (1996) 227 – 242. [40] W.H. Meck, Coincidence detection as the core process for interval timing in frontal–striatal circuits, NeuroImage (2002) 668. [41] W.H. Meck, Introduction: persistence of time, in: W.H. Meck (Ed.), Functional and Neural Mechanisms of Interval Timing, CRC Press, Boca Raton, FL, 2003, pp. xvii – xli. [42] W.H. Meck, Neuropsychology of timing and time perception, Brain and Cognition (2004) (in press). [43] W.H. Meck, S.C. Hinton, M.S. Matell, Coincidence-detection models of interval timing: evidence from fMRI studies of cortico-striatal circuits, NeuroImage 7 (1998) S284. [44] I. Nenadic, C. Gaser, H.-P. Volz, T. Rammsayer, F. H7ger, H. Sauer, Processing of temporal information and the basal ganglia: new evidence from fMRI, Experimental Brain Research 148 (2003) 238 – 246. [45] D.J. O’Boyle, J.S. Freeman, F.W.J. Cody, The accuracy and precision of timing of self-paced, repetitive movements in subjects with Parkinson’s disease, Brain 119 (1996) 51 – 70. [46] K.C.H. Pang, J.D. McAuley, Importance of frontal motor cortex in divided attention and simultaneous temporal processing, in: W.H. Meck (Ed.), Functional and Neural Mechanisms of Interval Timing, CRC Press, Boca Raton, FL, 2003, pp. 351 – 369. [47] M.A. Pastor, J. Artieda, M. Jahanshahi, J.A. Obeso, Performance of repetitive wrist movements in Parkinson’s disease, Brain 115 (1992) 875 – 891. [48] M.A. Pastor, B.L. Day, E. Macaluso, K.J. Friston, S.J. Frackowlak, The functional neuroanatomy of temporal discrimination, Journal of Neuroscience 24 (2004) 2585 – 2591. [49] V.B. Penhune, R.J. Zatorre, A. Evans, Cerebellar contributions to motor timing: a PET study of auditory and visual rhythm reproduction, Journal of Cognitive Neuroscience 10 (1998) 752 – 765. [50] T.B. Penney, Modality differences in interval timing: attention, clock speed, and memory, in: W.H. Meck (Ed.), Functional and Neural Mechanisms of Interval Timing, CRC Press, Boca Raton, FL, 2003, pp. 209 – 233. [51] V. Pouthas, Electrophysiological evidence for specific processing of temporal information in humans, in: W.H. Meck (Ed.), Functional and Neural Mechanisms of Interval Timing, CRC Press, Boca Raton, FL, 2003, pp. 439 – 456. [52] BC. Rakitin, J. Gibbon, TB. Penney, C. Malapani, SC. Hinton, W.H. Meck, Scalar expectancy theory and peak-interval timing in humans, Journal of Experimental Psychology. Animal Behavior Processes 24 (1998) 15 – 33. [53] T.H. Rammsayer, Neuropharmacological evidence for different timing mechanisms in humans, The Quarterly Journal of Experimental Psychology, B 52 (1999) 273 – 286. [54] S.M. Rao, D.L. Harrington, K.Y. Haaland, J.A. Bobholz, R.W. Cox, J.R. Binder, Distributed neural systems underlying the timing of movements, Journal of Neuroscience 17 (1997) 5528 – 5535. [55] S.M. Rao, A.R. Mayer, D.L. Harrington, The evolution of brain activation during temporal processing, Nature Neuroscience 4 (2001) 317 – 323.
Editorial [56] A. Santamaria, (2002). Interval timing: a cerebellar model and investigation of temporal production. Unpublished Masters thesis submitted to the Faculty of the Graduate School of the University of Colorado. [57] R.I. Schubotz, A.D. Friederici, D.Y. von Cramon, Time perception and motor timing: a common cortical and subcortical basis revealed by fMRI, NeuroImage 11 (2000) 1 – 12. [58] R.I. Schubotz, D.Y. von Cramon, Interval and ordinal properties of sequences are associated with distinct premotor areas, Cerebral Cortex 11 (2001) 210 – 222. [59] R.M. Spencer, H.N. Zelaznik, J. Diedrichsen, R.B. Ivry, Disrupted timing of discontinuous but not continuous movements by cerebellar lesions, Science 300 (2003) 1437 – 1439. [60] S.C. Tanaka, K. Doya, G. Okada, K. Ueda, Y. Okamoto, S. Yamawaki, Prediction of immediate and future rewards differentially recruits cortico-basal ganglia loops, Nature Neuroscience 7 (2004) 887 – 893. [61] H.-P. Volz, I. Nenadic, C. Gaser, T. Rammsayer, Time estimation in schizophrenia: an fMRI study at adjusted levels of difficulty, NeuroReport 12 (2001) 313 – 316.
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Warren H. Meck Department of Psychological and Brain Sciences, Duke University, Genome Sciences Research Building II-3rd Floor, 103 Research Drive-Box 91050, Durham, NC 27708, United States E-mail address: [email protected]. Corresponding author. Tel.: +1 919 660 5765; fax: +1 919 660 5798. Chara Malapani Temporal Cognition Laboratory, New York State Psychiatric Institute, New York, NY, United States Department of Psychiatry, Columbia University, New York, NY, United States
Editorial
Neuroimaging of interval timing
Abstract Exactly how the brain is able to measure the durations of events lasting from seconds to minutes while maintaining time-scale invariance remains largely a mystery. Neuroimaging studies are only now beginning to unravel the nature of interval timing and reveal whether different timing mechanisms are required for the perception and production of sub- and supra-second intervals that can be defined by different stimulus modalities. We here review the impact that neuroimaging studies have had on the field of timing and time perception and outline the major challenges that remain to be addressed before a physiologically realistic theory of interval timing can be established involving cortico-striatal circuits. D 2004 Elsevier B.V. All rights reserved. Theme: Neural Basis of Behavior Topic: Cognition Keywords: Timing; Time perception; Cerebral cortex; Basal ganglia; Caudate; Putamen; Cerebellum; fMRI
1. Introduction to special issue on the dneuroimaging of interval timingT Interval-timing studies using modern neuroimaging techniques such as positron emission tomography (PET), eventrelated functional magnetic resonance imaging (fMRI), electroencephalography (EEG) with its associated eventrelated potentials (ERP), and magnetoencephalography (MEG) have produced a variety of intriguing, but sometimes conflicting results [4,6,13,22–24,48,49,51]. Many studies have focused on motor timing, making it difficult to identify whether activation in systems traditionally associated with motor control, such as the basal ganglia and cerebellum, relates to more cognitively oriented domains of interval timing [19–21,32,49]. A few studies that used PET specifically examined time perception [19,21,35]. Unfortunately, the time scale of PET scanning is limited to blockedtrial designs that cannot disentangle processing associated with encoding an interval from processing associated with decision making and implementing a response. More recent studies using fMRI in humans and ensemble recording techniques in animals have provided clear evidence for the interdependency of cortical and sub-cortical structures such as the basal ganglia in timing and time perception [5,8,14,16,18,37,38,40,41,43,44,54,55,57, 58,60,61]. A common feature of many of these neuroimaging studies is the explicit attempt to dissect the contribution of 0926-6410/$ - see front matter D 2004 Elsevier B.V. All rights reserved. doi:10.1016/j.cogbrainres.2004.07.010
different timing components (e.g., clock, memory, and decision stages) as described by Gibbon et al. [11]. For example, by employing an innovative experimental design, Coull et al. [5] were able to isolate a functional anatomical network for perceptual (non-motor) timing in which linear increases in task performance were accompanied by corresponding increases in brain activity. The study made use of dynamically changing visual stimulus attributes (e.g., color and duration) that could be differentially attended to by the participants. Increasing attentional allocation to the temporal integration of stimulus duration selectively increased activity in a cortico-striatal network that included the pre-supplementary motor area, the right frontal operculum, and the right putamen. Conversely, increasing attention to the integration of the temporal variation in the color of the stimulus (rather than its duration) selectively increased activity in visual area V4. Thus, by parametrically increasing the attentional demands of the psychophysical task these researchers were able to identify the neural substrates of time and color perception. In another influential study, the within-trial evolution of interval timing was examined by Rao et al. [55] who reported that activation in the basal ganglia (right putamen and caudate) occurred early in the trial, and was uniquely associated with encoding time intervals, whereas cerebellar activation unfolded later, suggesting an involvement of processes other than explicit timing. Early cortical activation
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associated with encoding of time intervals was observed in the right inferior parietal cortex and bilateral premotor cortex, implicating these systems in attention and temporary maintenance of intervals. Later activation in the right dorsolateral prefrontal cortex emerged during comparison of time intervals. The authors claim their results illustrate a dynamic network of cortical–subcortical activation associated with different components of temporal information processing. However, there are several potential shortcomings concerning this study. First, the dynamics of brain activation patterns were studied for rather short delay periods (up to 4 s). Clearly, these delay periods should be extended to directly distinguish brain systems involved in encoding and short- and/or long-term maintenance of time intervals. Moreover, besides basal ganglia activation being observed early on in the course of temporal integration, multiple brain structures (including the basal ganglia) were equally activated during later stages suggesting that no clear conclusion could be made on the sole basis of the subtraction techniques used to identify activated areas. Nonetheless, the aforementioned studies constitute seminal contributions to the field of interval-timing research and demonstrate the important role that emerging neuroimaging technologies can play in dissecting cognitive functions of the normal and diseased brain. In a number of these neuroimaging studies, striatal activation has been strongly associated with the encoding of time intervals [5,8,14, 24,44,55]. These findings corroborate studies in Parkinson’s disease (PD) showing that dopaminergic treatment improves both motor timing [44–47] and time perception [33]. Pharmacological challenges in humans and other animals also indicate that dopaminergic antagonists and agonists, respectively, slow down and speed up interval-timing processes [2,27,39,41,53]. Contrary to one proposal [7,17,22,53], these and other studies show that the basal ganglia are involved in timing a wide range of intervals, from hundreds of milliseconds (e.g., 300 ms) to tens of seconds (e.g., 20 s) or longer ([12,15]—see also Ref. [32]). Consistent with these fMRI results is the recent discovery of the dopaminergic influence on both encoding and retrieval of temporal memories in PD [34,31,33], processes otherwise separable in their functional and neural correlates [12,28,36,54,55]. Collectively, these results implicate basal ganglia circuitry as well as dopaminergic neurotransmission within striatal and/or cortical sites in timing and time perception that affect cognitive functions as diverse as attention, counting, language, learning, and memory [1,2,9,25,28, 27,41,46,50]. The papers included in this special issue of Cognitive Brain Research are aimed at extending our current state of knowledge concerning the neuroanatomy of interval timing by addressing key questions that remain unanswered [29]. Do perception and production timing tasks activate similar brain areas in the same individual? What are the effects, if any, of timing across a wide range of durations, i.e., are different neural mechanisms involved in
the timing of short (ms to s) and long (min to h) durations? To what extent is interval timing modality specific and dependent upon attentional time sharing? Does the type of feedback and delay between learning and retrieval affect temporal processing? Are analog counting and timing subserved by the same type of integration mechanism? How does timing develop in the infant brain? Is there evidence for chronotopy in the basal ganglia or cortex? How is the scalar property (i.e., time-scale invariance) of interval timing implemented by the relevant neural substrates? Does differential brain activation within or across striatal–corticocerebellar circuits (in location, extent, or intensity) account for the observation of age-specific timing errors? Answers to all of these questions are still required to clarify the nature of the time-sense that distinguishes the intact brain from the diseased brain.
Fig. 1. Group data obtained from a fMRI experiment in which the time course of the hemodynamic response associated with the participant’s active production of a btimedQ response at either 11 or 17 s after signal onset (top panel) was compared with a passive, buntimedQ response triggered by a stimulus presentation at either 11 or 17 s after signal onset (bottom panel). The data have been normalized and replotted on a relative time scale after being adjusted for the obtained peaks (T*) in the hemodynamic response. See Hinton [14] for additional procedural details.
Editorial
2. Illustrations of the scalar property of interval timing using fMRI The scalar property is one of the major hallmarks of interval timing and reflects the observation that the variability associated with the precision of the binternal clockQ grows in proportion to the length of the interval being timed [3,11,30]. Multiplicative sources of variance (in either the clock or memory) contribute to time scale invariance where time is like a brubberbandQ that can be stretched to accommodate the relative signal durations experienced in any particular situation [10]. Consequently, it is important to determine which brain areas serve as scalar timekeepers and exhibit anticipation of the time of occurrence of future events [12]. In a pioneering fMRI study using a peak-interval timing procedure with 7- and 11-s signal durations, Hinton [14] reported that the putamen was the only brain region in which the time course of the hemodynamic response associated with interval timing preceded the activation due to a motor-control condition. This pattern of activation reflected anticipation of the response rather than its immediate preparation or execution. Other brain regions (e.g., primary motor cortex and supplementary motor area) did not exhibit differential activation between the interval-timing and the motor-control conditions. Furthermore, these brain regions showed much greater activation in the hemisphere contra-lateral to the hand used to make the simple reaction-time response. In contrast, the right putamen was more active than the left putamen under all timing conditions regardless of the hand used. This is a rather surprising result and lends considerable support to the finding of lateralization of interval timing to the right putamen [8]. When the normalized percent change in the hemodynamic response is plotted as a function of time since signal onset on a relative time scale the activation associated with producing a response at 11 or 17 s should superimpose if that brain region is directly involved in the timekeeping process. In contrast, if the hemodynamic response displays a constant (rather than a multiplicative) source of variability then the 17-s response function should be considerably sharper than the 11-s response function when plotted on a relative time scale. Each of these outcomes is illustrated in Fig. 1 which displays the type of interval-timing and motorcontrol data reported by Hinton [14]. The fMRI data have been normalized and replotted on a relative time scale after being adjusted for the obtained peaks (T*) in the hemodynamic response. These data clearly indicate that the scalar property of interval timing is observed in the activation pattern of the right putamen when it is associated with an interval-timing condition in which the production of a motor response must be timed and that a non-scalar pattern of activation is associated with the execution of a simple (i.e., non-timed) motor response. The scalar property of the hemodynamic response was not observed in any other brain region nor did any other brain region exhibit a differential time course of activation for the interval-timing versus the motor-control condition [14].
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3. Summary Neuroimaging techniques are essential in identifying brain areas whose activation correlates tightly with specific dimensions of the participants’ behavioral repertoire [14,26]. A tight correlation between cerebral activity and behavior underlies the logic of all brain-imaging experiments. If the logic of neuroimaging is correct, however, it should also be possible to reverse this sequence of operations. Once we understand the function of a given brain area or network of areas, it should be possible to use on-line activation measurements to infer what kind of psychological process the participant was performing. Reanalysis of imaging data for individual participants using correlation patterns of brain activity during single trials (see Refs. [3,11,12,52]) should open up new possibilities in understanding cognitive competence and its neural correlates. All of the papers contained in this special issue present the view that interval timing can be isolated from other cognitive processes using the appropriate experimental designs and neuroimaging techniques. The ultimate goal is to develop physiologically realistic models of interval timing that can be related to the activation of striatal–cortico-cerebellar circuits [5,8,28,29,34,33,36–38,40,42,48,51,54–60]. References [1] E.M. Brannon, J.D. Roitman, Nonverbal representations of time and number in animals and human infants, in: W.H. Meck (Ed.), Functional and Neural Mechanisms of Interval Timing, CRC Press, Boca Raton, FL, 2003, pp. 143 – 182. [2] C.V. Buhusi, Dopaminergic mechanisms of interval timing and attention, in: W.H. Meck (Ed.), Functional and Neural Mechanisms of Interval Timing, CRC Press, Boca Raton, FL, 2003, pp. 317 – 338. [3] R.M. Church, W.H. Meck, J. Gibbon, Application of scalar timing theory to individual trials, Journal of Experimental Psychology: Animal Behavior Processes 20 (1994) 135 – 155. [4] J.T. Coull, A.C. Nobre, Where and when to pay attention: the neural systems for directing attention to spatial locations and to time intervals as revealed by both PET and fMRI, Journal of Neuroscience 18 (1998) 7426 – 7435. [5] J.T. Coull, F. Vidal, B. Nazarian, F. Macar, Functional anatomy of the attentional modulation of time estimation, Science 303 (2004) 1506 – 1508. [6] C. Dale, G. Gratton, J. Gibbon, Event-related brain potentials isolate the motor component in a tapping task, NeuroReport 12 (2001) 3015 – 3018. [7] J. Diedrichsen, R.B. Ivry, J. Pressing, Cerebellar and basal ganglia contributions to interval timing, in: W.H. Meck (Ed.), Functional and Neural Mechanisms of Interval Timing, CRC Press, Boca Raton, FL, 2003, pp. 457 – 483. [8] A.M. Ferrandez, L. Hugueville, S. Lehe´ricy, J.B. Poline, C. Marsault, V. Pouthas, Basal ganglia and supplementary motor area subtend duration perception: an fMRI study, NeuroImage 19 (2003) 1532 – 1544. [9] C. Fortin, Attentional time-sharing in interval timing, in: W.H. Meck (Ed.), Functional and Neural Mechanisms of Interval Timing, CRC Press, Boca Raton, FL, 2003, pp. 235 – 260. [10] J. Gibbon, R.M. Church, Representation of time, Cognition 37 (1990) 23 – 54. [11] J. Gibbon, R.M. Church, W.H. Meck, Scalar timing in memory, Annals of The New York Academy of Sciences 423 (1984) 52 – 77.
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Warren H. Meck Department of Psychological and Brain Sciences, Duke University, Genome Sciences Research Building II-3rd Floor, 103 Research Drive-Box 91050, Durham, NC 27708, United States E-mail address: [email protected]. Corresponding author. Tel.: +1 919 660 5765; fax: +1 919 660 5798. Chara Malapani Temporal Cognition Laboratory, New York State Psychiatric Institute, New York, NY, United States Department of Psychiatry, Columbia University, New York, NY, United States