Christian G. Habeck

Multivariate and univariate neuroimaging biomarkers of Alzheimer's disease

We performed univariate and multivariate discriminant analysis of FDG-PET scans to evaluate their ability to identify Alzheimers disease (AD). FDG-PET scans came from two sources: 17 AD patients and 33 healthy elderly controls were scanned at the University of Michigan; 102 early AD patients and 20 healthy elderly controls were scanned at the Technical University of Munich, Germany. We selected a derivation sample of 20 AD patients and 20 healthy controls matched on age with the remainder divided into 5 replication samples. The sensitivity and specificity of diagnostic AD-markers and threshold criteria from the derivation sample were determined in the replication samples. Although both univariate and multivariate analyses produced markers with high classification accuracy in the derivation sample, the multivariate markers diagnostic performance in the replication samples was superior. Further, supplementary analysis showed its performance to be unaffected by the loss of key regions. Multivariate measures of AD utilize the covariance structure of imaging data and provide complementary, clinically relevant information that may be superior to univariate measures.

Reduction in cerebral blood flow in areas appearing as white matter hyperintensities on magnetic resonance imaging

The purpose of this 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.

Multivariate and univariate analysis of continuous arterial spin labeling perfusion MRI in Alzheimer's disease

Continuous arterial spin labeling (CASL) magnetic resonance imaging (MRI) was combined with multivariate analysis for detection of an Alzheimers 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 years, 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 years, 8 males). A covariance pattern for which the mean expression was significantly higher (P<0.0005) in AD than in 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, region of interest (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 versus 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.

A New Approach to Spatial Covariance Modeling of Functional Brain Imaging Data: Ordinal Trend Analysis

In neuroimaging studies of human cognitive abilities, brain activation patterns that include regions that are strongly interactive in response to experimental task demands are of particular interest. Among the existing network analyses, partial least squares (PLS; McIntosh, 1999; McIntosh, Bookstein, Haxby, & Grady, 1996) has been highly successful, particu-larly in identifying group differences in regional functional connectivity, including differences as diverse as those associated with states of aware-ness and normal aging. However, we address the need for a within-group model that identifies patterns of regional functional connectivity that ex-hibit sustained activity across graduated changes in task parameters. For example, predictions of sustained connectivity are commonplace in stud-ies of cognition that involve a series of tasks over which task difficulty increases (Baddeley, 2003). We designed ordinal trend analysis (OrT) to identify activation patterns that increase monotonically in their expres-sion as the experimental task parameter increases, while the correlative relationships between brain regions remain constant. Of specific interest are patterns that express positive ordinal trends on a subject-by-subject basis. A unique feature of OrT is that it recovers information about func-tional connectivity based solely on experimental design variables. In par-ticular, there is no requirement by OrT to provide either a quantitative model of the uncertain relationship between functional brain circuitry and subject variables (e.g., task performance and IQ) or partial informa-tion about the regions that are functionally connected. In this letter, we provide a step-by-step recipe of the computations performed in the new OrT analysis, including a description of the inferential statistical meth-ods applied. Second, we describe applications of OrT to an event-related fMRI study of verbal working memory and H2 15 O-PET study of visuo-motor learning. In sum, OrT has potential applications to not only studies of young adults and their cognitive abilities, but also studies of normal aging and neurological and psychiatric disease.

APOE related alterations in cerebral activation even at college age

Background: Associations between the APOE genotype and various medical conditions have been documented at a very young age. The association between the APOE genotype and cognitive performance varies at different ages. APOE related changes in brain activation have been recently reported for middle aged and elderly subjects. Objective: To explore APOE related alterations during cognitive activation in a population of young adults. Methods: Using H215O positron emission tomography (PET), imaging was carried out in 20 healthy young adults (age 19 to 28 years; four ε4 carriers and 16 non-ε4 carriers) during a non-verbal memory task. Voxel-wise multiple regression analyses were undertaken, with the activation difference PET counts as the dependent variable and the APOE genotype as the independent variable. Results: Brain regions were identified where ε4 carriers showed significantly lower or higher activation than non-carriers. Conclusions: The results suggest that APOE dependent modulation of cerebral flow may be present even at a young age. This may reflect an APOE related physiological heterogeneity which may or may not predispose to brain disease in the ensuing decades or, less likely, the effect of very early Alzheimer’s disease related pathological changes.

Covariance PET patterns in early Alzheimer's disease and subjects with cognitive impairment but no dementia: utility in group discrimination and correlations with functional performance.

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 Alzheimers disease (AD) or cognitive impairment. Nonquantitative H2(15)O 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 Noxel-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.

Increased sensorimotor network activity in DYT1 dystonia: a functional imaging study

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 (15)Oxygen-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.

Multivariate Data Analysis for Neuroimaging Data: Overview and Application to Alzheimer’s Disease

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.

Relation of cognitive reserve and task performance to expression of regional covariance networks in an event-related fMRI study of nonverbal memory

Cognitive reserve (CR) has been established as a mechanism that can explain individual differences in the clinical manifestation of neural changes associated with aging or neurodegenerative diseases. CR may represent individual differences in how tasks are processed (i.e., differences in the component processes), or in the underlying neural circuitry (of the component processes). CR may be a function of innate differences or differential life experiences. To investigate to what extent CR can account for individual differences in brain activation and task performance, we used fMRI to image healthy young individuals while performing a nonverbal memory task. We used IQ estimates as a proxy for CR. During both study and test phase of the task, we identified regional covariance patterns whose change in subject expression across two task conditions correlated with performance and CR. Common brain regions in both activation patterns were suggestive of a brain network previously found to underlie overt and covert shifts of spatial attention. After partialing out the influence of task performance variables, this network still showed an association with the CR, i.e., there were reserve-related physiological differences that presumably would persist were there no subject differences in task performance. This suggests that this network may represent a neural correlate of CR.

Imaging markers of mild cognitive impairment: Multivariate analysis of CBF SPECT

This study aimed to investigate cross-sectional and longitudinal changes of regional cerebral blood flow (rCBF) in preclinical dementia using single photon emission computed tomography (SPECT). SPECT and cognitive function were investigated in 39 mild cognitive impairment (MCI) subjects and 20 age-matched controls. All subjects were followed longitudinally 19 months on average, 16 MCI subjects progressed to Alzheimers disease (AD), who were retrospectively defined as progressive mild cognitive impairment (PMCI) at baseline and 23 MCI subjects remained stable and were defined as stable mild cognitive impairment (SMCI) at baseline. SPECT was performed both at the initial investigation and at follow-up. Image data were analyzed using multivariate analysis, SPM and volume of interest (VOI)-based analysis. Significant covariate patterns were derived, which differentiate among PMCI, SMCI and controls at baseline as well as describe the longitudinal progression of PMCI. The combined SPECT and neuropsychology increased the diagnostic accuracy of PMCI at baseline. SPECT and neuropsychological testing can be used objectively for both baseline diagnosis and to monitor changes in brain function during very early AD.