Brain Advance Access originally published online on May 2, 2006
Brain 2006 129(7):1780-1788; doi:10.1093/brain/awl102
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Differences between Alzheimer's disease and dementia with Lewy bodies: an fMRI study of task-related brain activity
1 King's College London, MRC Centre for Neurodegeneration Research, Section of Old Age Psychiatry, Institute of Psychiatry London, UK 2 Centre for Neuroimaging Sciences, Institute of Psychiatry London, UK
Correspondence to: Dr Justin Sauer, Section of Old Age Psychiatry, Institute of Psychiatry, Box P070, De Crespigny Park, Denmark Hill, London, SE5 8AF, UK E-mail: j.sauer{at}iop.kcl.ac.uk
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Summary |
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We investigated whether previously reported differences between Alzheimer's disease and dementia with Lewy bodies (DLB) in resting occipital activity lead to activation differences within functionally specialized visual cortical areas and deactivation differences in the default network. Patients with Alzheimer's disease (n = 10; 5 male), DLB (n = 9; 4 male) and controls (n = 13; 5 male) performed three functional MRI (fMRI) scanning experiments involving visual colour, face or motion stimuli. Reaction time or accuracy in DLB and Alzheimer's disease differed significantly from controls but not between patient groups, with the exception of accuracy in the face task (DLB < Alzheimer's disease; P = 0.038). The most significant fMRI activations in the pooled data set were in left V4
for the colour task (Talairach coordinate: –30, –52, –24; P = 0.002 corrected), the right fusiform face area (FFA) for the face task (34, –48, –22; P = 0.005 corrected) and right intra-parietal sulcus (30, –66, 42; P = 0.003 corrected) for the motion task, with additional activity in right V5 (48, –64, 0; P = 0.015 corrected). Each task was associated with decreases in activity within the default network with prominent deactivation foci bilaterally in the posterior cingulate gyrus (±8, –48, 26; left P < 0.001; right P < 0.001 corrected) and medial frontal cortex (±18, 42, 32; left P < 0.001; right P < 0.001 corrected). Comparing patterns of task-related activity across groups, DLB patients showed more activation than Alzheimer patients within the superior temporal sulcus (STS) for the motion task (right STS: 44, 0, –20; P = 0.004 corrected; left STS: –40, –4, –26; P = 0.07 corrected). This difference could not be attributed to task performance, cognitive score or age [analysis of covariance (ANCOVA)F (2, 18) = 8.44, P = 0.003]. Within regions of interest, group activation differences were found for the face task (Alzheimer's disease > DLB P = 0.05; Alzheimer's disease > controls P = 0.14) and the motion task (DLB < Alzheimer's disease P = 0.031 and DLB < control P = 0.048). However, these differences could be explained by behavioural performance, failing to reach significance in the ANCOVA analysis. In the default network, group deactivation differences between controls and both patient groups were found for the colour and motion task (colour: control < Alzheimer's disease P = 0.02; control < DLB P = 0.019; motion: control < Alzheimer's disease P = 0.118; control < DLB P = 0.118) but could be accounted for by behavioural performance. The results suggest that cognitive fMRI can be used to detect both performance-dependant and performance-independent differences between Alzheimer's disease and DLB, reflecting the distribution of functional pathology in the two conditions.
Key Words: Alzheimer's disease; dementia with Lewy bodies; functional magnetic resonance imaging; superior temporal sulcus
Abbreviations: DLB, dementia with Lewy bodies; FFA, fusiform face area; fMRI, functional magnetic resonance imaging; MMSE, Mini-Mental State Examination; SPM, statistical parametric mapping; STS, superior temporal sulcus
Received January 3, 2006. Revised March 24, 2006. Accepted March 27, 2006.
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Introduction |
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Dementia with Lewy bodies (DLB) is characterized by cognitive impairment accompanied by fluctuating cognitive function, recurrent visual hallucinations and parkinsonism (McKeith et al., 1996
) and accounts for 15–20% of dementia cases that come to neuropathological examination (McKeith et al., 2003). While ante-mortem differentiation of the two dementing conditions has important clinical implications, for example, avoidance of neuroleptic medication and positive therapeutic response to cholinesterase inhibitors (McKeith et al., 2003), no objective discriminatory biomarker, suitable for routine clinical application, has been identified. DLB patients perform worse than Alzheimer's disease patients on a range of visual perceptual, attentional and working memory tasks (Calderon et al., 2001; Collerton et al., 2003), the visual perceptual deficits affecting a broad range of visual domains including object/form vision, visual motion, spatial vision and colour-related pop-out (Mori et al., 2000; Simard et al., 2003; Cormack et al., 2004; Mosimann et al., 2004). Several studies report lower resting state regional cerebral blood flow and glucose metabolism in the occipital lobes of DLB patients compared with those with Alzheimer's disease (Imamura et al., 1997; Ishii et al., 1998, 1999; Lobotesis et al., 2001; Minoshima et al., 2001). The cause of these occipital deficits is unclear but does not relate to occipital atrophy (Middlekoop et al., 2001) or Lewy body deposition as this spares primary visual cortex (Perry et al., 1990).
Compared with Alzheimer's disease, the occipital resting deficits in DLB are not uniformly distributed but affect some occipital sub-regions more than others. For example, an early voxel-based study of DLB deficits in glucose metabolism found a greater deficit in lateral compared with medial and ventral occipitotemporal cortices (Imamura et al., 1997), a finding replicated in a later region of interest study (Ishii et al., 1998). This lateral occipitotemporal deficit predominance leads to an important functional prediction. Lateral occipitotemporal cortex contains areas specialized for different varieties of visual motion processing including coherent motion (Zeki et al., 1991; Watson et al., 1993), biological motion and optic flow (Howard et al., 1996). In contrast, ventral occipitotemporal cortex contains regions specialized for colour (Zeki et al., 1991; Mckeefry et al., 1997) and face perception (Kanwisher et al., 1997). The prediction would therefore be that DLB patients will be disproportionately impaired, both in terms of performance and functional activation, in visual processing tasks involving motion rather than faces or colour.
A second prediction relates to a recently described network of brain regions active during ‘default’ resting cognitive states (Shulman et al., 1997; Mazoyer et al., 2001; Raichle et al., 2001). Disengagement from the default resting state during task performance results in a decrease in activity within this network. Recent studies have shown the default network to be dysfunctional in Alzheimer's disease (Greicius et al., 2004) and describe a possible link between Alzheimer's-related amyloid plaque deposition, cortical atrophy and the default network (Buckner et al., 2005). Given the greater attentional deficits in DLB than Alzheimer's disease (Calderon et al., 2001; Collerton et al., 2003) and the link between default network deactivation and attentional demand (McKiernan et al., 2003), one would predict that the default network will be more dysfunctional in DLB than Alzheimer's disease. Here, we report a preliminary investigation of differences in occipitotemporal activation and default network deactivation in Alzheimer's disease and DLB, our aim being to identify functional differences that might reflect differences in the distribution of their respective pathologies.
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Methods |
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Participants
Thirty-two subjects, 10 with Alzheimer's disease (5 male), 9 with DLB (4 male) and 13 controls (5 male) were included in the study, all English-speaking, right-handed and all of whom gave written informed consent. Patients were recruited from the South London and Maudsley NHS Trust catchment area. Exclusion criteria consisted of previous head injury, alcoholic brain damage or any additional significant physical or psychiatric condition. Controls had no evidence of dementia as assessed clinically and by Mini-Mental State Examination (MMSE) (Folstein et al., 1975
) score of >28. Experienced senior psychiatrists performed the initial diagnostic interviews. Patient diagnosis was corroborated using the International Consensus Guidelines for DLB (McKeith et al., 1999) and the NINCDS-ADRDA (National Institute of Neurological and Communicative Diseases and Stroke, Alzheimer's Disease and Related Disorders Association) criteria for Alzheimer's disease (McKhann et al., 1984). All 10 patients in the Alzheimer group met the criteria for probable Alzheimer's disease. All 9 DLB patients met criteria for probable DLB: 8 (89%) with a history of visual hallucinations; 4 (44%) with parkinsonian features including tremor, rigidity and bradykinesia on physical examination and 9 (100%) with fluctuating attention assessed by case note review and task-specific fluctuation score (see below). The study was approved by the Institute of Psychiatry Research ethical committee.
Tasks
Visual stimuli were back-projected onto a screen at the end of the scanner bore and viewed through an angled mirror. Each task lasted 10 min 8 s and contained 38 individual trials (4 s stimulus, 12 s inter-stimulus gap). A white background and central cross-hair remained present throughout the experiments, although subjects were not required to maintain fixation. Subjects responded with a right hand, two-alternative key-press and were asked to respond as quickly and accurately as possible. Our strategy was to use tasks involving different visual attributes to probe function in the lateral and ventral occipitotemporal regions identified above and the default network. Our lateral occipitotemporal probe consisted of biological motion, a category of complex, high-level motion processing known to be impaired in psychophysical studies of Alzheimer's disease (Rizzo et al., 1998) but not yet examined in DLB. Two probes were used for ventral occipitotemporal function, a colour-related pop-out task for which performance is impaired in DLB compared with Alzheimer's disease (Cormack et al., 2004) and a face discrimination task.
- Colour task: Four coloured circles were presented at fixed location (12, 3, 6 and 9 o'clock). Subjects pressed one key if all four circles were blue and another if a red circle was present. The presence (50% of trials) and location of the red circle was randomized.
- Face task: A grey-scale face was presented at the centre of the screen (different face each trial). Subjects pressed one key if the face was male and another if female. Stimulus gender (50% male) was randomized.
- Motion task: A figure made up of 13 black dots (Johansson figure; Johansson et al., 1973) walking from right to left or left to right was presented embedded in 17 moving distracter dots. Subjects pressed one key if the figure was walking to the right and another if the figure was walking to the left. Walking direction was randomized (50% left).
As it was anticipated that some patients would be unable to complete all three tasks, task order was fixed (colour, face, motion) to ensure a complete data set for the first task. Subjects had two practice sessions for the colour and face tasks (the first at recruitment, the second 30 min before scanning) and were reminded of task requirements before each scan. For technical reasons subjects were only able to practise the motion task immediately before the motion scan.
Behavioural data analysis
Accuracy and reaction time were recorded for each response and examined in separate ANOVAs (analysis of variance) for each task using Group (control, Alzheimer's disease, DLB) as a between-subject factor. Significant group effects at P < 0.05 were examined post hoc (Scheffe tests). The subset of subjects for whom data were available for all three tasks were further examined in separate repeated-measures ANOVAs for reaction time and accuracy with task (colour, faces, motion) as a within-subject factor and group as a between-subject factor (Greenhouse–Geisser sphericity correction). Note that owing to our fixed experimental order, the task factor can be equally considered a time factor (1st, 2nd, 3rd experiment). To quantify the degree of attentional fluctuation, a fluctuation score was calculated for each subject and task (the within-subject standard deviation of reaction time). For each task the normal range of fluctuation was calculated using the control group (extreme outliers removed), the critical cut-off of normal performance being defined as the mean ± 2 SD of the control group fluctuation score. Pathological attentional fluctuation was deemed present in patients whose fluctuation score exceeded this cut-off value in one or more of the tasks.
Functional MRI (fMRI) data acquisition and analysis
Functional images were acquired on a 1.5 T GE Neuro-optimized Signa LX Horizon System (General Electric, Milwaukee, WI, USA). A gradient echo planar sequence sensitive to blood oxygenation level-dependent contrast (Kwong et al., 1992) was used [repetition time (TR) = 2 s; echo time (TE) = 40 ms; flip angle: 90°; 64 x 64 matrix; voxel size: 3.75 x 3.75 x 7.7 mm]. Three hundred and four volumes were acquired for each task. A high-resolution structural scan was also acquired [spoiled gradient-recalled (SPGR); TR = 16 ms; TE = 5 ms; inversion time (TI) = 300 ms; flip angle: 20°; 256 x 256 matrix; voxel size: 0.859 x 0.859 x 1.5 mm]. Images were analysed in SPM99 (http://www.fil.ion.ucl.ac.uk/spm/). The time series from each subject was movement-corrected, transformed into Talairach space and smoothed. Task-specific, event–related models were derived for each subject by convolving the haemodynamic response function with trial onset time. No distinction was made between correct and incorrect trial responses but trials not followed by a response were modelled as covariates of no interest and excluded from further analysis. Each model also contained a term related to the linear association of brain activity to reaction time. The results related to this term will be reported elsewhere. For each task, the t-contrast map from each subject was tested in an ANOVA model, thresholded at P < 0.05 corrected for multiple comparison at the voxel level for each of six comparisons (DLB > Alzheimer's disease, DLB < Alzheimer's disease, DLB > control, DLB < control, Alzheimer's disease > control, Alzheimer's disease < control). Selected regions of task-specific activation and default network deactivation were identified in one-sample t-test group activation maps derived from the t-contrast maps of all subjects, thresholded at P < 0.05 corrected for multiple comparisons at the voxel level. The subject-specific parameter estimates at these locations were extracted and further examined within Statistical Package for the Social Sciences (SPSS) within repeated-measures ANCOVAs (analysis of covariance) to control for confounding covariates (see below).
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Results |
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The three groups differed in MMSE score, with controls scoring higher than the two dementia groups [MMSE mean ± SD: control = 29.5 ± 0.7; Alzheimer's disease = 22.9 ± 3.2; DLB = 23.7 ± 2.5; F(2, 29) = 30.0; P < 0.001]. There was no significant MMSE difference between DLB and Alzheimer's disease groups on post hoc testing (P = 0.76). The three groups also differed in mean age with controls being the youngest [years mean ± SD: control = 71 ± 7; Alzheimer's disease = 78 ± 6; DLB = 78 ± 5; F(2, 29) = 4.4; P = 0.02]. There was no significant age difference between the DLB and Alzheimer's disease groups (P = 1.0).
Data set
Two DLB subjects were unable to tolerate the scanning procedure for all three tasks and only completed the colour and face tasks. Imaging data from one control subject in the colour task and one Alzheimer's disease and one control subject in the biological motion task were excluded from further analysis owing to scan acquisition artefacts. The imaging data set for the one-sample t-test and ANOVA models was therefore as follows: control: n = 12 colour, n = 13 faces, n = 12 biological motion; Alzheimer's disease: n = 10 colour, n = 10 faces, n = 9 biological motion; DLB: n = 9 colour, n = 9 faces, n = 7 biological motion. Difficulties with the button press resulted in the loss of all behavioural data for one DLB subject in the colour task, one DLB subject in the face task and two DLB subjects and one Alzheimer's disease subject in the motion task, although on post-scan debriefing the subjects confirmed that they had been performing the task. The imaging data from these subjects were modelled as if each trial had been responded to and included in the ANOVA and one-sample t-test models but, as no behavioural data were available, not in the ANCOVA models controlling for performance (ANCOVA data set: control: n = 12 colour, n = 13 faces, n = 12 biological motion; Alzheimer's disease: n = 10 colour, n = 10 faces, n = 8 biological motion; DLB: n = 8 colour, n = 8 faces, n = 5 biological motion).
Task performance
Figure 1 shows the reaction time and accuracy data for each experiment. In the reaction time data, a significant group effect was found for each task [colour F(2, 28) = 3.8, P = 0.036; face F(2, 28) = 7.7, P = 0.02; motion F(2, 24) = 5.5, P = 0.01]. On post hoc testing these effects related to differences between the control and dementia groups, with no significant difference between DLB and Alzheimer's disease performance for the colour or face task (Alzheimer's disease versus DLB colour P = 0.97; Alzheimer's disease versus DLB face P = 0.40) but a non-significant trend towards worse per-formance in the DLB group in the motion task (Alzheimer's disease versus DLB motion P = 0.13). The repeated-measures ANOVA showed a significant task (or time) effect [F(2, 46) = 11.65, P < 0.001] with reaction times slowing over successive experiments across all groups and a non-significant trend for a group by task (or time) interaction with a greater slowing in performance across task (or time) in the DLB group [F(4, 46) = 2.63, P = 0.062]. The linear nature of the effect suggests that it relates more to time than task. The accuracy data showed significant group differences for the face and motion task but not the colour task [face F(2, 28) = 6.6, P = 0.004; motion F(2, 24) = 3.9, P = 0.033; colour F(2, 28) = 2.0, P = 0.15]. Post hoc testing showed that the two dementia groups differed in the face task with DLB accuracy worse than Alzheimer's disease (Alzheimer's disease versus DLB face P = 0.038) and Alzheimer's disease accuracy matching that of controls (Alzheimer's disease versus control P = 0.76). No differences in accuracy were found between the dementia groups in the colour or motion tasks (Alzheimer's disease versus DLB colour P = 0.98; Alzheimer's disease versus DLB motion P = 0.79). The repeated-measures ANOVA for the accuracy data showed no significant task (or time) or group by task (or time) interaction [task F(2, 46) = 2.4, P = 0.1; task x group F(4, 46) = 1.27, P = 0.29].
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Brain activity
For each task, the one-sample t-test (all subjects included) revealed a distinct but partially overlapping network of distributed brain regions (Fig. 2A). The network node with the most significant activation in the colour experiment lay in ventral occipitotemporal cortex (Talairach coordinate: –30, –52, –24; P = 0.002 corrected) and matched the coordinates of the anterior subdivision (V4
) of the left human colour centre V4 (Bartels et al., 2000). To look for possible differences in the haemodynamic response of the three groups, the trial-related time course of the magnetic resonance signal (averaged over trial repeats) was extracted from V4 in those subjects with robust responses (activation at P < 0.001 uncorrected; control n = 10, Alzheimer's disease n = 8, DLB n = 4). The grand mean of the individual haemodynamic responses for each group is displayed in Fig. 2A. No gross differences in the form and latency of the haemodynamic response was found across the three groups. The network node with the most significant activation in the face experiment lay in ventral occipitotemporal cortex (34, –48, –22; P = 0.005 corrected), matching the coordinates of the right fusiform face area (FFA) (Kanwisher et al., 1997). In the motion task, a significant network node was found in lateral occipitotemporal cortex (48, –64, 0; P = 0.015 corrected) corresponding to the right human motion centre, V5 (Watson et al., 1993); however, the most significant activation lay in the right parietal lobe in close proximity to the intra-parietal sulcus [30, –66, 42; Brodmann area (BA) 7; P = 0.003 corrected], an area also reported in previous visual motion studies (Watson et al., 1993; Shipp et al., 1994). In addition to the activation networks described above, each task was associated with decreases in activity within the default network with prominent foci bilaterally in the posterior cingulate gyrus (±8, –48, 26; left P < 0.001; right P < 0.001 corrected) and medial frontal cortex (±18, 42, 32; left P < 0.001; right P < 0.001 corrected). Group differences in these patterns of task activation and deactivation were examined within statistical parametric mapping (SPM) ANOVA models. In the biological motion task, a significant difference (peak voxel P = 0.004 corrected; 44, 0, –20; BA 22/21) between DLB and Alzheimer's disease groups was found in the right temporal lobe at the fundus of the superior temporal sulcus (STS). There was an equivalent but sub-threshold activation at the fundus of the left STS (peak voxel P = 0.07 corrected; –40, –4, –26) (Fig. 3A). Figure 3C shows that this group difference related to an activation response in DLB (positive parameter estimates) and a deactivation response in Alzheimer's disease (negative parameter estimates). Since the STS was not one of the areas activated during the motion task in the one-sample t-test (all subjects included), we investigated the finding using a masking procedure to focus on brain regions activated during the task in the DLB or Alzheimer's disease groups separately (masks thresholded at P < 0.01 uncorrected). The STS formed part of the network of areas activated in the DLB group during the motion task, and when the SPM ANOVA was restricted to the DLB motion network, the difference between the DLB and Alzheimer's disease groups in the STS increased its significance (right STS P < 0.0001 corrected for search volume; left STS P < 0.005 corrected for search volume). No other areas within the DLB motion network emerged as significantly more active in DLB than Alzheimer's disease and none were more active in Alzheimer's disease than DLB. No Alzheimer's disease > DLB or DLB > Alzheimer's disease differential activations were found within the Alzheimer's disease motion network. No significant group differences in the SPM ANOVA were found for the colour or face experiment.
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As noted above, reaction times showed a non-significant trend towards a worse performance in the DLB group in the motion task and we wondered whether the STS group activation difference found in the SPM ANOVA was simply an artefact of this performance difference. We therefore extracted subject-specific effect sizes from the STS in both hemispheres (5 mm spherical volume centred on the peak coordinate) and examined them in a repeated-measures ANOVA with hemisphere as a within-subject factor (left, right) and a repeated-measures ANCOVA with hemisphere as a within-subject factor and reaction time, accuracy, age and MMSE as potential confounding covariates. The ANOVA confirmed a significant group effect [F(2, 25) = 21.27, P < 0.001] with post hoc differences between Alzheimer's disease and DLB (P = 0.05), DLB and controls (P = 0.05) and Alzheimer's disease and controls (P = 0.04). The ANCOVA analysis suggested that these group differences were independent of performance, age or cognitive score [group main effect F(2, 18) = 8.44, P = 0.003].
While group differences in the motion task within the STS were sufficiently large to be detected in an SPM ANOVA, we wondered whether there might be smaller differences within the networks of activation and deactivation found for each task that failed to reach the threshold of significance owing to the relatively small sample size. To explore this issue further, subject-specific parameter estimates were extracted from V4 in the colour task, the FFA in the face task, Brodmann area 7 (BA7) and V5 in the biological motion task and bilateral default network regions in the posterior cingulate and medial frontal cortices for all tasks. The extracted parameter estimates were tested in ANOVA and ANCOVA models, the latter controlling for accuracy and reaction time [within-subject factors for default network analysis: location (posterior cingulate, medial frontal) and hemisphere (left, right)]. The results are illustrated in Fig. 2B and C and are summarized in Table 1. In the face task, significant group effects were found in the FFA, with more activation in the Alzheimer's disease group than DLB or controls (Alzheimer's disease > DLB P = 0.05, Alzheimer's disease > controls P = 0.14). In the biological motion task, significant group effects were found in V5 with less activation in the DLB group than Alzheimer's disease or controls (DLB < Alzheimer's disease P = 0.031 and DLB < control P = 0.048). However, these activation differences in V5 and the FFA could be explained by differences in performance, the effects failing to reach significance in the ANCOVA analysis. In the default network as a whole (pooled over left and right hemispheres and posterior cingulate and medial frontal regions), significant group deactivation differences were found in the colour and motion experiment although these related to greater deactivation in controls than the two patient groups (colour: control < Alzheimer's disease P = 0.02, control < DLB P = 0.019; motion: control < Alzheimer's disease P = 0.118, control < DLB P = 0.118). These default network deactivation differences could be explained by performance, failing to reach significance in the ANCOVA. Post hoc comparisons revealed a trend towards greater deactivation in the pooled default network for Alzheimer's disease than DLB in the face task (P = 0.169) but no difference in the colour and motion tasks (colour P = 0.993; motion P = 0.992). There were no significant location by group, hemisphere by group or location by hemisphere by group interactions in the default network.
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Discussion |
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Our results reveal both similarities and differences in the brain activity of DLB and Alzheimer's disease patients for the three tasks investigated, some of which related to differences in behavioural performance, others independent of it. Below, we examine these differences in terms of the known functional pathology of Alzheimer's disease and DLB.
Occipitotemporal activations
Imaging studies in the resting state have suggested more prominent functional deficits in lateral compared with ventral and medial occipitotemporal cortex in DLB than Alzheimer's disease (Imamura et al., 1997; Ishii et al., 1998), although a recent study with post-mortem validation has suggested that the deficit may extend medially (Minoshima et al., 2001). As predicted, there were no significant differences between the DLB and Alzheimer subjects on the colour task in terms of ventral occipitotemporal brain activation. The equivalent performance of the DLB and Alzheimer groups in this task was unexpected as previous studies have shown differences with DLB patients performing more poorly in pop-out tasks (Cormack et al., 2004). In the face task, differences were found between DLB and Alzheimer's disease in performance accuracy and ventral occipitotemporal activation. Although unexpected, the findings related to an increase in occipitotemporal activation in the Alzheimer group above controls and not an unpredicted deficit in the DLB group. The motion task produced the predicted deficit in lateral activation and a trend towards a performance deficit in the reaction time data. This performance deficit is consistent with previous evidence of a visual motion processing deficit in DLB using a random dot task in which subjects were required to discriminate the velocity of dot motion (Mosimann et al., 2004).
Default network
Consistent with previous evidence (Greicius et al., 2004), we found differences in the default network in Alzheimer's disease compared with controls. In our study, this finding related to a decrease in default network deactivation during each task, whereas the previous evidence relates to decreased default network activation during rest. The two views of the default network are complementary (decreased activity at rest implies less activity to deactivate during task engagement) and both studies found abnormalities in the same posterior cingulate region. However, our results suggest that default network differences between Alzheimer's disease and controls may be more complex than simply resting state level, as no difference was found between the groups in the face task and, more importantly, differences that were found in other tasks disappeared when controlling for task performance. The implication is that default network disengagement as well as resting activity may be abnormal in Alzheimer's disease but further work is required to clarify the issue. Our hypothesis that the default network might also be affected in DLB was confirmed, as task-related deactivation of the network was decreased in DLB compared with controls in the colour and motion tasks. However, our study did not reveal the predicted greater deficit in DLB than Alzheimer's disease.
The superior temporal sulcus
Structural imaging studies have found several cortical regions selectively spared in DLB compared with Alzheimer's disease, particularly medial temporal lobe regions thought to underlie the relative preservation of memory in DLB (Barber et al., 2000; Ballmaier et al., 2004). However, selective atrophy in Alzheimer's disease compared with DLB has also been identified more laterally in the temporal lobe within the banks of the STS (Gomez-Isla et al., 1999). This region contains higher-order association cortex affected both by Lewy bodies in DLB and neurofibrillary tangles and plaques in Alzheimer's disease. Compared with controls, the number of neurons in the STS is reduced by 50% in Alzheimer's but only by 11% in DLB (Gomez-Isla et al., 1999). A previous functional imaging study has identified greater resting blood flow in DLB compared with Alzheimer's disease in a right temporal region reported as hippocampal (Ishii et al., 1999) but which extends to the same STS region as identified here. The significance of these structural and functional differences for our study becomes clear when one considers the role of the superior temporal region in motion processing. The superior, lateral temporal lobe plays a specific role in non-human primate studies of biological motion (Oram et al., 1994) and is consistently found active in studies of biological motion in man (Howard et al., 1996; Servos et al., 2002). The implication is that neuronal loss in the STS was highlighted in our study by a functional probe targeting one of its many processing functions. Although we did not perform quantitative assessments, Fig. 3B shows that the STS was not grossly atrophic in the average Alzheimer brain compared with the average DLB brain in our patient group. This observation argues against the possibility that the greater STS activation found in DLB compared with Alzheimer's disease was simply an artefact of differential STS volume loss in the two groups. Instead, it suggests that functional changes in the STS may be detectable at an early stage of neuronal loss, predating macroscopic atrophy. The finding of greater motion-related STS activation in DLB than Alzheimer's disease is important as it reduces the possibility that the DLB deficits in motion-task reaction time and V5 activation were caused by non-specific effects such as fatigue or a failure to engage with the task. Of interest is the fact that, unlike the differences in occipitotemporal activation and default network deactivation described above, the differential STS activation was independent of performance, cognitive score or age.
Study limitations
Our study is exploratory and there are a number of important issues to be resolved. In particular, while we have been able to differentiate two groups of patients that differ on research diagnostic criteria using a range of functional measures, without post-mortem validation we cannot know whether the diagnostic groupings are correct. It is also unclear whether task order was an important factor in discriminating the two groups as our design was not counterbalanced, or whether the fact that subjects practised the motion task less than the other two influenced the results. The possibility that other types of motion might also be used to differentiate DLB from Alzheimer's disease seems likely given that DLB motion performance deficits have been found in a random dot velocity discrimination task (Mosimann et al., 2004). Finally, although we did not identify gross group differences in the latency or form of the haemodynamic response in occipitotemporal cortex, it is possible that such differences exist in other brain regions. This would reduce the sensitivity of our regression technique to detect activations in these regions and, if linked to a particular pathology, could result in false-positive activation differences between groups.
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Conclusion |
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Our study demonstrates the practical feasibility of cognitive fMRI in patients with DLB and provides preliminary evidence of activation and deactivation patterns that differentiate such patients from those with Alzheimer's disease. These findings will need to be replicated but they raise the possibility of using cognitive fMRI as an adjunct to existing methods for the in vivo diagnosis of DLB.
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Acknowledgements |
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This research was supported by an MRC ROPA research grant. DHff was a Wellcome Clinician Scientist Fellow.
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References |
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Ballmaier M, O'Brien JT, Burton EJ, Thompson PM, Rex DE, Narr KL, et al. (2004) Comparing gray matter loss profiles between dementia with Lewy bodies and Alzheimer's disease using cortical pattern matching: diagnosis and gender effects. Neuroimage 23:325–35.[CrossRef][Web of Science][Medline]
Barber R, Ballard C, McKeith IG, Gholkar A, O'Brien JT. (2000) MRI volumetric study of dementia with Lewy bodies: a comparison with AD and vascular dementia. Neurology 54:1304–9.
Bartels A and Zeki S. (2000) The architecture of the colour centre in the human visual brain: new results, a review. Eur J Neurosci 12:172–93.[Web of Science][Medline]
Buckner RL, Snyder AZ, Shannon BJ, LaRossa G, Sachs R, Fotenos AF, et al. (2005) Molecular, structural, and functional characterization of Alzheimer's disease: evidence for a relationship between default activity, amyloid, and memory. J Neurosci 25:7709–17.
Calderon J, Perry RJ, Erzinclioglu SW, Berrios GE, Dening TR, Hodges JR. (2001) Perception, attention, working memory are disproportionately impaired in dementia with Lewy bodies compared with Alzheimer's disease. J Neurol Neurosurg Psychiatry 70:157–64.
Collerton D, Burn D, McKeith I, O'Brien J. (2003) Systematic review and meta-analysis show that dementia with Lewy bodies is a visual-perceptual and attentional-executive dementia. Dement Geriatr Cogn Disord 16:229–37.[CrossRef][Web of Science][Medline]
Cormack F, Gray A, Ballard C, Tovee MJ. (2004) A failure of ‘pop-out’ in visual search tasks in dementia with Lewy Bodies as compared to Alzheimer's and Parkinson's disease. Int J Geriatr Psychiatry 19:763–72.[CrossRef][Web of Science][Medline]
Folstein MF, Folstein SE, McHugh PR. (1975) ‘Mini-Mental State’. A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 12:189–98.[CrossRef][Web of Science][Medline]
Gomez-Isla T, Growdon WB, McNamara M, Newell K, Gomez-Tortosa E, Hedley-Whyte ET, et al. (1999) Clinicopathologic correlates in temporal cortex in dementia with Lewy bodies. Neurology 53:2003–9.
Greicius MD, Srivastava G, Reiss AL, Menon V. (2004) Default-mode network activity distinguishes Alzheimer's disease from healthy aging: evidence from functional MRI. Proc Natl Acad Sci USA 101:4637–42.
Howard RJ, Brammer M, Wright I, Woodruff PW, Bullmore ET. (1996) A direct demonstration of functional specialization within motion-related visual and auditory cortex of the human brain. Curr Biol 6:1015–9.[CrossRef][Web of Science][Medline]
Imamura T, Ishii K, Sasaki M, Kitagaki H, Yamaji S, Hirono N, et al. (1997) Regional cerebral glucose metabolism in dementia with Lewy bodies and Alzheimer's disease: a comparative study using positron emission tomography. Neurosci Lett 235:49–52.[CrossRef][Web of Science][Medline]
Ishii K, Imamura T, Sasaki M, Yamaji S, Sakamoto S, Kitagaki H, et al. (1998) Regional cerebral glucose metabolism in dementia with Lewy bodies and Alzheimer's disease. Neurology 51:125–30.
Ishii K, Yamaji S, Kitagaki H, Imamura T, Hirono N, Mori E. (1999) Regional cerebral blood flow difference between dementia with Lewy bodies and AD. Neurology 53:413–6.
Johansson G. (1973) Visual perception of biological motion and a model for its analysis. Percept Psychophys 14:201–11.[Web of Science]
Kanwisher N, McDermott J, Chun MM. (1997) The fusiform face area: a module in human extrastriate cortex specialised for face perception. J Neurosci 17:4302–11.
Kwong KK, Belliveau JW, Chesler DA, Goldberg IE, Weisskoff RM, Poncelet BP, et al. (1992) Dynamic magnetic resonance imaging of human brain activity during primary sensory stimulation. Proc Natl Acad Sci USA 89:5675–9.
Lobotesis K, Fenwick JD, Phipps A, Ryman A, Swann A, Ballard C, et al. (2001) Occipital hypoperfusion on SPECT in dementia with Lewy bodies but not AD. Neurology 56:643–9.
Mazoyer B, Zago L, Mellet E, Bricogne S, Etard O, Houde O, et al. (2001) Cortical networks for working memory and executive functions sustain the conscious resting state in man. Brain Res Bull 54:287–98.[CrossRef][Web of Science][Medline]
Mckeefry DJ and Zeki S. (1997) The position and topography of the human colour centre as revealed by functional magnetic resonance imaging. Brain 120:2229–42.
McKeith IG, Galasko D, Kosaka K, Perry EK, Dickson DW, Hansen LA, et al. (1996) Consensus guidelines for the clinical and pathologic diagnosis of dementia with Lewy bodies (DLB): report of the consortium on DLB international workshop. Neurology 47:1113–24.
McKeith IG, Perry EK, Perry RH. (1999) Report of the second dementia with Lewy body international workshop: diagnosis and treatment. Consortium on Dementia with Lewy Bodies. Neurology 53:902–5.
McKeith IG, Burn DJ, Ballard CG, Collerton D, Jaros E, Morris CM, et al. (2003) Dementia with Lewy bodies. Semin Clin Neuropsychiatry 8:46–57.[CrossRef][Medline]
McKhann G, Drachman D, Folstein M, Katzman R, Price D, Stadlan EM. (1984) Clinical diagnosis of Alzheimer's disease: report of the NINCDS-ADRDA Work Group under the auspices of the Department of Health and Human Services Task Force on Alzheimer's disease. Neurology 34:939–44.
McKiernan KA, Kaufman JN, Kucera-Thompson J, Binder JR. (2003) A parametric manipulation of factors affecting task-induced deactivation in functional neuroimaging. J Cogn Neurosci 15:394–408.[CrossRef][Web of Science][Medline]
Middelkoop HA, van der Flier WM, Burton EJ, Lloyd AJ, Paling S, Barber R, et al. (2001) Dementia with Lewy bodies and AD are not associated with occipital lobe atrophy on MRI. Neurology 57:2117–20.
Minoshima S, Foster NL, Sima AA, Frey KA, Albin RL, Kuhl DE. (2001) Alzheimer's disease versus dementia with Lewy bodies: cerebral metabolic distinction with autopsy confirmation. Ann Neurol 50:358–65.[CrossRef][Web of Science][Medline]
Mori E, Shimomura T, Fujimori M, Hirono N, Imamura T, Hashimoto M, et al. (2000) Visuoperceptual impairment in dementia with Lewy bodies. Arch Neurol 57:489–93.
Mosimann UP, Mather G, Wesnes KA, O'Brien JT, Burn DJ, McKeith IG. (2004) Visual perception in Parkinson disease dementia and dementia with Lewy bodies. Neurology 63:2091–6.
Oram MW and Perrett DI. (1994) Responses of anterior superior temporal polysensory (STPa) neurons to biological motion stimuli. J Cogn Neurosci 6:99–116.[Medline]
Perry RH, Irving D, Blessed G, Fairbairn A, Perry EK. (1990) Senile dementia of Lewy body type. A clinically and neuropathologically distinct form of Lewy body dementia in the elderly. J Neurol Sci 95:119–39.[CrossRef][Web of Science][Medline]
Raichle ME, MacLeod AM, Snyder AZ, Powers WJ, Gusnard DA, Shulman GL. (2001) A default mode of brain function. Proc Natl Acad Sci USA 98:676–82.
Rizzo M and Nawrot M. (1998) Perception of movement and shape in Alzheimer's disease. Brain 121:2259–70.
Servos P, Osu R, Santi A, Kawato M. (2002) The neural substrates of biological motion perception: an fMRI study. Cereb Cortex 12:772–82.
Shipp S, de Jong BM, Zihl J, Frackowiak RSJ, Zeki S. (1994) The brain activity related to residual motion vision in a patient with bilateral lesions of V5. Brain 117:1023–38.
Shulman GL, Fiez JA, Corbetta M, Buckner RL, Miezin FM, Raichle ME, et al. (1997) Common blood flow changes across visual tasks II. Decreases in cerebral cortex. J Cogn Neurosci 9:648–63.[Web of Science]
Simard M, van Reekum R, Myran D. (2003) Visuospatial impairment in dementia with Lewy bodies and Alzheimer's disease: a process analysis approach. Int J Geriatr Psychiatry 18:387–91.[CrossRef][Web of Science][Medline]
Watson JD, Myers R, Frackowiak RS, Hajnal JV, Woods RP, Mazziotta JC, et al. (1993) Area V5 of the human brain: evidence from a combined study using positron emission tomography and magnetic resonance imaging. Cereb Cortex 3:79–94.
Zeki S, Watson JDG, Lueck CJ, Friston KJ, Kennard C, Frackowiak RSJ. (1991) A direct demonstration of functional specialization in human visual cortex. J Neurosci 11:641–9.[Abstract]
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