Department of Anatomy and Neurobiology, , 1 Department of Radiology, Division of Radiological Sciences, , 2 Department of Neurology and Neurological Surgery, and , 3 Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO 63110, USA
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Abstract |
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Introduction |
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A related issue was potential identification of separate foci within somatosensory areas dedicated to processing different tactile stimulus attributes. In imaging studies of human visual attention, Corbetta and colleagues showed activations of different higher-order visual areas when subjects attended selectively to shape, color or motion speed attributes of a visual display (Corbetta et al., 1991). Although some tactile stimuli also can be parsed into different attributes (e.g. texture, shape, object length), currently only one brain imaging study has reported that separate activation foci might process signals related to different tactile stimulus attributes (Roland et al., 1998
). In this study, discrimination tasks involving a two-alternative, forced-choice discrimination of roughness differences between objects activated more anterior parts of the postcentral gyrus than tasks requiring discrimination of object shape or length attributes. Previously, however, we reported no significant differences in the cortical areas activated when embossed grating stimuli preferentially stimulated cutaneous compared to proprioceptive receptors in individual fingertips (Burton et al., 1997b
).
Further, in this study we examined whether tactile attention engages non-somatosensory cortical areas. Studies of the network associated with visual attention found many cortical regions engaged that occupied nonvisual as well as visual areas (Mesulam, 1990; Corbetta et al., 1991
, 1993
; Haxby et al., 1994
; Posner and Dehaene, 1994
; Vandenberghe et al., 1996
; Frith and Dolan, 1997
; Büchel et al., 1998
). Thus, visual attention is a distributed process (Posner and Dehaene, 1994
). In question is whether the same or different nonsensory cortical areas are active during a tactile attention task. These may act as cross-modal attentional foci and potential organizers of top-down mechanisms (Posner and Petersen, 1990
; Corbetta et al., 1991
, 1993
; Frith and Dolan, 1997
; Nobre et al., 1997
; Büchel et al., 1998
). One likely common region is the right posterior parietal cortex because lesions here are associated with neglect of visual and somatosensory stimuli located in extra-personal space contralateral to the lesion (Critchley, 1949
; Mesulam, 1981
; Posner et al., 1984
; Moscovitch and Behrmann, 1994
).
Another issue to be addressed is whether imaging data support the notion that foci activated by passive presentation of a stimulus are more highly activated when attention is directed to the same stimuli. Numerous studies have found evidence of increases in relative cerebral blood flow (rCBF) in appropriate sensory cortical areas during attention tasks engaging specific sensory channels (Corbetta et al., 1991, 1993
; Woldorff et al., 1993
; Woodruff et al., 1996
; Büchel et al., 1998
). Blood flow in S1 was 13% higher when subjects attended to vibrotactile stimuli than when they received the same stimuli but were engaged in a distraction task (Meyer et al., 1991
). These studies suggest that attention may involve early selective modulation within the appropriate sensory cortical areas.
Here we attempted to investigate three aspects of tactile attention: (i) location of foci showing increases in blood flow in sensory and nonsensory cortical areas; (ii) identification of separate activation foci for different attended tactile attributes; and (iii) evidence that some regions showing increased neural activity during control tasks involving passive tactile stimulation were further activated during the attention task (enhancement). The tactile attributes of surface roughness and stimulus duration were manipulated in the present study. A comparison of performance on (valid) trials, when cues predicted which attribute would change, to trials with a neutral cue allowed us to determine the benefit of devoting all resources to one feature and demonstrated that subjects' attention was manipulated by the different attention conditions. The rationale behind this testing was that on trials with valid cues subjects' ability to discriminate between small changes in the selected feature would be improved by selectively directing attention to one feature in a multidimensioned stimulus (Posner, 1986). On trials in which cues did not direct attention to either feature (neutral), resources had to be divided, and thus the probability of correctly discriminating differences between gratings based on each feature was expected to be lower. Importantly, this experimental design ensured balanced difficulty, arousal and vigilance across all trials since identical stimuli are presented across conditions.
We report here results from psychophysical experiments aimed at assessing task performance and positron emission tomography (PET) experiments directed toward identifying brain regions that mediate tactile attention.
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Materials and Methods |
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We conducted psychophysical experiments on 20 paid volunteers (11 males and 9 females) between the ages of 18 and 30 (mean 22.4). Ten subjects (6 males and 4 females; between the ages 18 and 27; mean 22.5) met performance criteria (as described below) and returned for scan sessions. All reported strong right-handed preference as measured by the Edinburgh Handedness Inventory (Raczkowski et al., 1974) and had no neurological or physical disabilities. Informed consent, obtained before participation in each part of the study, followed guidelines of the Human Studies Committee and the Radioactive Drug Research Committee of Washington University.
Stimulus Attributes
Tactile stimulation consisted of rubbing the right index finger with embossed gratings of alternating ridges and grooves, which were made by photo-etching polyamide plastic sheets (Process Color Plate, Chicago, IL). Ridge widths (0.25 mm) and groove depths (~0.5 mm) were constant, but groove width varied (see below). All gratings were 2 cm wide. Gratings were presented in discontinuous pairs. A smooth area of 4.5 cm separated one pair of surfaces from the next; a shorter smooth area of 1 cm separated the first pair member from the second (Fig. 1).
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Apparatus and Stimulus Application
For each of the behavioral tasks (see below), 32 different grating pairs were randomly distributed into four continuous strips (tracks), each consisting of eight pairs. These were wrapped around the perimeter of a cylinder (~10 cm height and 32 cm diameter). Three cylinders were constructed for a total of 96 grating pairs. Eight sequential pairs comprising a track were presented in one rotation of the cylinder, and through manual shifts each of the four tracks of grating pairs could be aligned under the fingertip. The three cylinders were exchanged during a testing session depending on the task. On the passive stimulation control cylinder' (explained below), the two gratings within a pair were identical in both features. The range of roughnesses and lengths for the different pairs matched those used during the attention tasks (described below). On the selective cylinder', the values of both attributes changed in 75% of the pairs. On 12.5% of the pairs only roughness changed, and on the remaining 12.5% of the pairs, only length changed. On the divided cylinder', the values of both attributes changed on 50% of the pairs. On 25% of the pairs only length changed, and on 25% of the pairs, only roughness changed.
The grating velocity was 30 mm/s. A constant force load of ~100 g was maintained by balancing the cylinder against a torsion counterbalance with an adjustable fulcrum. The finger was positioned so that the ridges aligned perpendicular to the long axis of the finger and moved down the finger from proximal to distal end.
A restraint, made of thermoplastic and foam, supported the subject's right forearm and hand. The right index finger extended through an opening in the restraint and was additionally supported in an individually fashioned mold made from Rolyan 50/50 Elastomer Putty (Smith and Nephew, WI). This finger-cast passively held the finger in a slightly flexed position, which aligned the distal fingertip against the grating surfaces. We instructed subjects to relax their arm, hand and fingers throughout the trials.
Behavioral Tasks
Subjects performed both control and attention tasks before and during PET scans.
Feature Attention Conditions
Using a two-alternative, forced-choice paradigm, each trial consisted of stimulation with a pair of gratings. Before each set of trials, verbal instructions cued the subject in one of three ways (Fig. 1). During the selective attention' task, instructions cued the subjects to detect and respond to changes in a single feature (either duration of contact or surface roughness) and to ignore changes in the other feature. The subject was asked to determine which surface felt rougher or was in contact with the finger for a longer period of time. Following each trial, the subject responded verbally with one' if the first (reference') surface in the pair was longer/rougher or two' if the second (test') surface in the pair was longer/rougher (Fig. 1
). Responses were tape-recorded using an audio cassette. In a selective attention trial, both features would change (a validly cued trial), the selective feature alone would change (a validly cued trial), or the unspecified feature alone would change (an invalidly cued trial). Subjects were not informed of the invalid trials, and therefore responses from these trials were not considered further. In the divided attention' task, subjects were instructed to detect and respond to changes in either feature (neutrally cued trial). Thus, subjects had to divide their attention between the two features in order to determine which of the two surfaces in a pair was in contact longer or was rougher. The same values of duration and groove width were used in the selective and divided attention tasks.
Control Conditions
There were three control conditions during PET scans, the last of which was practiced during the psychophysical testing sessions. The fingertip was restrained in a finger mold over the surfaces during all controls. In the least demanding control condition, named eyes-closed-rest', subjects were verbally instructed to close their eyes and not pay any attention to their fingertips. The grating pairs did not touch the subject's finger although the wheel rotated during the scan. In the next control condition, named passive stimulation', subjects also kept their eyes closed and were told to ignore their fingers while a series of paired surfaces whose members were identical in both features were presented. Subjects learned to perform the third control condition, named passive stimulation/counting', through several steps. First, subjects were told to ignore stimulation from rubbing paired gratings against the fingertip. Next, and without tactile stimulation, we instructed subjects to say one' or two' in random order at a rate of once per 4 s. Initially a timer beeped every 4 s to assist learning the desired interval; then the timer was turned on and off several times until the subjects' timing approximated the desired interval. Finally, the subject's finger was stimulated again by the control surfaces while the subject made random verbal responses. Subjects were informed that the order in which they verbalized the numbers was unimportant, that they should not base their choices on the surfaces (since the members of each pair were identical), and that they needed to respond at 4 s intervals, even though their responses would not coordinate with the onset or offset of surface pairs. Subjects practiced this task through multiple presentations until they made randomly chosen responses in a manner unaffected by the concurrent stimulation.
Psychophysical Testing
Testing extended over 2 days. On day 1 subjects first practiced the passive stimulation/counting control task and then did the attention tasks. On day 2 this order was reversed.
Subjects received specific instructions to attend selectively to one of the features or to divide their attention between features before each of the attention tasks. We then presented eight trials (one rotation of the appropriate cylinder) during which the experimenter provided correct answers. The cylinder was rotated to a different starting position and subjects next practiced with their own answers for another set of eight trials. Feedback on performance was provided at the end of these trials. Each day, the first and third attention treatment blocks contained selective attention trials in a random sequence between duration and roughness. The middle block contained only divided attention trials (neutrally cued trials). In counterbalanced order, the grating pairs for each attention task were rotated in both the forward and reverse drum directions across the two test days. This ensured that subjects encountered all surfaces in the first or second positions, thereby reducing the possibility of memorizing the pair relations and being able to answer based solely on the first member of a pair. On each day subjects performed 80 trials (10 complete cylinder rotations) for each of the selective attention tasks in one rotation direction. Thus, over the two days of testing, we collected responses to 160 trials for selectively attending to roughness and 160 trials for selectively attending to duration presented in each rotation direction. We presented 128 trials (16 rotations) for the divided attention task per test day. Following testing, subjects were questioned about their attention strategies and insights into the stimulus set.
Scan Procedures
Task-specific instructions were given before each of 10 scans. Task performance was started several minutes prior to the scans so that during the attention and passive stimulation/counting' control tasks 1624 trials were completed before the scan, leaving another 812 trials during the scan. Task-scan order was as follows: (i) scan 1 was always an eyes-closed-rest' control; (ii) scans 3, 5, 8 and 10 were appropriately counterbalanced to include selective attention to roughness or stimulus duration; (iii) scans 4 and 9 were the divided attention task; (iv) scans 2 and 7 were the passive stimulation /counting' task; and (v) scan 6 was the passive stimulation' control.
PET Scanning Techniques
We used a Siemens 953B scanner in the three-dimensional (septa retracted) mode (31 transaxial 3.375 mm slices, reconstructed pixel size of 2.086 mm2). We used previously described PET scanning activation methodology developed at Washington University (Fox et al., 1984, 1988
; Mintun et al., 1989
; Petersen et al., 1989
). A thermoplastic mask stabilized the subject's head. Black curtains surrounded the head and blocked all light. 15O-Labeled water (10 ml saline with ~15 mCi of radioactivity) was administered via an i.v. bolus injection to the left forearm. Forty second scans were acquired. Usually, we conducted 10 scans, each separated by 10 min to allow for almost complete decay of 15O between scans (five half-lives). We first performed an eyes-closed-rest' task, sham scan' during which only physiological saline was injected to reduce anxiety associated with injection of the radioactive tracer or other scan procedures (Coghill et al., 1994
).
PET difference images were computed by subtraction across scan pairs and averaged over subjects (Fox et al., 1988). This was accomplished with a single resampling (to 2 mm cubic voxels) using previously computed transformations and intensity scaling that (i) corrected for interscan head movement (Snyder, 1996
) and global activity variations, and (ii) transformed the images to a standard atlas space (Talairach and Tournoux, 1988
). Our atlas transformation strategy is similar to that described by Collins and colleagues (Collins et al., 1994
).
Our atlas representative target PET image consisted of averaged data from 12 normal, young adult subjects (not included in the present study), corrected, as above, for interscan head movement, and mutually co-registered (12 parameter affine transforms) to a selected individual. We similarly aligned structural MP-RAGE (Mugler and Brookeman, 1990) images obtained in the same 12 subjects. The averaged MP-RAGE image was then made to conform to the Talairach atlas using the SN spatial normalization procedure (Lancaster et al., 1995
). The averaged PET image then was aligned to the MP-RAGE image to produce the atlas representative, target PET image. This PET atlas representative image then was scaled to a whole-brain mean intensity of 1000 using boundaries defined on the co-registered MP-RAGE. Although the above sequence was described as if successive transformations were applied to cumulatively resampled data, it should be understood that the final product was produced by algebraic composition of transforms followed by one resampling (to 2 mm cubic voxels) and averaging of the originally reconstructed PET data.
To identify changes in blood flow, images from each subject were grouped into activation minus control pairs. The resulting difference images show foci of task-related changes in rCBF (Fox et al., 1984; Mintun et al., 1989
). Because the subject performed different behavioral tasks in the two scans that made up each pair, the subtracted image represents the blood flow change induced by the different processing demands of the two tasks.
PET Statistical Methods
We used a replication approach for data analyses to cross-validate identified regions of change in rCBF and to investigate their reliability (Squire et al., 1992; Burton et al., 1993
; Hunton et al., 1996
; Shulman et al., 1997
). This approach, which is based on testing the reproducibility of rCBF changes across data sets, ensures that regions identified as significant are unlikely to result from irrelevant factors (like movement or vessel artifacts) or image noise (Corbetta et al., 1991
; Buckner et al., 1995a
; Buckner et al., 1995b
; Buckner et al., 1996
). This strict analysis method was implemented to reduce type I errors in which false positives are accepted as significant.
Difference images (scans from each attention task minus scans from passive stimulation/counting' control) were summed together in one composite image. The subtraction pairs comprising this composite were then assigned to one of two data sets, the first of which (hypothesis generating) was used to define regions of interest. The second data set (hypothesis testing) was used for statistical testing of candidate focal responses identified in the first set. Only those subtraction pairs with repeated measures from the same subject were used in this analysis so that subjects contributed equally to both data sets. The subtraction pairs in each data set were proportionally weighted to equate contributions from each attention condition.
The hypothesis-generating, averaged-difference image was passed through a three-dimensional, fifth-order, low-pass Butterworth filter with a cut-off frequency of 0.7 cycles/cm. This processing produced an image with a resolution of ~11 mm full width at half maximum in all dimensions.
We used a computer algorithm to identify all rCBF maxima in the averaged difference images from the hypothesis-generating data sets (Fox et al., 1988; Mintun et al., 1989
). This search identified the location of foci with peak PET counts in a single 8 mm3 voxel at least 10% higher than the counts in neighboring pixels and at least 11 mm away from adjacent peaks. The resulting list identified the top maxima and showed stereo-taxic locations of potentially significant increases in rCBF. We selectively omitted from further analysis loci that were anatomically known to be within blood vessels, white matter, the ventricles or outside the brain. Next, to investigate whether the maxima identified in the hypothesis-generating data set were replicated in the hypothesis-testing data set, total PET counts from the individual (not averaged) difference images from the hypothesis-testing data set were determined. PET counts for each of the maxima identified in the hypothesis-generating data sets were then assessed with a one-sample Student t-test (upper for maxima) against the null hypothesis of 0 PET count differences in the hypothesis-testing data set. Mean PET counts within the identified regions whose t-values exceeded null hypothesis expectations with a P < 0.05 were considered leniently significant replicas of the focal peaks identified from searching the hypothesis-generating half of the data. Those regions whose t-values exceeded the null hypothesis with a Bonferroni correction for the number of t-tests performed were considered strictly significant replicas of the focal peaks. Those foci that reached significance could be attributed to at least one of the three attention tasks.
We report both leniently and strictly significant foci because of the conservative nature of the replication analysis, which might tend toward type II errors. However, the reliability of reported foci with strictly significant peaks is extremely high given the low probability of a type I error in these tests. The spatial resolution of the analysis was also close to that of our scanner, and therefore showed potential examples of multiple, yet proximate regions. In comparisons to voxel-by-voxel approaches (Friston et al., 1995) to assess the probability of observed PET difference counts at selected foci, cross-validation, two-stage procedures are extremely robust and have comparable statistical power (Holmes, 1994
). Spatial smoothing of the data is also unnecessary in cross-validation analyses as there are no assumptions about the underlying shape of the PET count distributions (i.e. Gaussian random fields). Hence, results can be viewed at resolutions approximating that of the scanner. The methods used to identify interesting regions in the hypothesis-generating data set also make little difference (Holmes, 1994
) although our searches for peaks in 8 mm3 spheres, with minimum separations between peaks of 11 mm, were consistent with the volumes studied in simulations. The major disadvantage of two-stage testing is reduced sensitivity from halving the degrees of freedom due to dividing the data. However, we compensated by using a replication design where each subject was studied twice for each attention and passive/counting task condition. Across all of the attention tasks, data were available from 60 scans (2 repetitions x 3 attention tasks x 10 subjects), which, when divided, provided samples of 30 for hypothesis generation and testing. This was ~6 times the sample shown in simulation studies to yield nearly comparable statistical power to voxel-based methods (Holmes, 1994
). Thus, the increased sample compensated for any possible loss in sensitivity while maintaining the better spatial resolution of an assumption-free approach to the distribution of PET counts
To determine the most accurate stereotaxic location for each of the maxima, the locations identified in the hypothesis-generating data set were visually compared to peak loci on a summed difference image composed of both hypothesis-generating and hypothesis-testing subtraction pairs (again weighed to balance conditions). This was done because the combined data set provides a better estimate of an activation's true location than either of the smaller data subsets used in replication analysis. These coordinates, which were all within millimeters of the coordinates used in the cross-validation analysis, are presented in the tables.
Within the text, coordinates are referred to in the x,y,z format (positive x = right; positive y = anterior; positive z = superior).
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Results |
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We first determined (by analyzing data from the 20 subjects psychophysically tested with a repeated-measures analysis of variance) whether our methods ensured that subjects were both sufficiently attentive and effective in ignoring uncued features on selected attention trials or dividing their attention between multiple features on divided attention trials. This analysis involved two measures. First, we compared performance on selective and divided attention trials in which only one feature changed. Subjects who performed correctly on more trials with valid than neutral cues probably divided their attention between the two features on divided trials, and thus lowered their performance. Second, we compared performance on validly cued trials in which a possible response to the uncued attribute changed in a negatively correlated, uncorrelated or positively correlated fashion relative to the cued attribute. Subjects who showed little difference in the percentage of correct trials in relation to changes in the uncued feature probably more effectively ignored the uncued feature. Ten subjects, who met these performance criteria in the initial psychophysical tests, returned for scan sessions.
The performance measure for each attention task was the percentage of correct responses. Data from those subjects chosen to return for scan sessions are shown in Figure 2. The main finding was that percentage correct was significantly higher (Bonferroni, P < 0.05) on validly cued trials (75%) than neutrally cued trials (68%). There were no significant effects of dimension or the specific values of roughness or duration on percentage correct. These results support the conclusion that subjects performed the task as instructed. Deficits in the neutral cue condition suggest a divided attention strategy.
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Psychophysics
Behavioral data obtained during the scan session was collected in the same way as during psychophysical testing. A statistical analysis of the results was not possible, however, because the 40 s scan interval did not allow for sufficient data collection. Qualitatively, the results were similar to those obtained during initial testing.
The following results discuss foci of change in rCBF that were tested for cross-validation between randomly separated halves of the data. Figure 3 shows, on matching columns of sagittal sections, the distribution of PET difference counts for the passive stimulation/counting versus eyes-closed-rest (leftmost column) and the summed image across all attention tasks versus passive stimulation/counting (middle column). The foci are correspondingly labeled in Tables 1 and 2
. [In addition to descriptions of gross anatomical features, like major gyri, the tables and text note Brodmann area (BA) designations as labeled in the Talairach atlas (Talairach and Tournoux, 1988
). These BA listings provide a convenient summary labeling convention that, in addition to the Talairach atlas coordinates, usefully points to results from other studies.]
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There were three foci of rCBF change in the vicinity of the precentral gyrus. One occupied the crown of the precentral gyrus ipsilateral to the stimulated fingertip (labeled D in Table 1). The other foci were also centered in precentral gyral cortex but contralateral to stimulation (A and E in Table 1
and Fig. 3
). The foci in opposite hemispheres involved partially analogous regions although the activated sites on the contralateral side were more extensive and included portions of the postcentral gyrus, and were therefore labeled as peri-Rolandic foci.
Two additional foci were found in frontal cortex. One was located on the medial wall in the paracentral lobule (C in Table 1 and Fig. 3
) contralateral to the stimulated finger. Significant rCBF changes were also found in the putamen that was contralateral to stimulation (Putamen, B in Table 1
).
Surprisingly, no isolated foci of significant increases in rCBF were found in either hemisphere within somatosensory cortex previously identified in the postcentral gyrus and parietal operculum (Burton et al., 1997a).
(2) Attention Tasks Minus Passive Stimulation/Counting' Control: Composite Analysis. Activity present during the passive stimulation/counting' control task was subtracted from activity present when the subject performed the attention tasks (selectively cued to roughness or to duration, or no cued attribute). In these subtraction images, any common activations due to verbal responses, passive tactile stimulation and extraneous effects of being scanned were removed. The remaining positive foci reflected activity from several possible processes. First, the foci may be part of an activated attention network that generates signals which modulate sensory processing in multiple modalities. Second, the foci may be components of the somatosensory system that are modulated by signals generated elsewhere, possibly by a nonsensory attention network. Third, the foci may be activated as a result of the increased arousal and greater memory demands of the attention tasks over the control task.
An ANOVA, performed for each significant focus from all subtraction pairs (hypothesis-generating and hypothesis-testing data sets), assessed whether the change in rCBF could be attributed to one attention condition or a subset of attention conditions rather than equally to all three attention conditions. For example, the selective tasks might have caused an increase in rCBF that replicated across data sets despite finding no change in rCBF for that region in the divided attention task. The dependent variable was change in rCBF and the main independent variables were subject, condition (selected roughness, selected duration, divided) and subject-by-condition. These ANOVA analyses yielded no significant effects, demonstrating that for each focus under investigation, no attention task accounted for significantly more of the rCBF changes. Thus, since the three attention conditions activated a common set of foci, further discussion mainly considers data collapsed across attention conditions; this has the added advantage of reducing background noise and increasing statistical power.
Increases in blood flow were identified in 11 foci; with the exception of a focus in the thalamus (labeled 1 in Table 2 and Figs 3 and 4
), these predominantly were in parietal cortex (Table 2
). Three foci (labeled 1, 2 and 11 in Table 2
and Figs 3 and 4
) satisfied the strictest, Bonferroni-corrected criteria and five (labeled 3, 4, 5, 8 and 9) passed the lenient criteria of 0.05. Three foci did not cross-validate (labeled 6, 7 and 10), but were prominent on the images, and were therefore included in the following description. Eight of the foci were found in the left hemisphere, contralateral to the stimulated finger. Many of the foci in parietal cortex occupied regions previously identified as parts of the somatosensory system.
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A pronounced focus was seen along the contralateral parietal operculum, close to the posterior third of the insula (labeled 2 on Figs 3 and 4). A smaller, less conspicuous locus of increased rCBF occupied a comparable position in the right hemisphere (labeled 7 in Fig. 4
). The ipsilateral focus did not cross-validate (Table 2
). The same contralateral site was identified in all three attention tasks but was not found during the control tasks (Fig. 3
).
Two activation foci lay along the postcentral gyrus contralateral to the stimulated fingertip. One occupied the crown of the postcentral gyrus, extending anteriorly toward the central sulcus and posteriorly to the postcentral sulcus (labeled 6 in Table 2 and Figs 3 and 4
). Although the same focus was observed across all attention conditions, it did not cross-validate between the two halves of the data (Table 2
). However, a significant single t-test result was obtained when all of the subject data (~50 subtraction pairs from 10 subjects) was included and with the blood flow measurements centered on the coordinates of focus 6 (t = 5.35, df = 9, P = 0.0005). The same region was not significantly activated when contrasting blood flow during the passive stimulation/counting control task to an eyes-closed-rest condition (Fig. 3, x
= 49 to 53).
Another postcentral gyrus region was also located on the crown of the postcentral gyrus (labeled 3 in Table 2 and Figs 3 and 4
). It was lateral and posterior to focus 6. This region cross-validated using lenient criteria for all three attention tasks (Table 2
). It was not seen during the control task (Fig. 3
). Focus 3 was contiguous to site 2 along the parietal operculum although, as shown in Figure 4
(y = 21 and 25), the two peaks were separable.
Figure 5 shows blood flow measurements obtained from comparable 11 mm diameter spheres, centered on foci 6 and 2, which respectively included S1 and S2. Predictably, across all tested conditions the highest blood flows appeared during the attention tasks, which principally accounted for significant F ratios for the task variable for each region [S1: F(3) = 4.32, P = 0.017; S2: F(3) = 10.09, P = 0.0003]. However, post hoc comparisons within regions found differences across the tasks. Thus, there was significantly greater blood flow through S2 in the attention tasks than all other tasks; blood flow measures were equal during the other three tasks. In S1 significantly greater blood flow similarly occurred during the attention tasks. In addition, significantly lower blood flow occurred during the passive stimulation/counting task; blood flow measures were equal during the eyes-closed-rest and passive-stimulation tasks. Blood flows during the attention tasks were significantly greater over S2 than S1.
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Blood Flow Increases in Frontal Cortex
Three foci were activated in the frontal cortex during the attention tasks. One focus occupied contralateral cortex within the precentral sulcus (labeled 9 in Table 2 and Fig. 3
). This focus, which cross-validated using lenient criteria (Table 2
), was present in all three attention conditions. The region covered by this activation was >1 cm medial to focus A found on the precentral gyrus in the control task (Fig. 3
). Thus, these foci do not overlap.
Another focus appeared on the anterior third of the insula on the contralateral side (labeled 10 in Table 2 and Fig. 3
). Possibly due to intersubject variability, it did not satisfy even the lenient criteria although it was consistently observed, especially during the roughness discrimination task. There was no evidence of activation on the insula in the control task.
The attention tasks activated a third frontal cortex focus that occupied a portion of the middle frontal gyrus, ipsilateral to the stimulated finger (labeled 8 in Table 2). This rCBF satisfied lenient cross-validation criteria and was present in all attention tasks.
Blood Flow Increases in the Cingulate Cortex
One focus was found near the superior margin of the cingulate gyrus in all three attention conditions, contralateral to stimulation (labeled 11 in Table 2 and Figs 3 and 4
). There was no comparable site activated during the control scans.
(3) Attention Tasks Minus Passive Stimulation/Counting' Control: Single Condition Analysis. In separate cross-validation analyses for each attention condition, we identified no regions that were only significantly activated by one of the conditions.
(4) Attention Task Comparisons. Potential differences in blood flow changes for the different attention tasks were analyzed with a cross-validation procedure that examined PET difference images created by contrasting scans obtained during all selective attention trials with scans when subjects divided their attention between both tactile attributes. Only bilateral cortical foci in the orbito-frontal region showed increased blood flow during the divided attention task. Only the left focus passed our stricter criterion for significance. Both foci occupied coordinates that placed them within the region labeled Brodmann area 10 in the Talairach atlas (left BA 10: 29, 61, 4; t = 3.3, df = 7; P = 0.013; right BA 10: 17, 53, 0; t = 2.26, df = 7; P = 0.058).
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Discussion |
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The psychophysical results showed the advantages of a selective attention strategy (Posner, 1986; Allport, 1989
; Posner and Driver, 1992
). As in prior studies with visual stimuli in humans (Corbetta et al., 1991
), the percentage correct was significantly higher when attention was selectively focused on a validly cued feature of a multidimensional tactile stimulus than when attention was divided between two features. Stimulus values and subjects' verbal responses were identical in the selected and divided conditions, ensuring that perceptual discrimination difficulty remained constant across trial types. However, there was a greater memory demand during the divided attention trials as both stimulus attributes required attention. The decreases in percentage correct on neutrally cued trials demonstrate the benefit of focusing limited resources on a single cued feature. It is unlikely that the selected attention advantage resulted from a reflexive process that drew attention to one of the stimulus features because performance was not significantly different on valid trials cued to texture or duration.
A cortical network of sensory and nonsensory regions has been proposed for visual attention processes (Posner and Petersen, 1990; Posner and Driver, 1992
; Posner and Dehaene, 1994
; Frith and Dolan, 1997
; Büchel et al., 1998
; Coull, 1998
). In a comparable arrangement the imaging data were expected to reveal components of the tactile attention network as the same tactile attention task was performed by the same subjects during scans. First, we discuss possible sites of attentional modulation within somatosensory foci. Next, we consider blood flow increases in several nonsensory cortical foci. Several of these were near or overlapped foci previously identified as nonsensory components of the visual attention network.
Blood Flow Increases Within the Somatosensory System
The current study did not find significant differences within the somatosensory network between selected and divided attention. Similarly, Corbetta and colleagues (Corbetta et al., 1991) found comparable activation of visual cortical foci for their selected and divided attention tasks. Thus, both types of attention tasks activate overlapping sensory cortex within their respective visual or tactile domains. In contrast, selected and divided attention tasks activated different foci outside the sensory regions (see below).
Modulation of rCBF in the Postcentral Gyrus
The activated focus across the contralateral postcentral gyral regions resembled the pattern reported in previous PET (Burton et al., 1997a; Roland et al., 1997
) and functional magnetic resonance imaging (Lin et al., 1996
) studies that involved tactile stimuli evoking a roughness perception. The most anterior part of this area, which extends into the central sulcus, possibly corresponds to the finger representation of area 3b (Woolsey et al., 1979
; Lin et al., 1996
; Burton et al., 1997a
; Roland et al., 1997
; White et al., 1997
). As noted previously (Burton et al., 1997a
), the more posterior aspects of this focus, which covers the postcentral gyrus and the anterior bank of the postcentral sulcus, suggest that in humans, like nonhuman primates (Pons et al., 1985
), the finger representations of Brodmann areas 1 and 2 were also engaged. However, separable foci were not observed and Brodmann area distinctions based on these PET imaging data were not possible. Therefore, the following discusses the collective activation across the postcentral gyrus as S1.
We observed significantly smaller changes in CBF in this region of the postcentral gyrus during all of the control tasks (eyes-closed-rest, passive tactile stimulation and passive stimulation/counting). In addition, the lowest blood flows over S1 occurred during the passive stimulation/counting task. There are several possible interpretations for these contrasting findings in S1. An unlikely technical explanation for observing lower increases in rCBF over S1 in the passive stimulation/counting control trials is that a dominant region of increased rCBF in the precentral gyrus, which probably reflected mouth and face movements during verbalizations, overwhelmed the resolution of our analysis routines. This implies that blood flow increases within the postcentral gyrus were subsumed under the motor-activated changes represented in the precentral gyrus. However, we observed two distinct foci, one on the precentral and one postcentral, on difference images created from contrasting the attention tasks with eyes-closed-rest control condition. These images showed no quenching of postcentral activation sites by blood flow changes on the precentral gyrus. In addition, Figure 3 shows that the precentral focus in the control task was entirely confined and did not spread across the central sulcus to the region of the S1 representation labeled 6 in the figures.
The significantly smaller local blood flow increases relative to the postcentral gyrus during the passive stimulation/counting control task possibly reflects engagement in the verbalization task. Thus, because S1 might have been inactivated when subjects engaged in a non-tactile task, we could not observe rCBF changes in S1 despite the presence of tactile stimulation during the passive stimulation/counting control task. Similarly, PET studies in which attention was directed to visual (Haxby et al., 1994), auditory (Fiez et al., 1995
) or other tactile (Drevets et al., 1995
) tasks also reported decreases in blood flow in S1. Anecdotally, most subjects reported being unaware of the tactile stimulation during control trials. When subjects receive passive tactile stimulation, but are not engaged in another task, limited resources are not being taxed, so S1, and possibly other components of the somatosensory system, are not depressed. Thus, passive stimulation with gratings, without a superimposed counting task (Lin et al., 1996
; Burton et al., 1997a
), or other studies that used a variety of somatosensory stimuli and response measurement or brain-imaging techniques, identified foci in this region (Woolsey et al., 1979
; Roland, 1981
; Hari et al., 1984
; Fox et al., 1987
; Seitz and Roland, 1992
; Burton et al., 1993
; Forss et al., 1994
).
During the attention tasks, increased rCBF was observed in the S1 cortex. However, these blood flow changes failed to reach significance in the cross-validation analysis, possibly because only the tip of a single digit received stimulation, and this may have activated too small a focus to survive the more conservative (and less sensitive) tests used in this study. Associated with this is the difficulty of cross-realigning data from several subjects in a region of highly varied anatomy (Rademacher et al., 1993; Damasio, 1995
; Zilles et al., 1997
). Thus, possible partial volume effects from having to realign around the central sulcus, coupled with an already small active focus, could have reduced reproducibility across subjects. As the cross-validation methods used maybe too insensitive to detect small foci in anatomically variable regions without having larger data sets, we reanalyzed the significance of blood flow changes in the volume centered on focus labeled 6. This t-test, which used all of the data, and therefore had twice the degrees of freedom, was significant, indicating that rCBF over focus 6 was substantially greater than background levels.
There was a smaller blood flow increase in S1, in comparison with S2 (see below), and this might reflect more limited involvement of S1 in attention. This suggestion is consistent with single-neuron data which show that cells from S1 more frequently display comparatively more minor modulation of responses and these effects appear in a smaller proportion of the cell sample (Hsiao et al., 1993b; Burton et al., 1997c
).
Increased rCBF in S1 during the attention tasks does not directly imply operation of an attention mechanism within an early hierarchical component of the somatosensory cortex because the subtraction from task conditions was a control state (passive stimulation/counting) with depressed blood flows in comparison to baseline conditions during eyes-closed-rest. The observed rCBF increases in S1 possibly resulted from passive stimulation activity that was not selectively depressed because tactile information was now behaviorally relevant. Attention-related modulation of S1 was previously described in a PET study in which blood flow to S1 was 13% higher when subjects attended to vibrotactile stimuli than when they received the same stimuli but also performed a non-tactile, distracting counting task (Meyer et al., 1991). The present data, therefore, suggest that S1 activity is boosted when tactile information is behaviorally relevant and depressed when information about other modalities or tasks must be processed.
The occurrence of similar changes in blood flow in the posterior thalamus suggests that top-down mechanisms might affect the input of information to somatosensory cortex from the thalamus. Thus, significant increases appeared in the thalamus only when contrasting attention tasks with the passive stimulation/counting control condition but not when the latter was contrasted with results from eyes-closed-rest scans. Further study of the role of subcortical structures during attention tasks are clearly needed.
Modulation of rCBF in the Parietal Opercular Cortex
Increases in rCBF bilaterally in parietal opercular cortex (e.g. S2) during the attention tasks confirm numerous reports of S2's role in somatosensory processing of innocuous tactile stimulation (Garcha and Ettlinger, 1978; LaMotte and Mountcastle, 1979
; Robinson and Burton, 1980
; Garcha et al., 1982
; Roland, 1987
; Carlson and Burton, 1988
; Burton and Sinclair, 1990
; Burton et al., 1993
, 1997a
, Burton et al., b
; Hsiao et al., 1993a
,b
; Sinclair and Burton, 1993
; Ledberg et al., 1995
; Huttunen et al., 1996
; Roland et al., 1998
). Nearly bilaterally matched foci along the parietal operculum showed increases in rCBF during the attention tasks (labeled 2 and 7 in Table 2
), but only the changes in the contralateral cortex were significant. The increase during the attention task reflected a change over a zero baseline because no blood flow increases were detected during the passive stimulation/ counting task and because the blood flow measurements for S2 during all control tasks were equal.
This enhanced rCBF suggests that when attention was directed to tactile information, S2 activity was even greater than when the subject received but ignored passive stimulation. This result was similar to the changes observed in S1, and further suggested that blood flow increases appear in somatosensory cortex for behaviorally relevant stimuli. Unlike the changes in S1, however, those over the contralateral S2 were of sufficient magnitude and consistency that they cross-validated. The blood flow increases over S2 were also significantly greater than those over S1. Thus, it is possible that S2 activity during these demanding attention tasks was enhanced above the level that would result from a less difficult vigilance task for passive tactile stimulation. This finding is consistent with results from neurophysiological studies in monkeys that described significant modulations of S2 activity during attention-demanding tasks (Poranen and Hyvärinen, 1982; Hsiao et al., 1993b
; Burton et al., 1997b
). Additionally, a recent PET study found activation near our parietal operculum focus during a roughness discrimination task (Roland et al., 1998
). However, there has been little investigation of the role of S2 in duration discrimination. The current results demonstrate that S2 is activated by attention tasks related to stimulus duration as well as stimulus texture. Collectively these results suggest that S2 provides somatosensory processing for tactile attention to a variety of stimulus features.
The greater increases in blood flow in S2 than S1 might reflect that S2 is an essential component of a descending control path within the tactile attention system. A top-down path, acting through an enhancement mechanism that primes the somatosensory regions, would enable nonsensory regions to regulate sensory regions or higher-level sensory regions like S2 to regulate lower-level sensory responses in S1. This network organization has been proposed in the visual attention system (Corbetta et al., 1991; Frith and Dolan, 1997
). A similar hypothesis regarding the predominance of S2 was obtained previously in a study of how limb movements affected sensory responses in S1 and S2. When sensory input was delivered to a moving limb, S1 activity decreased (Huttunen and Homberg, 1991
; Chapman, 1994
), but S2 activity increased (Huttunen et al., 1996
). The greater increases in rCBF observed in the current study, together with the results with a moving limb, suggested that signals which modulate S2 activity do not only ascend from S1 to S2, but possibly also descend to S2 from nonsensory areas. Thus, modulation from nonsensory areas might influence S2, which in the attention tasks, enabled S1 activity. If further studies confirm this speculation, it complicates interpretation of prior hypotheses about the serial and hierarchical flow of processing from S1 to S2 (Pons et al., 1987
).
Blood Flow Increases in the Posterior Parietal Cortex
A region in the posterior parietal cortex was activated bilaterally by the attention tasks. Clinical literature describing neglect syndromes (Mesulam, 1981; Moscovitch and Behrmann, 1994
) and neuroimaging studies of visuospatial attention (Haxby et al., 1991
; Corbetta et al., 1993
; Vandenberghe et al., 1996
; Nobre et al., 1997
; Corbetta, 1998
), vibrotactile attention (Johannsen et al., 1997
) and vigilance (Pardo et al., 1991
) have emphasized a role for posterior parietal region(s) in attention processes. Thus, a posterior parietal region may be capable of mediating attention to signal streams from multiple modalities (Andersen, 1997
). However, the exact location of the identified region differs between studies and modalities, suggesting that the different tasks possibly recruit slightly different anatomical regions (Vandenberghe et al., 1996
). For example, the focus found using the current paradigm was located in the depths of the postcentral sulcus at a distance from the more anteriorly located postcentral gyral site. According to the Tailarach atlas, the posterior parietal focus was likely in Brodmann area 7; it was ~1.5 cm anterior to the most anterior site described in visuospatial experiments, which occupied the posterior wall of the postcentral sulcus and extended posteriorly to the intraparietal sulcus (Nobre et al., 1997
; Corbetta, 1998
). Neurophysiological studies in area 7 of monkeys have shown activity reflecting body or visual spatial coordinate systems (Andersen, 1989
; Colby et al., 1993
). These observations, together with clinical (Mesulam, 1990
) and recent imaging data of activity in frontal cortex serving gaze control (Corbetta, 1998
), suggest that mechanisms for selecting stimuli in reference to body or visual spatial coordinates (extrapersonal space) may be crucial to attention processes. However, such spatial representations for the somatosensory system may occupy more anterior portions of the posterior parietal cortex than are involved with visually guided arm movements, which activate sites within the medial bank of the intraparietal sulcus (Kertzman et al., 1997
).
Consistent with reports of more frequent attention disorders in patients with lesions to the right parietal cortex (Mesulam, 1981, 1990
; Moscovitch and Behrmann, 1994
), visuospatial attention studies found that the right hemisphere was dominant (Corbetta et al., 1993
; Nobre et al., 1997
). Thus, the bilateral activations observed in the present study with subjects attending to right hemispace, relative to their bodies, are consistent with the role of the right hemisphere in directing attention to extrapersonal space irrespective of the body hemispace of selected stimuli (Mesulam, 1990
).
Other Blood Flow Increases
Cingulate Gyrus
Activation of an anterior cingulate site during visual attention tasks prompted the hypothesis that this region acts as part of an executive attention network which distributes resources between multiple dimensions of a stimulus when all are pertinent to a task the subject is motivated to perform (Posner and Petersen, 1990). Supporting evidence for the anterior cingulate's role in an attention system comes from clinical assessment of attention disorders in patients with strokes in this region (Laplane et al., 1981
; Mesulam, 1981
) or after anterior cingulotomies (Watson et al., 1973
; Janer and Pardo, 1991
). Common to all brain-imaging studies showing activation in the anterior cingulate was performance of a cognitively demanding stimulusresponse task that required selection between competing stimuli. Examples involving competing stimuli include the Stroop task conflict condition (Pardo et al., 1990
; Derbyshire et al., 1998
) and, most similar to the current experiment, during divided, but not selected, attention conditions in visual discriminations (Corbetta et al., 1991
, 1993
; Nobre et al., 1997
). In the present study, subjects encountered greater processing demands during the divided attention task in which information about both surface texture and stimulus duration had to be processed and retained in memory to make the discrimination. However, all of our attention tasks activated region 11, which involved parts of the anterior cingulate that included Brodmann area 32. In this study all of the tasks were demanding as shown by performance levels that seldom exceeded 75% correct responses. Therefore, despite significantly more errors during the divided attention trials, there were high processing demands throughout, and this might have resulted in consistent activation of the anterior cingulate region even during selective attention trials.
The anterior cingulate regions identified in most attention studies include Brodmann areas 24 and 32. This site was distinct from a posterior and superior site seen during the control scans (labeled C); the latter occupied a midline portion of Brodmann area 6 and probably involved the supplementary motor area. The coordinates of the anterior cingulate focus in the current study (1, 7, 48) overlap the mean coordinates found in visual spatial attention studies: 2.3, 22.4, 37.3; SD: 9.1, 9.9, 4.5 (Corbetta et al., 1993) and 8, 16, 44 (Nobre et al., 1997
). Combined, these activations are consistent with the theory that attention requires some nonsensory foci which process information from multiple modalities. However, the cingulate gyrus also contains a heterogeneous collection of cortical areas (Vogt et al., 1992
, 1996
; Picard and Strick, 1996
; Whalen et al., 1998
) that, in the mid-cingulate region, includes sites also activated when subjects receive painful stimuli (Vogt et al., 1996
; Derbyshire et al., 1998
).
Frontal/Motor Areas
Activation of several frontal regions during the control scans possibly reflects subjects' verbal responses, and hence the corresponding motor representation of the mouth (labeled A and D in Table 1) and a paracentral lobule region, corresponding to the supplementary motor area (SMA) (labeled C in Table 1
). Subtracting these activations from those present during the attention tasks, however, showed little remaining activation of motor cortex. Thus, the motor patterns for speaking were the same in both conditions and probably involved bilateral control.
After subtracting the precentral activations present in the control trials from the attention trials, significant blood flow increases were still seen in a medial sector of the contralateral precentral gyrus (labeled 9 in Table 2), which is included as part of Brodmann's area 6 in the Tailarach atlas (Talairach and Tournoux, 1988
). This increase during the attention tasks might reflect that more meaningful verbal responses were required because during these trials they were related to discrimination decisions rather than practiced repetitions of the same words.
Three additional frontal regions (anterior insula, Brodmann area 9 in the middle frontal gyrus and Brodmann area 10 on the orbital frontal cortex) showed increased blood flows only during the attention tasks. The affected sites overlapped with those previously activated in episodic retrieval tasks (Buckner and Tulving, 1995; MacLeod et al., 1998
). In all of the attention trials subjects had to remember some property of the first stimulus (its roughness or length) in order to make a paired comparison to the second stimulus. During the divided attention trials the memory load was probably greater because properties of both attributes had to be retained when comparing the second stimulus to the first. This might have contributed to bilateral activation of area 10, which was uniquely associated with the divided attention task when compared to trials with selective cuing.
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Notes |
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Address correspondence to Dr H. Burton, Department of Anatomy and Neurobiology, Campus Box Number 8108, Washington University School of Medicine, 4566 Scott Avenue, St Louis, MO 63110, USA. Email: harold{at}touch.wustl.edu.
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