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Neuropsychology of timing and time perception
Brain and Cognition 58 (2005) 1–8 www.elsevier.com/locate/b&c
Introduction
Neuropsychology of timing and time perception Warren H. Meck* Department of Psychological and Brain Sciences, Genome Sciences Research Building II, 3rd Floor, 103 Research Drive, Box 91050, Duke University, Durham, NC 27708, United States Accepted 16 September 2004 Available online 18 November 2004
Abstract Interval timing in the range of milliseconds to minutes is affected in a variety of neurological and psychiatric populations involving disruption of the frontal cortex, hippocampus, basal ganglia, and cerebellum. Our understanding of these distortions in timing and time perception are aided by the analysis of the sources of variance attributable to clock, memory, decision, and motor-control processes. The conclusion is that the representation of time depends on the integration of multiple neural systems that can be fruitfully studied in selected patient populations. Ó 2004 Elsevier Inc. All rights reserved.
Subjective or psychological time is the internal experience of how fast time is passing, or how much time has passed since the occurrence of some event. The ability to estimate objective or physical time has been shown to be a robust and stable function, varying only with severe psychiatric disorders, brain pathology, or pharmacological/toxicological challenges (e.g., Meck, 1996, 2003; Paule et al., 1999). Subjective time estimation requires the participant to use an internal clock in order to measure objective time without the benefit of cues from external clocks. Because of the difficulty in localizing this ‘‘internal clock’’ within the brain the discipline of timing and time perception has struggled to define its own identity and to separate itself from the study of other cognitive processes such as attention and memory. The concern has been that interval timing in the seconds to minutes range may be derivative from these other cognitive processes and may not possess its own defining characteristics or neural substrate (see Grimm, Widmann, & Schro¨ger, 2004; Macar, 2003; Zakay & Block, 1997). Fortunately, interval timing is becoming recognized as a fundamental component of cognition due to the recent identification of brain mechanisms specialized *
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for the encoding of stimulus duration (e.g., Coull, Vidal, Nazarian, & Macar, 2004; Gibbon, Malapani, Dale, & Gallistel, 1997; Harrington et al., 2004; Hazeltine, Helmuth, & Ivry, 1997; Hinton, 2003; Hinton & Meck, 1997, 2004; Ivry, 1996; Leon & Shadlen, 2003; Lewis & Miall, 2003a, 2003b; Lustig, Matell, & Meck, 2004; Matell & Meck, 2000, 2004; Meck & Benson, 2002; Pastor, Day, Macaluso, Friston, & Frackowlak, 2004; Pouthas, 2003; Rammsayer, 1997; Rao, Mayer, & Harrington, 2001; Spencer, Zelaznik, Diedrichsen, & Ivry, 2003) and because of the identification of interval-timing dysfunctions in a variety of neurological and psychiatric disorders as well as in normal aging (e.g., Barkely, Murphy, & Bush, 2001; Elvevag et al., 2004; Harrington & Haaland, 1999; Harrington, Haaland, & Knight, 1998; Levin et al., 1996; Lustig, 2003; Lustig & Meck, 2001; Malapani, Deweer, & Gibbon, 2002; Malapani & Rakitin, 2003; Malapani et al., 1998; Meck, 2003; Meck & Benson, 2002; Papagno, Allegra, & Cardaci, 2004; Pouthas & Perbal, 2004; Wimpory, Nicholas, & Nash, 2002). Numerous studies have examined abnormal time experience and time estimation in depressive patients (e.g., Blewett, 1992; Kitamura & Kumar, 1984; Kuhs, Hermann, Kammer, & To¨lle, 1991; Melges & Fougerousse, 1966; Mundt, Richter, van Hees, & Stumpf,
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1998; Mu¨nzel, Gendner, Steinberg, & Raith, 1988; Richter & Benzenhofer, 1985; Se´vigny, Everett, & Grondin, 2003). In one example, Elsass, Mellerup, Rafaelsen, and Theilgaard (1979) reported that time estimates varied between lithium-treated bipolar patients and untreated controls. This work has since been advanced by Tysk (1984) and Bschor et al. (2004) who have also reported that time estimation can vary with clinical state in bipolar disorders. In spite of the large number of patients tested, much more systematic research needs to be directed toward this issue in order to permit a distinction among attention, clock speed, and memory explanations of changes in timing behavior (see Gibbon & Church, 1990; Gibbon, Church, & Meck, 1984; Meck, 1983, 1996; Penney, Holder, & Meck, 1996). Rammsayer (1990) reported poorer time discrimination among schizophrenic and dysthymic patients than healthy controls and inferred differences in clock rate between these groups. Administration of the anti-psychotic agent haloperidol to healthy normal participants produced timing effects that implicate the dopaminergic system in the control of clock speed in the milliseconds and seconds ranges (Rammsayer, 1999). Subsequent neuroimaging studies revealed procedural learning and timing specific differences in schizophrenia mediated by cortico-striatal as well as cortico-cerebellar dysfunction (e.g., Kumari et al., 2002; Volz, Nenadic, Gaser, & Rammsayer, 2001). The primary cortico-striatal and cortico-cerebellar pathways relevant to these interval timing and neuroimaging data are illustrated in Fig. 1. There is ample reason to believe that humans and other animals have a well-developed time sense in the seconds-to-minutes range. Humans are excellent at interval timing and sequencing, they can make fine temporal discriminations and are sensitive to small perturbations in rhythm and musical structure (e.g., Epstein, 1989; Janata & Grafton, 2003; McAuley & Jones, 2003; Na¨a¨ta¨nen, Syssoeva, & Takegata, 2004). Estimating time intervals is an important adaptive skill, vital for making predictions and for motor control (e.g., Diedrichsen, Ivry, & Pressing, 2003; Ivry, 1996; Ivry & Richardson, 2002; Spencer et al., 2003). Evolutionarily, time estimations in the seconds-to-minutes range are important for making predictions about oneÕs environment, for example, about the appearance of predators or prey (e.g., Bateson, 2003; Gallistel & Gibbon, 2000). Millisecond time estimations are important for motor control and for rapid sequencing of cognitive operations, such as updating working memory and language processing (e.g., Justus & Ivry, 2001; Lustig et al., 2004; Meck & Benson, 2002; Schirmer, 2004). Although certain aspects of language are unique and highly specialized, its evolution has not been so selective that neural systems have been appropriated at the expense of other cognitive processes (Schirmer, 2004; Ullman, 2004). In fact, it appears that language shares
Fig. 1. A diagram of the cortico-striatal and cortico-cerebellar circuits thought to be involved in the interval-timing and motor-control components of procedural learning that are dysfunctional in schizophrenia (see Doyon et al., 2003; Kumari et al., 2002). Full colored lines represent excitatory input to various areas. Dashed lines and black lines represent inhibitory input to areas. MTL, medial temporal lobe; GPE, globus pallidus external capsule; GPI, globus pallidus internal capsule; SNC, substantia nigra pars compacta; PN, pontine nuclei; IO, inferior olive; Red N, red nucleus; Ret N, reticular nucleus; VN, vestibular nuclei; VLm, ventrolateral medial thalamic nucleus; VLo, ventrolateral thalamic nucleus—oral division; and VL c/x, ventrolateral thalamic nucleus—caudal and area x divisions.
temporal-lobe structures in order to store word-specific knowledge and activates frontal, basal ganglia, parietal, and cerebellar networks in order to provide grammatical structure for the various combinations of lexical items used in discourse. The important aspect of this ‘‘dualuse’’ strategy is that many of these same brain structures underlie the more general-purpose functions of declarative, procedural, and working memory as well as motor learning, set-switching, attention, and interval timing (see Lustig et al., 2004; Meck & Benson, 2002). Perhaps not too surprisingly, there has been some controversy in terms of identifying those brain structures that are critical for language just as there has been controversy in determining the precise contributions of frontal-striatal and cerebellar circuits to timing and time perception (see Diedrichsen et al., 2003; Gibbon et al., 1997; Harrington, Lee, Boyd, Rapcsak, & Knight, 2004; Ivry, 1996; Malapani, Dubois, Rancurel, & Gibbon, 1998; Meck, 2003; Spencer et al., 2003). One major source of
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agreement, however, is that motor control and its associated variance can be separated from the perceptual aspects of interval timing, thus defining a specialized process that has been referred to as the ‘‘internal clock.’’ Consequently, although there may be disagreement as to whether the internal clock takes the form of an oscillator or hourglass (see Pashler, 2001) there is substantial agreement that a specialized timing system exists—much like the language system described by Ullman (2004). Recently, an integrative model of timing and time perception has been proposed in which two parallel systems are required in order to account for the full range of durations resolved by the ‘‘internal clock’’ (Santamaria, 2002; see also Madison, 2001). This model includes a bottom-up system for timing in the milliseconds range— considered important for motor coordination and computed by the cerebellum. The other component involves a top–down system for timing in the seconds to minutes range—considered important for temporal estimation and computed by frontal-striatal circuits that are able to concatenate smaller intervals generated locally or by the cerebellum. To evaluate this model, Santamaria (2002) simulated a neural network of cerebellar activity that represented the millisecond timing system. Contrary to the initial predictions of nonlinearity in the output of this network, simulations indicated that timing error increased linearly as a function of interval length, but drift in the variability of the modelÕs output showed a systematic nonlinearity (see Crystal, 2003). It was also predicted that transfer of timing between different effector systems (e.g., left and right hands) would be minimal due to motor-specific interval learning by the cerebellum. In contrast, model simulations provided evidence for transfer of timing between hands indicating an unexpected robustness of the frontal networks and a surprising degree of independence from the cerebellum. One conclusion that can be drawn from this type of analysis is that frontal-striatal circuits are apparently able to rescale durations in a proportional manner and compensate for error differences generated by the cerebellum. This type of ‘‘scalar’’ representation of intervals (see Gibbon & Church, 1990; Gibbon et al., 1984; Malapani & Fairhurst, 2002) may contribute to the observed transfer among different effector systems by allowing for the encoding of duration in a less motor-specific fashion and establishes a manner in which different timing systems (e.g., cerebellum and basal ganglia) can interact across a wider range of durations (e.g., milliseconds to hours). A classic case study of the neuropsychology of timing and time perception comes from the renowned individual H.M., who underwent a bilateral medial temporal lobe (MTL) resection that resulted in a severe memory loss following surgery (Richards, 1973). When H.M. was required to reproduce durations ranging between 1 and 300 s he demonstrated reasonably accurate timing
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for durations <20 s, but systematic underestimation for durations >20 s. Eisler and Eisler (2001) fit a powerfunction model to these reproduction data and determined that H.M.Õs psychophysical function showed a distinct break, dividing the function into a lower and an upper segment. The conclusion was that the hippocampus and other temporal lobe structures are involved in the maintenance of task instructions in short-term memory, but that once accumulated, clock readings are retained in the absence of normal temporal lobe function. Despite this and other extremely interesting case studies (e.g., Perbal, Pouthas, & Van der Linden, 2000), much remains to be determined about the neuropsychology of interval timing. Some of the main goals of the field of timing and time perception are to determine how brain lesions, neurodegenerative disease states, pharmacological treatments, and normal aging contribute to changes in the speed of internal clock and/or memory storage processes (Gibbon et al., 1997; Malapani et al., 1998; Meck, 1983, 1996; Pouthas & Perbal, 2004). The observation of hemispheric asymmetries in the effects of MTL resection on timing and time perception has renewed interest in the lateralization of temporal processing. For example, patients with right MTL resections often exhibit impairments in the precision of their timing abilities that are associated with the underestimation of retrospective duration and little or no change in the accuracy of prospective timing. In contrast, patients with left MTL resections have been shown to exhibit either no impairments or an improvement in the precision of their timing abilities that may be accompanied by an ability to correct underestimations in retrospective time judgments as well as a persistent overestimation/ underproduction of prospective duration (e.g., Drane, Lee, Loring, & Meador, 1999; Vidalaki, Ho, Bradshaw, & Szabadi, 1999). These observations are of particular interest given the recent findings that hippocampal and striatal systems can interact competitively such that damage to one system can lead to facilitation in the other (e.g., Poldrack & Packard, 2003). This ‘‘see-saw’’ effect may be explained by a number of factors, including direct anatomical projections from the MTL to areas of the dorsal striatum that have been shown to be important for interval timing as illustrated in Fig. 2 (Matell, Meck, & Nicolelis, 2003; Sorensen & Witter, 1983). Furthermore, animal studies have indicated that lesions to the hippocampus can result in increased dopaminergic transmission in the portions of the striatum to which the hippocampus projects (e.g., Lipska, Jaskiw, Chrapusta, Karoum, & Weinberger, 1992) thereby producing long-term alterations in the accuracy and precision of interval timing in the seconds-to-minutes range (e.g., Buhusi, Mocanu, & Meck, 2004; Meck, 1988; Meck, Church, & Olton, 1984; Meck, Church, Wenk, & Olton, 1987; Olton, Meck, & Church, 1987; Olton, Wenk, Church, & Meck, 1988).
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Fig. 2. Outline of the neurotransmitter systems and cortico-striatal/ hippocampal circuitry proposed to mediate timing and time perception in the seconds-to-minutes range. Descriptions of these anatomical connections and how cortico-striatal coincidence detection and resulting thalamo-cortical feedback results in the temporal control of behavior is provided by Xiao and Barbas (2004) and Matell and Meck (2000, 2004), respectively. Ach, acetylcholine; Glu, glutamate; SP, substance P; Enk, enkephalin; GABA, c-aminobutyric acid; DA, dopamine; D1, dopamine D1 receptor subtype; D2, dopamine D2 receptor subtype; GPE, globus pallidus external capsule; GPI, globus pallidus internal capsule; SNC, substantia nigra pars compacta; SNR, substantia nigra pars reticulata; and STN, subthalamic nucleus.
An intriguing example of the neuropharmacological basis of interval timing is illustrated by the results obtained from an adult participant diagnosed with attentional-deficit disorder (ADD). This patientÕs reproduction of 7- and 17-s signal durations while performing a peak-interval procedure are displayed in Fig. 3 (see Levin et al., 1996, 1998; Lustig & Meck, 2005; Rakitin et al., 1998 for procedural details). The top panel displays percent maximum response rate for the participant in an unmedicated state (NicPre) plotted as a function of the 7- and 17-s criteria. In this procedure, a blue square presented on a computer monitor is transformed to magenta at the appropriate criterion time during fixed-time training trials. Thereafter, participants are requested to reproduce the temporal criterion for a sequence of test trials after which a distribution of their responses is plotted on a relative timescale at the completion of the trial during the inter-trial interval (ITI). This ITI feedback is displayed on the computer monitor and provides the participant with information concerning the relative accuracy and precision of their timing behavior on the preceding trial. ITI feedback can be randomly presented following a fixed proportion of trials (in this case 25 and 100%). As can be seen in the top panel of the figure, when the participant is provided with ITI feedback on 100% of the trials the PI functions are centered at the correct times showing excellent accuracy of the repro-
Fig. 3. Percent maximum response rate in the peak-interval procedure plotted as a function of signal duration for a single adult participant (ALB) diagnosed with attention deficit disorder (ADD) trained at two criterion times (7 and 17 s) under two conditions of intertrial interval (ITI) feedback (25 and 100%). The top panel shows performance at these two criterion times under the two ITI feedback conditions in an unmedicated state (NicPre) and the bottom panel shows performance in a medicated state (NicPost). See Levin et al. (1996, 1998) for additional procedural details.
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duced intervals. In contrast, when ITI feedback is provided on only 25% of the trials a proportional rightward shift is observed in the timing of the 7- and 17-s intervals, reflecting a discrepancy in the accuracy of temporal reproductions that is not observed in normal participants (e.g., Lustig & Meck, 2005; Rakitin et al., 1998). This rightward shift is accompanied by a broadening of the PI functions indicating a decrease in temporal precision with lower levels of feedback. Both of these findings are consistent with a slowing of the internal clock as a function of the probability of feedback and may be the result of a deficit in attention mediated the flickering of a mode switch that gates pulses from a pacemaker into an accumulator (e.g., Lustig, 2003; Lustig & Meck, 2005; Meck & Benson, 2002; Penney, 2003; Penney, Allan, Meck, & Gibbon, 1998; Penney, Gibbon, & Meck, 2000). Interestingly, the bottom panel indicates that when the participant is given a stimulant drug (e.g., 7 mg/day transdermal nicotine skin patch) that increases dopamine levels in the brain during the NicPost condition the effects of 25% ITI feedback are enhanced and produce levels of temporal accuracy and precision that are equivalent to the 100% ITI feedback condition in both the medicated and unmedicated states. These results suggest an equivalence of the ITI feedback effects and the types of pharmacological stimulation provided to ADD patients by drugs such as nicotine and methylphenidate (see Levin et al., 1996, 1998). These findings also support the proposal that deficits in attention can lead to the underestimation of signal durations in a manner consistent with a slowing of an internal clock that is sensitive to dopaminergic manipulations whether they are produced by behavioral (ITI feedback) or pharmacological means (see Buhusi, 2003; Buhusi & Meck, 2002). In the papers that follow in this special issue of Brain and Cognition on the ‘‘Neuropsychology of Timing and Time Perception,’’ the contributing authors explore the characteristics of the interval-timing system as it is perturbed by dopaminergic antagonists and feedback (Lustig & Meck, 2005), normal aging (Rakitin, Stern, & Malapani, 2005), ParkinsonÕs disease (Perbal et al., 2005; Jurkowski, Stepp, & Hackley, 2004; Spencer & Ivry, 2005), unilateral and focal lesions of the basal ganglia (Aparicio, Diedrichsen, & Ivry, 2005; Shin, Aparicio, & Ivry, 2004), cerebellar lesions (Spencer & Ivry, 2005), schizophrenia and/or its associated risk factors (e.g., Brown et al., 2005; Penney, Meck, Roberts, Gibbon, & Erlenmeyer-Kimling, 2005), MTL resection (Melgire et al., 2005), as well as hemispheric differences in temporal processing (Grondin & Girard, 2005) and the effects of musical expertise on timing and time perception (Ehrle´ & Samson, 2005). Without question, there is still much to be learned about how modifications in the neural systems that support interval timing contribute to cognitive dysfunction.
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Nevertheless, the neuropsychological evidence presented here from a variety of subject populations argues strongly for one or more dedicated timekeeping mechanisms that involve the integration of cortical circuits with the basal ganglia, cerebellum, and hippocampus in order to support temporal cognition and motor skill learning across a broad range of stimulus contexts and timescales (see Doyon, Penhune, & Ungerleider, 2003; Gibbon et al., 1997).
Acknowledgments The author is very grateful to Sid Segalowitz for his invitation to edit this special issue on the ‘‘Neuropsychology of Timing and Time Perception’’ and for his continued support and patience throughout all phases of production. Inspiration for this volume also came from the organizers of TENNET XV, Montre´al, Canada, June 24–26, 2004 with special thanks to Simon Grondin for assembling an excellent symposium on the ‘‘Neural Bases of Timing and Time Perception.’’
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Introduction
Neuropsychology of timing and time perception Warren H. Meck* Department of Psychological and Brain Sciences, Genome Sciences Research Building II, 3rd Floor, 103 Research Drive, Box 91050, Duke University, Durham, NC 27708, United States Accepted 16 September 2004 Available online 18 November 2004
Abstract Interval timing in the range of milliseconds to minutes is affected in a variety of neurological and psychiatric populations involving disruption of the frontal cortex, hippocampus, basal ganglia, and cerebellum. Our understanding of these distortions in timing and time perception are aided by the analysis of the sources of variance attributable to clock, memory, decision, and motor-control processes. The conclusion is that the representation of time depends on the integration of multiple neural systems that can be fruitfully studied in selected patient populations. Ó 2004 Elsevier Inc. All rights reserved.
Subjective or psychological time is the internal experience of how fast time is passing, or how much time has passed since the occurrence of some event. The ability to estimate objective or physical time has been shown to be a robust and stable function, varying only with severe psychiatric disorders, brain pathology, or pharmacological/toxicological challenges (e.g., Meck, 1996, 2003; Paule et al., 1999). Subjective time estimation requires the participant to use an internal clock in order to measure objective time without the benefit of cues from external clocks. Because of the difficulty in localizing this ‘‘internal clock’’ within the brain the discipline of timing and time perception has struggled to define its own identity and to separate itself from the study of other cognitive processes such as attention and memory. The concern has been that interval timing in the seconds to minutes range may be derivative from these other cognitive processes and may not possess its own defining characteristics or neural substrate (see Grimm, Widmann, & Schro¨ger, 2004; Macar, 2003; Zakay & Block, 1997). Fortunately, interval timing is becoming recognized as a fundamental component of cognition due to the recent identification of brain mechanisms specialized *
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for the encoding of stimulus duration (e.g., Coull, Vidal, Nazarian, & Macar, 2004; Gibbon, Malapani, Dale, & Gallistel, 1997; Harrington et al., 2004; Hazeltine, Helmuth, & Ivry, 1997; Hinton, 2003; Hinton & Meck, 1997, 2004; Ivry, 1996; Leon & Shadlen, 2003; Lewis & Miall, 2003a, 2003b; Lustig, Matell, & Meck, 2004; Matell & Meck, 2000, 2004; Meck & Benson, 2002; Pastor, Day, Macaluso, Friston, & Frackowlak, 2004; Pouthas, 2003; Rammsayer, 1997; Rao, Mayer, & Harrington, 2001; Spencer, Zelaznik, Diedrichsen, & Ivry, 2003) and because of the identification of interval-timing dysfunctions in a variety of neurological and psychiatric disorders as well as in normal aging (e.g., Barkely, Murphy, & Bush, 2001; Elvevag et al., 2004; Harrington & Haaland, 1999; Harrington, Haaland, & Knight, 1998; Levin et al., 1996; Lustig, 2003; Lustig & Meck, 2001; Malapani, Deweer, & Gibbon, 2002; Malapani & Rakitin, 2003; Malapani et al., 1998; Meck, 2003; Meck & Benson, 2002; Papagno, Allegra, & Cardaci, 2004; Pouthas & Perbal, 2004; Wimpory, Nicholas, & Nash, 2002). Numerous studies have examined abnormal time experience and time estimation in depressive patients (e.g., Blewett, 1992; Kitamura & Kumar, 1984; Kuhs, Hermann, Kammer, & To¨lle, 1991; Melges & Fougerousse, 1966; Mundt, Richter, van Hees, & Stumpf,
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1998; Mu¨nzel, Gendner, Steinberg, & Raith, 1988; Richter & Benzenhofer, 1985; Se´vigny, Everett, & Grondin, 2003). In one example, Elsass, Mellerup, Rafaelsen, and Theilgaard (1979) reported that time estimates varied between lithium-treated bipolar patients and untreated controls. This work has since been advanced by Tysk (1984) and Bschor et al. (2004) who have also reported that time estimation can vary with clinical state in bipolar disorders. In spite of the large number of patients tested, much more systematic research needs to be directed toward this issue in order to permit a distinction among attention, clock speed, and memory explanations of changes in timing behavior (see Gibbon & Church, 1990; Gibbon, Church, & Meck, 1984; Meck, 1983, 1996; Penney, Holder, & Meck, 1996). Rammsayer (1990) reported poorer time discrimination among schizophrenic and dysthymic patients than healthy controls and inferred differences in clock rate between these groups. Administration of the anti-psychotic agent haloperidol to healthy normal participants produced timing effects that implicate the dopaminergic system in the control of clock speed in the milliseconds and seconds ranges (Rammsayer, 1999). Subsequent neuroimaging studies revealed procedural learning and timing specific differences in schizophrenia mediated by cortico-striatal as well as cortico-cerebellar dysfunction (e.g., Kumari et al., 2002; Volz, Nenadic, Gaser, & Rammsayer, 2001). The primary cortico-striatal and cortico-cerebellar pathways relevant to these interval timing and neuroimaging data are illustrated in Fig. 1. There is ample reason to believe that humans and other animals have a well-developed time sense in the seconds-to-minutes range. Humans are excellent at interval timing and sequencing, they can make fine temporal discriminations and are sensitive to small perturbations in rhythm and musical structure (e.g., Epstein, 1989; Janata & Grafton, 2003; McAuley & Jones, 2003; Na¨a¨ta¨nen, Syssoeva, & Takegata, 2004). Estimating time intervals is an important adaptive skill, vital for making predictions and for motor control (e.g., Diedrichsen, Ivry, & Pressing, 2003; Ivry, 1996; Ivry & Richardson, 2002; Spencer et al., 2003). Evolutionarily, time estimations in the seconds-to-minutes range are important for making predictions about oneÕs environment, for example, about the appearance of predators or prey (e.g., Bateson, 2003; Gallistel & Gibbon, 2000). Millisecond time estimations are important for motor control and for rapid sequencing of cognitive operations, such as updating working memory and language processing (e.g., Justus & Ivry, 2001; Lustig et al., 2004; Meck & Benson, 2002; Schirmer, 2004). Although certain aspects of language are unique and highly specialized, its evolution has not been so selective that neural systems have been appropriated at the expense of other cognitive processes (Schirmer, 2004; Ullman, 2004). In fact, it appears that language shares
Fig. 1. A diagram of the cortico-striatal and cortico-cerebellar circuits thought to be involved in the interval-timing and motor-control components of procedural learning that are dysfunctional in schizophrenia (see Doyon et al., 2003; Kumari et al., 2002). Full colored lines represent excitatory input to various areas. Dashed lines and black lines represent inhibitory input to areas. MTL, medial temporal lobe; GPE, globus pallidus external capsule; GPI, globus pallidus internal capsule; SNC, substantia nigra pars compacta; PN, pontine nuclei; IO, inferior olive; Red N, red nucleus; Ret N, reticular nucleus; VN, vestibular nuclei; VLm, ventrolateral medial thalamic nucleus; VLo, ventrolateral thalamic nucleus—oral division; and VL c/x, ventrolateral thalamic nucleus—caudal and area x divisions.
temporal-lobe structures in order to store word-specific knowledge and activates frontal, basal ganglia, parietal, and cerebellar networks in order to provide grammatical structure for the various combinations of lexical items used in discourse. The important aspect of this ‘‘dualuse’’ strategy is that many of these same brain structures underlie the more general-purpose functions of declarative, procedural, and working memory as well as motor learning, set-switching, attention, and interval timing (see Lustig et al., 2004; Meck & Benson, 2002). Perhaps not too surprisingly, there has been some controversy in terms of identifying those brain structures that are critical for language just as there has been controversy in determining the precise contributions of frontal-striatal and cerebellar circuits to timing and time perception (see Diedrichsen et al., 2003; Gibbon et al., 1997; Harrington, Lee, Boyd, Rapcsak, & Knight, 2004; Ivry, 1996; Malapani, Dubois, Rancurel, & Gibbon, 1998; Meck, 2003; Spencer et al., 2003). One major source of
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agreement, however, is that motor control and its associated variance can be separated from the perceptual aspects of interval timing, thus defining a specialized process that has been referred to as the ‘‘internal clock.’’ Consequently, although there may be disagreement as to whether the internal clock takes the form of an oscillator or hourglass (see Pashler, 2001) there is substantial agreement that a specialized timing system exists—much like the language system described by Ullman (2004). Recently, an integrative model of timing and time perception has been proposed in which two parallel systems are required in order to account for the full range of durations resolved by the ‘‘internal clock’’ (Santamaria, 2002; see also Madison, 2001). This model includes a bottom-up system for timing in the milliseconds range— considered important for motor coordination and computed by the cerebellum. The other component involves a top–down system for timing in the seconds to minutes range—considered important for temporal estimation and computed by frontal-striatal circuits that are able to concatenate smaller intervals generated locally or by the cerebellum. To evaluate this model, Santamaria (2002) simulated a neural network of cerebellar activity that represented the millisecond timing system. Contrary to the initial predictions of nonlinearity in the output of this network, simulations indicated that timing error increased linearly as a function of interval length, but drift in the variability of the modelÕs output showed a systematic nonlinearity (see Crystal, 2003). It was also predicted that transfer of timing between different effector systems (e.g., left and right hands) would be minimal due to motor-specific interval learning by the cerebellum. In contrast, model simulations provided evidence for transfer of timing between hands indicating an unexpected robustness of the frontal networks and a surprising degree of independence from the cerebellum. One conclusion that can be drawn from this type of analysis is that frontal-striatal circuits are apparently able to rescale durations in a proportional manner and compensate for error differences generated by the cerebellum. This type of ‘‘scalar’’ representation of intervals (see Gibbon & Church, 1990; Gibbon et al., 1984; Malapani & Fairhurst, 2002) may contribute to the observed transfer among different effector systems by allowing for the encoding of duration in a less motor-specific fashion and establishes a manner in which different timing systems (e.g., cerebellum and basal ganglia) can interact across a wider range of durations (e.g., milliseconds to hours). A classic case study of the neuropsychology of timing and time perception comes from the renowned individual H.M., who underwent a bilateral medial temporal lobe (MTL) resection that resulted in a severe memory loss following surgery (Richards, 1973). When H.M. was required to reproduce durations ranging between 1 and 300 s he demonstrated reasonably accurate timing
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for durations <20 s, but systematic underestimation for durations >20 s. Eisler and Eisler (2001) fit a powerfunction model to these reproduction data and determined that H.M.Õs psychophysical function showed a distinct break, dividing the function into a lower and an upper segment. The conclusion was that the hippocampus and other temporal lobe structures are involved in the maintenance of task instructions in short-term memory, but that once accumulated, clock readings are retained in the absence of normal temporal lobe function. Despite this and other extremely interesting case studies (e.g., Perbal, Pouthas, & Van der Linden, 2000), much remains to be determined about the neuropsychology of interval timing. Some of the main goals of the field of timing and time perception are to determine how brain lesions, neurodegenerative disease states, pharmacological treatments, and normal aging contribute to changes in the speed of internal clock and/or memory storage processes (Gibbon et al., 1997; Malapani et al., 1998; Meck, 1983, 1996; Pouthas & Perbal, 2004). The observation of hemispheric asymmetries in the effects of MTL resection on timing and time perception has renewed interest in the lateralization of temporal processing. For example, patients with right MTL resections often exhibit impairments in the precision of their timing abilities that are associated with the underestimation of retrospective duration and little or no change in the accuracy of prospective timing. In contrast, patients with left MTL resections have been shown to exhibit either no impairments or an improvement in the precision of their timing abilities that may be accompanied by an ability to correct underestimations in retrospective time judgments as well as a persistent overestimation/ underproduction of prospective duration (e.g., Drane, Lee, Loring, & Meador, 1999; Vidalaki, Ho, Bradshaw, & Szabadi, 1999). These observations are of particular interest given the recent findings that hippocampal and striatal systems can interact competitively such that damage to one system can lead to facilitation in the other (e.g., Poldrack & Packard, 2003). This ‘‘see-saw’’ effect may be explained by a number of factors, including direct anatomical projections from the MTL to areas of the dorsal striatum that have been shown to be important for interval timing as illustrated in Fig. 2 (Matell, Meck, & Nicolelis, 2003; Sorensen & Witter, 1983). Furthermore, animal studies have indicated that lesions to the hippocampus can result in increased dopaminergic transmission in the portions of the striatum to which the hippocampus projects (e.g., Lipska, Jaskiw, Chrapusta, Karoum, & Weinberger, 1992) thereby producing long-term alterations in the accuracy and precision of interval timing in the seconds-to-minutes range (e.g., Buhusi, Mocanu, & Meck, 2004; Meck, 1988; Meck, Church, & Olton, 1984; Meck, Church, Wenk, & Olton, 1987; Olton, Meck, & Church, 1987; Olton, Wenk, Church, & Meck, 1988).
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Fig. 2. Outline of the neurotransmitter systems and cortico-striatal/ hippocampal circuitry proposed to mediate timing and time perception in the seconds-to-minutes range. Descriptions of these anatomical connections and how cortico-striatal coincidence detection and resulting thalamo-cortical feedback results in the temporal control of behavior is provided by Xiao and Barbas (2004) and Matell and Meck (2000, 2004), respectively. Ach, acetylcholine; Glu, glutamate; SP, substance P; Enk, enkephalin; GABA, c-aminobutyric acid; DA, dopamine; D1, dopamine D1 receptor subtype; D2, dopamine D2 receptor subtype; GPE, globus pallidus external capsule; GPI, globus pallidus internal capsule; SNC, substantia nigra pars compacta; SNR, substantia nigra pars reticulata; and STN, subthalamic nucleus.
An intriguing example of the neuropharmacological basis of interval timing is illustrated by the results obtained from an adult participant diagnosed with attentional-deficit disorder (ADD). This patientÕs reproduction of 7- and 17-s signal durations while performing a peak-interval procedure are displayed in Fig. 3 (see Levin et al., 1996, 1998; Lustig & Meck, 2005; Rakitin et al., 1998 for procedural details). The top panel displays percent maximum response rate for the participant in an unmedicated state (NicPre) plotted as a function of the 7- and 17-s criteria. In this procedure, a blue square presented on a computer monitor is transformed to magenta at the appropriate criterion time during fixed-time training trials. Thereafter, participants are requested to reproduce the temporal criterion for a sequence of test trials after which a distribution of their responses is plotted on a relative timescale at the completion of the trial during the inter-trial interval (ITI). This ITI feedback is displayed on the computer monitor and provides the participant with information concerning the relative accuracy and precision of their timing behavior on the preceding trial. ITI feedback can be randomly presented following a fixed proportion of trials (in this case 25 and 100%). As can be seen in the top panel of the figure, when the participant is provided with ITI feedback on 100% of the trials the PI functions are centered at the correct times showing excellent accuracy of the repro-
Fig. 3. Percent maximum response rate in the peak-interval procedure plotted as a function of signal duration for a single adult participant (ALB) diagnosed with attention deficit disorder (ADD) trained at two criterion times (7 and 17 s) under two conditions of intertrial interval (ITI) feedback (25 and 100%). The top panel shows performance at these two criterion times under the two ITI feedback conditions in an unmedicated state (NicPre) and the bottom panel shows performance in a medicated state (NicPost). See Levin et al. (1996, 1998) for additional procedural details.
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duced intervals. In contrast, when ITI feedback is provided on only 25% of the trials a proportional rightward shift is observed in the timing of the 7- and 17-s intervals, reflecting a discrepancy in the accuracy of temporal reproductions that is not observed in normal participants (e.g., Lustig & Meck, 2005; Rakitin et al., 1998). This rightward shift is accompanied by a broadening of the PI functions indicating a decrease in temporal precision with lower levels of feedback. Both of these findings are consistent with a slowing of the internal clock as a function of the probability of feedback and may be the result of a deficit in attention mediated the flickering of a mode switch that gates pulses from a pacemaker into an accumulator (e.g., Lustig, 2003; Lustig & Meck, 2005; Meck & Benson, 2002; Penney, 2003; Penney, Allan, Meck, & Gibbon, 1998; Penney, Gibbon, & Meck, 2000). Interestingly, the bottom panel indicates that when the participant is given a stimulant drug (e.g., 7 mg/day transdermal nicotine skin patch) that increases dopamine levels in the brain during the NicPost condition the effects of 25% ITI feedback are enhanced and produce levels of temporal accuracy and precision that are equivalent to the 100% ITI feedback condition in both the medicated and unmedicated states. These results suggest an equivalence of the ITI feedback effects and the types of pharmacological stimulation provided to ADD patients by drugs such as nicotine and methylphenidate (see Levin et al., 1996, 1998). These findings also support the proposal that deficits in attention can lead to the underestimation of signal durations in a manner consistent with a slowing of an internal clock that is sensitive to dopaminergic manipulations whether they are produced by behavioral (ITI feedback) or pharmacological means (see Buhusi, 2003; Buhusi & Meck, 2002). In the papers that follow in this special issue of Brain and Cognition on the ‘‘Neuropsychology of Timing and Time Perception,’’ the contributing authors explore the characteristics of the interval-timing system as it is perturbed by dopaminergic antagonists and feedback (Lustig & Meck, 2005), normal aging (Rakitin, Stern, & Malapani, 2005), ParkinsonÕs disease (Perbal et al., 2005; Jurkowski, Stepp, & Hackley, 2004; Spencer & Ivry, 2005), unilateral and focal lesions of the basal ganglia (Aparicio, Diedrichsen, & Ivry, 2005; Shin, Aparicio, & Ivry, 2004), cerebellar lesions (Spencer & Ivry, 2005), schizophrenia and/or its associated risk factors (e.g., Brown et al., 2005; Penney, Meck, Roberts, Gibbon, & Erlenmeyer-Kimling, 2005), MTL resection (Melgire et al., 2005), as well as hemispheric differences in temporal processing (Grondin & Girard, 2005) and the effects of musical expertise on timing and time perception (Ehrle´ & Samson, 2005). Without question, there is still much to be learned about how modifications in the neural systems that support interval timing contribute to cognitive dysfunction.
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Nevertheless, the neuropsychological evidence presented here from a variety of subject populations argues strongly for one or more dedicated timekeeping mechanisms that involve the integration of cortical circuits with the basal ganglia, cerebellum, and hippocampus in order to support temporal cognition and motor skill learning across a broad range of stimulus contexts and timescales (see Doyon, Penhune, & Ungerleider, 2003; Gibbon et al., 1997).
Acknowledgments The author is very grateful to Sid Segalowitz for his invitation to edit this special issue on the ‘‘Neuropsychology of Timing and Time Perception’’ and for his continued support and patience throughout all phases of production. Inspiration for this volume also came from the organizers of TENNET XV, Montre´al, Canada, June 24–26, 2004 with special thanks to Simon Grondin for assembling an excellent symposium on the ‘‘Neural Bases of Timing and Time Perception.’’
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