Background. The evaluation of effective disease-modifying therapies for neurodegenerative disorders relies on objective and accurate measures of progression in at-risk individuals. Here we used a computational approach to identify a functional brain network associated with the progression of preclinical Huntington’s disease (HD).
Methods. Twelve premanifest HD mutation carriers were scanned with [18F]-fluorodeoxyglucose PET to measure cerebral metabolic activity at baseline and again at 1.5, 4, and 7 years. At each time point, the subjects were also scanned with [11C]-raclopride PET and structural MRI to measure concurrent declines in caudate/putamen D2 neuroreceptor binding and tissue volume. The rate of metabolic network progression in this cohort was compared with the corresponding estimate obtained in a separate group of 21 premanifest HD carriers who were scanned twice over a 2-year period.
Results. In the original premanifest cohort, network analysis disclosed a significant spatial covariance pattern characterized by progressive changes in striato-thalamic and cortical metabolic activity. In these subjects, network activity increased linearly over 7 years and was not influenced by intercurrent phenoconversion. The rate of network progression was nearly identical when measured in the validation sample. Network activity progressed at approximately twice the rate of single region measurements from the same subjects.
Conclusion. Metabolic network measurements provide a sensitive means of quantitatively evaluating disease progression in premanifest individuals. This approach may be incorporated into clinical trials to assess disease-modifying agents.
Trial registration. Registration is not required for observational studies.
Funding. NIH (National Institute of Neurological Disorders and Stroke, National Institute of Biomedical Imaging and Bioengineering) and CHDI Foundation Inc.
The default-mode network (DMN) has become a well accepted concept in cognitive and clinical neuroscience over the last decade, and perusal of the recent literature attests to a stimulating research field of cognitive and diagnostic applications (for example, (Andrews-Hanna, Reidler, Huang, & Buckner, 2010; Koch et al., 2010; Sheline, Barch et al., 2009; Sheline, Raichle et al., 2009; Uddin et al., 2008; Uddin, Kelly, Biswal, Castellanos, & Milham, 2009; Weng et al., 2009; Yan et al., 2009)). However, a formal definition of what exactly constitutes a functional brain network is difficult to come by. In recent contributions, some researchers argue that the DMN is best understood as multiple interacting subsystems (Buckner, Andrews-Hanna, & Schacter, 2008) and have explored modular components of the DMN that have different functional specialization and could to some extent be identified separately (Fox et al., 2005; Harrison et al., 2008; Uddin et al., 2009). Such conception of modularity seems to imply an opposite construct of a ‘unified whole’, but it is difficult to locate proponents of the idea of a DMN who are supplying constraints that can be brought to bear on data in rigorous tests. Our aim in this paper is to present a principled way of deriving a single covariance pattern as the neural substrate of the DMN, test to what extent its behavior tracks the coupling strength between critical seed regions, and investigate to what extent our stricter concept of a network is consistent with the already established findings about the DMN in the literature. We show that our approach leads to a functional covariance pattern whose pattern scores are a good proxy for the integrity of the connections between a medioprefrontal, posterior cingulate and parietal seed regions. Our derived DMN network thus has potential for diagnostic applications that are simpler to perform than computation of pairwise correlational strengths or seed maps.
Default-mode network; resting fMRI; spatial covariance analysis; Principal Components Analysis
We performed a delayed-item-recognition task to investigate the neural substrates of non-verbal visual working memory with event-related fMRI (‘Shape task’). 25 young subjects (mean age: 24.0 years; STD=3.8 years) were instructed to study a list of either 1,2 or 3 unnamable nonsense line drawings for 3 seconds (‘stimulus phase’ or STIM). Subsequently, the screen went blank for 7 seconds (‘retention phase’ or RET), and then displayed a probe stimulus for 3 seconds in which subject indicated with a differential button press whether the probe was contained in the studied shape-array or not (‘probe phase’ or PROBE). Ordinal Trend Canonical Variates Analysis (Habeck et al., 2005a) was performed to identify spatial covariance patterns that showed a monotonic increase in expression with memory load during all task phases. Reliable load-related patterns were identified in the stimulus and retention phase (p<0.01), while no significant pattern could be discerned during the probe phase. Spatial covariance patterns that were obtained from an earlier version of this task (Habeck et al., 2005b) using 1, 3, or 6 letters (‘Letter task’) were also prospectively applied to their corresponding task phases in the current non-verbal task version. Interestingly, subject expression of covariance patterns from both verbal and non-verbal retention phases correlated positively in the non-verbal task for all memory loads (p<0.0001). Both patterns also involved similar frontoparietal brain regions that were increasing in activity with memory load, and mediofrontal and temporal regions that were decreasing. Mean subject expression of both patterns across memory load during retention also correlated positively with recognition accuracy (dL) in the Shape task (p<0.005). These findings point to similarities in the neural substrates of verbal and non-verbal rehearsal processes. Encoding processes, on the other hand, are critically dependent on the to-be-remembered material, and seem to necessitate material-specific neural substrates.
multivariate analysis; visual working memory; encoding; maintenance
Effects of dual-responding on tracking performance after 49-hr of sleep deprivation (SD) were evaluated behaviorally and with functional magnetic resonance imaging (fMRI). Continuous visuomotor tracking was performed simultaneously with an intermittent color-matching visual detection task in which a pair of color-matched stimuli constituted a target and non-matches were non-targets. Tracking error means were binned time-locked to stimulus onset of the detection task in order to observe changes associated with dual-responding by comparing the error during targets and non-targets. Similar comparison was made with fMRI data. Our result showed that despite a significant increase in the overall tracking error post SD, from 20 pixels pre SD to 45 pixels post SD, error decreased to a minimum of about 25 pixels 0 to 6 s after dual-response. Despite an overall reduced activation post SD, greater activation difference between targets and non-targets was found post SD in task-related regions, such as the left cerebellum, the left somatosensory cortex, the left extrastriate cortex, bilateral precuneus, the left middle frontal gyrus, and the left motor cortex. Our results suggest that dual-response helps to alleviate performance impairment usually associated with SD. The duration of the alleviation effect was on the order of seconds after dual-responding.
Visuomotor tracking; Visual detection; Continuous wakefulness; Dual responses; Dual tasks; Prefrontal cortex
The extent of task-related fMRI activation can vary as a function of task difficulty. Also the efficiency or capacity of the brain networks underlying task performance can change with aging. We asked whether the expression of a network underlying task performance would differ as a function of task demand in old and young individuals. 26 younger and 23 older healthy adults performed a delayed item recognition task that used the response signal method to parametrically manipulate the extrinsic difficulty of the task by imposing five different deadlines for recognition response. Both age groups showed a speed accuracy trade-off, but the younger group achieved greater discriminability at the longer deadlines. We identified a spatial pattern of fMRI activation during the probe phase whose expression increased as the response deadline shortened and the task became more difficult. This pattern was expressed to a greater degree by the old group at the long deadlines, when the task was easiest. By contrast, this pattern was expressed to greater degree by the younger group at the short deadlines, when the task was hardest. This suggests reduced efficiency and capacity of this network in older subjects. These findings suggest that neuroimaging studies comparing task-related activation across groups with different cognitive abilities must be interpreted in light of the relative difficulty of the task for each group.
fMRI; aging; working memory; speed-accuracy tradeoff
Subjects performed a continuous tracking concurrently with an intermittent visual detection task to investigate the existence of competition for a capacity-limited stage (a bottleneck stage). Both perceptual and response-related processes between the two tasks were examined behaviorally and the changes in brain activity during dual-tasking relative to single-task were also assessed. Tracking error and joystick speed were analyzed for changes that were time-locked to visual detection stimuli. The associated brain activations were examined with functional magnetic resonance imaging (fMRI). These were analyzed using mixed block and event-related models to tease apart sustained neural activity and activations associated with individual events. Increased tracking error and decreased joystick speed were observed relative to the target stimuli in the dual-task condition only, which supports the existence of a bottleneck stage in response-related processes. Neuroimaging data show decreased activation to target relative to non-target stimuli in the dual-task condition in the left primary motor and somatosensory cortices controlling right-hand tracking, consistent with the tracking interference observed in behavioral data. Furthermore, the ventral attention system, rather than the dorsal attention system, was found to mediate task coordination between tracking and visual detection.
fMRI; Compensatory tracking; Visual detection; Bottom-up attention system; Psychological refractory period; Dual-task interference
This functional neuroimaging (fMRI) study examined the neural networks (spatial patterns of covarying neural activity) associated with the speed-accuracy tradeoff (SAT) in younger adults. The response signal method was used to systematically increase probe duration (125, 250, 500, 1,000 2,000 ms) in a nonverbal delayed-item recognition task. A covariance-based multivariate approach identified three networks that varied with probe duration – indicating that the SAT is driven by three distributed neural networks.
Aging has a multi-faceted impact on brain structure, brain function and cognitive task performance, but the interaction of these different age-related changes is largely unexplored. We hypothesize that age-related structural changes alter the functional connectivity within the brain, resulting in altered task performance during cognitive challenges. In this neuroimaging study, we used independent components analysis to identify spatial patterns of coordinated functional activity involved in the performance of a verbal delayed item recognition task from 75 healthy young and 37 healthy old adults. Strength of functional connectivity between spatial components was assessed for age group differences and related to speeded task performance. We then assessed whether age-related differences in global brain volume were associated with age-related differences in functional network connectivity. Both age groups used a series of spatial components during the verbal working memory task and the strength and distribution of functional network connectivity between these components differed across the age groups. Poorer task performance, i.e. slower speed with increasing memory load, in the old adults was associated with decreases in functional network connectivity between components comprised of the supplementary motor area and the middle cingulate and between the precuneus and the middle/superior frontal cortex. Advancing age also led to decreased brain volume; however, there was no evidence to support the hypothesis that age-related alterations in functional network connectivity were the result of global brain volume changes. These results suggest that age-related differences in the coordination of neural activity between brain regions partially underlie differences in cognitive performance.
Resting-state functional connectivity has become a topic of enormous interest in the Neuroscience community in the last decade. Because resting-state data (1) harbor important information that often is diagnostically relevant and (2) are easy to acquire, there has been a rapid increase in the development of a variety of network analytic techniques for diagnostic applications, stimulating methodological research in general. While we are among those who welcome the increased interest in the resting state and multivariate analytic tools, we would like to draw attention to some entrenched practices that undermine the scientific quality of diagnostic functional-connectivity research, but whose correction is relatively easy to accomplish. With the current commentary we also hope to benefit the field at large and contribute to a healthy debate about research goals and best practices.
brain networks; correlation matrix; default mode network; independent component analysis (ICA); principal component analysis (PCA)
Spatiotemporal and recognition memory are affected by aging in humans and macaque monkeys. To investigate whether these deficits are coupled with atrophy of memory-related brain regions, T1-weighted magnetic resonance images were acquired and volumes of the cerebrum, ventricles, prefrontal cortex (PFC), calcarine cortex, hippocampus, and striatum were quantified in young and aged rhesus monkeys. Subjects were tested on a spatiotemporal memory procedure (delayed response [DR]) that requires the integrity of the PFC and a medial temporal lobe-dependent recognition memory task (delayed nonmatching to sample [DNMS]). Region of interest analyses revealed that age inversely correlated with striatal, dorsolateral prefrontal cortex (dlPFC), and anterior cingulate cortex volumes. Hippocampal volume predicted acquisition of the DR task. Striatal volume correlated with DNMS acquisition, whereas total prefrontal gray matter, prefrontal white matter, and dlPFC volumes each predicted DNMS accuracy. A regional covariance analysis revealed that age-related volumetric changes could be captured in a distributed network that was coupled with declining performance across delays on the DNMS task. This volumetric analysis adds to growing evidence that cognitive aging in primates arises from region-specific morphometric alterations distributed across multiple memory-related brain systems, including subdivisions of the PFC.
age-related memory impairment; medial temporal lobe; MRI; prefrontal cortex; rhesus monkey
By comparing hemodynamic signals acquired immediately before and during activation, functional magnetic resonance imaging (fMRI) is well suited for mapping acute changes in brain function. However, it remains unclear whether fMRI can map functional changes over longer periods. Here, we address this issue by empirically testing the feasibility of arterial spin labeling (ASL) fMRI to detect changes in cerebral blood flow (CBF) with baseline and task separated by 1 month. To increase the sensitivity of the method, we applied an algorithm that yielded flow density (CBFd) images that were independent of tissue content. To increase the accuracy, we developed a technique that generated arterial transit time at each voxel, independently. Results showed that activation changes in CBFd during the same session were statistically the same as across 30 days. The activation CBFd on day-30 was 34% (motor) and 25% (visual) higher than the respective baselines of 83 and 107 mL/100 g/min obtained on day-1. Furthermore, the signal-to-noise ratio of the CBFd measurement was 2.1 and 2.9 times higher than that of the conventional CBF for within-subject and across-subjects comparisons, respectively (n=9 healthy young subjects). Taken together, these results indicate that CBFd measure could be better suited than net CBF to map long-term changes in brain function.
ASL; arterial transit time; baseline drift; CBF; fMRI; 1/f noise; PVE
Functional magnetic resonance imaging (fMRI) studies have shown that repetition priming of visual objects is typically accompanied by a reduction in activity for repeated compared to new stimuli (repetition suppression). However, the spatial distribution and direction (suppression vs. enhancement) of neural repetition effects can depend on the pre-experimental familiarity of stimuli. The first goal of this study was to further probe the link between repetition priming and repetition suppression/enhancement for visual objects and how this link is affected by stimulus familiarity. A second goal was to examine whether priming of familiar and unfamiliar objects following a single stimulus repetition is supported by the same processes as priming following multiple repetitions within the same task. In this endeavor, we examined both between and within subjects correlations between priming and fMRI repetition effects for familiar and globally unfamiliar visual objects during the first and third repetition of the stimuli. We included reaction time of individual trials as a linear regressor to identify brain regions whose repetition effects varied with response facilitation on a trial-by-trial basis. The results showed that repetition suppression in bilateral fusiform gyrus, was selectively correlated with priming of familiar objects that had been repeated once, likely reflecting facilitated perceptual processing or the sharpening of perceptual representations. Priming during the third repetition was correlated with repetition suppression in prefrontal and parietal areas for both familiar and unfamiliar stimuli, possibly reflecting a shift from top-down controlled to more automatic processing that occurs for both item types.
priming; neural repetition suppression; neural repetition enhancement; fMRI; stimulus familiarity
Neurophysiological studies have provided evidence of primary motor cortex hyperexcitability in primary dystonia, but several functional imaging studies suggest otherwise. To address this issue, we measured sensorimotor activation at both the regional and network levels in carriers of the DYT1 dystonia mutation and in control subjects. We used 15Oxygen-labelled water and positron emission tomography to scan nine manifesting DYT1 carriers, 10 non-manifesting DYT1 carriers and 12 age-matched controls while they performed a kinematically controlled motor task; they were also scanned in a non-motor audio-visual control condition. Within- and between-group contrasts were analysed with statistical parametric mapping. For network analysis, we first identified a normal motor-related activation pattern in a set of 39 motor and audio-visual scans acquired in an independent cohort of 18 healthy volunteer subjects. The expression of this pattern was prospectively quantified in the motor and control scans acquired in each of the gene carriers and controls. Network values for the three groups were compared with ANOVA and post hoc contrasts. Voxel-wise comparison of DYT1 carriers and controls revealed abnormally increased motor activation responses in the former group (P < 0.05, corrected; statistical parametric mapping), localized to the sensorimotor cortex, dorsal premotor cortex, supplementary motor area and the inferior parietal cortex. Network analysis of the normative derivation cohort revealed a significant normal motor-related activation pattern topography (P < 0.0001) characterized by covarying neural activity in the sensorimotor cortex, dorsal premotor cortex, supplementary motor area and cerebellum. In the study cohort, normal motor-related activation pattern expression measured during movement was abnormally elevated in the manifesting gene carriers (P < 0.001) but not in their non-manifesting counterparts. In contrast, in the non-motor control condition, abnormal increases in network activity were present in both groups of gene carriers (P < 0.001). In this condition, normal motor-related activation pattern expression in non-manifesting carriers was greater than in controls, but lower than in affected carriers. In the latter group, measures of normal motor-related activation pattern expression in the audio-visual condition correlated with independent dystonia clinical ratings (r = 0.70, P = 0.04). These findings confirm that overexcitability of the sensorimotor system is a robust feature of dystonia. The presence of elevated normal motor-related activation pattern expression in the non-motor condition suggests that abnormal integration of audio-visual input with sensorimotor network activity is an important trait feature of this disorder. Lastly, quantification of normal motor-related activation pattern expression in individual cases may have utility as an objective descriptor of therapeutic response in trials of new treatments for dystonia and related disorders.
DYT1 dystonia; imaging marker; positron emission tomography; motor activation
Regional cerebral blood flow (CBF), a good indirect index of cerebral pathologic changes in Alzheimer disease (AD), is more severely reduced in patients with higher educational attainment and IQ when controlling for clinical severity. This has been interpreted as suggesting that cognitive reserve allows these patients to cope better with the pathologic changes in AD.
To evaluate whether premorbid engagement in various activities may also provide cognitive reserve.
We evaluated intellectual, social, and physical activities in 9 patients with early AD and 16 healthy elderly controls who underwent brain H215O positron emission tomography. In voxelwise multiple regression analyses that controlled for age and clinical severity, we investigated the association between education, estimated premorbid IQ, and activities, and CBF.
In accordance with previous findings, we replicated an inverse association between education and CBF and IQ and CBF in patients with AD. In addition, there was a negative correlation between previous reported activity score and CBF in patients with AD. When both education and IQ were added as covariates in the same model, a higher activity score was still associated with more prominent CBF deficits. No significant associations were detected in the controls.
At any given level of clinical disease severity, there is a greater degree of brain pathologic involvement in patients with AD who have more engagement in activities, even when education and IQ are taken into account. This may suggest that interindividual differences in lifestyle may affect cognitive reserve by partially mediating the relationship between brain damage and the clinical manifestation of AD.
Although multivariate analytic techniques might identify diagnostic patterns that are not captured by univariate methods, they have rarely been used to study the neural correlates of Alzheimer's disease (AD) or cognitive impairment. Nonquantitative
H215O PET scans were acquired during rest in 17 probable AD subjects selected for mild severity [mean-modified Mini Mental Status Examination (mMMS) 46/57; SD 5.1], 16 control subjects (mMMS 54; SD 2.5) and 23 subjects with minimal to mild cognitive impairment but no dementia (mMMS 53; SD 2.8). Expert clinical reading had low success in discriminating AD and controls. There were no significant mean flow differences among groups in traditional univariate SPM Voxel-wise analyses or region of interest (ROI) analyses. A covariance pattern was identified whose mean expression was significantly higher in the AD as compared to controls (P = 0.03; sensitivity 76–94%; specificity 63–81%). Sites of increased concomitant flow included insula, cuneus, pulvinar, lingual, fusiform, superior occipital and parahippocampal gyri, whereas decreased concomitant flow was found in cingulate, inferior parietal lobule, middle and inferior frontal, supramarginal and precentral gyri. The covariance analysis-derived pattern was then prospectively applied to the cognitively impaired subjects: as compared to subjects with Clinical Dementia Rating (CDR) = 0, subjects with CDR = 0.5 had significantly higher mean covariance pattern expression (P = 0.009). Expression of this pattern correlated inversely with Selective Reminding Test total recall (r = −0.401, P = 0.002), delayed recall (r = −0.351, P = 0.008) and mMMS scores (r = −0.401, P = 0.002) in all three groups combined. We conclude that patients with AD may differentially express resting cerebral blood flow covariance patterns even at very early disease stages. Significant alterations in expression of resting flow covariance patterns occur even for subjects with cognitive impairment. Expression of covariance patterns correlates with cognitive and functional performance measures, holding promise for meaningful associations with underlying biopathological processes.
Cognitive; Alzheimer's disease; Covariance; MCI; PET; CBF; diagnosis
In order to understand the brain networks that mediate cognitive reserve, we explored the relationship between subjects’ network expression during the performance of a memory test and an index of cognitive reserve. Using H215O positron emission tomography, we imaged 17 healthy older subjects and 20 young adults while they performed a serial recognition memory task for nonsense shapes under two conditions: low demand, with a unique shape presented in each study trial; and titrated demand, with a study list size adjusted so that each subject recognized shapes at 75% accuracy. A factor score that summarized years of education, and scores on the NART and the WAIS-R Vocabulary subtest was used as an index of cognitive reserve. The scaled subprofile model was used to identify a set of functionally connected regions (or topography) that changed in expression across the two task conditions and was differentially expressed by the young and elderly subjects. The regions most active in this topography consisted of right hippocampus, posterior insula, thalamus, and right and left operculum; we found concomitant deactivation in right lingual gyrus, inferior parietal lobe and association cortex, left posterior cingulate, and right and left calcarine cortex. Young subjects with higher cognitive reserve showed increased expression of the topography across the two task conditions. Because this topography, which is responsive to increased task demands, was differentially expressed as a function of reserve level, it may represent a neural manifestation of innate or acquired reserve. In contrast, older subjects with higher cognitive reserve showed decreased expression of the topography across tasks. This suggests some functional reorganization of the network used by the young subjects. Thus, for the old subjects this topography may represent an altered, compensatory network that is used to maintain function in the face of age-related physiological changes.
compensation; covariance analysis; education; H215O PET; IQ
Few previous studies have investigated the association between APOE genotype and brain activation during performance of cognitive tasks in healthy middle-aged and elderly subjects, and the results have been mixed. The authors investigated APOE-mediated differential brain activation in a group of healthy elderly subjects.
Using H2 15O positron emission tomography (PET), they imaged 32 healthy subjects (26 non-ε4 carriers and 6 ε4 carriers) performing a serial shape-recognition memory task under two conditions: Simple Demand (SD), in which one shape was presented in each study trial, and Titrated Demand (TD), in which study list length was adjusted so that each subject recognized words at approximately 75% accuracy. Multiple-regression analyses were performed, with the “activation” difference (TD–SD PET counts) as the dependent variable and the APOE genotype (presence versus absence of the ε4 allele) as the independent variable.
Compared with non-carriers, ε4 carriers exhibited significantly decreased TD–SD activation differences in the left superior temporal, right superior frontal, left postcental, left precuneus, and posterior cingulate gyrus because ε4 carriers (versus non-carriers) showed increased activation during the SD and decreased activation during the TD condition.
Patterns of brain activation during a nonverbal memory task differed as a function of APOE genotype and, therefore, of genetic risk for Alzheimer disease (AD). Differences in activation were not a reflection of task difficulty, but indicate memory-related altered cognitive processing. Brain regions with decreased activation in the ε4 subjects may result from subclinical incipient AD pathology and/or APOE-related neurophysiologic heterogeneity.
As clinical and cognitive neuroscience mature, the need for sophisticated neuroimaging analysis becomes more apparent. Multivariate analysis techniques have recently received increasing attention as they have many attractive features that cannot be easily realized by the more commonly used univariate, voxel-wise, techniques. Multivariate approaches evaluate correlation/covariance of activation across brain regions, rather than proceeding on a voxel-by-voxel basis. Thus, their results can be more easily interpreted as a signature of neural networks. Univariate approaches, on the other hand, cannot directly address functional connectivity in the brain. The covariance approach can also result in greater statistical power when compared with univariate techniques, which are forced to employ very stringent, and often overly conservative, corrections for voxel-wise multiple comparisons. Multivariate techniques also lend themselves much better to prospective application of results from the analysis of one dataset to entirely new datasets. Multivariate techniques are thus well placed to provide information about mean differences and correlations with behavior, similarly to univariate approaches, with potentially greater statistical power and better reproducibility checks. In contrast to these advantages is the high barrier of entry to the use of multivariate approaches, preventing more widespread application in the community. To the neuroscientist becoming familiar with multivariate analysis techniques, an initial survey of the field might present a bewildering variety of approaches that, although algorithmically similar, are presented with different emphases, typically by people with mathematics backgrounds. We believe that multivariate analysis techniques have sufficient potential to warrant better dissemination. Researchers should be able to employ them in an informed and accessible manner. The following article attempts to provide a basic introduction with sample applications to simulated and real-world data sets.
Alzheimer’s disease; Multivariate analysis; Principal components analysis; Brain reading; Classification; Cross validation; Nonparametric inference; Split-sample simulations
Research has indicated that there may be age-related and Alzheimer’s disease (AD)-related reductions in regional cerebral blood flow (rCBF) in the brain. This study explored differences in age- and AD-related rCBF patterns in the context of cognitive aging using a multivariate approach to the analysis of H2 15O PET data. First, an rCBF covariance pattern that distinguishes between a group of younger and older adults was identified. Individual subject’s expression of the identified age-related pattern was significantly correlated with their performance on tests of memory, even after controlling for the effect of age. This finding suggests that subject expression of the covariance pattern explained additional variation in performance on the memory tasks. The age-related covariance pattern was then compared to an AD-related covariance pattern. There was little evidence that the two covariance patterns were similar, and the age-related pattern did a poor job of differentiating between cognitively-healthy older adults and those with probable AD. The findings from this paper are consistent with the multifactorial nature of cognitive aging.
Alzheimer’s disease; dementia; memory; multivariate analysis; neuroimaging; Scaled Subprofile Model
The accuracy of the cerebral blood flow (CBF) imaging methods in humans has been impeded by the partial volume effects (PVE), which are a consequence of the limited spatial resolution. Because of brain atrophy, PVE can be particularly problematic in imaging the elderly and can considerably overestimate the CBF difference with the young. The primary goal of this study was to separate the structural decline from the true CBF reduction in elderly. To this end, a PVE-correction algorithm was applied on the CBF images acquired with spin-echo EPI continuous arterial spin labeling MRI (voxel size = 3.4 × 3.4 × 8 mm3). Tissue-specific CBF images that were independent of voxels’ tissue fractional volume were obtained in elderly (N = 30) and young (N = 26); mean age difference was 43 years. Globally, PVE-corrected gray matter CBF was 88.2 ± 16.1 and 107.3±17.5 mL/100g min in elderly and young, respectively. The largest PVE contribution was found in the frontal lobe and accounted for an additional 10% and 12% increase in the age-related CBF difference between men and women, respectively. The GM-to-WM CBF ratios were found to be on average 3.5 in elderly and 3.9 in young. Whole brain voxelwise comparisons showed marked CBF decrease in anterior cingulate (bilateral), caudate (bilateral), cingulate gyrus (bilateral), cuneus (left), inferior frontal gyrus (left), insula (left), middle frontal gyrus (left), precuneus (bilateral), prefrontal cortex (bilateral), superior frontal gyrus (bilateral) in men and amygdala (bilateral), hypothalamus (left), hippocampus (bilateral), and middle frontal gyrus (right) in women.
aging; arterial spin labeling (ASL); brain atrophy; cerebral blood flow (CBF); partial volume effects (PVE); perfusion MRI
Multivariate analysis techniques for neuroimaging data have recently received increasing attention as they have many attractive features that cannot be easily realized by the more commonly used univariate, voxel-wise, techniques1,5,6,7,8,9. Multivariate approaches evaluate correlation/covariance of activation across brain regions, rather than proceeding on a voxel-by-voxel basis. Thus, their results can be more easily interpreted as a signature of neural networks. Univariate approaches, on the other hand, cannot directly address interregional correlation in the brain. Multivariate approaches can also result in greater statistical power when compared with univariate techniques, which are forced to employ very stringent corrections for voxel-wise multiple comparisons. Further, multivariate techniques also lend themselves much better to prospective application of results from the analysis of one dataset to entirely new datasets. Multivariate techniques are thus well placed to provide information about mean differences and correlations with behavior, similarly to univariate approaches, with potentially greater statistical power and better reproducibility checks. In contrast to these advantages is the high barrier of entry to the use of multivariate approaches, preventing more widespread application in the community. To the neuroscientist becoming familiar with multivariate analysis techniques, an initial survey of the field might present a bewildering variety of approaches that, although algorithmically similar, are presented with different emphases, typically by people with mathematics backgrounds. We believe that multivariate analysis techniques have sufficient potential to warrant better dissemination. Researchers should be able to employ them in an informed and accessible manner. The current article is an attempt at a didactic introduction of multivariate techniques for the novice. A conceptual introduction is followed with a very simple application to a diagnostic data set from the Alzheimer s Disease Neuroimaging Initiative (ADNI), clearly demonstrating the superior performance of the multivariate approach.
The purpose of this preliminary study was to examine cerebral blood flow (CBF) as measured by arterial spin labeling (ASL) in tissue classified as white matter hyperintensities (WMH), normal appearing white matter, and grey matter. Seventeen healthy older adults received structural and ASL MRI. Cerebral blood flow was derived for three tissue types: WMH, normal appearing white matter, and grey matter. Cerebral blood flow was lower in WMH areas relative to normal appearing white matter, which in turn, was lower than grey matter. Regions with consistently lower CBF across individuals were more likely to appear as WMH. Results are consistent with an emerging literature linking diminished regional perfusion with the risk of developing WMH.
white matter hyperintensities; arterial spin labeling; MRI
To capture patterns of normal age-associated atrophy, we previously used a multivariate statistical approach applied to voxel based morphometry that identified age-associated gray and white matter covariance networks (Brickman, et al. 2007). The current study sought to examine the stability of these patterns by forward applying the identified networks to an independent sample of neurologically healthy younger and older adults. Forty-two younger and 35 older adults were imaged with standard high-resolution structural magnetic resonance imaging (MRI). Individual images were spatially normalized and segmented into gray and white matter. Covariance patterns that were previously identified with scaled subprofile model analyses were prospectively applied to the current sample to identify to what degree the age-associated patterns were manifest. Older individuals were also assessed with a modified version of the Mini Mental State Examination (mMMSE). Gray matter covariance pattern expression discriminated between younger and older participants with high optimal sensitivity (100%) and specificity (90.5%). While the two groups differed in the degree of white matter pattern expression (t (75) = 5.26, p < 0.001), classification based on white matter expression was relatively low (sensitivity = 80% and specificity = 61.9%). Among older adults, chronological age was significantly associated with increased gray matter pattern expression (r (32) = 0.591, p < 0.001) but not with performance on the mMMSE (r (31) = −0.314, p = 0.085). However, gray matter pattern expression was significantly associated with performance on the mMMSE (r (31) = −0.405, p = 0.024). The findings suggest that the previously derived age-associated covariance pattern for gray matter is reliable and may provide information that is more functionally meaningful than chronological age.
normal aging; structural MRI; subprofile scaling model; principal components analysis; voxel based morphometry; cognition
Continuous arterial spin labeling (CASL) MRI was combined with multivariate analysis for detection of an Alzheimer's Disease (AD) related cerebral blood flow (CBF) covariance pattern. Whole brain resting CBF maps were obtained using spin echo, echo planar imaging (SE-EPI) CASL in patients with mild AD (n=12, age = 70.7± 8.7, 7 males, modified Mini-Mental State Examination (mMMS) = 38.7/57 ± 11.1) and age-matched healthy controls (HC) (n = 20; age = 72.1 ± 6.5, 8 males). A covariance pattern for which the mean expression was significantly higher (p < 0.0005) in AD than HC was identified containing Posterior Cingulate, Superior Temporal, Parahippocampal, and Fusiform gyri, as well as Thalamus, Insula, and Hippocampus. The results from this analysis were supplemented with those from the more standard, ROI and voxelwise, univariate techniques. All ROIs (17/hemisphere) showed significant decrease in CBF in AD [p < 0.001 for all ROIs, αcorrected = 0.05]. The area under the ROC curve for discriminating AD vs. HC was 0.97 and 0.94 for covariance pattern and gray matter ROI, respectively. Fewer areas of depressed CBF in AD were detected using voxelwise analysis [corrected, p < 0.05]. These areas were: Superior Temporal, Cingulate, Middle Temporal, Fusiform gyri, as well as Inferior Parietal Lobule and Precuneus. When tested on extensive split-half analysis to map out the replicability of both multivariate and univariate approaches, the expression of the pattern from multivariate analysis was superior to that of the univariate.
AD; CASL; CBF; covariance pattern; multivariate analysis; perfusion