Brain, Vol. 125, No. 1, 123-139,
January 1, 2002
© 2002 Oxford University Press
The effect of spatial and temporal information on saccades and neural activity in oculomotor structures
1Departments of Psychology and Psychiatry, McGill University, 2Montreal Neurological Institute, 3McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal and 4Douglas Hospital Research Centre, Verdun, QC, Canada Correspondence to: Dr Gillian O’Driscoll, Department of Psychology, McGill University, 1205 Dr Penfield Ave., Montreal, QC, Canada H3A 1B1 E-mail: gillian{at}hebb.psych.mcgill.ca
Received April 30, 2001. Revised July 31, 2001. Accepted August 20, 2001. .
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It has been argued that saccade generation is supported by two systems, a ‘where’ system that decides the direction and extent of an impending saccade, and a ‘when’ system that is involved in the timing of the release of fixation. We evaluated the contributions of these systems to saccade latencies, and used functional MRI to identify the neural substrates of these systems. We found that advance knowledge of the direction and the timing of an impending target movement had both overlapping and discrete effects on saccade latencies and on neural activation. Knowledge of either factor decreased regular saccade latencies. However, knowledge of target direction increased the number of predictive and express saccades while knowledge of target timing did not. The brain activation data showed that advance knowledge of the direction or the timing of the target movement activated primarily overlapping structures. The precentral gyrus, in the region of the frontal eye fields, was more active in conditions in which some aspect of the target movement was predictable than in saccade control and fixation conditions. In the basal ganglia, activation discriminated between advance knowledge of target timing and target direction. The lenticular nuclei were more active when only target timing was known in advance, while the caudate was more active when only target direction was known in advance. These data suggest that the neural structures supporting the ‘where’ and ‘when’ systems are highly overlapping, although there is some dissociation subcortically. Knowledge of target timing and target direction converge in precentral gyrus, a region where there is strong evidence of context-dependent modulation of neural activity.
Keywords: saccades; predictability; frontal eye fields; supplementary eye fields; basal ganglia
Abbreviations: BOLD= blood-oxygen-level-dependent; CPT = completely predictable task; DPT = direction predictable task; FEF = frontal eye field; fMRI = functional MRI; MSEF = motor strip eye field; PEF = parietal eye field; SCT = saccade control task; SEF = supplementary eye field; TPT = timing predictable task; vPM = ventral premotor
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Introduction |
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It has been argued that saccade generation is supported by two systems, a ‘where’ system that decides the direction and extent of an impending saccade and a ‘when’ system that is involved in the timing of the release of fixation (e.g. Findlay and Walker, 1999
). Psychophysical studies have suggested that the time to initiate a saccade can be reduced when advance knowledge is available to either of these two systems (Ross and Ross, 1981; Fischer et al., 1984; Fischer and Ramsperger, 1986). When the direction of an impending target step can be predicted, saccade latency is reduced only when the target moves in the expected direction (Carpenter and Williams, 1995). In contrast, when the timing of the target step can be predicted, latencies are reduced to targets anywhere in the visual field (Kingstone and Klein, 1993). Direction-selective facilitation probably reflects oculomotor preparation (Kowler, 1990; Paré and Munoz, 1996), the process whereby saccade programmes are partially or completely prepared before target presentation. Direction non-selective processes may reflect either fixation disengagement before target presentation—which allows the more rapid release of saccades (Reuter-Lorenz et al., 1991; Munoz and Wurtz, 1992; Fischer and Weber, 1993; Kingstone and Klein, 1993; Tam and Ono, 1994)—or a generalized ‘readiness’ to respond that may reflect attentional rather than effector-specific processes (Ross and Ross, 1981; Reuter-Lorenz et al., 1995).
When a subject has advance information about an impending movement, the faster reaction times are thought to reflect increased preparatory activity in structures that process that information. For example, tasks in which the subject knows the direction of an impending movement are associated with greater preparatory activation in motor structures than movements in which direction is not predictable. Specifically, neurones in frontal motor areas and striatum increase their activity during a delay when the direction of an impending limb movement is cued in advance relative to when it is not (Wise, 1985; Alexander and Crutcher, 1990). In humans, lateralized readiness potentials recorded from motor structures with electroencephalography are larger for movements in which the direction of an impending movement is known than when it is not (e.g. Wauschkuhn et al., 1997). Likewise, tasks in which subjects can use predictable timing information to generate responses are thought to make larger demands on timing structures than those that do not (Ivry, 1993; Harrington and Haaland, 1999). For example, basal ganglia and cerebellar hemispheres are thought to be important to timing since damage to either of these structures results in an impairment in the generation of rhythmic movements and in the synchronization of movements with a rhythmic stimulus (Ivry et al., 1988; Crawford et al., 1989; Tian et al., 1991; Ventre et al., 1992).
When a target moves rhythmically between fixed locations, saccades that track the target become predictive, with near-zero latency (Findlay, 1981; Smit and Van Gisbergen, 1989). Both the ‘where’ and ‘when’ systems are likely to contribute to such saccades, since both the direction and the timing of the target movement are known in advance. However, it is not known to what extent each system contributes, nor whether these functions are subserved by the same or different neural structures. Studies of patients with brain lesions have implicated the frontal eye fields (FEFs), basal ganglia and cerebellum in the generation of predictive saccades because lesions to these areas affect predictive saccades more than reflexive saccades (Bronstein and Kennard, 1985; Tian et al., 1991; Rivaud et al., 1994; Isotalo et al., 1995). It is not known, however, whether these lesions impair the ability to use advance knowledge of target direction, timing or both.
A recent model of saccade generation has postulated that the neural coding of the timing and direction of saccades is largely separate (Findlay and Walker, 1999). But can these two systems be neurally dissociated, given evidence that activity in at least two oculomotor structures, the FEFs and superior colliculus, seem to encode both where the saccade will go (Robinson, 1972; Bruce et al., 1985; Schall et al., 1995) and when it will be released (Hanes and Schall, 1996; Dorris et al., 1997)? This evidence would seem to suggest that these two pathways may be overlapping rather than segregated. We manipulated the type of advance information available about the target movement (direction versus timing) to evaluate the separate contributions of the ‘where’ and ‘when’ systems to saccade performance, and used functional MRI (fMRI) to identify the neural substrates of these systems. A preliminary report of these data has been published (Gagnon et al., 2000).
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Subjects
Seventeen right-handed subjects with an average age of 21.3 years (2.6 SD) participated in the psychophysical part of the experiment (12 females, five males). Of these, seven subjects (five females, two males) were scanned with fMRI. The average age of these seven subjects was 21.1 years (SD 3.1). The psychophysical results of these subjects, which are presented along with the fMRI data, did not differ from those of the entire group. Subjects reported no history of psychiatric or neurological disorders. Written informed consent was obtained prior to the scanning session and the subjects were compensated for their participation. The protocol was approved by the Research Ethics Committee of the Montreal Neurological Institute.
Psychophysical testing
Subjects performed four different saccade tasks and a fixation task (see Fig. 1). Each task lasted 30 s. In all tasks, the target was a red square subtending 0.5° x 0.5° of visual angle. In all of the saccade tasks, the target moved in 14° steps at an average rate of once per second.
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Saccade control task (SCT)
The target moved from the centre to 14° left or 14° right at random. The timing of the target’s movements were randomized between 700, 900 or 1100 ms for movements from the central position and 900, 1100 or 1300 ms for movements from the left and right positions. Thus, neither the timing nor the direction of the target movement was predictable. This task was similar to the reflexive saccade tasks used in previous neuroimaging studies (Anderson et al., 1994
; O’Driscoll et al., 1995; Doricchi et al., 1997; Petit et al., 1997).
Timing predictable task (TPT)
The target was presented in the centre for 1000 ms, after which it stepped either to 14° left or to 14° right at random. It remained at the eccentric position for 1000 ms before stepping back to the centre. Thus, in this task the timing of the target movement was predictable, but the direction of the step from the centre was not.
Direction predictable task (DPT)
The target stepped in a repeating sequence from the centre to 14° right, to the centre, to 14° left, and back again. The direction of the target movement was always predictable. The timing of the target movement was randomized in the same way as in the SCT. Thus, in this task the direction and amplitude of each target step was known in advance while the moment the target would move was not.
Completely predictable task (CPT)
The target stepped in a repeating sequence from the centre to 14° right, to the centre, to 14° left, and back again. The target remained at each location for 1000 ms. Thus, both the direction and the timing of the target movement were predictable.
Fixation
The target remained stationary in the centre of the screen. Subjects were instructed to maintain their gaze on the target for the duration of the task.
An instruction screen preceded each task and identified which component of the task would be predictable (timing, direction, both or neither). Subjects were told to track the target as best they could, and not to precede or fall behind the target.
Each saccade task and fixation were presented twice in a single ‘run’ that each subject performed four times in the laboratory session and four times in the MRI scanner. Thus each task was performed eight times for 30 s in the laboratory (and in the scanner) for a total of 240 target steps in each task. Each individual run lasted 6 min (5 min of testing, plus the time between tasks and the instruction screens). Tasks were presented in palindromic order (ABCDEEDCBA) within each run, and the order was counterbalanced across subjects using a digram-balanced Latin square to ensure that each task appeared at least once in each position, and to ensure that each task preceded and followed each of the other four tasks at least once.
The stimuli were presented on a 17 inch NEC monitor running at 135 Hz. Eye movements were monitored in the laboratory using a 250 Hz high-speed video-based infrared pupil tracker (SR Research, Mississauga, Ontario, Canada). A three-target calibration and validation was performed across 28° of visual angle prior to testing. The average fixation error on validation was <0.5°, which is consistent with the expected variability in fixation. A drift correction was calculated by the system at the start of each run.
MRI
Subjects were scanned on a 1.5 tesla Siemens Vision scanner (Siemens Medical Systems, Erlangen, Germany). A spoiled gradient-recalled echo pulse sequence [TR (repetition time) = 22 ms, TE (echo time) = 10 ms, flip angle = 30°] was used to acquire 3D high-resolution T1-weighted anatomical scans through the whole head. This yielded 170 slices with 1 mm thickness and a nominal in-plane resolution of 1 mm x 1 mm (field of view = 256 mm, matrix = 256 x 256). T2*-weighted functional images sensitive to blood-oxygen-level-dependent (BOLD) contrast were acquired using a single-shot gradient-recalled echo-planar imaging sequence (TR = 3000 ms, TE = 50 ms, flip angle = 90°). Twenty-three 6 mm thick axial–oblique slices were selected from sagittal localizer images acquired about the midline. Slice coverage was chosen so that the whole brain was scanned including the cerebellum. In-plane resolution for these images was 5 mm x 5 mm (field of view = 320 mm, matrix = 64 x 64). To minimize head movement and motion artefact, each subject’s head was immobilized using ear-stabilizing cushions and a saddle-shaped plastic guide positioned on the bridge of the subject’s nose.
Subjects viewed the stimuli in the scanner via a NEC MultiSync MT1030+ (NEC Technologies, Inc., Itasca, Ill., USA) active-matrix projector running in 1024 x 768 mode at 60 Hz (light output 1100 ANSI lumens; contrast ratio 300 : 1). The projector was connected to PC supporting EyeLink software via a DB15 VGA cable. A mirror system positioned above the head coil allowed the subjects to view a screen positioned behind them in the bore of the magnet. Subjects performed the same run in the scanner as in the psychophysical session. For each run (performed four times), 120 scans of 3 s duration were acquired, yielding a total of 480 scans for each subject.
Evaluation of head movement and blinks
As some of our activations were located posteriorly in the central sulcus (see Results), we assessed whether either head movement or blinks could account for activity differences between tasks. Head movement was recorded outside the scanner in a separate session in two subjects while they performed, head unrestrained, the same four runs as in the psychophysical and scanning experiments. Head movement was monitored with an OPTOTRAK system (Northern Digital, Inc., Bakersfield, Calif., USA), an optoelectronic position-sensing system that measures the position of infrared-emitting diodes in 3D space (200 Hz sampling rate and spatial resolution of 0.5 mm). Three infrared-emitting diodes were mounted on the headband of the eye tracker to measure head movement in the three orthogonal planes (x-, y- and z-axes). We used the standard deviation of head position as the measure of head movement amplitude in each task, and compared the amplitude across all tasks using a repeated measures one-way ANOVA (analysis of variance).
To evaluate the contribution of blinks to activity in the central sulcus (Tehovnik et al., 2000), we measured the number of blinks made in each 30 s trial of each of the five tasks. A within-subjects one-way ANOVA was used to compare the number of blinks across tasks.
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Psychophysical data
For each target step, the automated software (SR Research, Mississauga, Ontario, Canada) selected a 600 ms block of time centred on the time at which the target changed position. Within this selection, the first saccade with amplitude >3° was selected. The criteria for a saccade were set to 4000°/s2 for acceleration and 22°/s for velocity. (Saccades had to meet both criteria.) Empirical tests with this system established that these criteria detected saccades as small as 0.25° while excluding artefacts. The experimenter verified all saccade selections. The dependent variables for each saccade were latency, amplitude and peak velocity. For the TPT and SCT, the direction of the target’s movement was unpredictable from the centre to the periphery, but predictable from the periphery back to the centre. Thus, only saccades from the centre were analysed in these tasks. For each saccade variable, a one-way within-subjects ANOVA was used to test for differences among the saccade conditions, with the P-value Bonferroni corrected for multiple comparisons (
= 0.016). Two-tailed paired t-tests were used to test for differences post hoc if the overall F of the ANOVA was significant. Left and rightward saccades were also compared within each saccade task using paired t-tests, with a Bonferroni correction for multiple comparisons. For each saccade task, the percentage of predictive saccades (latency <70 ms) (Smit and Van Gisbergen, 1989), express saccades (latencies between 70 ms and 120 ms) (Fischer and Weber, 1993) and regular saccades (latencies >120 ms) were calculated. Directional errors were also tabulated.
MRI data
Individual anatomical MRI images were transformed into 3D proportional stereotaxic space (Talairach and Tournoux, 1988) using a three-dimensional image cross-correlation algorithm (Collins et al., 1994) where the MRI is resampled by a linear transform to match the target volume (a database of 305 MRI volumes transformed to Talairach space through identification of neuroanatomical landmarks) (Evans et al., 1993, 1994). Transforming each individual MRI into stereotaxic space in this manner is effective in normalizing the images for individual differences in brain size.
Data were motion-corrected by co-registering all time points using a local routine developed at the Montreal Neurological Institute, with the third scan of each run as the reference. Functional data from each run were then subjected to low-pass filtration with a 6 mm full-width half-maximum Gaussian kernel.
Observed fMRI activation (positive BOLD signals) reflects decreases in the concentration of deoxyhaemoglobin within the microvasculature of metabolically active brain areas (Ogawa et al., 1992). This paradoxical decrease in deoxyhaemoglobin concentration occurs despite an increase in oxidative metabolism due to a disproportionately large increase in blood flow (Hoge et al., 1999).
Loci of significant increases in the BOLD signal from one task to another were calculated using in-house software (Worsley et al., 2000). These programs employ a random effects analysis that uses a general linear model with correlated errors. To take into account lag in the haemodynamic response present in fMRI data, a gamma-density response function with a mean lag of 6 s and a standard deviation of 3 s was used to convolve the design matrix of the model. The analyses also accounted for autocorrelations between scans, as well as any drift artefact. The 3 s instruction screen preceding each task, as well as the 3 s ‘blank’ time after each task, were excluded from the analysis. The first two scans of each run were also excluded from the analysis to ensure the MRI signal was in steady state.
Pairwise differences between tasks were calculated for each individual subject. Each task was performed eight times, twice within each run. For each subject, the differences in BOLD signal between two tasks were calculated within each run and then averaged across the four runs. Images reflecting activity differences for each individual were then transformed into the standard Talairach stereotaxic space (in the same manner as for the anatomical images) and resampled at a higher resolution (2 x 2 x 2 mm). Group maps representing activity differences between tasks averaged across subjects were then calculated and overlaid on high resolution 3D group average anatomical scans.
Brain areas of interest in our analyses were established a priori based on neuroimaging and electrophysiological studies of saccade generation and studies of predictive saccades in neurological populations. Regions of interest included the FEFs (Bruce et al., 1985; Bruce and Borden, 1986; Rivaud et al, 1994) and adjacent premotor cortex (Fujii et al., 1998), the supplementary eye fields (SEFs) (Schlag and Schlag-Rey, 1987; Schall, 1991), the parietal eye fields (PEF) (Gnadt and Andersen, 1988; Barash et al., 1991a, b), basal ganglia (Hikosaka and Sakamoto, 1986; Crawford et al., 1989; Harrington et al., 1998) and the cerebellum (Inhoff et al., 1989; Isotalo et al, 1995). [The superior colliculus is also involved, but activation of this structure has been observed with fMRI only with a special correction for brain pulsation (DuBois and Cohen, 2000).] The PEFs were defined as located in the intraparietal sulcus, 32–58 mm above the anterior–posterior commissure line, based on previous neuroimaging studies of saccades (Muri et al., 1996; Petit et al., 1996, 1999; Berman et al., 1999). Lesion studies suggest that the lateral cerebellar hemispheres are selectively involved in the functioning of an internal timing system, whereas the medial division is preferentially involved in executing the response (Ivry et al., 1988; Malapani et al., 1998). Timing-related activation in the cerebellar hemispheres has been identified at coordinates that correspond to lobule VI (Schmahmann et al., 1999; Kawashima et al., 2000; Schubotz et al., 2000). Thus, a priori regions in the cerebellum were the vermis and underlying nuclei (within 15 mm of the midline) and lobule VI of the hemispheres. Only the above a priori regions were considered in the analyses.
Three sets of activity differences were examined. First, each saccade task was compared to fixation. Secondly, each saccade task with a predictable component (CPT, DPT and TPT) was compared with the SCT. Thirdly, we identified the brain regions that showed a significant linear increase in the BOLD signal over time within a given task to determine which brain areas increase their activity with increasing familiarity with the target movement.
The significance criterion for the comparisons of the saccade tasks to fixation and the linear increases over time was set to a t-value of 4.37. This was based on the minimum given by a random field theory and a Bonferroni correction using a search volume of 1000 mm3 (Worsley et al., 1996). Because saccade tasks in which the target had a predictable component (CPT, DPT and TPT) were expected to activate many of the same areas as the SCT, the t-value threshold for these comparisons was set to 3.0 to increase power. This threshold was combined with a minimum cluster size criterion of 383 mm3 (Cao, 1999), so that reducing the t-threshold did not increase the rate of false positives. Activation peaks that meet both magnitude and cluster size criteria are significant at P < 0.05, Bonferroni corrected.
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Psychophysical results
Directional errors were excluded from saccade analyses as these were rare and constituted only 1.9% of all saccades. There were no significant differences between leftward and rightward saccades. Thus, psychophysical data were pooled across directions. The four saccade tasks and typical performance for one subject are shown in Fig. .
Since the saccade could be partially or completely prepared in advance, we hypothesized that knowledge of target direction would facilitate saccade latency to a greater extent than knowledge of target timing. Saccade latencies were significantly different between each saccade task (Table 1). The average saccade latency for each task over time is plotted in Fig. 2. There were main effects of knowledge of target timing [F(1,6) = 20.30, P < 0.004] and target direction [F(1,6) = 145.55, P < 0.001] on saccade latencies, and a trend for an interaction [F(1,6) = 5.63, P < 0.055]. The CPT was associated with the shortest saccade latencies, followed by the DPT, the TPT and the SCT; the latencies of each task were significantly different from each other (all P-values were <0.012). The average latencies of saccades in the CPT were <70 ms, while the latencies of saccades in the DPT task were in the express saccade range (between 70 and 120 ms) and the latencies of saccades in both the TPT and SCT were in the regular saccade range (>120 ms).
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There was a significant difference in the percentage of predictive saccades [F(3,18) = 48.84, P < 0.001], express saccades [F(3,18) = 21.85, P < 0.001] and regular saccades [F(3,18) = 103.95, P < 0.001] in the four saccade tasks. In the two conditions in which direction information was available in advance (CPT and DPT), predictive saccades and express saccades occurred significantly more often than they did when direction information was not available (TPT and SCT; see Fig. 3) (all P-values were <0.005). In the TPT, there was no significant increase in predictive saccades relative to the SCT (P > 0.13). There was a trend toward an increase in the percentage of express saccades relative to the SCT (P > 0.06) when timing was predictable; however, the difference (mean ± standard error) (TPT 3% ± 0.75; SCT 2% ± 0.75) corresponded to 0.3 of one saccade between the two conditions in a single run. Thus, in conditions in which a target is fixated foveally, subjects who are untrained will generally not make predictive saccades or express saccades unless they have prior knowledge of the direction of the impending target step.
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When predictive and express saccades were excluded from the latency analyses, knowledge of target direction and timing still reduced saccade latencies. In the DPT, latencies (mean ± standard error) of regular saccades were reduced by 12 ms ± 2 compared with the regular saccades in the SCT [t(6) = 5.2, P < 0.002]. In the TPT, regular saccade latencies were reduced by 11 ms ± 1.5 relative to the SCT [t(6) = 7.05, P < 0.001]. In the CPT, when both direction and timing were known, regular saccade latency was reduced by 20 ± 5 ms, an effect that was significantly larger than the effect of either factor alone (P < 0.03).
Saccades under internal control have been reported to have reduced amplitudes and peak velocities compared with saccades that are visually guided (Bronstein and Kennard, 1987; Kalesnykas and Hallet, 1987; Smit et al., 1987). Thus, conditions in which the proportion of predictive saccades increased were expected to have lower amplitudes and peak velocities than conditions in which the saccades were predominantly visually guided. Across the four saccade tasks, there were significant differences in both amplitude [F(3,18) = 29.96, P < 0.001] and peak velocity [F(3,18) = 9.55, P < 0.001] of saccades (Table 1). Saccades in the two conditions that had a high proportion of predictive saccades (CPT and DPT) had shorter amplitudes than the conditions in which predictive saccades were few (TPT and SCT) (all P-values were <0.001). The average peak velocity of saccades was lowest in the CPT, which was significantly lower than the peak velocity in the DPT (P < 0.014), which in turn was significantly lower than the peak velocity in the SCT (all P-values were <0.019). There was a trend for the peak velocity of saccades in the DPT to be significantly lower than in the TPT (P < 0.068). Peak velocity did not differ between the TPT and the SCT (P > 0.82). These results reflect the expected effect on saccade metrics of the higher proportion of voluntary saccades in conditions in which the target direction was predictable.
Overall, the psychophysical results suggest that advance knowledge of target direction reduces regular saccade latencies and makes an important contribution to the generation of both predictive and express saccades. Advance knowledge of target timing reduces saccade latencies independently from advance knowledge of direction, possibly by facilitating fixation disengagement, or by establishing a non-specific state of ‘readiness’.
fMRI results
Saccade tasks minus fixation
In humans, the FEFs are thought to be located in area 6 along the precentral gyrus (Darby et al., 1996), near the junction of the precentral sulcus and superior frontal sulcus (for a review, see Paus, 1996). Activity in this region was significantly greater in all saccade tasks than fixation. In conditions in which the direction was known in advance (CPT and DPT), the FEFs were significantly more active bilaterally than in fixation (Table 2). When the saccade metrics could not be prepared in advance (TPT and SCT), activity increases relative to fixation reached significance in the left FEF and were sub-threshold on the right. Within the left FEF region, there were two distinct activity foci, one laterally and one medially (Fig. 4). Distinct medial and lateral peaks in FEF have been observed in some previous studies (e.g. Petit et al., 1997; Shulman et al., 1999; Gitelman et al., 2000). In the behavioural data, subjects tended to generate large initial saccades followed by small secondary saccades (Fig. ). It is possible that the medial and lateral foci correspond to the large and small saccade regions of FEFs (Petit et al., 1997; Berman et al., 1999), with small differences in gyral anatomy accounting for the presence of distinct peaks on the left and the elongated peak on the right.
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In addition to the FEFs proper, two other peaks in the precentral gyrus were found, one
1 cm dorsal to the FEF in the superior frontal gyrus in the dorsal premotor area, and another 1 cm ventral to the FEFs, in the precentral gyrus in the ventral premotor area (Table 2). Discrete activations of both of these regions have been observed in previous studies of saccades, smooth pursuit and attentive tracking (Petit et al., 1996; Doricchi et al., 1997; Culham et al., 1998; Berman et al., 1999; O’Driscoll et al., 1999, 2000; Connolly et al., 2000).
Increased activity was found in medial area 6 in all subtractions comparing saccade tasks with fixation (Table 2 and Fig. ). Inspection of the individual activation foci revealed that the peaks were centred on a medial notch in the paracentral sulcus, corresponding to the SEFs in humans (Grosbras et al., 1999).
Relative to fixation, bilateral increases in activity were observed in the putamen in all tasks with a predictable target component, but not in the SCT (Table 2). The medial cerebellum was also significantly activated in all tasks in which the target movement had a predictable component, but again not in the SCT.
Saccades to predictable target movement versus SCT
To identify oculomotor brain regions that selectively increase activity when the timing or direction of an impending saccade is known, we subtracted out the motor component of saccades by comparing activation in each of the tasks with a predictable component (CPT, DPT and TPT) with activation in the SCT in which the target movement was random. These comparisons address more directly the areas involved in the putative ‘where’ and ‘when’ systems, since the control task is matched in motor demands to the experimental tasks. The brain areas that were significantly more active in each task with a predictable component than in the SCT are reported in Table 3. Below we report the areas more active in all three saccade tasks with a predictable component than in the SCT (‘common activations’), the activity increases that were observed only when both timing and direction were known (‘combined’) and the activity differences specific to advance knowledge of target timing or direction.
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Common activations. In all tasks in which the target had a predictable component, the left dorsal FEF was more active than it was in the SCT. Although the coordinates of FEF were somewhat posterior to those observed when the tasks were compared with fixation, similarly posterior locations of the FEFs in the precentral gyrus have been reported (Petit et al., 1996
; Sweeney et al., 1996; Luna et al., 1998; Petit and Haxby, 1999). Combined. When both the direction and the timing of the target movement were predictable, activity in the right dorsal FEF and the SEF were significantly higher than in the SCT.
Timing only. When only target timing was predictable, the lenticular nuclei (Fig. 5) were significantly more active than in the SCT. Significant activity increases in the lenticular nuclei consisted of activity increases in the globus pallidus bilaterally and in the putamen on the right. The right intraparietal sulcus was also more active when the target timing was predictable than in the SCT. This activation may correspond to the PEFs localized within the intraparietal sulcus (Andersen et al., 1992; Muri et al., 1996).
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Direction only. When the direction but not the timing of an impending saccade was known in advance, the left head of caudate was significantly more active than in the SCT (Fig. ).
Increases in activity over time
Saccade latencies showed a significant linear decrease over time in the CPT (r = –0.75, P = 0.01) and DPT (r = –0.72, P = 0.02) and showed a trend in the TPT (r = –0.52, P = 0.13) (Fig. ). Everling and Munoz (2000) found that pre-saccadic activity in FEFs was correlated with saccade reaction time, such that higher FEF activity was related to shorter latencies. Electrophysiological studies have shown that neurones in SEF increase their activity over time as a monkey learns novel oculomotor associations (Chen and Wise, 1995). Thus, we hypothesized that oculomotor areas subserving performance changes over time would increase their activity with increased exposure to the target in the predictable conditions, but not in the SCT or fixation.
Activity in the precentral gyrus and in the dorsomedial frontal cortex showed significant linear increases within each repetition of each of the predictable saccade conditions (Table 4 and Fig. 6), but not in the SCT or fixation. The precentral gyrus increases were located along the central rather than precentral sulcus, and thus were posterior to the FEF proper. In the CPT, the linear increases in precentral gyrus were bilateral while in the TPT and DPT they were found in the left hemisphere only. Since saccades to the left and right did not differ, these differences could reflect a greater contribution of the left precentral gyrus to oculomotor learning in humans.
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Evaluation of the contribution of head movement and blinks to activation
Both the eyeblink region and head movement region of motor cortex are located along the central sulcus posterior to the FEF proper (Rasmussen and Penfield, 1948
). Either of these two factors could account for the location of our posterior activations in the central sulcus (Figs and 4). Furthermore, blinks are known to produce modest increases in FEF activity (Bodis-Wollner et al., 1999).
We were able to exclude both head movement and blink rate as contributors to activity differences between tasks and to the increase in activity along the central sulcus. The amplitude of head movement was small in all tasks (standard deviations of position measured in degrees, ± standard error: CPT 0.05 ± 0.01; DPT 0.05 ± 0.01; TPT 0.04 ± 0.01; SCT 0.06 ± 0.01; fixation 0.07 ± 0.02). Head movement did not differ between tasks [F(4,4) = 1.94, P > 0.27]. Amplitude of head movement did not increase with time in any task (all P-values were >0.4). Although two subjects is not an adequate sample size to truly assess head movement effects, the small amplitude of the head movements (1° in all conditions) suggests that head movements are not an important contributor to the activations. Further, our findings are consistent with data from a previous study (Darby et al., 1996) in which EMG activity was recorded from the sternocleidomastoid muscle and was found not to increase during the performance of saccades of similar amplitudes to those generated in the current study.
In general, subjects made few blinks in the saccade tasks (mean ± standard error) [CPT 2.4 ± 1; DPT 2.2 ± 0.8; TPT 1.7 ± 0.6; SCT 1.5 ± 1.1; fixation 14.5 ± 5.5: F(4,24) = 7.90, P < 0.001]. There were significantly more blinks during fixation than during each of the saccade tasks (all P-values were <0.04). There were no significant differences in blink rate between saccade tasks with a predictable component and the SCT, and there were no significant changes in blink rate over time (all P-values were >0.3). Since there were more blinks in fixation than in the saccade tasks, activity increases during the saccade tasks relative to fixation cannot be related to blinks. Likewise, as blinks did not differ between tasks with a predictable component and the SCT, they cannot account for the activity differences between these tasks. Finally, since blink rate did not change over time in any of the tasks, they cannot account for the changes over time observed along the central sulcus.
Overall, the behaviour that did change with time was saccade-related (i.e. latency), suggesting that the increase in activity with time was not related to artefact, but may have subserved relevant performance changes.
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Advance knowledge of the direction and the timing of an impending target movement had mainly overlapping effects on saccade latencies and on neural activity, although discrete effects were also found. Knowledge of either direction or timing decreased the latency of regular saccades, but only knowledge of target direction increased the number of predictive and express saccades (Fig. ). Advance knowledge of target direction and target timing activated common neural structures. Greater activity in the precentral gyrus (in the region of the FEFs) was observed when knowledge of direction or timing or both were available compared with the saccade condition when neither was available. The basal ganglia were the areas where activity distinguished between knowledge of target direction and timing. There was greater activity in the caudate nucleus when the target direction was known in advance, but greater activity in the lenticular nucleus when timing information was known in advance. These findings will be discussed in relation to previous electrophysiological, lesion and neuroimaging studies.
Convergence in the precentral gyrus
It has previously been postulated that the ‘where’ and ‘when’ components of saccade generation are integrated in the FEFs (Frens et al., 1999; Quaia and Optican, 1999). This idea is supported by findings that: (i) neurones in the FEFs have fixed-vector movement fields specifying where to direct a saccade (Bruce et al., 1985); and (ii) activity in FEFs prior to a saccade is negatively correlated with saccade latency (Hanes and Schall, 1996; Everling and Munoz, 2000). Our results are consistent with this hypothesis, as FEF activity was modulated by advance knowledge of both target direction and target timing, and was greatest with knowledge of both (Fig. and Tables 2 and 3).
Our results are in accord with single-unit studies that have shown that the precentral gyrus, which in humans includes the FEFs, has context-dependent or ‘set-related’ activity that reflects the interface of cognition and motor control (Georgopoulos, 2000). For example, the level of activity in FEFs is different for movements made toward compared with away from a target (e.g. O’Driscoll et al., 1995; Connolly et al., 2000; Everling and Munoz, 2000). Within a task, activity in FEFs is primed by experience with the target in preceding trials (Hanes et al., 1998; Bichot and Schall, 1999). Thus, our results and those in non-human primates suggest that the FEFs do not code only saccade metrics but also the context in which the saccade is made.
The condition with the highest FEF activity, the CPT, elicited the highest proportion of predictive and express saccades (Table 1 and Fig. ). In humans, lesions to the FEFs abolish predictive saccades, but have minimal effects on regular saccades (Rivaud et al., 1994). Consistent with this, frontal cortical potentials are significantly larger for anticipatory saccades (i.e. predictive saccades) and express saccades than for regular saccades (Everling et al., 1996). In non-human primates, the level of pre-stimulus activity in FEFs is negatively related to saccadic reaction times, and is higher for express saccades than regular saccades (Everling and Munoz, 2000). A similar pattern is observed in the superior colliculus; activity in build-up neurones is higher for express saccades than regular saccades, and is highest for anticipations or predictive saccades (Dorris and Munoz, 1998). The FEFs have been postulated to be the source of the activity increases in the superior colliculus (Everling and Munoz, 2000; Sommer and Wurtz, 2000), as the FEFs project to the superior colliculus (Fries, 1984; Stanton et al., 1988b), and neurones in the FEFs are involved in both ‘fixation disengagement’ (Dias and Bruce, 1994; Everling and Munoz, 2000) and oculomotor preparation (Thompson et al., 1996). Both of these functions are likely to be important to the normal generation of predictive and express saccades.
In our study, neural activity in the precentral gyrus increased over time in each of the saccade tasks with predictable target movement, but not during the SCT or fixation (Fig. and Table 4). Thus, these increases seem to be specific to the conditions where experience expedited saccade generation. The increases were localized along the central sulcus, rather than the precentral sulcus, and thus were posterior to the FEF proper (Paus, 1996). The location of this activation could correspond to a second eye field reported in humans, located in the motor strip [motor strip eye field (MSEF)] (Rasmussen and Penfield, 1948; Tehovnik et al., 2000). In terms of its location, the MSEF could be the human homologue of the ventral premotor (vPM) eye field, which was described by Fujii et al. (1998) as being directly posterior to the spur of the arcuate sulcus (i.e. FEFs, Bruce et al., 1985) and adjacent to motor area 4. Since area 4 in humans is buried in the central sulcus (Brodmann, 1909; Economo and Koskinas, 1925), the homologue of the vPM eye field would be expected to border the central sulcus. Microstimulation of the vPM eye field in monkey elicits saccades that are craniotopically, rather than retinotopically, organized (Fujii et al., 1998). Voluntary, internally guided saccades are thought to be coded in craniotopic, rather than retinotopic, coordinates (Allin et al., 1996). If the MSEF corresponds to the vPM eye field, the increasing activation over time along the central sulcus may be related to a behavioural transition from retinally guided to internally guided saccades (Fig. ).
SEFs
In neuroimaging studies, SEF activation is generally observed during all saccade tasks (Anderson et al., 1994; Sweeney et al., 1996), and is enhanced when subjects are required to generate saccade sequences (Petit et al., 1996; Kawashima et al., 1998). Lesions to the SEF in humans do not affect single saccades, but do impair the execution of saccade sequences (Gaymard et al., 1990, 1993). In our study, the SEF was significantly more active in all saccade conditions than it was in fixation (Fig. and Table 2), and was significantly more active in the CPT than in the SCT (Table 3). In the CPT, saccades were generated in a sequence under mainly internal control. In contrast, in the DPT, in which SEF activation did not differ from the SCT, the movements were triggered by an unpredictable start signal that probably made it disadvantageous to prepare more than one saccade at a time. In the TPT, the saccade could not be prepared in advance since the direction of the movement was unknown. Thus, the pattern of SEF activation observed here is consistent with the notion that the SEF is involved in the generation of all saccades (Schlag and Schlag-Rey, 1987), and plays a larger role in tasks that involve the generation of saccade sequences (Sommer and Tehovnik, 1999).
Another important role ascribed to SEFs is motor learning. Several studies have reported that activity in SEFs increases during the learning of novel motor associations (Mann et al., 1988; Chen and Wise, 1995). Lesions to the dorsomedial frontal cortex impair the acquisitions of motor routines (Ackermann et al., 1996; Nakamura et al., 1999). Our data are consistent with the role of the SEFs in motor learning. Activity in this region increased significantly over time in all tasks with a predictable component, that is, in all tasks in which performance could be improved with experience, but did not significantly increase in fixation or the saccade control condition.
The increases over time in the dorsomedial frontal cortex were located posterior to the increases in activity observed in the subtractions. It is possible that the more posterior region corresponds to the supplementary motor area rather than the SEF, and could be the source of the ‘readiness potential’ observed at the vertex of the brain with electroencephalography. The ‘readiness potential’ is not effector-specific (it is observed during hand and eye movements), is stronger during voluntary than reflexive responses (Porter and Lemon, 1995), and is negatively correlated with reaction time (Rohrbaugh et al., 1976). Thus, increases in activity in this region in all the predictive saccade conditions may be related to a ‘readiness’ or ‘motor-set’ that increases with experience on those tasks and facilitates saccade generation.
Differentiation of the pathways in basal ganglia
Although we found that the ‘where’ and ‘when ‘ systems activated overlapping neural structures, activity within the basal ganglia distinguished between conditions in which the timing versus the direction of the target movement was predictable (Fig. and Table 3). The lenticular nuclei, including the right putamen and the globus pallidus bilaterally, were significantly more active in the TPT than the SCT. The left caudate was significantly more active in the DPT than the SCT.
The putamen, like the caudate, receives projections from FEF (Stanton et al., 1988a; Cui et al., 2000) and is thus well positioned to play a role in the guidance of saccades. Several studies have suggested that the putamen is critically involved in tasks requiring movement timing (Kimura, 1986; Kimura et al., 1990; Jaeger et al., 1995) and that, in humans, the right putamen may play a larger role (Rao et al., 2001). In non-human primates, a population of putamen neurones have a response that is time-locked to the target; these neural responses are observed only when the stimulus will elicit a movement, suggesting that they are not strictly sensory, but are involved in the rapid initiation of a behavioural response (Romo et al., 1992). The increase in activity in putamen in the repetitive timing condition is consistent with such an interpretation, since responses in the TPT were visually guided, but with significantly shorter latencies than those in the SCT. Surprisingly, the CPT was not associated with greater activation of putamen than the SCT. However, in single-unit studies, preparatory activity in the putamen has been shown to increase for each sensorially triggered movement. When a sequence of movements is triggered, the activity increases only until the initiation of the first movement of the sequence (Kimura, 1990), and does not persist during the execution of movements under internal control. Thus, the CPT may not have been associated with greater activation of the putamen because in this condition, in which the eye movements tended to precede the stimulus, the movements were no longer tied to the visual stimulus but rather were executed as a sequence under internal control.
In the DPT, there was robust activation of caudate that was not observed during the TPT. Previous studies have provided support for the notion that caudate selectively codes ‘where’ information, particularly when the ‘where’ information can facilitate movement preparation (Postle and D’Esposito, 1999a, b). However, several neuroimaging studies of memory-guided saccades (in which impending direction is known) have failed to activate caudate (Anderson et al., 1994; O’Sullivan et al., 1995; Sweeney et al., 1996). Further research is needed to clarify the specific conditions in which caudate activity will increase with direction information.
Acknowledgements
We would like to thank Daniel Guitton, Ph.D. and Tomas Paus, MD, Ph.D. for comments on an earlier version of this manuscript; Douglas Shiller, M.Sc. for running the OPTOTRAK system and providing the head movement data; Eyal Reingold, Ph.D. and David Stampe, Ph.D. (SR Research, Mississauga, Ontario, Canada) for developing the eye movement software; and Keith Worsley, Ph.D. and Valentina Petre for assistance with the fMRI analysis. This work was supported by a Natural Sciences and Engineering Research Council (NSERC) of Canada Graduate Scholarship (D.G.) and the Medical Research Council of Canada.
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References |
|---|
|
TopSummaryIntroductionMethodsAnalysisResultsDiscussionReferences |
|---|
Ackermann H, Daum I, Schugens MM, Grodd W. Impaired procedural learning after damage to the left supplementary motor area. J Neurol Neurosurg Psychiatry 1996; 60: 94–7.
Alexander GE, Crutcher MD. Preparation for movement: neural representations of intended direction in three motor areas of the monkey. J Neurophysiol 1990; 64: 133–50.
Allin F, Velay JL, Bouquerel A. Shift in saccadic direction induced in humans by proprioceptive manipulation: a comparison between memory-guided and visually guided saccades. Exp Brain Res 1996; 110: 473–81.[Web of Science][Medline]
Andersen RA, Brotchie PR, Mazzoni P. Evidence for the lateral intraparietal area as the parietal eye field. [Review]. Curr Opin Neurobiol 1992; 2: 840–6.[Medline]
Anderson TJ, Jenkins IH, Brooks DJ, Hawken MB, Frackowiak RS, Kennard C. Cortical control of saccades and fixation in man: a PET study. Brain 1994; 117: 1073–84.
Barash S, Bracewell RM, Fogassi L, Gnadt JW, Andersen RA. Saccade-related activity in the lateral intraparietal area. I. Temporal properties; comparison with area 7a. J Neurophysiol 1991a; 66: 1095–108.
Barash S, Bracewell RM, Fogassi L, Gnadt JW, Andersen RA. Saccade-related activity in the lateral intraparietal area. II. Spatial properties. J Neurophysiol 1991b; 66: 1109–24.
Berman RA, Colby CL, Genovese CR, Voyvodic JT, Luna B, Thulborn KR, et al. Cortical networks subserving pursuit and saccadic eye movements in humans: an fMRI study. Hum Brain Mapp 1999; 8: 209–25.[Web of Science][Medline]
Bichot NP, Schall JD. Effects of similarity and history on neural mechanisms of visual selection. Nat Neurosci 1999; 2: 549–54.[Web of Science][Medline]
Bodis-Wollner I, Bucher SF, Seelos KC. Cortical activation patterns during voluntary blinks and voluntary saccades. Neurology 1999; 53: 1800–5.
Brodmann K. Vergleichende Lokalisationslehre der Grosshirnrinde in ihren Prinzipien dargestellt auf Grund des Zellenbaues. Leipzig: Barth; 1909.
Bronstein AM, Kennard C. Predictive ocular motor control in Parkinson’s disease. Brain 1985; 108: 925–40.
Bronstein AM, Kennard C. Predictive saccades are different from visually triggered saccades. Vision Res 1987; 27: 517–20.[Web of Science][Medline]
Bruce CJ, Borden JA. The primate frontal eye fields are necessary for predictive saccade tracking [abstract]. Soc Neurosci Abstr 1986; 12: 1086.
Bruce CJ, Goldberg ME, Bushnell MC, Stanton GB. Primate frontal eye fields. II. Physiological and anatomical correlates of electrically evoked eye movements. J Neurophysiol 1985; 54: 714–34.
Cao J. The size of the connected components of excursion sets of x2, t and F fields. Adv Appl Probab 1999; 31: 579–95.
Carpenter RHS, Williams MLL. Neural computation of log likelihood in control of saccadic eye movements. Nature 1995; 377: 59–62.[Medline]
Chen LL, Wise SP. Neuronal activity in the supplementary eye field during acquisition of conditional oculomotor associations. J Neurophysiol 1995; 73: 1101–21.
Collins DL, Neelin P, Peters TM, Evans AC. Automatic 3D intersubject registration of MR volumetric data in standardized Talairach space. J Comput Assist Tomogr 1994; 18: 192–205.[Web of Science][Medline]
Connolly JD, Goodale MA, DeSouza JFX, Menon RS, Vilis T. A comparison of frontoparietal fMRI activation during anti-saccades and anti-pointing. J Neurophysiol 2000; 84: 1645–55.
Crawford T, Goodrich S, Henderson L, Kennard C. Predictive responses in Parkinson’s disease: manual keypresses and saccadic eye movements to regular stimulus events. J Neurol Neurosurg Psychiatry 1989; 52: 1033–42.
Cui DM, Yan YJ, Lynch JC. Basal ganglia circuits related to visual pursuit in monkey [abstract]. Soc Neurosci Abstr 2000; 26: 1717.
Culham JC, Brandt SA, Cavanagh P, Kanwisher NG, Dale AM, Tootell RB. Cortical fMRI activation produced by attentive tracking of moving targets. J Neurophysiol 1998; 80: 2657–70.
Darby DG, Nobre AC, Thangaraj V, Edelman R, Mesulam MM, Warach S. Cortical activation in the human brain during lateral saccades using EPISTAR functional magnetic resonance imaging. Neuroimage 1996; 3: 53–62.[Web of Science][Medline]
Dias EC, Bruce CJ. Physiological correlate of fixation disengagement in the primate’s frontal eye field. J Neurophysiol 1994; 72: 2532–7.
Doricchi F, Perani D, Incoccia C, Grassi F, Cappa SF, Bettinardi V, et al. Neural control of fast-regular saccades and antisaccades: an investigation using positron emission tomography. Exp Brain Res 1997; 116: 50–62.[Web of Science][Medline]
Dorris MC, Munoz DP. Saccadic probability influences motor preparation signals and time to saccadic initiation. J Neurosci 1998; 18: 7015–26.
Dorris MC, Pare M, Munoz DP. Neuronal activity in monkey superior colliculus related to the initiation of saccadic eye movements. J Neurosci 1997; 17: 8566–79.
DuBois RM, Cohen MS. Spatiotopic organization in human superior colliculus observed with fMRI. Neuroimage 2000; 12: 63–70.[Web of Science][Medline]
Economo C, Koskinas GN. Die Cytoarchitektonik der Hirnrinde des erwachsenen Menschen. Wien: J. Springer; 1925.
Evans AC, Collins DL, Mills SR, Brown ED, Kelly RL. 3D statistical neuroanatomical models from 305 MRI volumes. In: IEEE Conference Record, Nuclear Sciences Symposium and Medical Imaging Conference. San Francisco; 1993. p. 1813–17.
Evans AC, Kamber M, Collins DL, MacDonald D. An MRI-based probabilistic atlas of neuroanatomy. In: Shorvon SD, Fish DR, Andermann F, Bydder GM, Stefan H, editors. Magnetic resonance scanning and epilepsy. New York: Plenum Press; 1994. p. 263–74.
Everling S, Munoz DP. Neuronal correlates for preparatory set associated with pro-saccades and anti-saccades in the primate frontal eye field. J Neurosci 2000; 20: 387–400.
Everling S, Krappmann P, Spantekow A, Flohr H. Cortical potentials during the gap prior to express saccades and fast regular saccades. Exp Brain Res 1996; 111: 139–43.[Web of Science][Medline]
Findlay JM. Spatial and temporal factors in the predictive generation of saccadic eye movements. Vision Res 1981; 21: 347–54.[Web of Science][Medline]
Findlay JM, Walker R. A model of saccade generation based on parallel processing and competitive inhibition. Behav Brain Sci 1999; 22: 661–721.[Web of Science][Medline]
Fischer B, Ramsperger E. Human express saccades: effects of randomization and daily practice. Exp Brain Res 1986; 64: 569–78.[Web of Science][Medline]
Fischer B, Weber H. Express saccades and visual attention. [Review]. Behav Brain Sci 1993; 16: 553–610.[Web of Science]
Fischer B, Boch R, Ramsperger E. Express-saccades of the monkey: effect of daily training on probability of occurrence and reaction time. Exp Brain Res 1984; 55: 232–42.[Web of Science][Medline]
Frens MA, Hooge ITC, Goossens HHLM. Can parallel processing and competitive inhibition explain the generation of saccades? Behav Brain Sci 1999; 22: 685–6.[Web of Science]
Fries W. Cortical projections to the superior colliculus in the macaque monkey: a retrograde study using horseradish peroxidase. J Comp Neurol 1984; 230: 55–76.[Web of Science][Medline]
Fujii N, Mushiake H, Tanji J. An oculomotor representation area within the ventral premotor cortex. Proc Natl Acad Sci USA 1998; 95: 12034–7.
Gagnon D, O’Driscoll GA, Pike GB. Neural activity in the FEFs and SEFs related to the predictive control of eye movements [abstract]. Soc Neurosci Abstr 2000; 26: 965.
Gaymard B, Pierrot-Deseilligny C, Rivaud S. Impairment of sequences of memory-guided saccades after supplementary motor area lesions. Ann Neurol 1990; 28: 622–6.[Web of Science][Medline]
Gaymard B, Rivaud S, Pierrot-Deseilligny C. Role of the left and right supplementary motor areas in memory-guided saccade sequences. Ann Neurol 1993; 34: 404–6.[Web of Science][Medline]
Georgopoulos AP. Neural aspects of cognitive motor control. [Review]. Curr Opin Neurobiol 2000; 10: 238–41.[Web of Science][Medline]
Gitelman DR, Parrish TB, LaBar KS, Mesulam MM. Real-time monitoring of eye movements using infrared video-oculography during functional magnetic resonance imaging of the frontal eye fields. Neuroimage 2000; 11: 58–65.[Web of Science][Medline]
Gnadt JW, Andersen RA. Memory related motor planning activity in posterior parietal cortex of macaque. Exp Brain Res 1988; 70: 216–20.
Grosbras MH, Lobel E, Van de Moortele PF, LeBihan D, Berthoz A. An anatomical landmark for the supplementary eye fields in human revealed with functional magnetic resonance imaging. Cereb Cortex 1999; 9: 705–11.
Hanes DP, Schall JD. Neural control of voluntary movement initiation. Science 1996; 274: 427–30.
Hanes DP, Patterson WF, Schall JD. Role of frontal eye fields in countermanding saccades: visual, movement, and fixation activity. J Neurophysiol 1998; 79: 817–34.
Harrington DL, Haaland KY. Neural underpinnings of temporal processing: a review of focal lesion, pharmacological, and functional imaging research. [Review]. Rev Neurosci 1999; 10: 91–116.[Web of Science][Medline]
Harrington DL, Haaland KY, Hermanowicz N. Temporal processing in the basal ganglia. Neuropsychology 1998; 12: 3–12.[Web of Science][Medline]
Hikosaka O, Sakamoto M. Cell activity in monkey caudate nucleus preceding saccadic eye movements. Exp Brain Res 1986; 63: 659–62.
Hoge RD, Atkinson J, Gill B, Crelier GR, Marrett S, Pike GB. Linear coupling between cerebral blood flow and oxygen consumption in activated human cortex. Proc Natl Acad Sci USA 1999; 96: 9403–8.
Inhoff AW, Diener HC, Rafal RD, Ivry R. The role of cerebellar structures in the execution of serial movements. Brain 1989; 112: 565–81.
Isotalo E, Pyykko I, Juhola M, Aalto H. Predictable and pseudo random saccades in patients with acoustic neuroma. Acta Otolaryngol Suppl 1995; 520: 22–4.
Ivry R. Cerebellar involvement in the explicit representation of temporal information. [Review]. Ann NY Acad Sci 1993; 682: 214–30.[Web of Science][Medline]
Ivry RB, Keele SW, Diener HC. Dissociation of the lateral and medial cerebellum in movement timing and movement execution. Exp Brain Res 1988; 73: 167–80.[Web of Science][Medline]
Jaeger D, Gilman S, Aldridge JW. Neuronal activity in the striatum and pallidum of primates related to the execution of externally cued reaching movements. Brain Res 1995; 694: 111–27.[Web of Science][Medline]
Kalesnykas RP, Hallett PE. The differentiation of visually guided and anticipatory saccades in gap and overlap paradigms. Exp Brain Res 1987; 68: 115–21.[Web of Science][Medline]
Kawashima R, Tanji J, Okada K, Sugiura M, Sato K, Kinomura S, et al. Oculomotor sequence learning: a positron emission tomography study. Exp Brain Res 1998; 122: 1–8.[Web of Science][Medline]
Kawashima R, Okuda J, Umetsu A, Sugiura M, Inoue K, Suzuki K, et al. Human cerebellum plays an important role in memory-timed finger movement: an fMRI study. J Neurophysiol 2000; 83: 1079–87.
Kimura M. The role of primate putamen neurons in the association of sensory stimuli with movement. Neurosci Res 1986; 3: 436–43.
Kimura M. Behaviorally contingent property of movement-related activity of the primate putamen. J Neurophysiol 1990; 63: 1277–96.
Kimura M, Kato M, Shimazaki H. Physiological properties of projection neurones in the monkey striatum to the globus pallidus. Exp Brain Res 1990; 82: 672–6.[Web of Science][Medline]
Kingstone A, Klein RM. Visual offsets facilitate saccadic latency: does predisengagement of visuospatial attention mediate this gap effect? J Exp Psychol Hum Percept Perform 1993; 19: 1251–65.[Web of Science][Medline]
Kowler E. The role of visual and cognitive processes in the control of eye movements. In: Kowler E, editor. Eye movements and their role in visual and cognitive processes. Reviews of oculomotor research, Vol. 4. New York: Elsevier; 1990. p. 1–70.
Luna B, Thulborn KR, Strojwas MH, McCurtain BJ, Berman RA, Genovese CR, et al. Dorsal cortical regions subserving visually guided saccades in humans: an fMRI study. Cereb Cortex 1998; 8: 40–7.
Malapani C, Dubois B, Rancurel G, Gibbon J. Cerebellar dysfunctions of temporal processing in the seconds range in humans. Neuroreport 1998; 9: 3907–12.[Web of Science][Medline]
Mann SE, Thau R, Schiller PH. Conditional task-related responses in monkey dorsomedial frontal cortex. Exp Brain Res 1988: 69: 460–8.
Munoz DP, Wurtz RH. Role of the rostral superior colliculus in active visual fixation and execution of express saccades. J Neurophysiol 1992; 67: 1000–2.
Muri RM, Iba-Zizen MT, Derosier C, Cabanis EA, Pierrot-Deseilligny C. Location of the human posterior eye field with functional magnetic resonance imaging. J Neurol Neurosurg Psychiatry 1996; 60: 445–8.
Nakamura K, Sakai K, Hikosaka O. Effects of local inactivation of monkey medial frontal cortex in learning of sequential procedures. J Neurophysiol 1999; 82: 1063–8.
O’Driscoll GA, Alpert NM, Matthysse SM, Levy DL, Rauch SL, Holzman PS. Functional neuroanatomy of antisaccade eye movements investigated with positron emission tomography. Proc Natl Acad Sci USA 1995; 92: 925–9.
O’Driscoll GA, Benkelfat C, Florencio PS, Wolff ALV, Joober R, Lal S, et al. Neural correlates of eyetracking deficits in first-degree relatives of schizophrenic patients: a PET study. Arch Gen Psychiatry 1999; 56: 1127–34.
O’Driscoll GA, Wolff ALV, Benkelfat C, Florencio PS, Lal S, Evans AC. Functional neuroanatomy of smooth pursuit and predictive saccades. Neuroreport 2000; 11: 1335–40.[Web of Science][Medline]
Ogawa S, Tank DW, Menon R, Ellermann JM, Kim SG, Merkle H, et al. Intrinsic signal changes accompanying sensory stimulation: functional brain mapping with magnetic resonance imaging. Proc Natl Acad Sci USA 1992; 89: 5951–5.
O’Sullivan EP, Jenkins IH, Henderson L, Kennard C, Brooks DJ. The functional anatomy of remembered saccades: a PET study. Neuroreport 1995; 6: 2141–4.[Web of Science][Medline]
Paré M, Munoz DP. Saccadic reaction time in the monkey: advanced preparation of oculomotor programs is primarily responsible for express saccade occurrence. J Neurophysiol 1996; 76: 3666–81.
Paus T. Location and function of the human frontal eye-field: a selective review. [Review]. Neuropsychologia 1996; 34: 475–83.[Web of Science][Medline]
Petit L, Haxby JV. Functional anatomy of pursuit eye movements in humans as revealed by fMRI. J Neurophysiol 1999; 82: 463–71.
Petit L, Orssaud C, Tzourio N, Crivello F, Berthoz A, Mazoyer B. Functional anatomy of a prelearned sequence of horizontal saccades in humans. J Neurosci 1996; 16: 3714–26.
Petit L, Clark VP, Ingeholm J, Haxby JV. Dissociation of saccade-related and pursuit-related activation in human frontal eye fields as revealed by fMRI. J Neurophysiol 1997; 77: 3386–90.
Porter R, Lemon R. Corticospinal function and voluntary movement. Oxford: Oxford University Press; 1995.
Postle BR, D’Esposito M. ‘What’-Then-‘Where’ in visual working memory: an event-related fMRI study. J Cogn Neurosci 1999a; 11: 585–97.[Web of Science][Medline]
Postle BR, D’Esposito M. Dissociation of human caudate nucleus activity in spatial and nonspatial working memory: an event-related fMRI study. Brain Res Cogn Brain Res 1999b; 8: 107–15.[Medline]
Quaia C, Optican LM. No ‘when’ without ‘where’. Behav Brain Sci 1999; 22: 696–7.[Web of Science]
Rao SM, Mayer AR, Harrington DL. The evolution of brain activation during temporal processing. Nat Neurosci 2001; 4: 317–23.[Web of Science][Medline]
Rasmussen T, Penfield W. Movement of head and eyes from stimulation of human frontal cortex. Res Publ Assoc Res Nerv Ment Dis 1948; 27: 346–61.[Web of Science][Medline]
Reuter-Lorenz PA, Hughes HC, Fendrich R. The reduction of saccadic latency by prior offset of the fixation point: an analysis of the gap effect. Percept Psychophys 1991; 49: 167–75.[Web of Science][Medline]
Reuter-Lorenz PA, Oonk HM, Barnes LL, Hughes HC. Effects of warning signals and fixation point offsets on the latencies of pro- versus antisaccades: implications for an interpretation of the gap effect. Exp Brain Res 1995; 103: 287–93.[Web of Science][Medline]
Rivaud S, Muri RM, Gaymard B, Vermersch AI, Pierrot-Deseilligny C. Eye movement disorders after frontal eye field lesions in humans. Exp Brain Res 1994; 102: 110–20.[Web of Science][Medline]
Robinson DA. Eye movements evoked by collicular stimulation in the alert monkey. Vision Res 1972; 12: 1795–808.[Web of Science][Medline]
Rohrbaugh JW, Syndulko K, Lindsley DB. Brain wave components of the contingent negative variation in humans. Science 1976; 191: 1055–7.
Romo R, Scarnati E, Schultz W. Role of primate basal ganglia and frontal cortex in the internal generation of movements. II. Movement-related activity in the anterior striatum. Exp Brain Res 1992; 91: 385–95.[Web of Science][Medline]
Ross SM, Ross LE. Saccade latency and warning signals: effects of auditory and visual stimulus onset and offset. Percept Psychophys 1981; 29: 429–37.[Web of Science][Medline]
Schall JD. Neuronal activity related to visually guided saccadic eye movements in the supplementary motor area of rhesus monkeys. J Neurophysiol 1991; 66: 530–58.
Schall JD, Hanes DP, Thompson KG, King DJ. Saccade target selection in frontal eye field of macaque. I. Visual and premovement activation. J Neurosci 1995; 15: 6905–18.
Schlag J, Schlag-Rey M. Evidence for a supplementary eye field. J Neurophysiol 1987; 57: 179–200.
Schmahmann JD, Doyon J, McDonald D, Holmes C, Lavoie K, Hurwitz AS, et al. Three-dimensional MRI atlas of the human cerebellum in proportional stereotaxic space. Neuroimage 1999; 10: 233–60.[Web of Science][Medline]
Schubotz RI, Friederici AD, von Cramon DY. Time perception and motor timing: a common cortical and subcortical basis revealed by fMRI. Neuroimage 2000; 11: 1–12.[Web of Science][Medline]
Shulman GL, Ollinger JM, Akbudak E, Conturo TE, Snyder AZ, Petersen SE, et al. Areas involved in encoding and applying directional expectations to moving objects. J Neurosci 1999; 19: 9480–96.
Smit AC, Van Gisbergen JA. A short-latency transition in saccade dynamics during square-wave tracking and its significance for the differentiation of visually-guided and predictive saccades. Exp Brain Res 1989; 76: 64–74.[Web of Science][Medline]
Smit AC, Van Gisbergen JA, Cools AR. A parametric analysis of human saccades in different experimental paradigms. Vision Res 1987; 27: 1745–62.[Web of Science][Medline]
Sommer MA, Tehovnik EJ. Reversible inactivation of macaque dorsomedial frontal cortex: effects on saccades and fixations. Exp Brain Res 1999; 124: 429–46.[Web of Science][Medline]
Sommer MA, Wurtz RH. Composition and topographic organization of signals sent from the frontal eye field to the superior colliculus. J Neurophysiol 2000; 83: 1979–2001.
Stanton GB, Goldberg ME, Bruce CJ. Frontal eye field efferents in the macaque monkey: I. Subcortical pathways and topography of striatal and thalamic terminal fields. J Comp Neurol 1988a; 271: 473–92.[Web of Science][Medline]
Stanton GB, Goldberg ME, Bruce CJ. Frontal eye field efferents in the macaque monkey: II. Topography of terminal fields in midbrain and pons. J Comp Neurol 1988b; 271: 493–506.[Web of Science][Medline]
Sweeney JA, Mintun MA, Kwee S, Wiseman MB, Brown DL, Rosenberg DR, et al. Positron emission tomography study of voluntary saccadic eye movements and spatial working memory. J Neurophysiol 1996; 75: 454–68.
Talairach J, Tournoux P. Co-planar stereotaxic atlas of the human brain. Stuttgart: Thieme; 1988.
Tam WJ, Ono H. Fixation disengagement and eye-movement latency. Percept Psychophys 1994; 56: 251–60.
Tehovnik EJ, Sommer MA, Chou IH, Slocum WM, Schiller PH. Eye fields in the frontal lobes of primates. [Review]. Brain Res Brain Res Rev 2000; 32: 413–48.[Medline]
Thompson KG, Hanes DP, Bichot NP, Schall JD. Perceptual and motor processing stages identified in the activity of macaque frontal eye field neurons during visual search. J Neurophysiol 1996; 76: 4040–55.
Tian JR, Zee DS, Lasker AG, Folstein SE. Saccades in Huntington’s disease: predictive tracking and interaction between release of fixation and initiation of saccades. Neurology 1991; 41: 875–81.
Ventre J, Zee DS, Papageorgiou H, Reich S. Abnormalities of predictive saccades in hemi-Parkinson’s disease. Brain 1992; 115: 1147–65.
Wauschkuhn B, Wascher E, Verleger R. Lateralized cortical activity due to preparation of saccades and finger movements: a comparative study. Electroencephalogr Clin Neurophysiol 1997; 102: 114–24.[Web of Science][Medline]
Wise SP. The primate premotor cortex: past, present and preparatory. [Review]. Annu Rev Neurosci 1985; 8: 1–19.[Web of Science][Medline]
Worsley KJ, Marrett S, Neelin P, Vandal AC, Friston KJ, Evans AC. A unified statistical approach for determining significant signals in images of cerebral activation. Hum Brain Mapp 1996; 4: 58–73.[Web of Science]
Worsley KJ, Liao C, Grabove M, Petre V, Ha B, Evans AC. A general statistical analysis for fMRI data. Neuroimage 2000; 11 (5 Pt 2): S648.
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