Keeping time: Effects of focal frontal lesions

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1 Neuropsychologia 44 (2006) Keeping time: Effects of focal frontal lesions Terence W. Picton a,b,, Donald T. Stuss a,b, Tim Shallice a,c,d, Michael P. Alexander a,e,f, Susan Gillingham a a The Rotman Research Institute, Baycrest Centre for Geriatric Care, 3560 Bathurst Street, Toronto, Ont., Canada M6A 2E1 b University of Toronto, Toronto, Ont., Canada c Institute of Cognitive Neuroscience, London, UK d SISSA, Trieste, Italy e Beth Israel Deaconess Medical Center, MA, USA f Harvard Medical School, MA, USA Received 20 May 2005; received in revised form 27 September 2005; accepted 2 October 2005 Available online 2 November 2005 Abstract This study examined the performance of 32 normal subjects and 39 patients with focal lesions of the frontal lobes on two simple timing tasks responding in time with a tone that regularly repeated at a rate of once every 1.5 s, and then maintaining the same regular response rhythm without any external stimulus. The hypothesis was that lesions to the right prefrontal cortex would disrupt timing performance. The two main findings were (1) an abnormally high variability in the timing performance (both self-timed and tone-timed) of patients with lesions to the right lateral frontal lobe, particularly involving Brodmann area 45 and subjacent regions of the basal ganglia; (2) an increase in the variability of timing performance as the task continued in patients with lesions to the superior medial regions of the frontal lobe. These findings indicate that the right lateral frontal lobe is crucially involved in the ongoing control of timed behavior, either because of its role in generating time intervals or in monitoring the passage of these intervals. In contrast, the superior medial regions of the frontal lobe are necessary to maintain consistent timing performance over prolonged periods of time Elsevier Ltd. All rights reserved. Keywords: Timing; Motor control; Monitoring; Variability 1. Introduction The frontal lobes are crucially involved in voluntary movements. Neurons in the precentral gyrus form the final common path for the execution of movements, and more anterior regions of the frontal lobes are involved in the control of these movements (Passingham, 1993). Although most people would believe that Lashley s serial order of behavior (1951) is played out under the supervision of these anterior regions of the brain, how the different frontal regions interact to bring this about remains unclear. Motor programming must set both the sequence of motor events and the timing of their occurrence. Several studies have looked at the effects of frontal lobe lesions on the sequencing of motor acts. The main finding is that the integrity of the dorsolateral prefrontal regions is essen- Corresponding author. Tel.: x3505; fax: address: tpicton@rotman-baycrest.on.ca (T.W. Picton). tial for self-ordered activity (e.g., Petrides, 2000; Petrides & Milner, 1982) and that the supplementary motor area on the medial surface of the frontal lobe is involved in the initiation and execution of complex sequences or novel movements (e.g., Passingham, 1993; Picard & Strick, 1996). Lesions to the frontal lobes also affect the perception of time (Mangels, Ivry, & Shimizu, 1998; Nichelli, Clark, Hollnagel, & Grafman, 1995). Some neurophysiological studies have suggested that times of up to several seconds may be estimated on the basis of sustained firing of prefrontal neurons (Kitano, Okamoto, & Fukai, 2003; Niki & Watanabe, 1979) or inhibitory interactions between these neurons (Constantinidis, Williams, & Goldman-Rakic, 2002; Lewis, 2002). Others have suggested that the timing derives from oscillatory activity (the ticking of a clock) generated in the cerebellum (Hazeltine, Helmuth, & Ivry, 1997; Keele & Ivry, 1990) or basal ganglia (Meck & Benson, 2002) with regions of the prefrontal cortex integrating this activity (counting the ticks) to assess the passage of time. A recent study has shown that lesions to the right hemisphere (either /$ see front matter 2005 Elsevier Ltd. All rights reserved. doi: /j.neuropsychologia

2 1196 T.W. Picton et al. / Neuropsychologia 44 (2006) frontal or parietal) caused significant disorders of time perception (Harrington, Haaland, & Knight, 1998). Our study focused on the role played by different regions of the frontal lobes in the timing of simple motor acts. Our experimental task required subjects to press a button in time with an auditory tone occurring regularly at a rate of once every 1.5 s. Once they had practiced this externally paced response they were asked to continue responding at the same regular rate for fifty button-presses. Similar paradigms have been used extensively to assess the variability of both of the internal clock and the response execution (Madison, 2001; Vorberg & Hambuch, 1978; Wing, 2002; Wing & Kristofferson, 1973a, 1973b). We used an interval of 1.5 s since this was longer than intervals at which normal subjects spontaneously and automatically respond (personal tempo), usually estimated at about 600 ms, and longer than the familiar intervals used in speaking, counting and music-making, usually between 200 and 1000 ms (Fraisse, 1982). It was also longer than the common 1-s interval of mechanical clocks and human experiments. However, the interval was still short enough that normal subjects could synchronize their responses to external stimuli by anticipating their timing rather than by responding to the stimuli after they had occurred, a phenomenon which normally occurs at intervals above 2 or 3 s (Mates, Müller, Radil, &Pöppel, 1994; Pöppel, 1997). We examined these two tasks in groups of patients with focal damage to different areas of the frontal lobe left dorsolateral, right dorsolateral, superior medial, and inferior medial as part of the Rotman-Baycrest Battery to Investigate Attention (ROBBIA), which we have been using to investigate how different regions of the frontal lobes contribute to attentional tasks (Stuss, Shallice, Alexander, & Picton, 1995; Stuss et al., 2005). This battery is based on the idea that the frontal lobes control the operation of schemata automatic programs for handling the flow of information in the brain through five processes. Setting organizes which schemata are activated for a particular task and if then processes determine how they interact. Monitoring checks the level of activation of particular schemata. This level of activation is primarily determined by the amount of information being handled by the schema. Activation declines when the schema is not used. However, when particular events are improbable but still important, energizing can maintain an effective level of activation. Schemata are also de-activated by lateral inhibition from other activated schemata or by direct top down inhibition. Our hypotheses were that patients with right lateral frontal lesions would not be able to perform accurately because of a deficit in accurately monitoring the passage of the intervals, and that patients with superior medial lesions would have difficulty maintaining accurate timing over prolonged periods because of a deficit in energizing. 2. Methods 2.1. Subjects We initially examined forty-three patients with focal lesions to the frontal lobes and thirty-eight age-matched normal control subjects. The frontal lesions, localized using MRI or CAT scans and a standard anatomical template (Stuss et al., 2002) were left lateral (LL) in 11, right lateral (RL) in 6, inferior medial (IM) in 15, and superior medial (SM) in 11. Four patients and six control subjects were eliminated because of insufficient data for analysis (see section on measurements ) and other subjects (eliminated from our source group for the preceding paper) were added, so that our final grouping was 10 LL, 6 RL, 14 IM, 9 SM, and 32 controls. The exact locations of the lesions, etiologies, time since injury, and handedness for most of the patients are presented in a preceding paper (Alexander, Stuss, Shallice, Picton, and Gillingham, 2005). Patients 2056, 2153, 2180, and 2185 were excluded from the present study. The superimposed lesion-locations for the patients evaluated in this experiment are shown in Fig. 1. The different etiologies were not equally represented in the different patient groups. A χ 2 test showed that the RL group had significantly fewer trauma patients than the whole group, and the IM group significantly more trauma patients and fewer tumour patients. Differences attributed to lesion location may therefore have been caused by differences in etiology (as discussed by Stuss et al., 1995). Although we considered this highly unlikely since the patients were chronic and clinically stable, we checked our most striking finding (the increased variability of timing in the RL group) by performing an etiology-based as well as localization-based ANOVA. The demographic variables, results of basic neuropsychological tests, and lesion data are presented in Table 1. We checked for any significant inter-group differences in the basic demographic, neuropsychological and lesion data using analyses of variance (ANOVAs). The only variable that showed clearly significant (p < 0.01) variation across groups was the years of education, with the LL patients having fewer than controls (and than the RL patients). There were tendencies (0.01 < p < 0.05) for the LL to score less than controls on the National Adult Reading Test Revised (NART-R) and for the SM to score less than the controls on the Boston Naming Test. One patient (in the IM group) and three control subjects were left-handed and five patients (two in the IM group and three in the SM group) were ambidextrous. Left-handed subjects responded with their left index finger whereas all others responded with their right. The results of the left-handed subjects were within 2 S.D. of the mean for their group Apparatus The paradigms were programmed using MEL2 (Psychology Software tools, Inc.) and run on a PC computer. Responses were collected on the first (leftmost) button on a MEL s200a serial response box Paradigm The experiment recorded the timing of responses in two conditions. In the first tone-paced condition, 53 brief tones occurred regularly at a rate of once every 1.5 s. The tones had a frequency of 1000 Hz, a total duration of 50 ms, rise and fall times of 4.5 ms each. The tones were played on the computer s speaker at a level of db peak SPL (about 70 db above threshold). The subjects task was to press a button with their right index finger at the same time as the tones. In the second self-paced condition, the subjects responded at the same time as the tones for three responses and, when the tones ceased, continued to respond at the same rate for another 50 responses. The introductory sequence of three tones was less than the 20 or so usually employed but, coming as it did after a block of 50 tone-paced trials, was adequate to set the timing. The two conditions were then repeated in reverse order so that there were four blocks of measurements for each subject (1 and 4 were tone-paced and 2 and 3 were self-paced) Measurements The paradigms provided two measurements. The first, available only in the tone-paced blocks, was the time of the response relative to the onset of the tone or the tone-response interval (TRI), with negative values indicating a response that preceded the tone. Since subjects generally anticipated the occurrence of the tone, this measurement varied around a mean that was close to zero. The second measurement was the inter-response interval (IRI) the time between the successive presses of the button. This measurement occurred in all blocks, and varied around the 1500-ms interval required by the task. The first three

3 T.W. Picton et al. / Neuropsychologia 44 (2006) Fig. 1. Lesion locations. The diagrams show the overlapped lesion-locations for the subjects in each of the patient groups. Darker shading indicates greater overlap. Scans were unavailable for plotting (though they had been assessed for lesion location) for one patient in the LL group and one in the IM group. Sections are taken parallel to the supraorbital-meatal line and proceed upward as the scans go from left to right in the figure. Radiological convention is followed with the left side of the brain being on the right side of the scan and vice versa. trials in each block were used to establish the timing. We analyzed 47 of the subsequent 50 measurements (eliminating the first two and last one). The recorded set of data quickly taught us that recording responses from patients and older subjects is not the same as from the young normal subjects on whom the paradigm was initially tested. Three unusual response-patterns occurred. First, subjects occasionally failed to press the button hard enough for the response to register. This was easy to recognize in the tone-paced condition since the tone would occur without any nearby response (and the program would code the trial as no-response). We eliminated these trials (1.4% of the total) from the final data set and moved all succeeding measurements in that block back one in terms of the trial number. In the self-paced condition, all that was seen was a sudden increase in the IRI to about twice that expected. We identified these measurements by calculating the difference between the present IRI and the preceding IRI, eliminating those trials (1.5% of the total) from the data set where this difference exceeded 1200 ms, and moving the succeeding measurements back one. The second abnormality, only occurring in the self-paced trials, was an unusually short IRI. This was likely due to some tremulousness causing the button to be pressed twice instead of once ( bounces in the Morse-key literature Wing & Kristofferson, 1973b). The programming eliminated any second response in the tone-paced blocks but not in the self-paced blocks. We handled these anomalies (3.5% of total) by eliminating any IRI with a value of less than 600 ms, adding this IRI to the immediately following IRI and then moving all the succeeding measurements back one. The incidence of the different anomalous trials was similar across the subject groups according to χ 2 testing (with Yates correction) at p < 0.05, except for the SM group which showed more missed trials on blocks 1 and 4 and fewer short trials (bounces) on blocks 2 and 3 compared to CTL. Having eliminated these anomalous measurements, we then eliminated from further analysis four patients and six control subjects who wound up with less than 40 measurements in any of the four blocks. The statistical analysis was then based on the first 40 measurements. The final number of subjects rejected did not differ between any of the patient groups and the controls as evaluated using χ 2 testing. The third anomaly, only occurring in the self-paced condition, was a slowly increasing IRI over the block of 40 measurements. This happened most prominently in two CTL subjects who increased their IRI to over 3000 ms in the second self-paced condition. We decided not to eliminate these data but to compensate for their drift (and lesser drifts in other subjects). We used a simple Table 1 Demographic, neuropsychological, and lesion data CTL LL RL IM SM Number (female/total) 19/32 2/10 2/6 5/14 5/9 Age (year) 49 ± ± ± ± ± 17 Education (year) 15 ± 2 13± 2 ** 16 ± 2 14± 2 14± 3 NART-R 112 ± ± 9 * 113 ± ± ± 10 Digit span 6.9 ± ± ± ± ± 1.7 Boston naming test 56 ± 3 54± 4 57± 3 53± 9 51± 3 * Beck depression inventory 5 ± 5 10± 8 11± 12 7 ± 9 8± 10 Lesion size (% brain) 1.2 ± ± ± ± 3.2 Time since injury (month) 21 ± ± 8 31± ± 15 Means ± standard deviations for all data except the numbers of subjects. NART-R is National Adult Reading Test Revised. Asterisks show significant differences from CTLs ( ** p < 0.01; * p < 0.05).

4 1198 T.W. Picton et al. / Neuropsychologia 44 (2006) linear regression to measure the slope of the change in the two self-paced blocks (in ms/response). In order to ensure that the data were reasonably stationary, we subtracted this regression estimate from the measurements, and centered the measurements over the mean value for the 40 trials. More complex modeling of the drift (e.g., Collier & Ogden, 2004; Madison, 2001) did not seem warranted given the small number of responses in each block and the small number of subjects exhibiting a clear drift. We found no significant effects of group or block on the slope of the regression line that was used to remove the drift on the self-paced trials, and the average slope was not significantly different from zero Analysis We used the standard deviation of the measurements for each individual subject as the main measure of the variability of the responses. In order to differentiate this from the standard deviation across subjects we called it the individual standard deviation (cf. Stuss, Murphy, Binns, & Alexander, 2003). The group mean of this individual standard deviation would thus estimate the group s response variability. Another terminology considers the standard deviation across subjects as a measure of disparity and the mean of the individual standard deviations as a measure of dispersion (Shammi, Bosman, & Stuss, 1998). For each block of the tone-paced conditions, we calculated the individual mean and individual standard deviation of the TRI measurement for each subject. For each block of responses (two for each condition), the individual mean and individual standard deviation of the IRI were then calculated for each subject. The IRI data were then analyzed according to the Wing and Kristofferson (1973b) model (recently reviewed by Wing, 2002). Fig. 2 shows the basic concept of the model. At a rate set to estimate the required real-time intervals, an internal timekeeper provides a trigger to initiate the response, which then occurs with a brief response delay (D) after the trigger. We shall use the terminology internal clock and motor response for these processes. Both are variable from trial to trial. On the jth trial the measured inter-response interval I j is determined by the clock interval C j and by the motor response delays on both that trial and the preceding trial: I j = C j D j 1 + D j As illustrated in the diagram, when a motor response delay is longer than its mean (e.g., D j in Fig. 1), the subsequently measured interval (I j +1 ) will tend to be shorter, and vice versa. Even if there are no mechanisms at play other than the clock trigger and the motor response delay, there is a negative correlation between the adjacent measurements. This lag-1 serial correlation can then be calculated in the following manner. First the lag-1 covariance is estimated: N (I J Ī)(I j 1 Ī) G I (1) = N 1 j=2 where N is the number of trials and Ī is the mean interval between responses. The variance of the intervals (or lag-0 covariance) is then calculated. This measurement is identical to the square of the individual standard deviation of the IRI: N (I J Ī) 2 G I (0) = N j=1 The lag-1 serial correlation ρ I (1) is then estimated as: ρ I (1) = G I(1) G I (0) The variances of the internal clock SC 2 and of the motor response S2 D are then calculated: S 2 C = G I(0) + 2G I (1) S 2 D = G I(1) These calculations indicate that the lag-1 serial correlation is generally between 0 and 0.5 depending on ratio between the variance of the clock and the variance of the motor response. Due to statistical fluctuations in the recorded data, the correlation may occasionally be positive. We decided not to reject these measurements, which were more common in the self-paced trials, so as not to bias the measurements away from a mean near zero. These issues are discussed in several papers (Harrington, Lee, Boyd, Rapcsak, & Knight, 2004; O Boyle, Freeman, & Cody, 1996; Pastor, Jahanshahi, Artieda, & Obeso, 1992; Wing, 2002). These measurements were designed specifically for paradigms using selfpaced responses, but have also been used to evaluate stimulus-paced responses (Madison, 2001; Wing, 2002). More complex models of timing behavior (Vorberg & Wing, 1996) consider how a subject corrects performance based on perceived synchronization with the pacing stimulus, but this initially shows as a more negative lag-1 serial correlation. In order to make the numbers tractable for statistical comparison across the subject-groups, we derived the square roots of the variance measurements to give individual standard deviations for the internal clock and the motor response. In case the measurement was negative, the square root was performed on the absolute value and the result then made negative (cf. Madison, 2001). Fig. 2. Clock and response times. This diagram shows the basic concept of the Wing and Kristofferson (1973b) model for the timing of discrete motor responses. There are three variables: C the interval between clock triggers, D the delay between the recognition of the trigger and the motor response, and I the measured interval between the responses.

5 T.W. Picton et al. / Neuropsychologia 44 (2006) Statistics A sequence of ANOVAs was used to evaluate the experimental effects (cf. Stuss et al., 2005). The first analysis looked at the entire group of subjects (both CTL and patients) to determine the general response to the experimental manipulations. For this we used a nested response-type (tone-paced or selfpaced) by repetition (first or second block for that response-type) design. For the TRI only one factor (repetition) was used in the ANOVA. Four subsequent separate ANOVAs were then conducted to compare each of the patient groups to CTL, and to assess interactions between group and experimental manipulations (type and repetition). These ANOVAs determined whether any patient group was behaving abnormally. If this occurred, a final ANOVA compared that patient group to all the other patients combined in order to determine if the abnormality was specific to the localization of the lesion. We used a criterion for significance of p < If the group-analysis based on large subdivisions of the frontal lobes showed significant effects, we also localized the abnormal behavior using more refined architectonic divisions (Stuss et al., 2002) based on the work of Petrides and Pandya (1994). The performance of patients with lesions to a specific area of the frontal lobe was compared to the performance of all patients who had no damage to that area using a t-test (further details are provided in Stuss et al., 2005). Areas showing differences with p < 0.05 were considered as crucial to the performance being measured, and areas with 0.05 < p < 0.10 as likely involved. 3. Results 3.1. Synchronization (TRI) The mean TRI measurements for each of the groups and for each of the blocks are shown in Table 2. A few CTL subjects and some patients may have responded to the tone (since their average TRI measure was several hundred milliseconds), but there was an overwhelming tendency to anticipate the tone, with normal subjects responding on average 9 ms ahead of the tone onset. This relative timing decreased significantly from block 1 to block 4(F = 7.8; d.f. 1,66; p < 0.01). The RL patients had more negative values than the CTL subjects (F = 6.2; d.f. 1,66; p < 0.05) but were not significantly different from the other patients. The intra-subject variability of the TRI showed no significant change from block 1 to block 4. However, the RL and SM patients both showed greater variability of performance (F = 5.3 and 5.5 respectively; d.f. 1,66; p < 0.05) than the CTL subjects. Because two groups were affected, comparisons between each of these groups and the other patients were not significant. A prominent finding was that SM patients showed a significant increase in the variability of the responses in block 4 compared to block 1 when compared to CTL subjects or to the other patients (F = 7.9; Fig. 3. Tone-response intervals. The figure shows the tone-response intervals in the second tone-paced condition (block 4) for each of the subject groups. The performance of the LL and SM patients was more variable than the CTL subjects. d.f. 1,37; p < 0.01). These results are illustrated in Fig. 3 which shows the TRI measurements in block 4 for all subjects. In this block, both the RL and SM patients were more variable than the CTL subjects. In block 1, the RL patients were more variable than the CTL but the SM were not (see data in Table 2) Accuracy and variability of timing (IRI) The mean IRI was close to the required 1500 ms in both selfpaced and tone-paced responding. There was a tendency for the IM group to underestimate the interval in the self-paced blocks compared to the CTL (1419 ms versus 1571 ms) but Table 2 Tone-response interval (ms) on tone-paced blocks CTL LL RL IM SM Ind. Mean Block 1 5 ± ± ± ± ± 206 Block 4 22 ± ± ± ± ± 189 ISD Block ± ± ± ± ± 52 Block 4 80 ± ± ± ± ± 104 Data presented are means ± standard deviations. Time is relative to the onset of the tone, with negative latencies indicating that the response preceded the tone. Ind. Mean is the mean of the 40 responses for each subject. ISD is the individual standard deviation a measure of the variability in the response timing. The RL patients were more variable than CTL subjects in both blocks. The SM patients became more variable from block 1 to 4 whereas the CTL subjects became less.

6 1200 T.W. Picton et al. / Neuropsychologia 44 (2006) Table 3 Individual standard deviations of the inter-response interval (ms) CTL LL RL IM SM Block 1 Tone-paced 107 ± ± ± ± ± 51 Block 2 Self-paced 106 ± ± ± ± ± 46 Block 3 Self-paced 101 ± ± ± ± ± 79 Block 4 Tone-paced 92 ± ± ± ± ± 73 Data shown are means ± standard deviations. The main findings were that the RL patients had significantly higher individual standard deviations than the CTL subjects and that the SM patients increased their variability in blocks 3 and 4. this difference did not reach significance (F = 3.39; d.f. 1,66; p = 0.07). The means of the individual standard deviations of the IRI are shown in Table 3. There were no significant differences between the self-paced and tone-paced blocks. The patients in the RL group had significantly greater individual standard deviations of the IRI than the CTL subjects (F = 10.1; d.f. 1,66; p < 0.01), but were not quite significantly different from all the other patients grouped together. Although the overall main effect was not significant post hoc testing showed that the RL group was significantly more variable than the LL and IM groups (p < 0.05). The lack of a simple main effect was likely because the SM patients showed increased variability in the third and fourth blocks (interaction between group and repetition, F = 9.2; d.f. 1,66; p < 0.01). This was similar to the findings in the TRI variability analysis. 1 A parallel analysis of the frontal patients based on etiology of lesion (trauma, cerebrovascular infarct, tumour resection) showed no effects (all post hoc effects p > 0.4). The variability of the IRI results is diagrammed in Fig. 4 which shows the histograms of the individual absolute deviations from the mean (the root mean square of which would be the standard deviation) for all groups in the different blocks Clock and response variability The Wing Kristofferson model allowed us to dissect the variability of the IRI into two sources (internal clock and motor response) by evaluating the correlations between adjacent trials. The average lag-1 serial correlation was negative in the tone-paced blocks and essentially zero in the self-paced blocks (F = 13.8, d.f. 1,66; p < 0.001). The values for all the patients taken together were 0.31 and 0.07 and for the controls were 0.31 and The variability of the clock as determined using the Wing Kristofferson model was significantly larger in the selfpaced blocks than in the tone-paced blocks (F = 4.2, d.f. 1,66; p < 0.05). The RL patients had significantly greater clock variability than the controls (F = 11.7, d.f. 1,166; p < 0.001) and than the other patients taken together (F = 8.3; d.f. 1,37; p < A 1 In blocks 1 and 4, the intra-individual standard deviations of the TRI (Table 2) and the IRI (Table 3) are affected by the same response variability and show the same basic pattern of results. However, the numbers are different since the standard deviation of the TRI is related to the 1500 ms timing of the tones whereas the standard deviation of the IRI combines the timing variability of two responses and is related to the mean value of the IRI which could differ from 1500 ms for each subject. significant group by repetition interaction (F = 19.5, d.f. 1,66; p < 0.001) indicated that the SM group were also abnormal, having a significantly greater variability in the third and fourth blocks. The pattern of the results is shown in Fig. 5. Motor response variability was positive in the tone-paced blocks and much greater than in the self-paced blocks (F = 9.7; d.f. 3,198; p < 0.001). However, there were no significant group effects Architectonic localization The regions of the brain associated with higher values for the IRI individual standard deviation variable are given in Table 4 for each of the four blocks. The most consistent locations are cortical areas 45A and 45B and regions of the right basal ganglia (pallidus and caudate). Right areas 6 and 8 may also be involved, particularly in the tone-timed blocks. Fig. 6 shows the locations combined across the blocks for the tone-paced (blocks 1 and 4) and self-paced (blocks 2 and 3) conditions. In order to localize the deterioration in performance that occurred in the SM group of patients, we subtracted the mean individual standard deviation of the IRI over the first two blocks from the mean standard deviation over the last two blocks for each subject and used this as a localization variable. As shown in Table 4 Localization of areas related to variability of the inter-response interval Overall Block 1 Block 2 Block 3 Block 4 R glob pall ** ** ** ** R 45B ** ** ** * R 45A ** ** ** * * R 8Ad ** * ** R caudate * * * ** R 24s * ** ** R9s * ** * R6B * * ** R 47/12 * ** * R44 ** * R8Av ** R6A ** L 47/12 * R13 * R 9/46d ** R 9dl * R8B * ** Means that the patients with lesions in those areas were significantly more variable (on the ISD of the IRI) than all the other patients at p < * Means the same comparison with 0.05 < p < 0.10.

7 T.W. Picton et al. / Neuropsychologia 44 (2006) Fig. 4. Variability of the inter-response intervals. The graph plots histograms of the absolute deviations from the mean inter-response interval. The root mean square of these values in a single subject would be equivalent to the individual standard deviation. Tone-paced trials are shown in the upper half of the graph and self-paced trials below. The histogram for the first of the two blocks of trials in each condition (block 1 for the tone-paced and block 2 for the self-paced) is given to the left of the vertical axis, and the second of the two blocks is to the right. A narrower histogram stretching more upward (i.e, those for the RL group) indicates a greater variability of the response timing. Any lopsidedness of the diagrams (e.g., in the SM group) would indicate changes in this variability between the two repeated blocks of the condition. Fig. 5. Variability of the clock. This figure shows the standard deviation of the clock timing (as calculated from the Wing Kristofferson model) for each subject group over the four blocks. The arrows highlight the main effects. The variability is consistently greater during the self-paced blocks (2 and 3). In addition, the RL group is significantly more variable than CTL and the SM group gets more variable with time. Fig. 7, this localized bilaterally to regions of the medial frontal lobe. The architectonic localization thus confirmed the localization of increased overall variability to lesions of the right lateral frontal cortex and of the abnormally increasing variability to lesions of the superior medial frontal cortices. 4. Discussion These experiments replicated the findings in the literature concerning normal performance on tasks wherein subjects keep time in response to either a regular external stimulus or an internal clock. The subjects generally anticipated the occurrence of the external stimulus rather than waiting for it to occur and then responding to it. In the tone-paced conditions all subjects showed a negative lag-1 serial correlation, which is likely associated with processing the feedback information in the tones. The patients with focal lesions to the frontal lobe performed like normal subjects, with two exceptions. Patients with right lateral lesions were more variable in their timing than normal subjects and patients with lesions to the superior medial regions of the frontal lobes showed deterioration in their performance over time. The variability of the patients with right lateral lesions may have been due to the cortical lesions or to the lesions in the subjacent basal ganglia or to some combination of these lesions. Another possibility is that the lesions may have disrupted subcortical connections among prefrontal regions or between prefrontal regions and other areas of the brain. Unfortunately, we have too few RL subjects to distinguish these possibilities. Furthermore, since we did not have any left-handed subjects in either the LL or the RL groups, we could not determine whether our right lateralization was related to cerebral dominance or not. We shall discuss our measurements, then relate our findings to those obtained in other studies (lesion studies, imaging, electrophysiology) of human time processing, and finally comment on the implications of our findings for understanding human frontal lobe function Normal and abnormal timing behavior Our measurements of the IRI individual standard deviations in the CTL group 100 ms for the tone-paced and 104 ms for the self-paced were generally similar to those reported for other groups of normal subjects. The standard deviation of the inter-response interval is greater for longer intervals (Madison, 2001; Wing & Kristofferson, 1973a), tending to be about 4 7% of the actual interval. Mates et al. (1994) reported that individual standard deviations of the IRI were between 80 and 130 ms for tone-paced responses at intervals of 1800 ms. Madison (2001) found mean standard deviations of 90 ms for 1400-ms intervals and 120 ms for 1800-ms intervals when sound-paced, and 75 and 110 ms when self-paced. Our CTL subjects were older than their subjects, and we have found that young normal subjects (age years) performed the task with less variability than the CTL subjects in this experiment: their average standard deviations were 66 and 105 ms for the tone-paced and self-paced

8 1202 T.W. Picton et al. / Neuropsychologia 44 (2006) Fig. 6. Localization of lesions associated with timing variability. The figure shows the regions of the brain where the standard deviation of the inter-response interval was largest. The analysis only showed regions in the right hemisphere. The right hemisphere is therefore illustrated for both the tone-paced and self-paced conditions. The upper diagram shows the lateral view and the lower diagram the medial view. conditions (unpublished data). Although some studies report that performance on simple motor timing tasks does not change much with aging (Vanneste, Pouthas, & Weardon, 2001), others have shown an increased variability in the production of regularly timed responses (Shammi et al., 1998) and deterioration in the estimation of intervals lasting more than several seconds (Block, Zakay, & Hancock, 1998). We found no significant differences between the performance on the self-paced and tone-paced conditions in the normal subjects. For stimulus rates of less than about 3 s, human subjects generally anticipate the occurrence of the stimulus so that their response is emitted synchronously with rather than triggered by the stimulus (Mates et al., 1994). This requires that they estimate the interval in much the same way as they are required to do in the self-paced condition. Almost all our subjects did this, although a few CTL subjects responded several hundred milliseconds after the tone in the first block. They may have been responding in reaction rather than anticipation. Clearly, there was some subject option in how the task is performed that we did not fully control by our instructions. Patients with focal frontal lobe lesions were able to perform normally on the tasks with two exceptions. First, patients with Fig. 7. Localization of lesions associated with performance deterioration. The figure shows the regions of the brain where the standard deviation of the inter-response interval increased the most between the first two blocks and the last two blocks. The right hemisphere is shown on the left and the left hemisphere on the right.

9 T.W. Picton et al. / Neuropsychologia 44 (2006) RL lesions had a significantly higher intra-subject variability in their timing than the CTL subjects. This occurred for both tonepaced and self-paced responding. Second, although SM patients performed well at the beginning of the task, their performance deteriorated in blocks 3 and 4. The model of Wing and Kristofferson (1973b) separates the variability of the IRI into that related to clock timing and that related to motor response delay. The clock timing includes the actual operation of the clock and the reading of the time, and the motor delay includes all that happens between the clock trigger being recognized and the response being executed. At the relatively long intervals that we used, the contribution of the motor delay to the variance of the response interval is not large and we found no meaningful effects on this variable. Our results indicate that the main abnormality in the RL patients is in the clock timing, and that the deterioration of performance that occurs in the SM group is also mediated by a deterioration in clock timing over time. The lag-1 serial correlation in our results was near zero in the self-paced tasks and was definitely negative in the tone-paced task. This change occurred consistently for both CTL subjects and the frontally lesioned patients. In our young normal subjects, we found mean values of 0.33 and which are very similar to those in this experiment (unpublished data). The consistently near-zero value in the self-paced task is probably caused by the variance of the clock significantly exceeding the variance of the motor delay at the 1.5-s interval (longer than that normally used in timing studies). The negative correlation in the tone-paced task would then be related to error correction as the asynchrony between the stimulus and the response is detected, the subject adjusts the timing of the response on the next trial to be longer if the present one was too short and vice versa (Madison, 2001; Wing, 2002). Although the Wing Kristofferson model was originally designed for the self-paced task, its application to the tone-paced task can, therefore, show that the subjects are attending to their behavior and adjusting their performance on the basis of how well their responses are synchronized to the stimuli. All of our subjects did this. Nevertheless, patients with RL lesions showed increased clock variability and patients with SM lesions showed deterioration in performance when the task was repeated Lesion studies of timing Two important studies proposed that lesions to either the cerebellum or the basal ganglia affect the ability of the patients to time motor acts or perceive intervals of time. Ivry and Keele (1989) found that patients with cerebellar lesions were significantly more variable than elderly controls or patients with Parkinson s disease both during a self-paced tapping task using intervals of 550 ms and when discriminating time intervals near 400 ms. An extensive study of patients with Parkinson s disease showed that they underestimated the passage of time and overestimated when they tried to reproduce a given time interval from 3 to 9 s (Pastor, Artieda, Jahanshahi, & Obeso, 1992), and that they performed repetitive movements (at rates of Hz) less accurately due to variance in both timekeeper and motor delay (Pastor, Jahanshahi, et al., 1992). The perceptual results suggest that these patients have a slow internal clock and the motor results suggest that the clock is variable. Both abnormalities were improved by treatment with levodopa, indicating and that the clock is modulated or controlled by dopamine. The idea that the cerebellum is involved for short times and the basal ganglia for longer times was raised by Ivry (1996). Fronto-striatal networks may maintain information over periods of seconds, and fronto-cerebellar networks may subserve a rapid clearance or transfer of information in the sub-second range. Subsequent studies have suggested that our understanding of the roles of the cerebellum and basal ganglia in timing is not that clear. Harrington et al. (2004) reported that patients with cerebellar infarcts are not distinguishable from normal control subjects on several measurements of timing behavior. O Boyle et al. (1996) and Harrington, Haaland, and Hermanowicz (1998) replicated the findings of Pastor, Artieda, et al. (1992) and Pastor, Jahanshahi, et al. (1992) in patients with Parkinson s Disease. However, Spencer and Ivry (2005) found that patients with Parkinson s Disease were not impaired in simple motor timing tasks (on which patients with cerebellar lesions were impaired). Aparicio, Diedrichsen, and Ivry (2005) found no timing impairment in patients with focal lesions of the basal ganglia (all right sided). Two studies have specifically considered the role of the frontal cortex in time perception. Nichelli et al. (1995) showed that patients with lesions to the frontal lobes were impaired in discriminating time durations both for short intervals between 100 and 900 ms and long intervals between 8 and 32 s. They attributed this impairment to problems in maintaining accurate representations of temporal duration. Mangels et al. (1998) found that patients with frontal lobe lesions were impaired when discriminating long intervals (near 4 s) but not short intervals (near 400 ms), whereas patients with cerebellar lesions were impaired at both. They attributed the impairments of the frontal patients to problems with supportive processes such as monitoring, and the impairments of the cerebellar patients to problems in the clock. Neither of these papers noted any asymmetries. The main issue raised by both papers is whether the frontal involvement is related specifically to timing processes or more generally to attention. One does not know what time it is if one does not look at the clock. Other studies of patients with cerebral lesions have suggested that time perception likely depends on network connections between multiple brain regions rather than focal areas. Rubia, Schuri, von Cramon, and Pöppel (1997) implicated lesions in the posterior supralenticular white matter in disordered time estimation and production with intervals of s. These lesions may have disrupted connections between cortex and striatum. Harrington, Haaland, and Hermanowicz (1998), and Harrington, Haaland, and Knight (1998), and Harrington and Haaland (1999) distinguished disorders of time perception (for 300 and 600-ms intervals) from more general perceptual disorders in patients with lesions to the right hemisphere, either frontal or parietal. They concluded that timing involves a right hemisphere network connecting the prefrontal and inferior parietal regions.

10 1204 T.W. Picton et al. / Neuropsychologia 44 (2006) Berlin, Rolls, and Kischka (2004) found that patients with lesions to the orbito-frontal cortex responded more quickly than control subjects when producing a long time interval (90 s), and also over-estimated the passage of time over a similar interval. Our results suggested a similar effect with the IM group responding more quickly in the self paced task, but this effect was not quite significant. Two studies have reported the effects of repetitive transcranial magnetic stimulation (rtms) on time estimation in normal subjects. This procedure transiently disrupts the activity of the cortical regions underlying the stimulator and can be considered a reversible lesion. Stimulation of the right dorsolateral prefrontal cortex caused subjects to underestimate a brief time intervals of 2 s (Jones, Rosenkranz, Rothwell, & Jahanshahi, 2004) or several seconds (Koch, Olivieri, & Caltagirone, 2003) whereas stimulation over the left dorsolateral prefrontal cortex or other areas did not affect performance. Lesion studies have thus implicated multiple regions of the brain in timing behavior. There may be several clocks, each appropriate to different intervals (cerebellum for milliseconds, basal ganglia for seconds and prefrontal cortex for longer times) but all regions likely participate in networks to control timed behavior. There may be some overlap in the timing abilities of the different regions so that the network may sometimes function despite lesions to particular areas. The right dorsolateral region may be an important region in these networks, perhaps as a focus for initiating, controlling or monitoring the clocks Imaging studies of motor timing The imaging study that most closely resembles ours in terms of its experimental paradigm is that of Rao et al. (1997). They used a block-design BOLD fmri study to measure regional blood flow when subjects made regular responses with the right index finger at rates of once every 300 or 600 ms in either tone-paced or self-paced conditions. Both the tone-paced and self-paced responding conditions showed activations (relative to a resting condition) in the left motor cortex, right cerebellum and right superior temporal gyrus. The right superior temporal gyrus was likely associated with auditory processing since it was also activated in control conditions recorded when subjects passively listened to the tones or paid attention to them in order to detect changes in their pitch. The self-paced condition also showed activation in the supplementary motor area, putamen, thalamus and right inferior frontal gyrus (Brodmann 44). The authors attributed the latter activation to rehearsal of the internal auditory representations and suggested that their subjects may have been timing their responses by playing out a memory of the regularly repeating tone that they had heard in the preceding tone-paced condition. Studies of Zatorre, Halpern, Perry, Meyer and Evans (1996, reviewed in Halpern, 2001) have shown that the right inferior frontal gyrus and superior temporal gyrus were both active during musical imagery. However, our young normal subjects did not often report that their behavior was directed by remembered tones and, even when it was, the imagined tones were difficult to sustain. The most common strategy was to synchronize their button press to some repetitive act such as breathing, foot-tapping, or sub-vocal counting. (Unfortunately, we did not debrief either the patients or the control subjects in the present experiment.) Furthermore, exactly what the right inferior frontal region is doing during musical imagery is not clear it may be as much monitoring or playing the melody as hearing it. Lewis, Wing, Pope, Praamstra, and Miall (2004) studied the fmri activity during the production of different tapping rhythms either synchronizing these rhythms with brief auditory cues or continuing on when the cues ceased. The continuation of the rhythm was associated with increased activation of the SMA (supplementary motor area), pre-sma, premotor cortices, and other regions. During the synchronization phase the complexity of the task correlated with activity in the right dorsolateral prefrontal regions as well as premotor and SMA regions. PET studies of subjects reproduced rapid rhythms of increasing complexity have highlighted the roles of the cerebellum in these timed behaviors (Penhune, Zatorre, & Evans, 1998). Two PET studies wherein subjects either synchronized their response to regular visual stimuli at intervals of 2700 ms (Lejeune et al., 1997), or reproduced an interval of several seconds (Macar et al., 2002) found activation of the right prefrontal regions (in addition to the striatum, cerebellum and SMA). Imaging studies have indicated that multiple regions of the brain are involved in the production of simple timed responses. Two areas that consistently show activity are the SMA region of the superior medial frontal cortex and the right lateral cortex. Our studies of focal lesions implicated both these areas in the performance of a simple periodic motor response Imaging studies of time perception Jueptner et al. (1995) using PET showed activation of the cerebellum when subjects discriminated the durations of auditory stimuli. Many recent fmri imaging studies have measured which regions of the brain are active during the perception and discrimination of time intervals. Rao, Mayer, and Harrington (2001) used an event-related design to look at cerebral blood flow when subjects compared either the timing (standard 1200 ms) or the pitch of two auditory stimuli. The right putamen and caudate were uniquely associated with encoding time intervals (first stimulus) and the right dorsolateral prefrontal cortex (Brodmann 46, 10, 9) uniquely activated during the time comparison (second stimulus) and not during the pitch comparison. The authors suggested that the basal ganglia may act as a timekeeper and that the dorsolateral prefrontal cortex may be involved in executive functions related to working memory. Lewis and Miall (2003) found activation of multiple areas of the brain when subjects discriminated stimulus durations near 600 ms (as opposed to the size of the visual stimulus), the most significant regions being the right lateral prefrontal cortex and the presma regions bilaterally. Smith, Taylor, Lidzba, and Rubia (2003) used a time perception task with intervals of s and compared this to a control condition where the order rather than the duration of the stimuli was discriminated. They found fmri activation in both supplementary motor areas, the left cerebellum and in the right lateral frontal cortex (Brodmann areas 9, 44, and 46). Because