A commonly carried allele of the obesity-related FTO gene is associated with reduced brain volume in the healthy elderly

A recently identified variant within the fat mass and obesity-associated (FTO) gene is carried by 46% of Western Europeans and is associated with an approximately 1.2 kg higher weight, on average, in adults and an approximately 1 cm greater waist circumference. With >1 billion overweight and 300 million obese persons worldwide, it is crucial to understand the implications of carrying this very common allele for the health of our aging population. FTO is highly expressed in the brain and elevated body mass index (BMI) is associated with brain atrophy, but it is unknown how the obesity-associated risk allele affects human brain structure. We therefore generated 3D maps of regional brain volume differences in 206 healthy elderly subjects scanned with MRI and genotyped as part of the Alzheimer's Disease Neuroimaging Initiative. We found a pattern of systematic brain volume deficits in carriers of the obesity-associated risk allele versus noncarriers. Relative to structure volumes in the mean template, FTO risk allele carriers versus noncarriers had an average brain volume difference of approximately 8% in the frontal lobes and 12% in the occipital lobes-these regions also showed significant volume deficits in subjects with higher BMI. These brain differences were not attributable to differences in cholesterol levels, hypertension, or the volume of white matter hyperintensities; which were not detectably higher in FTO risk allele carriers versus noncarriers. These brain maps reveal that a commonly carried susceptibility allele for obesity is associated with structural brain atrophy, with implications for the health of the elderly.

Sex and age differences in atrophic rates: an ADNI study with n=1368 MRI scans

We set out to determine factors that influence the rate of brain atrophy in 1-year longitudinal magnetic resonance imaging (MRI) data. With tensor-based morphometry (TBM), we mapped the 3-dimensional profile of progressive atrophy in 144 subjects with probable Alzheimer's disease (AD) (age: 76.5 +/- 7.4 years), 338 with amnestic mild cognitive impairment (MCI; 76.0 +/- 7.2), and 202 healthy controls (77.0 +/- 5.1), scanned twice, 1 year apart. Statistical maps revealed significant age and sex differences in atrophic rates. Brain atrophic rates were about 1%-1.5% faster in women than men. Atrophy was faster in younger than older subjects, most prominently in mild cognitive impairment, with a 1% increase in the rates of atrophy and 2% in ventricular expansion, for every 10-year decrease in age. TBM-derived atrophic rates correlated with reduced beta-amyloid and elevated tau levels (n = 363) at baseline, baseline and progressive deterioration in clinical measures, and increasing numbers of risk alleles for the ApoE4 gene. TBM is a sensitive, high-throughput biomarker for tracking disease progression in large imaging studies; sub-analyses focusing on women or younger subjects gave improved sample size requirements for clinical trials.

Atrophy progression in semantic dementia with asymmetric temporal involvement: a tensor-based morphometry study

We performed a longitudinal anatomical study to map the progression of gray matter atrophy in anatomically defined predominantly left (LTLV) and right (RTLV) temporal lobe variants of semantic dementia (SD). T1-weighted MRI scans were obtained at presentation and one-year follow-up from 13 LTLV, 6 RTLV, and 25 control subjects. Tensor-based morphometry (TBM) in SPM2 was applied to derive a voxel-wise estimation of regional tissue loss over time from the deformation field required to warp the follow-up scan to the presentation scan in each subject. When compared to controls, both LTLV and RTLV showed significant progression of gray matter atrophy not only within the temporal lobe most affected at presentation, but also in the controlateral temporal regions (p<0.05 FWE corrected). In LTLV, significant progression of volume loss also involved the ventromedial frontal and the left anterior insular regions. These results identified the anatomic substrates of the previously reported clinical evolution of LTLV and RTLV into a unique 'merged' clinical syndrome characterized by semantic and behavioral deficits and bilateral temporal atrophy.

Obesity is linked with lower brain volume in 700 AD and MCI patients

Obesity is associated with lower brain volumes in cognitively normal elderly subjects, but no study has yet investigated the effects of obesity on brain structure in patients with mild cognitive impairment (MCI) or Alzheimer's disease (AD). To determine if higher body mass index (BMI) is associated with brain volume deficits in cognitively impaired elderly subjects, we analyzed brain magnetic resonance imaging (MRI) scans of 700 MCI or AD patients from 2 different cohorts: the Alzheimer's Disease Neuroimaging Initiative (ADNI) and the Cardiovascular Health Study-Cognition Study (CHS-CS). Tensor-based morphometry (TBM) was used to create 3-dimensional maps of regional tissue excess or deficits in subjects with MCI (ADNI, n = 399; CHS-CS, n = 77) and AD (ADNI, n = 188; CHS, n = 36). In both AD and MCI groups, higher body mass index was associated with brain volume deficits in frontal, temporal, parietal, and occipital lobes; the atrophic pattern was consistent in both ADNI and CHS populations. Cardiovascular risk factors, especially obesity, should be considered as influencing brain structure in those already afflicted by cognitive impairment and dementia.

Depressive symptoms in mild cognitive impairment predict greater atrophy in Alzheimer's disease-related regions

BACKGROUND

Depression has been associated with higher conversion rates from mild cognitive impairment (MCI) to Alzheimer's disease (AD) and may be a marker of prodromal AD that can be used to identify individuals with MCI who are most likely to progress to AD. Thus, we examined the neuroanatomical changes associated with depressive symptoms in MCI.

METHODS

Two-hundred forty-three MCI subjects from the Alzheimer's Disease Neuroimaging Initiative who had brain magnetic resonance imaging scans at baseline and 2-year follow-up were classified into depressed (n = 44), nondepressed with other neuropsychiatric symptoms (n = 93), and no-symptom (NOSYMP; n = 106) groups based on the Neuropsychiatric Inventory Questionnaire. Tensor-based morphometry was used to create individual three-dimensional maps of 2-year brain changes that were compared between groups.

RESULTS

Depressed subjects had more frontal (p = .024), parietal (p = .030), and temporal (p = .038) white matter atrophy than NOSYMP subjects. Those whose depressive symptoms persisted over 2 years also had higher conversion to AD and more decline on measures of global cognition, language, and executive functioning compared with stable NOSYMP subjects. Nondepressed with other neuropsychiatric symptoms and NOSYMP groups exhibited no differences in rates of atrophy.

CONCLUSIONS

Depressive symptoms were associated with greater atrophy in AD-affected regions, increased cognitive decline, and higher rates of conversion to AD. Depression in individuals with MCI may be associated with underlying neuropathological changes, including prodromal AD, and may be a potentially useful clinical marker in identifying MCI patients who are most likely to progress to AD.

Structural consequences of diffuse traumatic brain injury: a large deformation tensor-based morphometry study

Traumatic brain injury (TBI) is one of the most common causes of long-term disability. Despite the importance of identifying neuropathology in individuals with chronic TBI, methodological challenges posed at the stage of inter-subject image registration have hampered previous voxel-based MRI studies from providing a clear pattern of structural atrophy after TBI. We used a novel symmetric diffeomorphic image normalization method to conduct a tensor-based morphometry (TBM) study of TBI. The key advantage of this method is that it simultaneously estimates an optimal template brain and topology preserving deformations between this template and individual subject brains. Detailed patterns of atrophies are then revealed by statistically contrasting control and subject deformations to the template space. Participants were 29 survivors of TBI and 20 control subjects who were matched in terms of age, gender, education, and ethnicity. Localized volume losses were found most prominently in white matter regions and the subcortical nuclei including the thalamus, the midbrain, the corpus callosum, the mid- and posterior cingulate cortices, and the caudate. Significant voxel-wise volume loss clusters were also detected in the cerebellum and the frontal/temporal neocortices. Volume enlargements were identified largely in ventricular regions. A similar pattern of results was observed in a subgroup analysis where we restricted our analysis to the 17 TBI participants who had no macroscopic focal lesions (total lesion volume >1.5 cm(3)). The current study confirms, extends, and partly challenges previous structural MRI studies in chronic TBI. By demonstrating that a large deformation image registration technique can be successfully combined with TBM to identify TBI-induced diffuse structural changes with greater precision, our approach is expected to increase the sensitivity of future studies examining brain-behavior relationships in the TBI population.

Brain atrophy over time in genetic and sporadic frontotemporal dementia: a study of 198 serial magnetic resonance images

BACKGROUND AND PURPOSE

The aim of our study was to determine the utility of longitudinal magnetic resonance imaging (MRI) measurements as potential biomarkers in the main genetic variants of frontotemporal dementia (FTD), including microtubule-associated protein tau (MAPT) and progranulin (GRN) mutations and C9ORF72 repeat expansions, as well as sporadic FTD.

METHODS

In this longitudinal study, 58 subjects were identified who had at least two MRI and MAPT mutations (n = 21), GRN mutations (n = 11), C9ORF72 repeat expansions (n = 11) or sporadic FTD (n = 15). A total of 198 serial MRI measurements were analyzed. Rates of whole brain atrophy were calculated using the boundary shift integral. Regional rates of atrophy were calculated using tensor-based morphometry. Sample size estimates were calculated.

RESULTS

Progressive brain atrophy was observed in all groups, with fastest rates of whole brain atrophy in GRN, followed by sporadic FTD, C9ORF72 and MAPT. All variants showed greatest rates in the frontal and temporal lobes, with parietal lobes also strikingly affected in GRN. Regional rates of atrophy across all lobes were greater in GRN compared to the other groups. C9ORF72 showed greater rates of atrophy in the left cerebellum and right occipital lobe than MAPT, and sporadic FTD showed greater rates in the anterior cingulate than C9ORF72 and MAPT. Sample size estimates were lowest using temporal lobe rates in GRN, ventricular rates in MAPT and C9ORF72, and whole brain rates in sporadic FTD.

CONCLUSION

These data support the utility of using rates of atrophy as outcome measures in future drug trials in FTD and show that different imaging biomarkers may offer advantages in the different variants of FTD.

Brain structure changes visualized in early- and late-onset blind subjects

We examined 3D patterns of volume differences in the brain associated with blindness, in subjects grouped according to early and late onset. Using tensor-based morphometry, we mapped volume reductions and gains in 16 early-onset (EB) and 16 late-onset (LB) blind adults (onset <5 and >14 years old, respectively) relative to 16 matched sighted controls. Each subject's structural MRI was fluidly registered to a common template. Anatomical differences between groups were mapped based on statistical analysis of the resulting deformation fields revealing profound deficits in primary and secondary visual cortices for both blind groups. Regions outside the occipital lobe showed significant hypertrophy, suggesting widespread compensatory adaptations. EBs but not LBs showed deficits in the splenium and the isthmus. Gains in the non-occipital white matter were more widespread in the EBs. These differences may reflect regional alterations in late neurodevelopmental processes, such as myelination, that continue into adulthood.

Reduced cortical volume and elevated astrocyte density in rats chronically treated with antipsychotic drugs-linking magnetic resonance imaging findings to cellular pathology

BACKGROUND

Increasing evidence suggests that antipsychotic drugs (APD) might affect brain structure directly, particularly the cerebral cortex. However, the precise anatomical loci of these effects and their underlying cellular basis remain unclear.

METHODS

With ex vivo magnetic resonance imaging in rats treated chronically with APDs, we used automated analysis techniques to map the regions that show maximal impact of chronic (8 weeks) treatment with either haloperidol or olanzapine on the rat cortex. Guided by these imaging findings, we undertook a focused postmortem investigation with stereology.

RESULTS

We identified decreases in the volume and thickness of the anterior cingulate cortex (ACC) after chronic APD treatment, regardless of the APD administered. Postmortem analysis confirmed these volumetric findings and demonstrated that chronic APD treatment had no effect on the total number of neurons or S100β+ astrocytes in the ACC. In contrast, an increase in the density of these cells was observed.

CONCLUSIONS

This study demonstrates region-specific structural effects of chronic APD treatment on the rat cortex, primarily but not exclusively localized to the ACC. At least in the rat, these changes are not due to a loss of either neurons or astrocytes and are likely to reflect a loss of neuropil. Although caution needs to be exerted when extrapolating results from animals to patients, this study highlights the power of this approach to link magnetic resonance imaging findings to their histopathological origins.

Surface fluid registration of conformal representation: application to detect disease burden and genetic influence on hippocampus

In this paper, we develop a new automated surface registration system based on surface conformal parameterization by holomorphic 1-forms, inverse consistent surface fluid registration, and multivariate tensor-based morphometry (mTBM). First, we conformally map a surface onto a planar rectangle space with holomorphic 1-forms. Second, we compute surface conformal representation by combining its local conformal factor and mean curvature and linearly scale the dynamic range of the conformal representation to form the feature image of the surface. Third, we align the feature image with a chosen template image via the fluid image registration algorithm, which has been extended into the curvilinear coordinates to adjust for the distortion introduced by surface parameterization. The inverse consistent image registration algorithm is also incorporated in the system to jointly estimate the forward and inverse transformations between the study and template images. This alignment induces a corresponding deformation on the surface. We tested the system on Alzheimer's Disease Neuroimaging Initiative (ADNI) baseline dataset to study AD symptoms on hippocampus. In our system, by modeling a hippocampus as a 3D parametric surface, we nonlinearly registered each surface with a selected template surface. Then we used mTBM to analyze the morphometry difference between diagnostic groups. Experimental results show that the new system has better performance than two publicly available subcortical surface registration tools: FIRST and SPHARM. We also analyzed the genetic influence of the Apolipoprotein E[element of]4 allele (ApoE4), which is considered as the most prevalent risk factor for AD. Our work successfully detected statistically significant difference between ApoE4 carriers and non-carriers in both patients of mild cognitive impairment (MCI) and healthy control subjects. The results show evidence that the ApoE genotype may be associated with accelerated brain atrophy so that our work provides a new MRI analysis tool that may help presymptomatic AD research.

Increasing power for voxel-wise genome-wide association studies: the random field theory, least square kernel machines and fast permutation procedures

Imaging traits are thought to have more direct links to genetic variation than diagnostic measures based on cognitive or clinical assessments and provide a powerful substrate to examine the influence of genetics on human brains. Although imaging genetics has attracted growing attention and interest, most brain-wide genome-wide association studies focus on voxel-wise single-locus approaches, without taking advantage of the spatial information in images or combining the effect of multiple genetic variants. In this paper we present a fast implementation of voxel- and cluster-wise inferences based on the random field theory to fully use the spatial information in images. The approach is combined with a multi-locus model based on least square kernel machines to associate the joint effect of several single nucleotide polymorphisms (SNP) with imaging traits. A fast permutation procedure is also proposed which significantly reduces the number of permutations needed relative to the standard empirical method and provides accurate small p-value estimates based on parametric tail approximation. We explored the relation between 448,294 single nucleotide polymorphisms and 18,043 genes in 31,662 voxels of the entire brain across 740 elderly subjects from the Alzheimer's disease neuroimaging initiative (ADNI). Structural MRI scans were analyzed using tensor-based morphometry (TBM) to compute 3D maps of regional brain volume differences compared to an average template image based on healthy elderly subjects. We find method to be more sensitive compared with voxel-wise single-locus approaches. A number of genes were identified as having significant associations with volumetric changes. The most associated gene was GRIN2B, which encodes the N-methyl-d-aspartate (NMDA) glutamate receptor NR2B subunit and affects both the parietal and temporal lobes in human brains. Its role in Alzheimer's disease has been widely acknowledged and studied, suggesting the validity of the approach. The various advantages over existing approaches indicate a great potential offered by this novel framework to detect genetic influences on human brains.

Multi-template tensor-based morphometry: application to analysis of Alzheimer's disease

In this paper methods for using multiple templates in tensor-based morphometry (TBM) are presented and compared to the conventional single-template approach. TBM analysis requires non-rigid registrations which are often subject to registration errors. When using multiple templates and, therefore, multiple registrations, it can be assumed that the registration errors are averaged and eventually compensated. Four different methods are proposed for multi-template TBM. The methods were evaluated using magnetic resonance (MR) images of healthy controls, patients with stable or progressive mild cognitive impairment (MCI), and patients with Alzheimer's disease (AD) from the ADNI database (N=772). The performance of TBM features in classifying images was evaluated both quantitatively and qualitatively. Classification results show that the multi-template methods are statistically significantly better than the single-template method. The overall classification accuracy was 86.0% for the classification of control and AD subjects, and 72.1% for the classification of stable and progressive MCI subjects. The statistical group-level difference maps produced using multi-template TBM were smoother, formed larger continuous regions, and had larger t-values than the maps obtained with single-template TBM.

Sex differences in brain structure in auditory and cingulate regions

We applied a new method to visualize the three-dimensional profile of sex differences in brain structure based on MRI scans of 100 young adults. We compared 50 men with 50 women, matched for age and other relevant demographics. As predicted, left hemisphere auditory and language-related regions were proportionally expanded in women versus men, suggesting a possible structural basis for the widely replicated sex differences in language processing. In men, primary visual, and visuo-spatial association areas of the parietal lobes were proportionally expanded, in line with prior reports of relative strengths in visuo-spatial processing in men. We relate these three-dimensional patterns to prior functional and structural studies, and to theoretical predictions based on nonlinear scaling of brain morphometry.

Relationship between structural brainstem and brain plasticity and lower-limb training in spinal cord injury: a longitudinal pilot study

Rehabilitative training has shown to improve significantly motor outcomes and functional walking capacity in patients with incomplete spinal cord injury (iSCI). However, whether performance improvements during rehabilitation relate to brain plasticity or whether it is based on functional adaptation of movement strategies remain uncertain. This study assessed training improvement-induced structural brain plasticity in chronic iSCI patients using longitudinal MRI. We used tensor-based morphometry (TBM) to analyze longitudinal brain volume changes associated with intensive virtual reality (VR)-augmented lower limb training in nine traumatic iSCI patients. The MRI data was acquired before and after a 4-week training period (16-20 training sessions). Before training, voxel-based morphometry (VBM) and voxel-based cortical thickness (VBCT) assessed baseline morphometric differences in nine iSCI patients compared to 14 healthy controls. The intense VR-augmented training of limb control improved significantly balance, walking speed, ambulation, and muscle strength in patients. Retention of clinical improvements was confirmed by the 3-4 months follow-up. In patients relative to controls, VBM revealed reductions of white matter volume within the brainstem and cerebellum and VBCT showed cortical thinning in the primary motor cortex. Over time, TBM revealed significant improvement-induced volume increases in the left middle temporal and occipital gyrus, left temporal pole and fusiform gyrus, both hippocampi, cerebellum, corpus callosum, and brainstem in iSCI patients. This study demonstrates structural plasticity at the cortical and brainstem level as a consequence of VR-augmented training in iSCI patients. These structural changes may serve as neuroimaging biomarkers of VR-augmented lower limb neurorehabilitation in addition to performance measures to detect improvements in rehabilitative training.

Apolipoprotein E genotype is associated with temporal and hippocampal atrophy rates in healthy elderly adults: a tensor-based morphometry study

Apolipoprotein E (ApoE) ε4 genotype is a strong risk factor for developing Alzheimer's disease (AD). Conversely, the presence of the ε2 allele has been shown to mitigate cognitive decline. Tensor-based morphometry (TBM), a novel computational approach for visualizing longitudinal progression of brain atrophy, was used to determine whether cognitively intact elderly participants with the ε4 allele demonstrate greater volume reduction than those with the ε2 allele. Healthy "younger elderly" volunteers, aged 55-75, were recruited from the community and hospital staff. They were evaluated with a baseline and follow-up MRI scan (mean scan interval = 4.72 years, s.d. = 0.55) and completed ApoE genotyping. Twenty-seven participants were included in the study of which 16 had the ε4 allele (all heterozygous ε3ε4 genotype) and 11 had the ε2ε3 genotype. The two groups did not differ significantly on any demographic characteristics and all subjects were cognitively "normal" at both baseline and follow-up time points. TBM was used to create 3D maps of local brain tissue atrophy rates for individual participants; these spatially detailed 3D maps were compared between the two ApoE groups. Regional analyses were performed and the ε4 group demonstrated significantly greater annual atrophy rates in the temporal lobes (p = 0.048) and hippocampus (p = 0.016); greater volume loss was observed in the right hippocampus than the left. TBM appears to be useful in tracking longitudinal progression of brain atrophy in cognitively asymptomatic adults. Possession of the ε4 allele is associated with greater temporal and hippocampal volume reduction well before the onset of cognitive deficits.

Characterizing aging in the human brainstem using quantitative multimodal MRI analysis

Aging is ubiquitous to the human condition. The MRI correlates of healthy aging have been extensively investigated using a range of modalities, including volumetric MRI, quantitative MRI (qMRI), and diffusion tensor imaging. Despite this, the reported brainstem related changes remain sparse. This is, in part, due to the technical and methodological limitations in quantitatively assessing and statistically analyzing this region. By utilizing a new method of brainstem segmentation, a large cohort of 100 healthy adults were assessed in this study for the effects of aging within the human brainstem in vivo. Using qMRI, tensor-based morphometry (TBM), and voxel-based quantification (VBQ), the volumetric and quantitative changes across healthy adults between 19 and 75 years were characterized. In addition to the increased R2* in substantia nigra corresponding to increasing iron deposition with age, several novel findings were reported in the current study. These include selective volumetric loss of the brachium conjunctivum, with a corresponding decrease in magnetization transfer and increase in proton density (PD), accounting for the previously described "midbrain shrinkage." Additionally, we found increases in R1 and PD in several pontine and medullary structures. We consider these changes in the context of well-characterized, functional age-related changes, and propose potential biophysical mechanisms. This study provides detailed quantitative analysis of the internal architecture of the brainstem and provides a baseline for further studies of neurodegenerative diseases that are characterized by early, pre-clinical involvement of the brainstem, such as Parkinson's and Alzheimer's diseases.

Comparing registration methods for mapping brain change using tensor-based morphometry

Measures of brain changes can be computed from sequential MRI scans, providing valuable information on disease progression for neuroscientific studies and clinical trials. Tensor-based morphometry (TBM) creates maps of these brain changes, visualizing the 3D profile and rates of tissue growth or atrophy. In this paper, we examine the power of different nonrigid registration models to detect changes in TBM, and their stability when no real changes are present. Specifically, we investigate an asymmetric version of a recently proposed Unbiased registration method, using mutual information as the matching criterion. We compare matching functionals (sum of squared differences and mutual information), as well as large-deformation registration schemes (viscous fluid and inverse-consistent linear elastic registration methods versus Symmetric and Asymmetric Unbiased registration) for detecting changes in serial MRI scans of 10 elderly normal subjects and 10 patients with Alzheimer's Disease scanned at 2-week and 1-year intervals. We also analyzed registration results when matching images corrupted with artificial noise. We demonstrated that the unbiased methods, both symmetric and asymmetric, have higher reproducibility. The unbiased methods were also less likely to detect changes in the absence of any real physiological change. Moreover, they measured biological deformations more accurately by penalizing bias in the corresponding statistical maps.

Midlife measurements of white matter microstructure predict subsequent regional white matter atrophy in healthy adults

OBJECTIVES

Although age-related brain changes are becoming better understood, midlife patterns of change are still in need of characterization, and longitudinal studies are lacking. The aim of this study was to determine if baseline fractional anisotropy (FA), obtained from diffusion tensor imaging (DTI) predicts volume change over a 4-year interval.

EXPERIMENTAL DESIGN

Forty-four cognitively healthy middle-age adults underwent baseline DTI and longitudinal T1-weighted magnetic resonance imaging. Tensor-based morphometry methods were used to evaluate volume change over time. FA values were extracted from regions of interest that included the cingulum, entorhinal white matter, and the genu and splenium of the corpus callosum. Baseline FA was used as a predictor variable, whereas gray and white matter atrophy rates as indexed by Tensor-based morphometry were the dependent variables.

PRINCIPAL OBSERVATIONS

Over a 4-year period, participants showed significant contraction of white matter, especially in frontal, temporal, and cerebellar regions (P < 0.05, corrected for multiple comparisons). Baseline FA in entorhinal white matter, genu, and splenium was associated with longitudinal rates of atrophy in regions that included the superior longitudinal fasciculus, anterior corona radiata, temporal stem, and white matter of the inferior temporal gyrus (P < 0.001, uncorrected for multiple comparisons).

CONCLUSIONS

Brain change with aging is characterized by extensive shrinkage of white matter. Baseline white matter microstructure as indexed by DTI was associated with some of the observed regional volume loss. The findings suggest that both white matter volume loss and microstructural alterations should be considered more prominently in models of aging and neurodegenerative diseases.

Effect of cocaine on structural changes in brain: MRI volumetry using tensor-based morphometry

Magnetic resonance imaging (MRI) was performed in cocaine-dependent subjects to determine the structural changes in brain compared to non-drug using controls. Cocaine-dependent subjects and controls were carefully screened to rule out brain pathology of undetermined origin. Magnetic resonance images were analyzed using tensor-based morphometry (TBM) and voxel-based morphometry (VBM) without and with modulation to adjust for volume changes during normalization. For TBM analysis, unbiased atlases were generated using two different inverse consistent and diffeomorphic nonlinear registration techniques. Two different control groups were used for generating unbiased atlases. Independent of the nonlinear registration technique and normal cohorts used for creating the unbiased atlases, our analysis failed to detect any statistically significant effect of cocaine on brain volumes. These results show that cocaine-dependent subjects do not show differences in regional brain volumes compared to non-drug using controls.

Comparison of In Vivo and Ex Vivo MRI for the Detection of Structural Abnormalities in a Mouse Model of Tauopathy

With increasingly large numbers of mouse models of human disease dedicated to MRI studies, compromises between in vivo and ex vivo MRI must be fully understood in order to inform the choice of imaging methodology. We investigate the application of high resolution in vivo and ex vivo MRI, in combination with tensor-based morphometry (TBM), to uncover morphological differences in the rTg4510 mouse model of tauopathy. The rTg4510 mouse also offers a novel paradigm by which the overexpression of mutant tau can be regulated by the administration of doxycycline, providing us with a platform on which to investigate more subtle alterations in morphology with morphometry. Both in vivo and ex vivo MRI allowed the detection of widespread bilateral patterns of atrophy in the rTg4510 mouse brain relative to wild-type controls. Regions of volume loss aligned with neuronal loss and pathological tau accumulation demonstrated by immunohistochemistry. When we sought to investigate more subtle structural alterations in the rTg4510 mice relative to a subset of doxycycline-treated rTg4510 mice, ex vivo imaging enabled the detection of more regions of morphological brain changes. The disadvantages of ex vivo MRI may however mitigate this increase in sensitivity: we observed a 10% global shrinkage in brain volume of the post-mortem tissues due to formalin fixation, which was most notable in the cerebellum and olfactory bulbs. However, many central brain regions were not adversely affected by the fixation protocol, perhaps due to our “in-skull” preparation. The disparity between our TBM findings from in vivo and ex vivo MRI underlines the importance of appropriate study design, given the trade-off between these two imaging approaches. We support the utility of in vivo MRI for morphological phenotyping of mouse models of disease; however, for subtler phenotypes, ex vivo offers enhanced sensitivity to discrete morphological changes.

Structural and Functional Reorganization of the Brain in Migraine Without Aura

It remains unknown whether migraine headache has a progressive component in its pathophysiology. Quantitative MRI may provide valuable insight into abnormal changes in the migraine interictum and assist in identifying disrupted brain networks. We carried out a data-driven study of structural integrity and functional connectivity of the resting brain in migraine without aura. MRI scanning was performed in 36 patients suffering from episodic migraine without aura and 33 age-matched healthy subjects. Voxel-wise analysis of regional brain volume was performed by registration of the T1-weighted MRI scans into a common study brain template using the tensor-based morphometry (TBM) method. Changes in functional synchronicity of the brain networks were assessed using probabilistic independent component analysis (ICA). TBM revealed that migraine is associated with reduced volume of the medial prefrontal cortex (mPFC). Among 375 functional brain networks, resting-state connectivity was decreased between two components spanning the visual cortex, posterior insula, and parietal somatosensory cortex. Our study reveals structural and functional alterations of the brain in the migraine interictum that may stem from underlying disease risk factors and the "silent" aura phenomenon. Longitudinal studies will be needed to investigate whether interictal brain changes are progressive and associated with clinical disease trajectories.

Persistent Homology in Sparse Regression and Its Application to Brain Morphometry

Sparse systems are usually parameterized by a tuning parameter that determines the sparsity of the system. How to choose the right tuning parameter is a fundamental and difficult problem in learning the sparse system. In this paper, by treating the the tuning parameter as an additional dimension, persistent homological structures over the parameter space is introduced and explored. The structures are then further exploited in drastically speeding up the computation using the proposed soft-thresholding technique. The topological structures are further used as multivariate features in the tensor-based morphometry (TBM) in characterizing white matter alterations in children who have experienced severe early life stress and maltreatment. These analyses reveal that stress-exposed children exhibit more diffuse anatomical organization across the whole white matter region.

AGREEMENT BETWEEN THE WHITE MATTER CONNECTIVITY BASED ON THE TENSOR-BASED MORPHOMETRY AND THE VOLUMETRIC WHITE MATTER PARCELLATIONS BASED ON DIFFUSION TENSOR IMAGING

We are interested in investigating white matter connectivity using a novel computational framework that does not use diffusion tensor imaging (DTI) but only uses T1-weighted magnetic resonance imaging. The proposed method relies on correlating Jacobian determinants across different voxels based on the tensor-based morphometry (TBM) framework. In this paper, we show agreement between the TBM-based white matter connectivity and the DTI-based white matter atlas. As an application, altered white matter connectivity in a clinical population is determined.

Neuropsychological and Neuroanatomical Correlates of the Social Norms Questionnaire in Frontotemporal Dementia Versus Alzheimer's Disease

Traditional neuropsychological batteries may not distinguish early behavioral variant frontotemporal dementia (bvFTD) from Alzheimer's disease (AD) without the inclusion of a social behavioral measure. We compared 33 participants, 15 bvFTD, and 18 matched patients with early-onset AD (eAD), on the Social Norms Questionnaire (SNQ), neuropsychological tests and 3-dimensional T1-weighted magnetic resonance imaging (MRI). The analyses included correlations of SNQ results (total score, overendorsement or "overadhere" errors, and violations or "break" errors) with neuropsychological results and tensor-based morphometry regions of interest. Patients with BvFTD had significantly lower SNQ total scores and higher overadhere errors than patients with eAD. On neuropsychological measures, the SNQ total scores correlated significantly with semantic knowledge and the overadhere subscores with executive dysfunction. On MRI analysis, the break subscores significantly correlated with lower volume of lateral anterior temporal lobes (aTL). The results also suggest that endorsement of social norm violations corresponds to the role of the right aTL in social semantic knowledge.

Rhesus Macaque Brain Developmental Trajectory: A Longitudinal Analysis Using Tensor-Based Structural Morphometry and Diffusion Tensor Imaging

The typical developmental trajectory of brain structure among nonhuman primates (NHPs) remains poorly understood. In this study, we characterized the normative trajectory of developmental change among a cohort of rhesus monkeys (n = 28), ranging in age from 2 to 22 months, using structural MRI datasets that were longitudinally acquired every 3-4 months. We hypothesized that NHP-specific transient intracranial volume decreases reported during late infancy would be part of the typical developmental process, which is driven by volumetric contraction of gray matter in primary functional areas. To this end, we performed multiscale analyses from the whole brain to voxel level, characterizing regional heterogeneity, hemispheric asymmetry, and sexual dimorphism in developmental patterns. The longitudinal trajectory of brain development was explained by three different regional volumetric growth patterns (exponentially decreasing, undulating, and linearly increasing), which resulted in developmental brain volume curves with transient brain volumetric decreases. White matter (WM) fractional anisotropy increased with age, corresponding to WM volume increases, while mean diffusivity (MD) showed biphasic patterns. The longitudinal trajectory of brain development in young rhesus monkeys follows typical maturation patterns seen in humans, but regional volumetric and MD changes are more dynamic in rhesus monkeys compared with humans, with marked decreases followed by "rebound-like" increases.