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A Frontostriatal Circuit for Timing the Duration of Events
A Frontostriatal Circuit for Timing the Duration of Events JT Coull, Aix-Marseille Universite´, Marseille, France ã 2015 Elsevier Inc. All rights reserved.
Glossary Motor timing An estimate of stimulus duration is provided by a motor response whose duration, delay, or frequency matches that of the stimulus being timed. Perceptual timing An estimate of stimulus duration is provided by a perceptual judgement
Accurate timing is implicit in many cognitive processes, such as sensorimotor control or decision making. Closing one’s fingers at just the right moment to catch a ball requires accurate timing in the range of tens of milliseconds. Deciding if there is enough time to race safely through the amber traffic light requires accurate timing in the range of hundreds of milliseconds to seconds. But timing can also be measured more explicitly. For instance, you could probably give a fair estimate of how long it has taken to read the first few sentences of this article. But despite this ‘sense’ of time, there is no dedicated neural machinery for perceiving the duration of a stimulus in the way that there are dedicated areas of the brain for perceiving other features of a stimulus, such as color, form, and motion. This lack of functional localization may be partly due to the cognitive complexity of estimating duration (Michon, 1985; Zakay & Block, 1996). In contrast to color or spatial processing, which is almost instantaneous, temporal processing requires that the initial moment of stimulus onset be held in working memory (WM), for attention to be maintained on the stimulus throughout the duration of its presentation and for the contents of WM to be continually updated as a function of elapsing time. That accurate timing (at least in the range of hundreds of milliseconds and beyond) depends upon sustained attention and WM updating very likely contributes to the extensive corticostriatal network of regions typically observed in neuroimaging studies of duration estimation (e.g., Allman, Teki, Griffiths, & Meck, 2014; Coull & Nobre, 2008; Lewis & Miall, 2003a; Merchant, Harrington, & Meck, 2013; Wittmann, 2013). This article aims to provide a brief overview of the most significant studies and the most consistent findings in neuroimaging of timing or, more specifically, perception and estimation of duration.
Motor and Perceptual Timing Estimates of the duration of a stimulus, or the interval between two stimuli, can be measured either with a perceptual discrimination (perceptual timing), in which subjects judge whether one stimulus duration is shorter or longer than another, or by a timed motor response (motor timing), in which subjects reproduce stimulus duration with a sustained, delayed, or periodic motor act. Some of the earliest neuroimaging studies of motor timing employed finger-tapping tasks (e.g., Rao et al., 1997), in which
Brain Mapping: An Encyclopedic Reference
of the relative duration of one sensory stimulus compared to another (e.g. longer/shorter; same/ different). Rhythmic (beat-based) timing An estimate is provided of the temporal regularity/metricity of a sequence of stimuli, rather than the duration of a single stimulus.
participants first tapped along to a sensory pacing rhythm (synchronization phase) and then continued to tap at the same rate once the pacing rhythm had been removed (continuation phase). To isolate activity related to internally generated timing, brain activity recorded during the synchronization phase was subtracted from that recorded during the continuation phase (e.g., Ja¨ncke, Loose, Lutz, Specht, & Shah, 2000; Lewis, Wing, Pope, Praamstra, & Miall, 2004) or to activity induced by syncopated, rather than synchronized, tapping (Jantzen, Steinberg, & Kelso, 2004; Mayville, Jantzen, Fuchs, Steinberg, & Kelso, 2002). Generally, timing-related activity was found in the supplementary motor area (SMA), basal ganglia, inferior frontal cortex, and cerebellum. Very similar regions have also been found using temporal reproduction tasks in which, rather than a series of taps, participants produce a single, discrete motor response after a self-timed interval (Bueti, Walsh, Frith, & Rees, 2008; Coull, Davranche, Nazarian, & Vidal, 2013; Jahanshahi, Jones, Dirnberger, & Frith, 2006; Lewis & Miall, 2002; Wittmann, Simmons, Aron, & Paulus, 2010). Perceptual timing has most commonly been measured with temporal discrimination tasks, in which volunteers judge whether stimulus duration is shorter or longer than a memorized standard and provide a (nontimed) choice response. To control for sensorimotor processing, this task is compared to cognitively challenging control tasks, such as pitch discrimination in the auditory domain (e.g., Rao, Mayer, & Harrington, 2001; Schubotz, Friederichi, & von Cramon, 2000) or color (e.g., Coull, Vidal, Nazarian, & Macar, 2004), intensity (Ferrandez et al., 2003), or length (Lewis & Miall, 2003b) discrimination in the visual domain. Yet a crucial challenge for fMRI studies of timing is how to disentangle the attentional and mnemonic processes required for duration estimation, from the temporal ones. Although the need to sustain attention and update WM cannot be eliminated from tasks of timing, they can, at least, be controlled for. Since sustained attention and WM updating are dynamic, constantly evolving cognitive processes, one solution is for the control task to make similarly dynamic demands. Lewis and Miall (2003b) pioneered this approach, using a moving line stimulus, and this ingenious idea has since been adopted, and adapted, by a number of investigators (Bueti & Macaluso, 2011; Coull, Nazarian, & Vidal, 2008; Coull et al., 2004; Livesey, Wall, & Smith, 2007; Morillon, Kell, & Giraud, 2009). When both perceptual timing and control tasks require sustained attention and WM
http://dx.doi.org/10.1016/B978-0-12-397025-1.00285-2
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INTRODUCTION TO COGNITIVE NEUROSCIENCE | A Frontostriatal Circuit for Timing the Duration of Events
updating, activations in areas such as the SMA, basal ganglia, and inferior frontal cortex can be more confidently attributed to temporal processes. Using a meta-analytic approach, Wiener, Turkeltaub, and Coslett (2010) revealed that, by comparison to cognitively challenging control tasks, perceptual timing tasks consistently activate the SMA, left putamen, right prefrontal cortex, and insula, while motor timing tasks activate the SMA, prefrontal cortices bilaterally, left insula, and right inferior parietal cortex. The SMA and right inferior frontal cortex, around the frontal operculum, were the only two regions common to both perceptual and motor timing and, additionally, to timing in the subsecond and suprasecond duration ranges. However, subsequent meta-analyses have revealed functional specialization within SMA, such that preSMA is engaged preferentially by perceptual, suprasecond timing, whereas SMA proper is preferentially recruited by motor, subsecond timing (Schwartze, Rothermich, & Kotz, 2012; Wiener, Matell, & Coslett, 2011).
Context-Independent Timing? Influence of Duration Range and Modality Involvement of the right inferior frontal cortex for timing in both sub- and suprasecond duration ranges was confirmed by voxel-based lesion mapping analysis of patients with focal brain lesions (Gooch, Wiener, Hamilton, & Coslett, 2011). On the other hand, converging evidence from fMRI (Aso, Hanakawa, Aso, & Fukuyama, 2010; Lewis & Miall, 2003b; Wiener et al., 2010), structural MRI (Hayashi, Kantele, Walsh, Carlson, & Kanai, 2014), and transcranial magnetic stimulation (TMS) (Koch et al., 2007; Lee et al., 2007) suggests that the cerebellum seems to be preferentially recruited for timing in the subsecond (500 ms) range. There is less of a consensus for timing in the suprasecond range, potentially due to its reliance on a number of different cognitive processes such as attention and WM, though a recent voxel-based morphometry study suggests the right inferior parietal cortex may be particularly implicated (Hayashi et al., 2014). Yet, while the sub- versus suprasecond division is undoubtedly a useful metric, it may be rather artificial, from a cognitive point of view, to divide tasks on this basis. Empirically, it seems there is, instead, a functional distinction between timing in the tens of milliseconds range up to 300 ms (Buonomano, Bramen, & Khodadadifar, 2009; Spencer, Karmarkar, & Ivry, 2009) and timing in the range of several hundreds of milliseconds to seconds (Gibbon, Malapani, Dale, & Gallistel, 1997). Indeed, if we accept a functional division at 300 ms, rather than 1000 ms, it becomes easier to resolve some apparent inconsistencies in the literature and, more usefully, helps shed light on a hotly debated topic in the timing literature: Is time represented in a context-dependent or contextindependent manner in the brain (Ivry & Schlerf, 2008; Merchant et al., 2013)? In other words, is duration coded directly in context-specific processing areas (e.g., visual durations are coded in the visual cortex, whereas auditory durations are coded in the auditory cortex) or by an amodal, contextindependent timing network? Although there is psychophysical evidence for modalityspecific representations of time, particularly in the visual
system (e.g., Johnston, Arnold, & Nishida, 2006; Karmarkar & Buonomano, 2007; Morrone, Ross, & Burr, 2005), conclusions should be tempered by the fact that these studies almost always use very short durations. TMS techniques, on the other hand, reveal that while modality-specific timing occurs in the primary visual cortex for very short (200 ms) visual stimuli (Salvioni, Murray, Kalmbach, & Bueti, 2013), this is not the case for longer (600 ms) stimuli (Kanai, Lloyd, Bueti, & Walsh, 2011). Modality-specific timing of longer visual stimuli occurs, instead, in higher visual association areas, such as the inferior temporal cortex (MT/V5) (Bueti, Bahrami, et al., 2008; Jantzen, Steinberg, & Kelso, 2005). By contrast, context-independent timing of stimuli in this longer (several hundreds of milliseconds to seconds) time range recruits a distributed corticostriatal network (Ivry & Schlerf, 2008; Lewis & Miall, 2003a; Merchant et al., 2013). Neuroimaging studies have shown that activity in the inferior frontal cortex, SMA, and basal ganglia is independent of the modality (visual/auditory) of the stimulus being timed (Schubotz et al., 2000; Shih, Kuo, Yeh, Tzeng, & Hsieh, 2009). Interestingly, in contrast to the context-dependent nature of timing in the visual cortex, the primary auditory cortex appears to also contain an amodal representation of time, being recruited not only for auditory timing (Bueti, van Dongen, et al., 2008) but also for visual timing, even in the longer duration range (Gilae-Dotan, Kanai, & Rees, 2011; Kanai et al., 2011). Recently, Bueti, Lasaponara, Cercignani, and Macaluso (2012) provided evidence for context-independent representation of time even for very short durations. Training on a 200 ms duration in the visual modality improved timing of this duration in the auditory modality. Such cross modal transfer supports the existence of an amodal timing mechanism. Associated fMRI data revealed that amodal timing was associated with activity in the left posterior insula, an area previously linked to encoding of duration in the longer (seconds) time range (Wittmann et al., 2010).
Memory for Time The study by Bueti et al. (2012) identified amodal (as well as modality-specific) representations of time in long-term memory, that is, after 5 days of training. Other studies of perceptual timing, on the other hand, have isolated representations of time in short-term or WM. In the temporal discrimination paradigm, in which the duration of a probe stimulus is compared to that of a prior standard, encoding and storage of duration into WM occur during presentation of the standard stimulus, whereas retrieval and comparison of stimulus duration occur during presentation of the probe. Event-related fMRI studies of temporal discrimination paradigms, in both the auditory (Harrington, Zimbelman, Hinton, & Rao, 2010; Rao et al., 2001) and the visual (Coull et al., 2008; Wencil, Coslett, Aguirre, & Chatterjee, 2010) domains, have found that the basal ganglia are activated selectively during timing of the initial standard, whereas the frontal and temporal cortices are activated during timing of the probe. These convergent findings strongly suggest that the basal ganglia mediate the shortterm representation of time in WM. Incidentally, common to timing of both standard and probe stimuli was the SMA (Coull
INTRODUCTION TO COGNITIVE NEUROSCIENCE | A Frontostriatal Circuit for Timing the Duration of Events
et al., 2008; Harrington et al., 2010) whose activity has also been shown to increase as a function of stimulus duration (Morillon et al., 2009; Wencil et al., 2010). Given that timing of a currently elapsing duration is the only process common to both stages of the task, these data strongly support a role for SMA in timing an ongoing duration. The functional selectivity of the basal ganglia (particularly the putamen) for the initial encoding of duration into memory is corroborated by several other pieces of evidence. First, the basal ganglia have also been implicated selectively during the encoding, but not reproduction, phase of motor timing (Bueti & Macaluso, 2011), although this was true for durations up to 3 s but not for those substantially longer (up to 18 s) (Wittmann et al., 2010). Second, the putamen is selectively activated when subjects are required to produce their own internal representation of a variable time interval (Cunnington, Windischberger, Deecke, & Moser, 2002; Garraux et al., 2005), as opposed to one externally specified by sensory stimuli, again consistent with a role in temporal memory. Finally, significant correlations between basal ganglia activity and timing performance (Coull et al., 2008; Harrington et al., 2004) reveal that the more basal ganglia is activated during initial encoding, the more accurately participants eventually perform the task. These data suggest that the amplitude of basal ganglia activity mediates the depth of encoding of stimulus duration, resulting in a more accurate representation of time.
Distorting the Magnitude of Time Activity in the basal ganglia correlates not only with accuracy but also with the degree to which time is subjectively lengthened (Bueti & Macaluso, 2011). The perception of time is rather fragile and is susceptible to modulation by factors such as stimulus size (Xuan, Zhang, He, & Chen, 2007), location (Vicario et al., 2008), and speed or frequency (Brown, 1995; Kanai, Paffen, Hogendoorn, & Verstraten, 2006). In Bueti and Macaluso’s (2011) study, increasing the speed of the stimulus to be timed led participants to overestimate its duration. And the more time was subjectively ‘stretched’ in this way, the greater was activity in the putamen of the basal ganglia, as well as the right lateralized anterior insula/frontal operculum and superior temporal gyrus. But how can findings that putamen activity increases with the degree of overestimation (Bueti & Macaluso, 2011) be reconciled with findings that it increases as a function of enhanced memory for duration (Coull et al., 2008; Harrington et al., 2010)? The answer might lie in the results of a recent study by Dirnberger et al. (2012). They showed that the degree of temporal distortion induced by emotional stimuli was correlated with better recognition memory for those stimuli, suggesting a functional link between the overestimation of duration and memory performance. Moreover, activity in the anterior insula and putamen correlated with memory performance exclusively during trials in which stimulus duration was overestimated, further suggesting that the basal ganglia are critical in mediating the functional association between temporal distortion and memory performance. The subjective perception of time can be modulated not only by physical stimulus characteristics, but also neurochemically. Studies in animals, healthy volunteers, and patients with
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Parkinson’s disease or schizophrenia (Allman & Meck, 2012; Coull, Cheng, & Meck, 2011) have consistently implicated the dopaminergic (DA) system in timing. Specifically, diminished DA function impairs timing performance and slows down the internal clock (Buhusi & Meck, 2005). By combining psychopharmacological manipulation with functional neuroimaging, we can explore the complex relationship between cognition, neurochemistry, and anatomy in the healthy human brain and so begin to identify the anatomical bases for the DA modulation of timing. For example, Coull, Hwang, Leyton, and Dagher (2012) recently showed that DA modulation in healthy volunteers not only impaired perceptual timing performance but also attenuated activity in the basal ganglia and SMA. Moreover, these effects were correlated such that the more activity was attenuated by the DA manipulation, the more timing performance was impaired. The temporal resolution of event-related fMRI pinpointed these effects to the initial encoding stage of the task, suggesting that the DA manipulation impaired eventual timing performance by reducing activity in those areas of the brain responsible for the initial storage of temporal information into WM. More recently, timingrelated activity was found to be higher in not only the basal ganglia but also the right prefrontal cortex in carriers of a gene associated with reduced striatal D2 density (Wiener, Lee, Lohoff, & Coslett, 2014). Moreover, psychopharmacological fMRI studies of timing in patients with Parkinson’s disease reported predominantly frontal patterns of DA effect (Harrington et al., 2011; Jahanshahi et al., 2010). Together, these studies suggest that when the basal ganglia are compromised in some way, DA modulates timing by modulating activity in frontal, rather than striatal, nodes of the timing network. Rather than deliberately distorting perceived duration by pharmacological intervention or physical stimulus characteristics, a complementary approach is to harness naturally occurring individual differences in the subjective perception of time. For example, timing-induced activity in the putamen and right inferior frontal cortex is higher in those individuals with better temporal discrimination performance (Wiener et al., 2014), while activity in the SMA and right inferior frontal cortex is greater in participants who subjectively perceive time as lasting longer (Tipples, Brattan, & Johnston, 2013). The latter finding in particular confirms and extends previous findings that activity in the SMA and inferior frontal cortex also increases in line with the objective duration of a stimulus (Pouthas et al., 2005; Wencil et al., 2010), underlining the critical role of these areas in the ‘accumulation’ of information over time. Finally, while converging evidence seems to support a role for the SMA, right inferior frontal cortex, and basal ganglia in processing the magnitude of duration, processing of magnitude more generally (i.e., common to time, space, or number) seems to depend rather upon activity in the right inferior parietal cortex (Dormal, Dormal, Joassin, & Pesenti, 2012; Hayashi et al., 2013).
Rhythmic Timing Most of the aforementioned studies have investigated the timing of single durations or intervals. By contrast, rhythm perception requires that a sequence of multiple intervals be timed,
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INTRODUCTION TO COGNITIVE NEUROSCIENCE | A Frontostriatal Circuit for Timing the Duration of Events
in order to extract any temporal structure inherent in the sequence. Generally, the typical frontostriatal timing circuit described earlier is engaged to an even greater degree by rhythmic timing than by timing of single durations (Teki, Grube, Kumar, & Griffiths, 2011). More specifically, neuroimaging studies of rhythm (e.g., Chen, Zatorre, & Penhune, 2006; Ja¨ncke et al., 2000; Rao et al., 1997) have identified motor regions, such as the premotor cortex, SMA, and cerebellum, even when tasks did not require timed motor responding (Bengtsson et al., 2009; Chen, Penhune, & Zatorre, 2008; Schubotz et al., 2000). In addition, the perception of a metrical beat within complex rhythms activates the SMA and basal ganglia (Lewis et al., 2004; Bengtsson, Ehrsson, Forsberg, & Ullen, 2005; Grahn & Brett, 2007; Grahn, Henry, & McAuley, 2011; Kung, Chen, Zatorre, & Penhune, 2013) as well as reinforcing their functional interconnectivity (Grahn & Rowe, 2009). Intriguingly, the central role of the basal ganglia in rhythmic timing is not inconsistent with its role in temporal memory, discussed earlier: perceiving temporal regularity in a sequence necessarily implies that the duration of a current interval is recognized as being the same (or part of the same metrical structure) as intervals presented previously. The basal ganglia are also activated by more implicit measures of beat-based timing, when the mere presentation of a rhythmic, as opposed to an irregular, temporal structure facilitates auditory (Geiser, Notter, & Gabrieli, 2012) or visual (Marchant & Driver, 2012) discrimination of events occurring on temporally predictable beats. On the other hand, improvements in auditory and visual discrimination for events occurring on strong versus weak beats within a rhythmic structure are associated with left inferior parietal cortex activation (Bolger, Coull, & Scho¨n, 2014). Therefore, although the basal ganglia and SMA may be activated by the fundamental perception of a temporally regular beat, the left inferior parietal cortex is activated when temporal regularity (or predictability) encourages attention to be oriented toward particular beats within the rhythm, thereby optimizing processing of events occurring on those beats.
Time in the Future In synthesizing all of these findings, a simplified anatomical schema for timing emerges (Figure 1), in which the SMA and right inferior frontal cortex (in the region of the frontal operculum and insula) appear to be particularly implicated in timing a currently elapsing duration, with perhaps some suggestion of a functional dissociation between the ‘accumulation’ of temporal information in the SMA and updating of WM as a function of time in the right inferior frontal cortex. Basal ganglia activity is associated with memorizing duration, which could encompass the need to memorize successive intervals in a sequence in order to determine rhythmicity. The parietal cortices, on the other hand, appear to be less implicated in the perception of duration per se: The left inferior parietal cortex is involved more in orienting attention toward predictable moments in time, whereas the right inferior parietal cortex is implicated in processing magnitude general. A future challenge for neuroimaging studies of timing is to continue, and refine, investigations into potential zones of functional specialization within key timing areas as a function of timing characteristics, such as duration range or stimulus modality (e.g., Wiener et al., 2011; Schwartze et al., 2012). High-field (7T) imaging seems particularly suited to this endeavor. A related challenge is to improve the anatomical localization of timing-related areas. For example, some authors have highlighted the role of the inferior frontal cortex in timing, while others have emphasized the anterior insula. However, these distinct anatomical labels might simply reflect the difficulty in (subjectively) localizing activity to one of these two areas. For instance, in Wiener et al.’s (2010) meta-analysis, the x; y; z coordinates of the maximum peak of the right inferior frontal gyrus cluster, common to motor, perceptual, subsecond, and suprasecond timing, were 47, 10, 15 mm. However, this was extremely close to the peak coordinates of clusters common to subsecond motor (46, 8, 16 mm) or subsecond perceptual (46, 10, 16 mm) tasks, which were identified as the right insula. Given the spatial resolution of fMRI
Accumulation Updating
Encoding and Rhythm Prediction x = 48 mm
y = 14 mm
Magnitude z = 46 mm
Figure 1 Brain regions commonly activated by duration estimation. Each region is putatively functionally specialized for distinct aspects of timing: The SMA (pink) is implicated in the accumulation of currently elapsing temporal information; the right inferior frontal gyrus (red) in the updating of temporal information in working memory, particularly for suprasecond durations; the putamen (blue) in encoding temporal information into memory and perceiving rhythmic sequences; the left inferior parietal cortex (green) in predicting when a future event is likely to happen; and the right inferior parietal cortex (yellow) in estimating magnitude generally (temporal, spatial, or numerical). Regions were defined using the AAL regions (http://www.gin.cnrs.fr/spip.php?article217) from the WFU PickAtlas toolbox (http://fmri.wfubmc.edu/software/PickAtlas) and projected onto a template brain using MRIcron (http://www.mccauslandcenter.sc.edu/mricro/mricron/).
INTRODUCTION TO COGNITIVE NEUROSCIENCE | A Frontostriatal Circuit for Timing the Duration of Events
data (usually smoothed with an 8 mm filter), it is not clear that these areas can really be distinguished anatomically. Alternatively, these distinct anatomical labels might, in fact, belie the existence of a common functional area that straddles the anatomical boundary of these neighboring regions (Harrington et al., 2010; Livesey et al., 2007; Rao et al., 2001; Wittmann et al., 2010). Finally, the discrepancy in anatomical labeling might reflect the inadequacies of the spatial normalization procedure commonly used in group studies, in which interindividual variations in anatomy are discounted. The x; y; z coordinate identified by a group analysis might lie in the frontal operculum in one participant but in the anterior insula in another. Advances in methodologies that retain, and even harness, individual differences in anatomy may help resolve some of the apparent inconsistency in the literature.
See also: INTRODUCTION TO ACQUISITION METHODS: fMRI at High Magnetic Field: Spatial Resolution Limits and Applications; High-Field Acquisition; INTRODUCTION TO COGNITIVE NEUROSCIENCE: Music; Neuropsychopharmacology of Cognitive Flexibility; Numerosity; Prediction and Expectation; Working Memory; INTRODUCTION TO METHODS AND MODELING: Meta-Analyses in Functional Neuroimaging; Voxel-Based Morphometry; INTRODUCTION TO SOCIAL COGNITIVE NEUROSCIENCE: Emotion Perception and Elicitation; INTRODUCTION TO SYSTEMS: Directing Attention in Time as a Function of Temporal Expectation; Motion Perception; Neural Codes for Shape Perception; Primate Color Vision; Working Memory.
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Hayashi, M. J., Kantele, M., Walsh, V., Carlson, S., & Kanai, R. (2014). Dissociable neuroanatomical correlates of subsecond and suprasecond time perception. Journal of Cognitive Neuroscience, 26, 1685–1693. Ivry, R. B., & Schlerf, J. E. (2008). Dedicated and intrinsic models of time perception. Trends in Cognitive Sciences, 12, 273–280. Jahanshahi, M., Jones, C. R., Dirnberger, G., & Frith, C. D. (2006). The substantia nigra pars compacta and temporal processing. Journal of Neuroscience, 26, 12266–12273. Jahanshahi, M., Jones, C. R., Zijlmans, J., Katzenschlager, R., Lee, L., Quinn, N., et al. (2010). Dopaminergic modulation of striato-frontal connectivity during motor timing in Parkinson’s disease. Brain, 133, 727–745. Ja¨ncke, L., Loose, R., Lutz, K., Specht, K., & Shah, N. J. (2000). Cortical activations during paced finger-tapping applying visual and auditory pacing stimuli. Cognitive Brain Research, 10, 51–66. Jantzen, K. J., Steinberg, F. L., & Kelso, J. A.S (2004). Brain networks underlying human timing behavior are influenced by prior context. Proceedings of the National Academy of Sciences of the United States of America, 101, 6815–6820. Jantzen, K. J., Steinberg, F. L., & Kelso, J. A. (2005). Functional MRI reveals the existence of modality and coordination-dependent timing networks. NeuroImage, 25, 1031–1042. Johnston, A., Arnold, D. H., & Nishida, S. (2006). Spatially localized distortions of event time. Current Biology, 16, 472–479. Kanai, R., Lloyd, H., Bueti, D., & Walsh, V. (2011). Modality-independent role of the primary auditory cortex in time estimation. Experimental Brain Research, 209, 465–471. Kanai, R., Paffen, C. L.E, Hogendoorn, H., & Verstraten, F. A. J. (2006). Time dilation in dynamic visual display. Journal of Vision, 6, 1421–1430. Karmarkar, U. R., & Buonomano, D. V. (2007). Timing in the absence of clocks: Encoding time in neural network states. Neuron, 53, 427–438. Koch, G., Oliveri, M., Torriero, S., Salerno, S., Lo Gerfo, E., & Caltagirone, C. (2007). Repetitive TMS of cerebellum interferes with millisecond time processing. Experimental Brain Research, 179, 291–299. Kung, S.-J., Chen, J. L., Zatorre, R. J., & Penhune, V. B. (2013). Interacting cortical and basal ganglia networks underlying find and tapping to the musical beat. Journal of Cognitive Neuroscience, 25, 401–420. Lee, K. H., Egleston, P. N., Brown, W. H., Gregory, A. N., Barker, A. T., & Woodruff, P. W. (2007). The role of the cerebellum in subsecond time perception: Evidence from repetitive transcranial magnetic stimulation. Journal of Cognitive Neuroscience, 19, 147–157. Lewis, P. A., & Miall, R. C. (2002). Brain activity during non-automatic motor production of discrete multi-second intervals. Neuroreport, 13, 1731–1735. Lewis, P. A., & Miall, R. C. (2003a). Distinct systems for automatic and cognitively controlled time measurement: Evidence from neuroimaging. Current Opinion in Neurobiology, 13, 250–255. Lewis, P. A., & Miall, R. C. (2003b). Brain activation patterns during measurement of sub- and supra-second intervals. Neuropsychologia, 41, 1583–1592. Lewis, P. A., Wing, A. M., Pope, P. A., Praamstra, P., & Miall, R. C. (2004). Brain activity correlates differentially with increasing temporal complexity of rhythms during initialisation, synchronisation, and continuation phases of paced finger tapping. Neuropsychologia, 42, 1301–1312. Livesey, A. C., Wall, M. B., & Smith, A. T. (2007). Time perception: Manipulation of task difficulty dissociates clock functions from other cognitive demands. Neuropsychologia, 45, 321–331. Marchant, J. L., & Driver, J. (2012). Visual and audiovisual effects of isochronous timing on visual perception and brain activity. Cerebral Cortex, 23, 1290–1298. Mayville, J. M., Jantzen, K. J., Fuchs, A., Steinberg, F. L., & Kelso, J. A. S. (2002). Cortical and subcortical networks underlying syncopated and synchronized coordination revealed using fMRI. Human Brain Mapping, 17, 214–229. Merchant, H., Harrington, D. L., & Meck, W. H. (2013). Neural basis of the perception and estimation of time. Annual Review of Neuroscience, 36, 313–336.
Michon, J. A. (1985). The complete time experiencer. In J. A. Michon & J. L. J. Jackson (Eds.), Time, mind and behavior (pp. 20–54). Berlin: Springer. Morillon, B., Kell, C. A., & Giraud, A. L. (2009). Three stages and four neural systems in time estimation. Journal of Neuroscience, 29, 14803–14811. Morrone, M. C., Ross, J., & Burr, D. (2005). Saccadic eye movements cause compression of time as well as space. Nature Neuroscience, 8, 950–954. Penhune, V. B., Zattore, R. J., & Evans, A. C. (1998). Cerebellar contributions to motor timing: A PET study of auditory and visual rhythm reproduction. Journal of Cognitive Neuroscience, 10, 752–765. Pouthas, V., George, N., Poline, J. B., Pfeuty, M., Vandemoorteele, P. F., Hugueville, L., et al. (2005). Neural network involved in time perception: An fMRI study comparing long and short interval estimation. Human Brain Mapping, 25, 433–441. Rao, S. M., Harrington, D. L., Haaland, K. Y., Bobholz, J. A., Cox, R. W., & Binder, J. R. (1997). Distributed neural systems underlying the timing of movements. Journal of Neuroscience, 17, 5528–5535. Rao, S. M., Mayer, A. R., & Harrington, D. L. (2001). The evolution of brain activation during temporal processing. Nature Neuroscience, 4, 317–323. Salvioni, P., Murray, M. M., Kalmbach, L., & Bueti, D. (2013). How the visual brain encodes and keeps track of time. Journal of Neuroscience, 33, 12423–12429. Schubotz, R. I., Friederichi, A. D., & von Cramon, D. T. (2000). Time perception and motor timing: A common cortical and subcortical basis revealed by fMRI. NeuroImage, 11, 1–12. Schwartze, M., Rothermich, K., & Kotz, S. A. (2012). Functional dissociation of pre-SMA and SMA-proper in temporal processing. NeuroImage, 60, 290–298. Shih, L. Y., Kuo, W. J., Yeh, T. C., Tzeng, O. J., & Hsieh, J. C. (2009). Common neural mechanisms for explicit timing in the sub-second range. Neuroreport, 20, 897–901. Spencer, R. M. C., Karmarkar, U., & Ivry, R. B. (2009). Evaluating dedicated and intrinsic models of temporal encoding by varying context. Philosophical Transactions of the Royal Society of London B, 364, 1853–1863. Teki, S., Grube, M., Kumar, S., & Griffiths, T. D. (2011). Distinct neural substrates of duration-based and beat-based auditory timing. Journal of Neuroscience, 31, 3805–3812. Tipples, J., Brattan, V., & Johnston, P. (2013). Neural bases for individual differences in the subjective experience of short durations (less than 2 seconds). PloS One, 8, e54669. Vicario, C. M., Pecoraro, P., Turriziani, P., Koch, G., Caltagirone, C., & Oliveri, M. (2008). Relativistic compression and expansion of experiential time in the left and right space. PloS One, 3, e1716. Wencil, E. B., Coslett, H. B., Aguirre, G. K., & Chatterjee, A. (2010). Carving the clock at its component joints: Neural bases for interval timing. Journal of Neurophysiology, 104, 160–168. Wiener, M., Lee, Y. S., Lohoff, F. W., & Coslett, H. B. (2014). Individual differences in the morphometry and activation of time perception networks are influenced by dopamine genotype. NeuroImage, 89, 10–22. Wiener, M., Matell, M. S., & Coslett, H. B. (2011). Multiple mechanisms for temporal processing. Frontiers in Integrative Neuroscience, 5, 31. Wiener, M., Turkeltaub, P., & Coslett, H. B. (2010). The image of time: A voxel-wise meta analysis. NeuroImage, 49, 1728–1740. Wittmann, M. (2013). The inner sense of time: How the brain creates a representation of duration. Nature Reviews. Neuroscience, 14, 217–223. Wittmann, M., Simmons, A. N., Aron, J. L., & Paulus, M. P. (2010). Accumulation of neural activity in the posterior insula encodes the passage of time. Neuropsychologia, 48, 3110–3120. Xuan, B., Zhang, D., He, S., & Chen, X. (2007). Larger stimuli are judged to last longer. Journal of Vision, 7, 1–5. Zakay, D., & Block, R. A. (1996). The role of attention in time estimation processes. In M. A. Pastor, & J. Artieda (Eds.), Time, internal clocks and movement (pp. 143–164). New York: Elsevier Sciences.
Glossary Motor timing An estimate of stimulus duration is provided by a motor response whose duration, delay, or frequency matches that of the stimulus being timed. Perceptual timing An estimate of stimulus duration is provided by a perceptual judgement
Accurate timing is implicit in many cognitive processes, such as sensorimotor control or decision making. Closing one’s fingers at just the right moment to catch a ball requires accurate timing in the range of tens of milliseconds. Deciding if there is enough time to race safely through the amber traffic light requires accurate timing in the range of hundreds of milliseconds to seconds. But timing can also be measured more explicitly. For instance, you could probably give a fair estimate of how long it has taken to read the first few sentences of this article. But despite this ‘sense’ of time, there is no dedicated neural machinery for perceiving the duration of a stimulus in the way that there are dedicated areas of the brain for perceiving other features of a stimulus, such as color, form, and motion. This lack of functional localization may be partly due to the cognitive complexity of estimating duration (Michon, 1985; Zakay & Block, 1996). In contrast to color or spatial processing, which is almost instantaneous, temporal processing requires that the initial moment of stimulus onset be held in working memory (WM), for attention to be maintained on the stimulus throughout the duration of its presentation and for the contents of WM to be continually updated as a function of elapsing time. That accurate timing (at least in the range of hundreds of milliseconds and beyond) depends upon sustained attention and WM updating very likely contributes to the extensive corticostriatal network of regions typically observed in neuroimaging studies of duration estimation (e.g., Allman, Teki, Griffiths, & Meck, 2014; Coull & Nobre, 2008; Lewis & Miall, 2003a; Merchant, Harrington, & Meck, 2013; Wittmann, 2013). This article aims to provide a brief overview of the most significant studies and the most consistent findings in neuroimaging of timing or, more specifically, perception and estimation of duration.
Motor and Perceptual Timing Estimates of the duration of a stimulus, or the interval between two stimuli, can be measured either with a perceptual discrimination (perceptual timing), in which subjects judge whether one stimulus duration is shorter or longer than another, or by a timed motor response (motor timing), in which subjects reproduce stimulus duration with a sustained, delayed, or periodic motor act. Some of the earliest neuroimaging studies of motor timing employed finger-tapping tasks (e.g., Rao et al., 1997), in which
Brain Mapping: An Encyclopedic Reference
of the relative duration of one sensory stimulus compared to another (e.g. longer/shorter; same/ different). Rhythmic (beat-based) timing An estimate is provided of the temporal regularity/metricity of a sequence of stimuli, rather than the duration of a single stimulus.
participants first tapped along to a sensory pacing rhythm (synchronization phase) and then continued to tap at the same rate once the pacing rhythm had been removed (continuation phase). To isolate activity related to internally generated timing, brain activity recorded during the synchronization phase was subtracted from that recorded during the continuation phase (e.g., Ja¨ncke, Loose, Lutz, Specht, & Shah, 2000; Lewis, Wing, Pope, Praamstra, & Miall, 2004) or to activity induced by syncopated, rather than synchronized, tapping (Jantzen, Steinberg, & Kelso, 2004; Mayville, Jantzen, Fuchs, Steinberg, & Kelso, 2002). Generally, timing-related activity was found in the supplementary motor area (SMA), basal ganglia, inferior frontal cortex, and cerebellum. Very similar regions have also been found using temporal reproduction tasks in which, rather than a series of taps, participants produce a single, discrete motor response after a self-timed interval (Bueti, Walsh, Frith, & Rees, 2008; Coull, Davranche, Nazarian, & Vidal, 2013; Jahanshahi, Jones, Dirnberger, & Frith, 2006; Lewis & Miall, 2002; Wittmann, Simmons, Aron, & Paulus, 2010). Perceptual timing has most commonly been measured with temporal discrimination tasks, in which volunteers judge whether stimulus duration is shorter or longer than a memorized standard and provide a (nontimed) choice response. To control for sensorimotor processing, this task is compared to cognitively challenging control tasks, such as pitch discrimination in the auditory domain (e.g., Rao, Mayer, & Harrington, 2001; Schubotz, Friederichi, & von Cramon, 2000) or color (e.g., Coull, Vidal, Nazarian, & Macar, 2004), intensity (Ferrandez et al., 2003), or length (Lewis & Miall, 2003b) discrimination in the visual domain. Yet a crucial challenge for fMRI studies of timing is how to disentangle the attentional and mnemonic processes required for duration estimation, from the temporal ones. Although the need to sustain attention and update WM cannot be eliminated from tasks of timing, they can, at least, be controlled for. Since sustained attention and WM updating are dynamic, constantly evolving cognitive processes, one solution is for the control task to make similarly dynamic demands. Lewis and Miall (2003b) pioneered this approach, using a moving line stimulus, and this ingenious idea has since been adopted, and adapted, by a number of investigators (Bueti & Macaluso, 2011; Coull, Nazarian, & Vidal, 2008; Coull et al., 2004; Livesey, Wall, & Smith, 2007; Morillon, Kell, & Giraud, 2009). When both perceptual timing and control tasks require sustained attention and WM
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updating, activations in areas such as the SMA, basal ganglia, and inferior frontal cortex can be more confidently attributed to temporal processes. Using a meta-analytic approach, Wiener, Turkeltaub, and Coslett (2010) revealed that, by comparison to cognitively challenging control tasks, perceptual timing tasks consistently activate the SMA, left putamen, right prefrontal cortex, and insula, while motor timing tasks activate the SMA, prefrontal cortices bilaterally, left insula, and right inferior parietal cortex. The SMA and right inferior frontal cortex, around the frontal operculum, were the only two regions common to both perceptual and motor timing and, additionally, to timing in the subsecond and suprasecond duration ranges. However, subsequent meta-analyses have revealed functional specialization within SMA, such that preSMA is engaged preferentially by perceptual, suprasecond timing, whereas SMA proper is preferentially recruited by motor, subsecond timing (Schwartze, Rothermich, & Kotz, 2012; Wiener, Matell, & Coslett, 2011).
Context-Independent Timing? Influence of Duration Range and Modality Involvement of the right inferior frontal cortex for timing in both sub- and suprasecond duration ranges was confirmed by voxel-based lesion mapping analysis of patients with focal brain lesions (Gooch, Wiener, Hamilton, & Coslett, 2011). On the other hand, converging evidence from fMRI (Aso, Hanakawa, Aso, & Fukuyama, 2010; Lewis & Miall, 2003b; Wiener et al., 2010), structural MRI (Hayashi, Kantele, Walsh, Carlson, & Kanai, 2014), and transcranial magnetic stimulation (TMS) (Koch et al., 2007; Lee et al., 2007) suggests that the cerebellum seems to be preferentially recruited for timing in the subsecond (500 ms) range. There is less of a consensus for timing in the suprasecond range, potentially due to its reliance on a number of different cognitive processes such as attention and WM, though a recent voxel-based morphometry study suggests the right inferior parietal cortex may be particularly implicated (Hayashi et al., 2014). Yet, while the sub- versus suprasecond division is undoubtedly a useful metric, it may be rather artificial, from a cognitive point of view, to divide tasks on this basis. Empirically, it seems there is, instead, a functional distinction between timing in the tens of milliseconds range up to 300 ms (Buonomano, Bramen, & Khodadadifar, 2009; Spencer, Karmarkar, & Ivry, 2009) and timing in the range of several hundreds of milliseconds to seconds (Gibbon, Malapani, Dale, & Gallistel, 1997). Indeed, if we accept a functional division at 300 ms, rather than 1000 ms, it becomes easier to resolve some apparent inconsistencies in the literature and, more usefully, helps shed light on a hotly debated topic in the timing literature: Is time represented in a context-dependent or contextindependent manner in the brain (Ivry & Schlerf, 2008; Merchant et al., 2013)? In other words, is duration coded directly in context-specific processing areas (e.g., visual durations are coded in the visual cortex, whereas auditory durations are coded in the auditory cortex) or by an amodal, contextindependent timing network? Although there is psychophysical evidence for modalityspecific representations of time, particularly in the visual
system (e.g., Johnston, Arnold, & Nishida, 2006; Karmarkar & Buonomano, 2007; Morrone, Ross, & Burr, 2005), conclusions should be tempered by the fact that these studies almost always use very short durations. TMS techniques, on the other hand, reveal that while modality-specific timing occurs in the primary visual cortex for very short (200 ms) visual stimuli (Salvioni, Murray, Kalmbach, & Bueti, 2013), this is not the case for longer (600 ms) stimuli (Kanai, Lloyd, Bueti, & Walsh, 2011). Modality-specific timing of longer visual stimuli occurs, instead, in higher visual association areas, such as the inferior temporal cortex (MT/V5) (Bueti, Bahrami, et al., 2008; Jantzen, Steinberg, & Kelso, 2005). By contrast, context-independent timing of stimuli in this longer (several hundreds of milliseconds to seconds) time range recruits a distributed corticostriatal network (Ivry & Schlerf, 2008; Lewis & Miall, 2003a; Merchant et al., 2013). Neuroimaging studies have shown that activity in the inferior frontal cortex, SMA, and basal ganglia is independent of the modality (visual/auditory) of the stimulus being timed (Schubotz et al., 2000; Shih, Kuo, Yeh, Tzeng, & Hsieh, 2009). Interestingly, in contrast to the context-dependent nature of timing in the visual cortex, the primary auditory cortex appears to also contain an amodal representation of time, being recruited not only for auditory timing (Bueti, van Dongen, et al., 2008) but also for visual timing, even in the longer duration range (Gilae-Dotan, Kanai, & Rees, 2011; Kanai et al., 2011). Recently, Bueti, Lasaponara, Cercignani, and Macaluso (2012) provided evidence for context-independent representation of time even for very short durations. Training on a 200 ms duration in the visual modality improved timing of this duration in the auditory modality. Such cross modal transfer supports the existence of an amodal timing mechanism. Associated fMRI data revealed that amodal timing was associated with activity in the left posterior insula, an area previously linked to encoding of duration in the longer (seconds) time range (Wittmann et al., 2010).
Memory for Time The study by Bueti et al. (2012) identified amodal (as well as modality-specific) representations of time in long-term memory, that is, after 5 days of training. Other studies of perceptual timing, on the other hand, have isolated representations of time in short-term or WM. In the temporal discrimination paradigm, in which the duration of a probe stimulus is compared to that of a prior standard, encoding and storage of duration into WM occur during presentation of the standard stimulus, whereas retrieval and comparison of stimulus duration occur during presentation of the probe. Event-related fMRI studies of temporal discrimination paradigms, in both the auditory (Harrington, Zimbelman, Hinton, & Rao, 2010; Rao et al., 2001) and the visual (Coull et al., 2008; Wencil, Coslett, Aguirre, & Chatterjee, 2010) domains, have found that the basal ganglia are activated selectively during timing of the initial standard, whereas the frontal and temporal cortices are activated during timing of the probe. These convergent findings strongly suggest that the basal ganglia mediate the shortterm representation of time in WM. Incidentally, common to timing of both standard and probe stimuli was the SMA (Coull
INTRODUCTION TO COGNITIVE NEUROSCIENCE | A Frontostriatal Circuit for Timing the Duration of Events
et al., 2008; Harrington et al., 2010) whose activity has also been shown to increase as a function of stimulus duration (Morillon et al., 2009; Wencil et al., 2010). Given that timing of a currently elapsing duration is the only process common to both stages of the task, these data strongly support a role for SMA in timing an ongoing duration. The functional selectivity of the basal ganglia (particularly the putamen) for the initial encoding of duration into memory is corroborated by several other pieces of evidence. First, the basal ganglia have also been implicated selectively during the encoding, but not reproduction, phase of motor timing (Bueti & Macaluso, 2011), although this was true for durations up to 3 s but not for those substantially longer (up to 18 s) (Wittmann et al., 2010). Second, the putamen is selectively activated when subjects are required to produce their own internal representation of a variable time interval (Cunnington, Windischberger, Deecke, & Moser, 2002; Garraux et al., 2005), as opposed to one externally specified by sensory stimuli, again consistent with a role in temporal memory. Finally, significant correlations between basal ganglia activity and timing performance (Coull et al., 2008; Harrington et al., 2004) reveal that the more basal ganglia is activated during initial encoding, the more accurately participants eventually perform the task. These data suggest that the amplitude of basal ganglia activity mediates the depth of encoding of stimulus duration, resulting in a more accurate representation of time.
Distorting the Magnitude of Time Activity in the basal ganglia correlates not only with accuracy but also with the degree to which time is subjectively lengthened (Bueti & Macaluso, 2011). The perception of time is rather fragile and is susceptible to modulation by factors such as stimulus size (Xuan, Zhang, He, & Chen, 2007), location (Vicario et al., 2008), and speed or frequency (Brown, 1995; Kanai, Paffen, Hogendoorn, & Verstraten, 2006). In Bueti and Macaluso’s (2011) study, increasing the speed of the stimulus to be timed led participants to overestimate its duration. And the more time was subjectively ‘stretched’ in this way, the greater was activity in the putamen of the basal ganglia, as well as the right lateralized anterior insula/frontal operculum and superior temporal gyrus. But how can findings that putamen activity increases with the degree of overestimation (Bueti & Macaluso, 2011) be reconciled with findings that it increases as a function of enhanced memory for duration (Coull et al., 2008; Harrington et al., 2010)? The answer might lie in the results of a recent study by Dirnberger et al. (2012). They showed that the degree of temporal distortion induced by emotional stimuli was correlated with better recognition memory for those stimuli, suggesting a functional link between the overestimation of duration and memory performance. Moreover, activity in the anterior insula and putamen correlated with memory performance exclusively during trials in which stimulus duration was overestimated, further suggesting that the basal ganglia are critical in mediating the functional association between temporal distortion and memory performance. The subjective perception of time can be modulated not only by physical stimulus characteristics, but also neurochemically. Studies in animals, healthy volunteers, and patients with
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Parkinson’s disease or schizophrenia (Allman & Meck, 2012; Coull, Cheng, & Meck, 2011) have consistently implicated the dopaminergic (DA) system in timing. Specifically, diminished DA function impairs timing performance and slows down the internal clock (Buhusi & Meck, 2005). By combining psychopharmacological manipulation with functional neuroimaging, we can explore the complex relationship between cognition, neurochemistry, and anatomy in the healthy human brain and so begin to identify the anatomical bases for the DA modulation of timing. For example, Coull, Hwang, Leyton, and Dagher (2012) recently showed that DA modulation in healthy volunteers not only impaired perceptual timing performance but also attenuated activity in the basal ganglia and SMA. Moreover, these effects were correlated such that the more activity was attenuated by the DA manipulation, the more timing performance was impaired. The temporal resolution of event-related fMRI pinpointed these effects to the initial encoding stage of the task, suggesting that the DA manipulation impaired eventual timing performance by reducing activity in those areas of the brain responsible for the initial storage of temporal information into WM. More recently, timingrelated activity was found to be higher in not only the basal ganglia but also the right prefrontal cortex in carriers of a gene associated with reduced striatal D2 density (Wiener, Lee, Lohoff, & Coslett, 2014). Moreover, psychopharmacological fMRI studies of timing in patients with Parkinson’s disease reported predominantly frontal patterns of DA effect (Harrington et al., 2011; Jahanshahi et al., 2010). Together, these studies suggest that when the basal ganglia are compromised in some way, DA modulates timing by modulating activity in frontal, rather than striatal, nodes of the timing network. Rather than deliberately distorting perceived duration by pharmacological intervention or physical stimulus characteristics, a complementary approach is to harness naturally occurring individual differences in the subjective perception of time. For example, timing-induced activity in the putamen and right inferior frontal cortex is higher in those individuals with better temporal discrimination performance (Wiener et al., 2014), while activity in the SMA and right inferior frontal cortex is greater in participants who subjectively perceive time as lasting longer (Tipples, Brattan, & Johnston, 2013). The latter finding in particular confirms and extends previous findings that activity in the SMA and inferior frontal cortex also increases in line with the objective duration of a stimulus (Pouthas et al., 2005; Wencil et al., 2010), underlining the critical role of these areas in the ‘accumulation’ of information over time. Finally, while converging evidence seems to support a role for the SMA, right inferior frontal cortex, and basal ganglia in processing the magnitude of duration, processing of magnitude more generally (i.e., common to time, space, or number) seems to depend rather upon activity in the right inferior parietal cortex (Dormal, Dormal, Joassin, & Pesenti, 2012; Hayashi et al., 2013).
Rhythmic Timing Most of the aforementioned studies have investigated the timing of single durations or intervals. By contrast, rhythm perception requires that a sequence of multiple intervals be timed,
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INTRODUCTION TO COGNITIVE NEUROSCIENCE | A Frontostriatal Circuit for Timing the Duration of Events
in order to extract any temporal structure inherent in the sequence. Generally, the typical frontostriatal timing circuit described earlier is engaged to an even greater degree by rhythmic timing than by timing of single durations (Teki, Grube, Kumar, & Griffiths, 2011). More specifically, neuroimaging studies of rhythm (e.g., Chen, Zatorre, & Penhune, 2006; Ja¨ncke et al., 2000; Rao et al., 1997) have identified motor regions, such as the premotor cortex, SMA, and cerebellum, even when tasks did not require timed motor responding (Bengtsson et al., 2009; Chen, Penhune, & Zatorre, 2008; Schubotz et al., 2000). In addition, the perception of a metrical beat within complex rhythms activates the SMA and basal ganglia (Lewis et al., 2004; Bengtsson, Ehrsson, Forsberg, & Ullen, 2005; Grahn & Brett, 2007; Grahn, Henry, & McAuley, 2011; Kung, Chen, Zatorre, & Penhune, 2013) as well as reinforcing their functional interconnectivity (Grahn & Rowe, 2009). Intriguingly, the central role of the basal ganglia in rhythmic timing is not inconsistent with its role in temporal memory, discussed earlier: perceiving temporal regularity in a sequence necessarily implies that the duration of a current interval is recognized as being the same (or part of the same metrical structure) as intervals presented previously. The basal ganglia are also activated by more implicit measures of beat-based timing, when the mere presentation of a rhythmic, as opposed to an irregular, temporal structure facilitates auditory (Geiser, Notter, & Gabrieli, 2012) or visual (Marchant & Driver, 2012) discrimination of events occurring on temporally predictable beats. On the other hand, improvements in auditory and visual discrimination for events occurring on strong versus weak beats within a rhythmic structure are associated with left inferior parietal cortex activation (Bolger, Coull, & Scho¨n, 2014). Therefore, although the basal ganglia and SMA may be activated by the fundamental perception of a temporally regular beat, the left inferior parietal cortex is activated when temporal regularity (or predictability) encourages attention to be oriented toward particular beats within the rhythm, thereby optimizing processing of events occurring on those beats.
Time in the Future In synthesizing all of these findings, a simplified anatomical schema for timing emerges (Figure 1), in which the SMA and right inferior frontal cortex (in the region of the frontal operculum and insula) appear to be particularly implicated in timing a currently elapsing duration, with perhaps some suggestion of a functional dissociation between the ‘accumulation’ of temporal information in the SMA and updating of WM as a function of time in the right inferior frontal cortex. Basal ganglia activity is associated with memorizing duration, which could encompass the need to memorize successive intervals in a sequence in order to determine rhythmicity. The parietal cortices, on the other hand, appear to be less implicated in the perception of duration per se: The left inferior parietal cortex is involved more in orienting attention toward predictable moments in time, whereas the right inferior parietal cortex is implicated in processing magnitude general. A future challenge for neuroimaging studies of timing is to continue, and refine, investigations into potential zones of functional specialization within key timing areas as a function of timing characteristics, such as duration range or stimulus modality (e.g., Wiener et al., 2011; Schwartze et al., 2012). High-field (7T) imaging seems particularly suited to this endeavor. A related challenge is to improve the anatomical localization of timing-related areas. For example, some authors have highlighted the role of the inferior frontal cortex in timing, while others have emphasized the anterior insula. However, these distinct anatomical labels might simply reflect the difficulty in (subjectively) localizing activity to one of these two areas. For instance, in Wiener et al.’s (2010) meta-analysis, the x; y; z coordinates of the maximum peak of the right inferior frontal gyrus cluster, common to motor, perceptual, subsecond, and suprasecond timing, were 47, 10, 15 mm. However, this was extremely close to the peak coordinates of clusters common to subsecond motor (46, 8, 16 mm) or subsecond perceptual (46, 10, 16 mm) tasks, which were identified as the right insula. Given the spatial resolution of fMRI
Accumulation Updating
Encoding and Rhythm Prediction x = 48 mm
y = 14 mm
Magnitude z = 46 mm
Figure 1 Brain regions commonly activated by duration estimation. Each region is putatively functionally specialized for distinct aspects of timing: The SMA (pink) is implicated in the accumulation of currently elapsing temporal information; the right inferior frontal gyrus (red) in the updating of temporal information in working memory, particularly for suprasecond durations; the putamen (blue) in encoding temporal information into memory and perceiving rhythmic sequences; the left inferior parietal cortex (green) in predicting when a future event is likely to happen; and the right inferior parietal cortex (yellow) in estimating magnitude generally (temporal, spatial, or numerical). Regions were defined using the AAL regions (http://www.gin.cnrs.fr/spip.php?article217) from the WFU PickAtlas toolbox (http://fmri.wfubmc.edu/software/PickAtlas) and projected onto a template brain using MRIcron (http://www.mccauslandcenter.sc.edu/mricro/mricron/).
INTRODUCTION TO COGNITIVE NEUROSCIENCE | A Frontostriatal Circuit for Timing the Duration of Events
data (usually smoothed with an 8 mm filter), it is not clear that these areas can really be distinguished anatomically. Alternatively, these distinct anatomical labels might, in fact, belie the existence of a common functional area that straddles the anatomical boundary of these neighboring regions (Harrington et al., 2010; Livesey et al., 2007; Rao et al., 2001; Wittmann et al., 2010). Finally, the discrepancy in anatomical labeling might reflect the inadequacies of the spatial normalization procedure commonly used in group studies, in which interindividual variations in anatomy are discounted. The x; y; z coordinate identified by a group analysis might lie in the frontal operculum in one participant but in the anterior insula in another. Advances in methodologies that retain, and even harness, individual differences in anatomy may help resolve some of the apparent inconsistency in the literature.
See also: INTRODUCTION TO ACQUISITION METHODS: fMRI at High Magnetic Field: Spatial Resolution Limits and Applications; High-Field Acquisition; INTRODUCTION TO COGNITIVE NEUROSCIENCE: Music; Neuropsychopharmacology of Cognitive Flexibility; Numerosity; Prediction and Expectation; Working Memory; INTRODUCTION TO METHODS AND MODELING: Meta-Analyses in Functional Neuroimaging; Voxel-Based Morphometry; INTRODUCTION TO SOCIAL COGNITIVE NEUROSCIENCE: Emotion Perception and Elicitation; INTRODUCTION TO SYSTEMS: Directing Attention in Time as a Function of Temporal Expectation; Motion Perception; Neural Codes for Shape Perception; Primate Color Vision; Working Memory.
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