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Functional imaging during covert auditory attention in multiple sclerosis
Journal of the Neurological Sciences 218 (2004) 9 – 15 www.elsevier.com/locate/jns
Functional imaging during covert auditory attention in multiple sclerosis Michael P. Santa Maria a, Ralph H.B. Benedict a,*, Rohit Bakshi a, Mary Lou Coad b,c, David Wack b,c, Robert Burkard d, Bianca Weinstock-Guttman a, Susan Roberts d, Alan H. Lockwood a,b,c a
Department of Neurology, School of Medicine, State University of New York (SUNY) at Buffalo, Buffalo General Hospital, Neurology, Suite D-6 Buffalo, 100 High Street, Buffalo, NY 14203, USA b Department of Nuclear Medicine, State University of New York (SUNY) at Buffalo, Buffalo, NY, USA c VA Western New York Healthcare System of Buffalo, Buffalo, NY, USA d Department of Communicative Disorders and Science, State University of New York (SUNY) at Buffalo, Buffalo, NY, USA Received 25 June 2003; received in revised form 4 September 2003; accepted 1 October 2003
Abstract Recent literature suggests that the brain in multiple sclerosis (MS) undergoes reorganization that subserves the performance of visual and motor tasks. We identified sites of cerebral activity in 16 MS patients while performing a covert attention (CA) task, presented in the auditory modality. Positron emission tomography (PET) revealed activation of rostral/dorsal anterior cingulate cortex (ACC) in normal subjects studied previously. Activity in this region was not significant in MS patients, but there was a large region of activity in superior temporal cortex. Decreased activation of frontal attentional networks and greater activity in sensory/perceptual cortical areas (auditory association cortex) suggests a reduction of transmission along white matter tracts connecting these regions. This study demonstrates cingulate hypoactivity and cerebral reorganization during auditory attention in MS. D 2003 Elsevier B.V. All rights reserved. Keywords: Multiple sclerosis; Attention; PET
1. Introduction Cognitive dysfunction occurs in roughly 50% of multiple sclerosis (MS) patients [1] and its adverse impact is well documented in studies of employment, avocational activity and instrumental activities of daily living [2,3]. The hallmarks of MS-associated cognitive disorder are slowed processing speed and impaired new learning [1,4,5]. The Paced Auditory Serial Addition Test (PASAT) [6], an auditory task emphasizing processing speed and working memory, is sensitive to neuropsychological dysfunction in MS [4]. The PASAT requires patients to monitor a series of audiotaped digits while adding each consecutive digit to the preceding digit. An oral (i.e., motor) response is required. Due to its reliability and sensitivity, the PASAT was included in the MS Functional Composite, a common clinical
* Corresponding author. Tel.: +1-716-859-1403; fax: +1-716-8591419. E-mail address: [email protected] (R.H.B. Benedict). 0022-510X/$ - see front matter D 2003 Elsevier B.V. All rights reserved. doi:10.1016/j.jns.2003.10.019
outcome measure [7]. A visual analog to PASAT was recently used in a functional imaging study of MS patients. Compared with normal controls, patients failed to activate anterior cingulate cortex (ACC), but activated new regions suggesting cerebral reorganization or plasticity [8]. The role of the ACC in cognition has been studied intensely in recent years [9,10]. While the ACC is a primary substrate for attention, it is also widely recognized as an integral region for premotor function [11 –13]. Recognizing that the PASAT lacks specificity for discrete cognitive processes [12], we chose to disentangle the influence of attention and motoric responding in a study of continuous auditory attention in healthy volunteers [14]. Participants were asked to mentally note targets without responding orally or manually. To document attention we recorded event related potentials and found significantly higher P3 responses following target, compared to non-target, stimuli. Simultaneously obtained 15O-H2O positron emission tomography (PET) revealed activity within the right ACC, Brodmann area (BA) 32, approximating dorsal ACC. The site of maximum activity was in a voxel 36 mm anterior to
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that identified in a prior study using similar stimuli with a motor response [9]. We therefore argued that sub-regions within the ACC can be distinguished: a mid- or rostral – dorsal sub-region (BA 32V) that supports attention and a caudal area (BA 24cV) that mediates initiation of a modalityspecific motor response [11]. This cingulofrontal transition zone [13] is interconnected with prefrontal cortex and deep gray matter via white-matter, which courses proximally to the lateral ventricles [13]. Therefore, ACC-dependent cognitive functions like attention should be disrupted in a white matter disease such as MS. The covert continuous performance task described above provides an opportunity to study auditory attention in patients with MS. Accordingly, we used this task to study 16 MS patients. Our primary objective was to determine what regions of the brain are activated by this paradigm. We hypothesized that patients would fail to activate anterior attention zones but activate other regions of the brain.
2. Methods 2.1. Subjects We studied 16 MS patients diagnosed by consensus criteria [15] with a mean age of 41.4 years (S.D. = 6.9). All were right-handed and 11 were female. Twelve patients had relapsing-remitting disease and four had secondary progressive course. Disease duration ranged from 2 to 17 years (M = 9.6, S.D. = 5.1). Physical disability was assessed by an experienced neurologist specializing in MS, blind to PET findings, using Expanded Disability Status Score (EDSS) [16]. Median EDSS was 2.5 (S.D. = 1.8, range = 1.0 –7.0). In some analyses, these patient data were compared with data derived previously from healthy adult volunteers (6 male 6 female; 15 Caucasian, 1 Black; mean age = 41.4, S.D. = 6.8, mean education = 14.2, S.D. = 1.6) [14]. None of the patients had other major medical illnesses or had undergone corticosteroid treatment within 4 weeks of the study. All participants provided written consent and were provided with a written description of the study, which had been approved by an institutional review board. Other exclusion criteria included (1) comorbid physical illness that could potentially impact neurologic or cognitive function; (2) severe motor or sensory defect that would substantially interfere with neuropsychological testing; (3) current psychiatric disorder other than personality or behavior changes secondary to MS or minor depression; (4) current medications that contraindicate experimental procedures or that could potentially impair or facilitate cognitive function; (5) MS relapse within four weeks of the study; (6) pregnancy. Psychotropic medications for minor depression, insomnia and fatigue were permitted. All patients underwent audiometric testing and were required to have 90% speech discrimination in each ear, and reliably perceive tones of
z 25 dB HL in the 250– 2000 Hz range and 35 dB HL in the 4000– 8000 Hz range. 2.2. Neuropsychological testing and MRI Neuropsychological tests emphasizing attention and memory were selected to divide patients into ‘high’ and ‘low’ functioning subgroups. These tests included the Total Recall and Delayed Recall indices from the California Verbal Learning Test-II [17] and the Brief Visuospatial Memory Test-Revised [18], as well as the Trail Making Test [19] and PASAT. Standard scores were calculated for each test using published normative data tables. The neuropsychological index was calculated by taking the mean standard score across these measures. MS patients were divided into ‘high’ and ‘low’ performing subgroups based on a median split of the index distribution. These sub-groups did not differ significantly in age (low 39.8 S.D. = 5.6; high 43.1 S.D. = 7.9), education (low 16.3 S.D. = 2.2; high 14.9 S.D. = 1.9), disease duration (low 9.6 S.D. = 5.2; high 9.6 S.D. = 5.3), EDSS (low 3.8 S.D. = 2.2; high 2.5 S.D. = 1.0), gender (low 3 male 5 female; high 2 male 6 female), or race (low 7 Caucasian, 1 Black; high all Caucasian) by t or v2 test. Brain MRI was obtained on a Philips Gyroscan ACS-NT 1.5-T scanner (Best, The Netherlands). Axial T1-weighted images (TR/TE: 400/10) were used to co-register with PET in order to more accurately define individual brains and group rCBF. Axial fast fluid-attenuated inversion-recovery (FLAIR) images (TR/TE/TI: 8000/120/2200) were obtained to estimate hyperintense lesion burden. For both pulse sequences, the matrix size was 192 256, number of signal averages (excitations) was 2, number of slices was 24, and section thickness was 5-mm with no inter-slice gaps. Images were obtained parallel to the canthomeatal plane using internal landmarks. Analysis of MRI lesion load was performed using a Sun Ultra 10 workstation (Sun Microsystems, Santa Clara, CA) using Java Image software (version 1.0, Xinapse Systems, Northants, UK, http://www.xinapse. com) by a trained technician blind to clinical data, using previously described methods [20]. Briefly, all FLAIR axial slices from midpoint of the cerebellum to the vertex were entered into an algorithm involving masking and thresholding to separate hyperintense lesions from the nonlesional tissue. The software then automatically calculated the total FLAIR lesion volume (FLV) by multiplying lesion area by slice thickness. 2.3. PET and activation task Participants underwent 15O-H2O PET and EEG recording simultaneously, in a single session, during which they performed auditory tasks. The stimuli, presented with a NeuroScan computer system (NeuroScan, Hearndon, VA), were previously recorded human-voiced English syllables ending with /a/ and beginning with either a stop or nasal consonant. These stimuli had been developed through the
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recordings of 8 speakers (4 male, 4 female) who generated 64 original stimuli, 8 for each of the following syllables (/ba/, /da/, /ga/, /pa/, /ma/, /na/, /ta/, /ka/). All were digitized to a rate of 41,000 Hz for a duration of 200 ms. The same stimuli were employed in three repetitions of the activation (covert attention or CA) and control (listen only or LO) tasks via foam cushion insert-earphones. The peak sound pressure level approximated 90 dB. The inter-stimulus interval was 1 s and the target probability rate was 0.19. Each sequence lasted approximately 5 min and included 333 randomly ordered stimuli. The experiment included three presentations of the two tasks employed previously [14]: CA and LO control state. During CA, patients were instructed to note the occurrence of the designated target without making a motor or oral response. During the LO condition, patients were told to only listen to the auditory stimuli. These conditions were presented in one of the following counterbalanced orders: CA – LO – CA – LO – CA – LO or LO – CA – LO – CA – LO – CA. We employed a Siemens ECAT 951/31R tomograph, modified for 3D data collection, so that the inferior image plane coincided with the canthomeatal line. To reduce ambient noise, either Cabot Safety Model 3000 earmuffs or a Bose Active Noise Suppression headset was placed over both ears. Head position was maintained by means of an individually fitted thermoplastic mask. After a 20-min transmission scan (examples of stimuli were presented during transmission scan to insure accurate comprehension), six emission scans were obtained. Each scan began with the slow i.v. injection of a bolus (15-s injection followed by a 15-s flush) of 7 mCi or less of 15O-water as a tracer of CBF. Activation procedures began 20 s before beginning the injection and continued throughout the scan. Sixty seconds of emission data, timed from the arrival of the 15O-water in the brain, were used for image reconstruction (random coincidence correction, measured attenuation, Hann filter, cutoff frequency 0.4 cycles/pixel) and analysis. EEG signals were recorded from three gold electrodes (Fz, Cz, Pz according to the International 10/20 System). A ground electrode was placed on the forehead. Ocular movements were monitored and recorded from vertical (VEOG) and horizontal (HEOG) channels. Images were converted to the Analyze format and analyzed using the 1999 version of Statistical Parametric Mapping (SPM) [21]. Images were corrected for between-
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scan movement, normalized into standard space and normalized to a common mean CBF value by analysis of covariance. A 15-mm Gaussian smoothing filter was employed to increase the signal-to-noise ratio, condition the data to conform with the requirements of Gaussian field theory and to minimize confounding of results due to individual anatomical differences. The normalization parameters derived from the T1-weighted MRI were used to warp the coregistered PET scans into a standard stereotaxic space. This template conforms to the space defined by the International Consortium for Brain Mapping project (ICBM) (NIH P-20 grant), and closely approximates the space described in the atlas of Talairach and Tournoux [22]. The registration of the normalized mean PET, MRI images and the template was checked manually to confirm that excessive warping had not occurred. 2.4. Statistical analysis Statistical tests were based on the cognitive subtraction technique wherein the activation pattern for one condition is subtracted from the activation pattern for another. The CA – LO contrast was designed to isolate attention while controlling for neural activity unrelated to the attention task (e.g., motor activity). Subtracting LO from CA thus served to neutralize extraneous factors that are alike during both conditions such as primary auditory processing (as opposed to attending to auditory stimuli), tactile stimulation due to contact with the PET apparatus and padding, and subjectspecific thoughts and mood states, and other neutral activity present in a ‘‘resting state’’. The MS patient data were merged with the normal control group from a previous study [14]. We first examined within-subjects effects for the MS patients and controls separately, and then tested betweengroups effects. Analyses were based on a threshold of p < 0.05, corrected for multiple comparisons, searching the entire image. For some analyses, a more restricted analysis was performed wherein a mask was created that limited the analysis to a subset of voxels (defined by the voxels included in the CA – LO contrast in normals and MS patients at the p = 0.001 level of significance, uncorrected for multiple comparisons). Within these restricted volumes, we searched for sites active in one group and not the other, e.g., [normal(CA – LO) MS(CA –LO)], thus increasing the statistical power of the analysis by excluding voxels that are unlikely to participate in the task. The correlation between
Table 1 Within-group, single points of significant maximal activity (by SPM) for auditory attention tasks using same stimuli and contrasted against a passive, listening control task Study group
Region
healthy volunteer
Right rostral/dorsal ACC; BA [32] Left superior temporal gyrus; BA [22] Left lateral prefrontal cortex; BA [44, 45, 46, 10] Left superior temporal gyrus; BA [22, 38, 42] Right and Left ACC; BA [32]
MS
x 6 58 32 64 4
y
z
p cluster
p voxel
26 38 48 16 12
30 12 20 8 40
< 0.001 0.002 < 0.001 < 0.001 < 0.01
< 0.001 .03 < 0.001 < 0.001 ns
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activity specified by the CA – LO contrast and FLV was tested using analysis of covariance.
3. Results
Fig. 1. Regions of increased rCBF analyzed by SPM projected on the same template brain in two panels. CA is contrasted against passive listening (LO) to identical stimuli (CA – LO) where CA requires discrimination of targets from non-targets. In each panel, the top image shows regions rendered on to the lateral surface of the left hemisphere. The lower image shows activity as viewed is from the frontal pole. All activity is presented with darker red representing more reliable or denser activity. (A) Previously published data obtained from 16 healthy volunteers. The contrast is shown at a conservative threshold of p = 0.00001 to separate more clearly the various maxima. There is a region of activity within the right dorsal aspect of the cingulate gyrus, and three other regions of activity including left lateral prefrontal cortex, premotor cortex and posterior temporal cortex. (B) Activity obtained from 16 MS patients. The only significant region at the voxel level occurs in the superior temporal gyrus (STG). The STG activation is large, encompassing anterior left superior temporal gyrus extending to posterior superior temporal gyrus (BA 39). Maxima within the ACC are present but of marginal significance.
Mean standard scores on neuropsychological tests ranged from 81 on the visual memory test (Brief Visuospatial Memory Test-Revised delayed recall) to 98 on the verbal memory test (California Verbal Learning Test-II trials 1– 5). The mean standard score across all tests was 90 (S.D. = 14.2). The ERP data were subjected to a withinsubjects comparison of amplitudes by stimulus type (target, non-target), which was not significant. The coordinates of significant maxima observed are presented in Table 1 along with maxima from our previous work with healthy volunteers [14]. Images from the analysis of PET data are presented in Fig. 1 (Fig. 1A, normal subjects and b, MS). For both groups, the CA – LO contrast derived from within-subjects analyses revealed activity in right ACC. While locations of the maxima were generally the same, the activation was only significant at the voxel level among normal subjects. Among patients, the only statistically significant region (voxel, p < 0.001) was the left superior temporal gyrus. This region was quite large (2037 voxels), encompassing anterior and posterior subregions and spanning BAs 22, 38 and 42. When the ‘high’ and ‘low’ performing MS subgroups (based on median split) were compared [high(CA – LO) vs. low(CA – LO)], there were no significant maxima detected. When the analysis was repeated using a mask to restrict the voxels examined to those activated in the CA –LO contrast in normals, we again failed to find significant differences between these subgroups.
Fig. 2. Graphical representations of the effects of interest (CA and LO) for normal controls and MS patients. (A) illustrates data at the 4, 24, 48 coordinate in the anterior cingulate gyrus and (B) illustrates data at the 68, 16, 10 coordinate in the left superior temporal gyrus. The effect size is the mean percent change from the blood flow value (normalized to 50 ml/100 g/min) with error bars equal to the standard error of the mean. Abbreviations are: LO = listen only, CA = covert attention, MS = multiple sclerosis patients, N = normal controls.
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Contrasts seeking differences between MS and controls that included all voxels in the image set failed to reveal differences (i.e., contrasts [normal(CA – LO) MS(CA – LO)] and [MS(CA – LO) normal(CA –LO)]). Accordingly, we restricted our search volume to those voxels activated in the normal(CA –LO) contrast at the p = 0.001 level for the normal(CA – LO) MS(CA – LO) query. This analysis showed significantly greater activity in normals at right ACC (4, 24, 48, p = 0.012; 4, 32, 22, p = 0.04) compared to the MS patients. Similarly, we restricted our search volume to voxels activated in the MS(CA – LO) contrast at p = 0.001 for the MS(CA –LO) normal(CA – LO) query. This analysis revealed significantly more activity in the superior temporal gyrus of the MS group, compared to the normals ( 68, 16, 12, p = 0.008). This effect is illustrated in Fig. 2 where we have graphed the effect size for each task (i.e., CA and LO) for the normal controls and the MS patients at the 4, 24, 48 and 68, 16, 12 coordinates. The ANCOVA model which included FLV as a covariate predicting maxima of activity related to lesion burden revealed no significant effects after correction for multiple comparisons.
4. Discussion We used regional cerebral blood flow (rCBF) as a surrogate marker of neural activity to define sites that mediate auditory attention without motor activity. This study shows disparate topographies of brain activation in MS vs. normal controls. Compared with passive listening, this task has been shown to activate rostral/dorsal right ACC, left prefrontal cortex and left temporal cortex in healthy volunteers [14]. In the MS group, significant activity was confined to the (left) primary and secondary auditory cortex. MS ACC activity, while found in the same general area as in the normal group, failed to reach statistical significance at the voxel level of comparison. As noted above, ACC can be conceived of as region of conscious attention interconnected with dorsal – lateral prefrontal cortex and deep gray matter structures [11,13]. Our finding of reduced activity in this region among MS patients is consistent with earlier work of Bakshi et al. [23] who reported marked hypometabolism during rest in MS patients measured by fluorodeoxyglucose PET. While hypometabolic areas were found throughout the brain, defects were most notable in the frontal cortex, particularly superior/ mesial frontal cortex (i.e., ACC). Taken together, these findings underscore the importance of the ACC in attention and the vulnerability of this region to the MS disease process. To the best of our knowledge, this is the first published study examining cerebral activity in MS patients during non-motor, auditory processing. Adaptive changes during functional imaging have been reported in MS patients during finger tapping [24] and complex visual attention
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[8] tasks. In Staffen et al.’s work [8], some MS patients activated lateral aspects of prefrontal cortex (BAs 6, 8 and 9) compared to only right ACC activity found in normals. They employed a visual PASAT, which required multiple cognitive operations such as sustaining attention, working memory and calculation. Lateral prefrontal cortex subserves executive functions such as working memory, supporting the idea that such relocalization of activity mediated cognitive functions that were required for the activation task. In our study, MS patients also failed to significantly activate ACC but instead of lateral prefrontal cortex, new activity was confined to association cortex in the left temporal lobe. The lack of lateral prefrontal cortex activity might be explained by the use of a simpler activation task that is non-motor and requires no working memory. Thus, in MS, where long white matter tracts are predominantly affected, patients may fail to activate higher level attentional networks and rely on other regions to mediate performance. In the complex visual task, prefrontal cortex is recruited. When performing the simpler auditory task, patients compensate by relying on lower level processing (primary and secondary auditory cortex). This latter pattern of neural activity is similar to that found in normal subjects during dichotic listening [25]. Cognitive processes, like motor circuits, are probably represented by parallel tracts in normal brain, and a dominant circuit predominates until injury gives rise to disinhibition of other circuits or initiates activation of alternate circuits for task completion [26]. MS has long been thought of as a white matter disease that disconnects brain regions. Thus, it is reasonable to propose that transformations in the neural pathways that mediate our auditory attention task are the result of a partial disconnection of the ACC from other structures. While Reddy et al. [24] showed that so-called ‘‘plastic’’ changes in cerebral activity during motor activity were associated with T2 hyperintense lesion burden, this relationship is yet to be reported in MS cognitive activation studies. Staffen’s group [8] did not report correlations between lesion burden and fMRI activity. In the present study, there was no statistical association between rCBF changes and lesion burden. However, a growing body of evidence indicates that gray matter is also affected in MS [27]. Evidence for gray matter involvement is mounting not only from studies of generalized atrophy [28], but also cortical atrophy [29,30]. Gray matter pathology involving the subcortical nuclei has also been shown by T2 hypointensity [31] and increased water diffusion [32]. Thus, the lack of correlation between FLV and cerebral activity in this study may reflect a dependence on gray matter, rather than white matter tissue changes. There are some limitations in this study. First, we employed historical controls and therefore our data may have been affected by drift in scanner performance. While this concern is mitigated by our frequent renormalizations to minimize drift and SPM’s normalization of blood flow values within each image set to a common value, this
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methodology may have reduced the reliability and power of our study. Also, unlike our prior investigations using normal volunteers [14,33], there was a lack of P3 effect in this study. There are several possible explanations for this finding. First, it may be that MS patients were less attentive to the activation task. Second, there was a P3 but a higherlevel of unintentional motoric activity occurred in MS patients leading to a decrease in signal-to-noise ratio thus precluding the observation of P3. In this context, we note that the P3 amplitude was modest in the control group when compared to the more standard motor-based P3 [14]. Third, the disease process itself may have caused enough neural damage to diminish the P3. This latter interpretation is, in our view, most parsimonious. Temporal cortex activity was actually greater in patients than controls, which argues against an attention-to-task confound. We propose that both PET and ERP data converge to demonstrate hypoactivity of anterior attention networks, as has been shown in other research [8,23]. In our future work, we will attempt to replicate our findings using an easier activation task that is shown to generate a P3 response in both normals and patients. In addition, analyses assessing correlations between hypoactivity during attention and MRI indices of disease activity are planned. In conclusion, our study replicated an earlier finding in another sensory modality showing that MS is associated with hypoactivity of ACC during attention challenge. In addition, different topographies of brain activation were demonstrated in MS and healthy controls. In contrast to marked frontal lobe activation in normals, activation in MS patients was largely confined to the (left) primary and secondary auditory cortex. This may reflect greater reliance on lower level processing due to failure to activate frontal attention networks.
Acknowledgements This research was supported by research grants from the James H. Cummings Foundation (Benedict), National Institutes of Health (NIH-NINDS 1 K23 NS42379-01) (Bakshi) and National Multiple Sclerosis Society (RG 3258A2/1) (Bakshi).
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Functional imaging during covert auditory attention in multiple sclerosis Michael P. Santa Maria a, Ralph H.B. Benedict a,*, Rohit Bakshi a, Mary Lou Coad b,c, David Wack b,c, Robert Burkard d, Bianca Weinstock-Guttman a, Susan Roberts d, Alan H. Lockwood a,b,c a
Department of Neurology, School of Medicine, State University of New York (SUNY) at Buffalo, Buffalo General Hospital, Neurology, Suite D-6 Buffalo, 100 High Street, Buffalo, NY 14203, USA b Department of Nuclear Medicine, State University of New York (SUNY) at Buffalo, Buffalo, NY, USA c VA Western New York Healthcare System of Buffalo, Buffalo, NY, USA d Department of Communicative Disorders and Science, State University of New York (SUNY) at Buffalo, Buffalo, NY, USA Received 25 June 2003; received in revised form 4 September 2003; accepted 1 October 2003
Abstract Recent literature suggests that the brain in multiple sclerosis (MS) undergoes reorganization that subserves the performance of visual and motor tasks. We identified sites of cerebral activity in 16 MS patients while performing a covert attention (CA) task, presented in the auditory modality. Positron emission tomography (PET) revealed activation of rostral/dorsal anterior cingulate cortex (ACC) in normal subjects studied previously. Activity in this region was not significant in MS patients, but there was a large region of activity in superior temporal cortex. Decreased activation of frontal attentional networks and greater activity in sensory/perceptual cortical areas (auditory association cortex) suggests a reduction of transmission along white matter tracts connecting these regions. This study demonstrates cingulate hypoactivity and cerebral reorganization during auditory attention in MS. D 2003 Elsevier B.V. All rights reserved. Keywords: Multiple sclerosis; Attention; PET
1. Introduction Cognitive dysfunction occurs in roughly 50% of multiple sclerosis (MS) patients [1] and its adverse impact is well documented in studies of employment, avocational activity and instrumental activities of daily living [2,3]. The hallmarks of MS-associated cognitive disorder are slowed processing speed and impaired new learning [1,4,5]. The Paced Auditory Serial Addition Test (PASAT) [6], an auditory task emphasizing processing speed and working memory, is sensitive to neuropsychological dysfunction in MS [4]. The PASAT requires patients to monitor a series of audiotaped digits while adding each consecutive digit to the preceding digit. An oral (i.e., motor) response is required. Due to its reliability and sensitivity, the PASAT was included in the MS Functional Composite, a common clinical
* Corresponding author. Tel.: +1-716-859-1403; fax: +1-716-8591419. E-mail address: [email protected] (R.H.B. Benedict). 0022-510X/$ - see front matter D 2003 Elsevier B.V. All rights reserved. doi:10.1016/j.jns.2003.10.019
outcome measure [7]. A visual analog to PASAT was recently used in a functional imaging study of MS patients. Compared with normal controls, patients failed to activate anterior cingulate cortex (ACC), but activated new regions suggesting cerebral reorganization or plasticity [8]. The role of the ACC in cognition has been studied intensely in recent years [9,10]. While the ACC is a primary substrate for attention, it is also widely recognized as an integral region for premotor function [11 –13]. Recognizing that the PASAT lacks specificity for discrete cognitive processes [12], we chose to disentangle the influence of attention and motoric responding in a study of continuous auditory attention in healthy volunteers [14]. Participants were asked to mentally note targets without responding orally or manually. To document attention we recorded event related potentials and found significantly higher P3 responses following target, compared to non-target, stimuli. Simultaneously obtained 15O-H2O positron emission tomography (PET) revealed activity within the right ACC, Brodmann area (BA) 32, approximating dorsal ACC. The site of maximum activity was in a voxel 36 mm anterior to
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that identified in a prior study using similar stimuli with a motor response [9]. We therefore argued that sub-regions within the ACC can be distinguished: a mid- or rostral – dorsal sub-region (BA 32V) that supports attention and a caudal area (BA 24cV) that mediates initiation of a modalityspecific motor response [11]. This cingulofrontal transition zone [13] is interconnected with prefrontal cortex and deep gray matter via white-matter, which courses proximally to the lateral ventricles [13]. Therefore, ACC-dependent cognitive functions like attention should be disrupted in a white matter disease such as MS. The covert continuous performance task described above provides an opportunity to study auditory attention in patients with MS. Accordingly, we used this task to study 16 MS patients. Our primary objective was to determine what regions of the brain are activated by this paradigm. We hypothesized that patients would fail to activate anterior attention zones but activate other regions of the brain.
2. Methods 2.1. Subjects We studied 16 MS patients diagnosed by consensus criteria [15] with a mean age of 41.4 years (S.D. = 6.9). All were right-handed and 11 were female. Twelve patients had relapsing-remitting disease and four had secondary progressive course. Disease duration ranged from 2 to 17 years (M = 9.6, S.D. = 5.1). Physical disability was assessed by an experienced neurologist specializing in MS, blind to PET findings, using Expanded Disability Status Score (EDSS) [16]. Median EDSS was 2.5 (S.D. = 1.8, range = 1.0 –7.0). In some analyses, these patient data were compared with data derived previously from healthy adult volunteers (6 male 6 female; 15 Caucasian, 1 Black; mean age = 41.4, S.D. = 6.8, mean education = 14.2, S.D. = 1.6) [14]. None of the patients had other major medical illnesses or had undergone corticosteroid treatment within 4 weeks of the study. All participants provided written consent and were provided with a written description of the study, which had been approved by an institutional review board. Other exclusion criteria included (1) comorbid physical illness that could potentially impact neurologic or cognitive function; (2) severe motor or sensory defect that would substantially interfere with neuropsychological testing; (3) current psychiatric disorder other than personality or behavior changes secondary to MS or minor depression; (4) current medications that contraindicate experimental procedures or that could potentially impair or facilitate cognitive function; (5) MS relapse within four weeks of the study; (6) pregnancy. Psychotropic medications for minor depression, insomnia and fatigue were permitted. All patients underwent audiometric testing and were required to have 90% speech discrimination in each ear, and reliably perceive tones of
z 25 dB HL in the 250– 2000 Hz range and 35 dB HL in the 4000– 8000 Hz range. 2.2. Neuropsychological testing and MRI Neuropsychological tests emphasizing attention and memory were selected to divide patients into ‘high’ and ‘low’ functioning subgroups. These tests included the Total Recall and Delayed Recall indices from the California Verbal Learning Test-II [17] and the Brief Visuospatial Memory Test-Revised [18], as well as the Trail Making Test [19] and PASAT. Standard scores were calculated for each test using published normative data tables. The neuropsychological index was calculated by taking the mean standard score across these measures. MS patients were divided into ‘high’ and ‘low’ performing subgroups based on a median split of the index distribution. These sub-groups did not differ significantly in age (low 39.8 S.D. = 5.6; high 43.1 S.D. = 7.9), education (low 16.3 S.D. = 2.2; high 14.9 S.D. = 1.9), disease duration (low 9.6 S.D. = 5.2; high 9.6 S.D. = 5.3), EDSS (low 3.8 S.D. = 2.2; high 2.5 S.D. = 1.0), gender (low 3 male 5 female; high 2 male 6 female), or race (low 7 Caucasian, 1 Black; high all Caucasian) by t or v2 test. Brain MRI was obtained on a Philips Gyroscan ACS-NT 1.5-T scanner (Best, The Netherlands). Axial T1-weighted images (TR/TE: 400/10) were used to co-register with PET in order to more accurately define individual brains and group rCBF. Axial fast fluid-attenuated inversion-recovery (FLAIR) images (TR/TE/TI: 8000/120/2200) were obtained to estimate hyperintense lesion burden. For both pulse sequences, the matrix size was 192 256, number of signal averages (excitations) was 2, number of slices was 24, and section thickness was 5-mm with no inter-slice gaps. Images were obtained parallel to the canthomeatal plane using internal landmarks. Analysis of MRI lesion load was performed using a Sun Ultra 10 workstation (Sun Microsystems, Santa Clara, CA) using Java Image software (version 1.0, Xinapse Systems, Northants, UK, http://www.xinapse. com) by a trained technician blind to clinical data, using previously described methods [20]. Briefly, all FLAIR axial slices from midpoint of the cerebellum to the vertex were entered into an algorithm involving masking and thresholding to separate hyperintense lesions from the nonlesional tissue. The software then automatically calculated the total FLAIR lesion volume (FLV) by multiplying lesion area by slice thickness. 2.3. PET and activation task Participants underwent 15O-H2O PET and EEG recording simultaneously, in a single session, during which they performed auditory tasks. The stimuli, presented with a NeuroScan computer system (NeuroScan, Hearndon, VA), were previously recorded human-voiced English syllables ending with /a/ and beginning with either a stop or nasal consonant. These stimuli had been developed through the
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recordings of 8 speakers (4 male, 4 female) who generated 64 original stimuli, 8 for each of the following syllables (/ba/, /da/, /ga/, /pa/, /ma/, /na/, /ta/, /ka/). All were digitized to a rate of 41,000 Hz for a duration of 200 ms. The same stimuli were employed in three repetitions of the activation (covert attention or CA) and control (listen only or LO) tasks via foam cushion insert-earphones. The peak sound pressure level approximated 90 dB. The inter-stimulus interval was 1 s and the target probability rate was 0.19. Each sequence lasted approximately 5 min and included 333 randomly ordered stimuli. The experiment included three presentations of the two tasks employed previously [14]: CA and LO control state. During CA, patients were instructed to note the occurrence of the designated target without making a motor or oral response. During the LO condition, patients were told to only listen to the auditory stimuli. These conditions were presented in one of the following counterbalanced orders: CA – LO – CA – LO – CA – LO or LO – CA – LO – CA – LO – CA. We employed a Siemens ECAT 951/31R tomograph, modified for 3D data collection, so that the inferior image plane coincided with the canthomeatal line. To reduce ambient noise, either Cabot Safety Model 3000 earmuffs or a Bose Active Noise Suppression headset was placed over both ears. Head position was maintained by means of an individually fitted thermoplastic mask. After a 20-min transmission scan (examples of stimuli were presented during transmission scan to insure accurate comprehension), six emission scans were obtained. Each scan began with the slow i.v. injection of a bolus (15-s injection followed by a 15-s flush) of 7 mCi or less of 15O-water as a tracer of CBF. Activation procedures began 20 s before beginning the injection and continued throughout the scan. Sixty seconds of emission data, timed from the arrival of the 15O-water in the brain, were used for image reconstruction (random coincidence correction, measured attenuation, Hann filter, cutoff frequency 0.4 cycles/pixel) and analysis. EEG signals were recorded from three gold electrodes (Fz, Cz, Pz according to the International 10/20 System). A ground electrode was placed on the forehead. Ocular movements were monitored and recorded from vertical (VEOG) and horizontal (HEOG) channels. Images were converted to the Analyze format and analyzed using the 1999 version of Statistical Parametric Mapping (SPM) [21]. Images were corrected for between-
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scan movement, normalized into standard space and normalized to a common mean CBF value by analysis of covariance. A 15-mm Gaussian smoothing filter was employed to increase the signal-to-noise ratio, condition the data to conform with the requirements of Gaussian field theory and to minimize confounding of results due to individual anatomical differences. The normalization parameters derived from the T1-weighted MRI were used to warp the coregistered PET scans into a standard stereotaxic space. This template conforms to the space defined by the International Consortium for Brain Mapping project (ICBM) (NIH P-20 grant), and closely approximates the space described in the atlas of Talairach and Tournoux [22]. The registration of the normalized mean PET, MRI images and the template was checked manually to confirm that excessive warping had not occurred. 2.4. Statistical analysis Statistical tests were based on the cognitive subtraction technique wherein the activation pattern for one condition is subtracted from the activation pattern for another. The CA – LO contrast was designed to isolate attention while controlling for neural activity unrelated to the attention task (e.g., motor activity). Subtracting LO from CA thus served to neutralize extraneous factors that are alike during both conditions such as primary auditory processing (as opposed to attending to auditory stimuli), tactile stimulation due to contact with the PET apparatus and padding, and subjectspecific thoughts and mood states, and other neutral activity present in a ‘‘resting state’’. The MS patient data were merged with the normal control group from a previous study [14]. We first examined within-subjects effects for the MS patients and controls separately, and then tested betweengroups effects. Analyses were based on a threshold of p < 0.05, corrected for multiple comparisons, searching the entire image. For some analyses, a more restricted analysis was performed wherein a mask was created that limited the analysis to a subset of voxels (defined by the voxels included in the CA – LO contrast in normals and MS patients at the p = 0.001 level of significance, uncorrected for multiple comparisons). Within these restricted volumes, we searched for sites active in one group and not the other, e.g., [normal(CA – LO) MS(CA –LO)], thus increasing the statistical power of the analysis by excluding voxels that are unlikely to participate in the task. The correlation between
Table 1 Within-group, single points of significant maximal activity (by SPM) for auditory attention tasks using same stimuli and contrasted against a passive, listening control task Study group
Region
healthy volunteer
Right rostral/dorsal ACC; BA [32] Left superior temporal gyrus; BA [22] Left lateral prefrontal cortex; BA [44, 45, 46, 10] Left superior temporal gyrus; BA [22, 38, 42] Right and Left ACC; BA [32]
MS
x 6 58 32 64 4
y
z
p cluster
p voxel
26 38 48 16 12
30 12 20 8 40
< 0.001 0.002 < 0.001 < 0.001 < 0.01
< 0.001 .03 < 0.001 < 0.001 ns
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activity specified by the CA – LO contrast and FLV was tested using analysis of covariance.
3. Results
Fig. 1. Regions of increased rCBF analyzed by SPM projected on the same template brain in two panels. CA is contrasted against passive listening (LO) to identical stimuli (CA – LO) where CA requires discrimination of targets from non-targets. In each panel, the top image shows regions rendered on to the lateral surface of the left hemisphere. The lower image shows activity as viewed is from the frontal pole. All activity is presented with darker red representing more reliable or denser activity. (A) Previously published data obtained from 16 healthy volunteers. The contrast is shown at a conservative threshold of p = 0.00001 to separate more clearly the various maxima. There is a region of activity within the right dorsal aspect of the cingulate gyrus, and three other regions of activity including left lateral prefrontal cortex, premotor cortex and posterior temporal cortex. (B) Activity obtained from 16 MS patients. The only significant region at the voxel level occurs in the superior temporal gyrus (STG). The STG activation is large, encompassing anterior left superior temporal gyrus extending to posterior superior temporal gyrus (BA 39). Maxima within the ACC are present but of marginal significance.
Mean standard scores on neuropsychological tests ranged from 81 on the visual memory test (Brief Visuospatial Memory Test-Revised delayed recall) to 98 on the verbal memory test (California Verbal Learning Test-II trials 1– 5). The mean standard score across all tests was 90 (S.D. = 14.2). The ERP data were subjected to a withinsubjects comparison of amplitudes by stimulus type (target, non-target), which was not significant. The coordinates of significant maxima observed are presented in Table 1 along with maxima from our previous work with healthy volunteers [14]. Images from the analysis of PET data are presented in Fig. 1 (Fig. 1A, normal subjects and b, MS). For both groups, the CA – LO contrast derived from within-subjects analyses revealed activity in right ACC. While locations of the maxima were generally the same, the activation was only significant at the voxel level among normal subjects. Among patients, the only statistically significant region (voxel, p < 0.001) was the left superior temporal gyrus. This region was quite large (2037 voxels), encompassing anterior and posterior subregions and spanning BAs 22, 38 and 42. When the ‘high’ and ‘low’ performing MS subgroups (based on median split) were compared [high(CA – LO) vs. low(CA – LO)], there were no significant maxima detected. When the analysis was repeated using a mask to restrict the voxels examined to those activated in the CA –LO contrast in normals, we again failed to find significant differences between these subgroups.
Fig. 2. Graphical representations of the effects of interest (CA and LO) for normal controls and MS patients. (A) illustrates data at the 4, 24, 48 coordinate in the anterior cingulate gyrus and (B) illustrates data at the 68, 16, 10 coordinate in the left superior temporal gyrus. The effect size is the mean percent change from the blood flow value (normalized to 50 ml/100 g/min) with error bars equal to the standard error of the mean. Abbreviations are: LO = listen only, CA = covert attention, MS = multiple sclerosis patients, N = normal controls.
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Contrasts seeking differences between MS and controls that included all voxels in the image set failed to reveal differences (i.e., contrasts [normal(CA – LO) MS(CA – LO)] and [MS(CA – LO) normal(CA –LO)]). Accordingly, we restricted our search volume to those voxels activated in the normal(CA –LO) contrast at the p = 0.001 level for the normal(CA – LO) MS(CA – LO) query. This analysis showed significantly greater activity in normals at right ACC (4, 24, 48, p = 0.012; 4, 32, 22, p = 0.04) compared to the MS patients. Similarly, we restricted our search volume to voxels activated in the MS(CA – LO) contrast at p = 0.001 for the MS(CA –LO) normal(CA – LO) query. This analysis revealed significantly more activity in the superior temporal gyrus of the MS group, compared to the normals ( 68, 16, 12, p = 0.008). This effect is illustrated in Fig. 2 where we have graphed the effect size for each task (i.e., CA and LO) for the normal controls and the MS patients at the 4, 24, 48 and 68, 16, 12 coordinates. The ANCOVA model which included FLV as a covariate predicting maxima of activity related to lesion burden revealed no significant effects after correction for multiple comparisons.
4. Discussion We used regional cerebral blood flow (rCBF) as a surrogate marker of neural activity to define sites that mediate auditory attention without motor activity. This study shows disparate topographies of brain activation in MS vs. normal controls. Compared with passive listening, this task has been shown to activate rostral/dorsal right ACC, left prefrontal cortex and left temporal cortex in healthy volunteers [14]. In the MS group, significant activity was confined to the (left) primary and secondary auditory cortex. MS ACC activity, while found in the same general area as in the normal group, failed to reach statistical significance at the voxel level of comparison. As noted above, ACC can be conceived of as region of conscious attention interconnected with dorsal – lateral prefrontal cortex and deep gray matter structures [11,13]. Our finding of reduced activity in this region among MS patients is consistent with earlier work of Bakshi et al. [23] who reported marked hypometabolism during rest in MS patients measured by fluorodeoxyglucose PET. While hypometabolic areas were found throughout the brain, defects were most notable in the frontal cortex, particularly superior/ mesial frontal cortex (i.e., ACC). Taken together, these findings underscore the importance of the ACC in attention and the vulnerability of this region to the MS disease process. To the best of our knowledge, this is the first published study examining cerebral activity in MS patients during non-motor, auditory processing. Adaptive changes during functional imaging have been reported in MS patients during finger tapping [24] and complex visual attention
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[8] tasks. In Staffen et al.’s work [8], some MS patients activated lateral aspects of prefrontal cortex (BAs 6, 8 and 9) compared to only right ACC activity found in normals. They employed a visual PASAT, which required multiple cognitive operations such as sustaining attention, working memory and calculation. Lateral prefrontal cortex subserves executive functions such as working memory, supporting the idea that such relocalization of activity mediated cognitive functions that were required for the activation task. In our study, MS patients also failed to significantly activate ACC but instead of lateral prefrontal cortex, new activity was confined to association cortex in the left temporal lobe. The lack of lateral prefrontal cortex activity might be explained by the use of a simpler activation task that is non-motor and requires no working memory. Thus, in MS, where long white matter tracts are predominantly affected, patients may fail to activate higher level attentional networks and rely on other regions to mediate performance. In the complex visual task, prefrontal cortex is recruited. When performing the simpler auditory task, patients compensate by relying on lower level processing (primary and secondary auditory cortex). This latter pattern of neural activity is similar to that found in normal subjects during dichotic listening [25]. Cognitive processes, like motor circuits, are probably represented by parallel tracts in normal brain, and a dominant circuit predominates until injury gives rise to disinhibition of other circuits or initiates activation of alternate circuits for task completion [26]. MS has long been thought of as a white matter disease that disconnects brain regions. Thus, it is reasonable to propose that transformations in the neural pathways that mediate our auditory attention task are the result of a partial disconnection of the ACC from other structures. While Reddy et al. [24] showed that so-called ‘‘plastic’’ changes in cerebral activity during motor activity were associated with T2 hyperintense lesion burden, this relationship is yet to be reported in MS cognitive activation studies. Staffen’s group [8] did not report correlations between lesion burden and fMRI activity. In the present study, there was no statistical association between rCBF changes and lesion burden. However, a growing body of evidence indicates that gray matter is also affected in MS [27]. Evidence for gray matter involvement is mounting not only from studies of generalized atrophy [28], but also cortical atrophy [29,30]. Gray matter pathology involving the subcortical nuclei has also been shown by T2 hypointensity [31] and increased water diffusion [32]. Thus, the lack of correlation between FLV and cerebral activity in this study may reflect a dependence on gray matter, rather than white matter tissue changes. There are some limitations in this study. First, we employed historical controls and therefore our data may have been affected by drift in scanner performance. While this concern is mitigated by our frequent renormalizations to minimize drift and SPM’s normalization of blood flow values within each image set to a common value, this
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methodology may have reduced the reliability and power of our study. Also, unlike our prior investigations using normal volunteers [14,33], there was a lack of P3 effect in this study. There are several possible explanations for this finding. First, it may be that MS patients were less attentive to the activation task. Second, there was a P3 but a higherlevel of unintentional motoric activity occurred in MS patients leading to a decrease in signal-to-noise ratio thus precluding the observation of P3. In this context, we note that the P3 amplitude was modest in the control group when compared to the more standard motor-based P3 [14]. Third, the disease process itself may have caused enough neural damage to diminish the P3. This latter interpretation is, in our view, most parsimonious. Temporal cortex activity was actually greater in patients than controls, which argues against an attention-to-task confound. We propose that both PET and ERP data converge to demonstrate hypoactivity of anterior attention networks, as has been shown in other research [8,23]. In our future work, we will attempt to replicate our findings using an easier activation task that is shown to generate a P3 response in both normals and patients. In addition, analyses assessing correlations between hypoactivity during attention and MRI indices of disease activity are planned. In conclusion, our study replicated an earlier finding in another sensory modality showing that MS is associated with hypoactivity of ACC during attention challenge. In addition, different topographies of brain activation were demonstrated in MS and healthy controls. In contrast to marked frontal lobe activation in normals, activation in MS patients was largely confined to the (left) primary and secondary auditory cortex. This may reflect greater reliance on lower level processing due to failure to activate frontal attention networks.
Acknowledgements This research was supported by research grants from the James H. Cummings Foundation (Benedict), National Institutes of Health (NIH-NINDS 1 K23 NS42379-01) (Bakshi) and National Multiple Sclerosis Society (RG 3258A2/1) (Bakshi).
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