Brain structure in movement disorders: a neuroimaging perspective.

Purpose of review: An overview of recent advances in structural neuroimaging and their impact on movement disorders research is presented. Recent findings: Novel developments in computational neuroanatomy and improvements in magnetic resonance image quality have brought further insight into the pathophysiology of movement disorders. Sophisticated automated techniques allow for sensitive and reliable in-vivo differentiation of phenotype/genotype related traits and their interaction even at presymptomatic stages of disease. Summary: Voxel-based morphometry consistently demonstrates well defined patterns of brain structure changes in movement disorders. Advanced stages of idiopathic Parkinson's disease are characterized by grey matter volume decreases in basal ganglia. Depending on the presence of cognitive impairment, volume changes are reported in widespread cortical and limbic areas. Atypical Parkinsonian syndromes still pose a challenge for accurate morphometry-based classification, especially in early stages of disease progression. Essential tremor has been mainly associated with thalamic and cerebellar changes. Studies on preclinical Huntington's disease show progressive loss of tissue in the caudate and cortical thinning related to distinct motor and cognitive phenotypes. Basal ganglia volume in primary dystonia reveals an interaction between genotype and phenotype such that brain structure changes are modulated by the presence of symptoms under the influence of genetic factors. Tics in Tourette's syndrome correlate with brain structure changes in limbic, motor and associative fronto-striato-parietal circuits. Computational neuroanatomy provides useful tools for in-vivo assessment of brain structure in movement disorders, allowing for accurate classification in early clinical stages as well as for monitoring therapy effects and/or disease progression.

Structural brain plasticity in Parkinson's disease induced by balance training.

We investigated morphometric brain changes in patients with Parkinson's disease (PD) that are associated with balance training. A total of 20 patients and 16 healthy matched controls learned a balance task over a period of 6 weeks. Balance testing and structural magnetic resonance imaging were performed before and after 2, 4, and 6 training weeks. Balance performance was re-evaluated after ∼20 months. Balance training resulted in performance improvements in both groups. Voxel-based morphometry revealed learning-dependent gray matter changes in the left hippocampus in healthy controls. In PD patients, performance improvements were correlated with gray matter changes in the right anterior precuneus, left inferior parietal cortex, left ventral premotor cortex, bilateral anterior cingulate cortex, and left middle temporal gyrus. Furthermore, a TIME × GROUP interaction analysis revealed time-dependent gray matter changes in the right cerebellum. Our results highlight training-induced balance improvements in PD patients that may be associated with specific patterns of structural brain plasticity. In summary, we provide novel evidence for the capacity of the human brain to undergo learning-related structural plasticity even in a pathophysiological disease state such as in PD.

Altered brain mechanisms of emotion processing in pre-manifest Huntington's disease.

Huntington's disease is an inherited neurodegenerative disease that causes motor, cognitive and psychiatric impairment, including an early decline in ability to recognize emotional states in others. The pathophysiology underlying the earliest manifestations of the disease is not fully understood; the objective of our study was to clarify this. We used functional magnetic resonance imaging to investigate changes in brain mechanisms of emotion recognition in pre-manifest carriers of the abnormal Huntington's disease gene (subjects with pre-manifest Huntington's disease): 16 subjects with pre-manifest Huntington's disease and 14 control subjects underwent 1.5 tesla magnetic resonance scanning while viewing pictures of facial expressions from the Ekman and Friesen series. Disgust, anger and happiness were chosen as emotions of interest. Disgust is the emotion in which recognition deficits have most commonly been detected in Huntington's disease; anger is the emotion in which impaired recognition was detected in the largest behavioural study of emotion recognition in pre-manifest Huntington's disease to date; and happiness is a positive emotion to contrast with disgust and anger. Ekman facial expressions were also used to quantify emotion recognition accuracy outside the scanner and structural magnetic resonance imaging with voxel-based morphometry was used to assess the relationship between emotion recognition accuracy and regional grey matter volume. Emotion processing in pre-manifest Huntington's disease was associated with reduced neural activity for all three emotions in partially separable functional networks. Furthermore, the Huntington's disease-associated modulation of disgust and happiness processing was negatively correlated with genetic markers of pre-manifest disease progression in distributed, largely extrastriatal networks. The modulated disgust network included insulae, cingulate cortices, pre- and postcentral gyri, precunei, cunei, bilateral putamena, right pallidum, right thalamus, cerebellum, middle frontal, middle occipital, right superior and left inferior temporal gyri, and left superior parietal lobule. The modulated happiness network included postcentral gyri, left caudate, right cingulate cortex, right superior and inferior parietal lobules, and right superior frontal, middle temporal, middle occipital and precentral gyri. These effects were not driven merely by striatal dysfunction. We did not find equivalent associations between brain structure and emotion recognition, and the pre-manifest Huntington's disease cohort did not have a behavioural deficit in out-of-scanner emotion recognition relative to controls. In addition, we found increased neural activity in the pre-manifest subjects in response to all three emotions in frontal regions, predominantly in the middle frontal gyri. Overall, these findings suggest that pathophysiological effects of Huntington's disease may precede the development of overt clinical symptoms and detectable cerebral atrophy.

In vivo assessment of use-dependent brain plasticity--beyond the "one trick pony" imaging strategy.

This article has been written as a comment to Dr Thomas and Dr Baker's article "Teaching an adult brain new tricks: A critical review of evidence for training-dependent structural plasticity in humans". We deliberately expand on the key question about the biological substrates underlying use-dependent brain plasticity rather than reiterating the authors' main points of criticism already addressed in more general way by previous publications in the field. The focus here is on the following main issues: i) controversial brain plasticity findings in voxel-based morphometry studies are partially due to the strong dependency of the widely used T1-weighted imaging protocol on varying magnetic resonance contrast contributions; ii) novel concepts in statistical analysis allow one to directly infer topological specificity of structural brain changes associated with plasticity. We conclude that iii) voxel-based quantification of relaxometry derived parameter maps could provide a new perspective on use-dependent plasticity by characterisation of brain tissue property changes beyond the estimation of volume and cortical thickness changes. In the relevant sections we respond to the concerns raised by Dr Thomas and Dr Baker from the perspective of the proposed data acquisition and analysis strategy.

An evaluation of volume-based morphometry for prediction of mild cognitive impairment and Alzheimer's disease.

Voxel-based morphometry from conventional T1-weighted images has proved effective to quantify Alzheimer's disease (AD) related brain atrophy and to enable fairly accurate automated classification of AD patients, mild cognitive impaired patients (MCI) and elderly controls. Little is known, however, about the classification power of volume-based morphometry, where features of interest consist of a few brain structure volumes (e.g. hippocampi, lobes, ventricles) as opposed to hundreds of thousands of voxel-wise gray matter concentrations. In this work, we experimentally evaluate two distinct volume-based morphometry algorithms (FreeSurfer and an in-house algorithm called MorphoBox) for automatic disease classification on a standardized data set from the Alzheimer's Disease Neuroimaging Initiative. Results indicate that both algorithms achieve classification accuracy comparable to the conventional whole-brain voxel-based morphometry pipeline using SPM for AD vs elderly controls and MCI vs controls, and higher accuracy for classification of AD vs MCI and early vs late AD converters, thereby demonstrating the potential of volume-based morphometry to assist diagnosis of mild cognitive impairment and Alzheimer's disease.

Influence of magnetic field strength and image registration strategy on voxel-based morphometry in a study of Alzheimer's disease.

Multi-centre data repositories like the Alzheimer's Disease Neuroimaging Initiative (ADNI) offer a unique research platform, but pose questions concerning comparability of results when using a range of imaging protocols and data processing algorithms. The variability is mainly due to the non-quantitative character of the widely used structural T1-weighted magnetic resonance (MR) images. Although the stability of the main effect of Alzheimer's disease (AD) on brain structure across platforms and field strength has been addressed in previous studies using multi-site MR images, there are only sparse empirically-based recommendations for processing and analysis of pooled multi-centre structural MR data acquired at different magnetic field strengths (MFS). Aiming to minimise potential systematic bias when using ADNI data we investigate the specific contributions of spatial registration strategies and the impact of MFS on voxel-based morphometry in AD. We perform a whole-brain analysis within the framework of Statistical Parametric Mapping, testing for main effects of various diffeomorphic spatial registration strategies, of MFS and their interaction with disease status. Beyond the confirmation of medial temporal lobe volume loss in AD, we detect a significant impact of spatial registration strategy on estimation of AD related atrophy. Additionally, we report a significant effect of MFS on the assessment of brain anatomy (i) in the cerebellum, (ii) the precentral gyrus and (iii) the thalamus bilaterally, showing no interaction with the disease status. We provide empirical evidence in support of pooling data in multi-centre VBM studies irrespective of disease status or MFS.

Genotype-phenotype interactions in primary dystonias revealed by differential changes in brain structure.

Our understanding of how genotype determines phenotype in primary dystonia is limited. Familial young-onset primary dystonia is commonly due to the DYT1 gene mutation. A critical question, given the 30% penetrance of clinical symptoms in DYT1 mutation carriers, is why the same genotype leads to differential clinical expression and whether non-DYT1 adult-onset primary dystonia, with and without family history share pathophysiological mechanisms with DYT1 dystonia. This study examines the relationship between dystonic phenotype and the DYT1 gene mutation by monitoring whole-brain structure using voxel-based morphometry. We acquired magnetic resonance imaging data of symptomatic and asymptomatic DYT1 mutation carriers, of non-DYT1 primary dystonia patients, with and without family history and control subjects with normal DYT1 alleles. By crossing the factors genotype and phenotype we demonstrate a significant interaction in terms of brain anatomy confined to the basal ganglia bilaterally. The explanation for this effect differs according to both gene and dystonia status: non-DYT1 adult-onset dystonia patients and asymptomatic DYT1 carriers have significantly larger basal ganglia compared to healthy subjects and symptomatic DYT1 mutation carriers. There is a significant negative correlation between severity of dystonia and basal ganglia size in DYT1 mutation carriers. We propose that differential pathophysiological and compensatory mechanisms lead to brain structure changes in non-DYT1 primary adult-onset dystonias and DYT1 gene carriers. Given the range of age of onset, there may be differential genetic modulation of brain development that in turn determines clinical expression. Alternatively, a DYT1 gene dependent primary defect of motor circuit development may lead to stress-induced remodelling of the basal ganglia and hence dystonia.

Advances in MRI-based computational neuroanatomy: from morphometry to in-vivo histology.

PURPOSE OF REVIEW: Current computational neuroanatomy based on MRI focuses on morphological measures of the brain. We present recent methodological developments in quantitative MRI (qMRI) that provide standardized measures of the brain, which go beyond morphology. We show how biophysical modelling of qMRI data can provide quantitative histological measures of brain tissue, leading to the emerging field of in-vivo histology using MRI (hMRI). RECENT FINDINGS: qMRI has greatly improved the sensitivity and specificity of computational neuroanatomy studies. qMRI metrics can also be used as direct indicators of the mechanisms driving observed morphological findings. For hMRI, biophysical models of the MRI signal are being developed to directly access histological information such as cortical myelination, axonal diameters or axonal g-ratio in white matter. Emerging results indicate promising prospects for the combined study of brain microstructure and function. SUMMARY: Non-invasive brain tissue characterization using qMRI or hMRI has significant implications for both research and clinics. Both approaches improve comparability across sites and time points, facilitating multicentre/longitudinal studies and standardized diagnostics. hMRI is expected to shed new light on the relationship between brain microstructure, function and behaviour, both in health and disease, and become an indispensable addition to computational neuroanatomy.

Linking brain structure and activation in the temporoparietal junction to explain the neurobiology of human altruism

Human altruism shaped our evolutionary history and pervades social and political life. There are, however, enormous individual differences in altruism. Some people are almost completely selfish, while others display strong altruism, and the factors behind this heterogeneity are only poorly understood. We examine the neuroanatomical basis of these differences with voxel-based morphometry and show that gray matter (GM) volume in the right temporoparietal junction (TPJ) is strongly associated with both individuals' altruism and the individual-specific conditions under which this brain region is recruited during altruistic decision making. Thus, individual differences in GM volume in TPJ not only translate into individual differences in the general propensity to behave altruistically, but they also create a link between brain structure and brain function by indicating the conditions under which individuals are likely to recruit this region when they face a conflict between altruistic and selfish acts.

Effects of Obesity and Weight Loss Following Bariatric Surgery on Brain Function, Structural Integrity and Metabolism

Obesity is one of the key challenges to health care system worldwide and its prevalence is estimated to rise to pandemic proportions. Numerous adverse health effects follow with increasing body weight, including increased risk of hypertension, diabetes, hypercholesterolemia, musculoskeletal pain and cancer. Current evidence suggests that obesity is associated with altered cerebral reward circuit functioning and decreased inhibitory control over appetitive food cues. Furthermore, obesity causes adverse shifts in metabolism and loss of structural integrity within the brain. Prior cross-sectional studies do not allow delineating which of these cerebral changes are recoverable after weight loss. We compared morbidly obese subjects with healthy controls to unravel brain changes associated with obesity. Bariatric surgery was used as an intervention to study which cerebral changes are recoverable after weight loss. In Study I we employed functional magnetic resonance imaging (fMRI) to detect the brain basis of volitional appetite control and its alterations in obesity. In Studies II-III we used diffusion tensor imaging (DTI) and voxel-based morphometry (VBM) to quantify the effects of obesity and the effects of weight loss on structural integrity of the brain. In study IV we used positron emission tomography (PET) with [18F]-FDG in fasting state and during euglycemic hyperinsulinemia to quantify effects of obesity and weight loss on brain glucose uptake. The fMRI experiment revealed that a fronto-parietal network is involved in volitional appetite control. Obese subjects had lower medial frontal and dorsal striatal brain activity during cognitive appetite control and increased functional connectivity within the appetite control circuit. Obese subjects had initially lower grey matter and white matter densities than healthy controls in VBM analysis and loss of integrity in white matter tracts as measured by DTI. They also had initially elevated glucose metabolism under insulin stimulation but not in fasting state. After the weight loss following bariatric surgery, obese individuals’ brain volumes recovered and the insulin-induced increase in glucose metabolism was attenuated. In conclusion, obesity is associated with altered brain function, coupled with loss of structural integrity and elevated glucose metabolism, which are likely signs of adverse health effects to the brain. These changes are reversed by weight loss after bariatric surgery, implicating that weight loss has a causal role on these adverse cerebral changes. Altogether these findings suggest that weight loss also promotes brain health.Key words: brain, obesity, bariatric surgery, appetite control, structural magnetic resonance

Grey matter volume in the cerebellum is related to processing of grammatical rules in a second language: a structural Voxel-Based Morphometry study

The experience of learning and using a second language (L2) has been shown to affect the grey matter (GM) structure of the brain. Importantly, GM density in several cortical and subcortical areas has been shown to be related to performance in L2 tasks. Here we show that bilingualism can lead to increased GM volume in the cerebellum, a structure that has been related to the processing of grammatical rules. Additionally, the cerebellar GM volume of highly proficient L2 speakers is correlated to their performance in a task tapping on grammatical processing in a L2, demonstrating the importance of the cerebellum for the establishment and use of grammatical rules in a L2.

New structural brain imaging endophenotype in bipolar disorder

Neuroimaging studies suggest anterior-limbic structural brain abnormalities in patients with bipolar disorder (BD), but few studies have shown these abnormalities in unaffected but genetically liable family members. In this study, we report morphometric correlates of genetic risk for BD using voxel-based morphometry. In 35 BD type I (BD-I) patients, 20 unaffected first-degree relatives (UAR) of BD patients and 40 healthy control subjects underwent 3 T magnetic resonance scanner imaging. Preprocessing of images used DARTEL (diffeomorphic anatomical registration through exponentiated lie algebra) for voxel-based morphometry in SPM8 (Wellcome Department of Imaging Neuroscience, London, UK). The whole-brain analysis revealed that the gray matter (GM) volumes of the left anterior insula and right inferior frontal gyrus showed a significant main effect of diagnosis. Multiple comparison analysis showed that the BD-I patients and the UAR subjects had smaller left anterior insular GM volumes compared with the healthy subjects, the BD-I patients had smaller right inferior frontal gyrus compared with the healthy subjects. For white matter (WM) volumes, there was a significant main effect of diagnosis for medial frontal gyrus. The UAR subjects had smaller right medial frontal WM volumes compared with the healthy subjects. These findings suggest that morphometric brain abnormalities of the anterior-limbic neural substrate are associated with family history of BD, which may give insight into the pathophysiology of BD, and be a potential candidate as a morphological endophenotype of BD. Molecular Psychiatry (2012) 17, 412-420; doi: 10.1038/mp.2011.3; published online 15 February 2011

Cortical morphometry in narcolepsy with cataplexy

The sleep-wake disorder narcolepsy with cataplexy is associated with the loss of hypocretin-(orexin-) producing neurons in the lateral hypothalamus. Several studies have reported abnormal cerebral activation in patients with narcolepsy with cataplexy. It remains unclear, however, whether these functional changes are related to structural alterations, particularly at the cortical level. To quantify structural brain changes associated with narcolepsy with cataplexy, we used high-resolution T1-weighted magnetic resonance imaging (MRI) in 12 patients compared with 12 healthy participants matched for age and gender. Subcortical and regional cortical volumes were measured using a method unbiased by non-linear registration. Further whole-brain analyses were conducted, measuring cortical characteristics, such as cortical thickness and gyrification, at thousands of points across each hemisphere using validated algorithms. Statistical analyses accounted for an effect of age and gender. We observed decreased cortical volume in the left paracentral lobule and increased cortical volume in the left caudal part of the middle frontal gyrus in narcoleptic patients compared with controls. Cortical thickness in prefrontal areas was inversely correlated with the severity of narcolepsy. Further, we observed several clusters of cortical thinning in patients with childhood or adolescent onset of narcolepsy compared with patients with adult onset of the disease. Our results suggest that specific anatomical changes may differentiate subgroups of narcolepsy patients with different clinical profiles (such as varying symptom severity or different age at onset). Future studies with larger groups of sleepy patients are required to assess whether distinct patterns of anatomical changes may distinguish narcolepsy from non-hypocretin-deficient hypersomnia disorders.

FUNCTIONAL PRINCIPAL COMPONENTS MODEL FOR HIGH-DIMENSIONAL BRAIN IMAGING

We establish a fundamental equivalence between singular value decomposition (SVD) and functional principal components analysis (FPCA) models. The constructive relationship allows to deploy the numerical efficiency of SVD to fully estimate the components of FPCA, even for extremely high-dimensional functional objects, such as brain images. As an example, a functional mixed effect model is fitted to high-resolution morphometric (RAVENS) images. The main directions of morphometric variation in brain volumes are identified and discussed.

Deep gray matter atrophy in multiple sclerosis: a tensor based morphometry.

Tensor based morphometry (TBM) was applied to determine the atrophy of deep gray matter (DGM) structures in 88 relapsing multiple sclerosis (MS) patients. For group analysis of atrophy, an unbiased atlas was constructed from 20 normal brains. The MS brain images were co-registered with the unbiased atlas using a symmetric inverse consistent nonlinear registration. These studies demonstrate significant atrophy of thalamus, caudate nucleus, and putamen even at a modest clinical disability, as assessed by the expanded disability status score (EDSS). A significant correlation between atrophy and EDSS was observed for different DGM structures: (thalamus: r=-0.51, p=3.85 x 10(-7); caudate nucleus: r=-0.43, p=2.35 x 10(-5); putamen: r=-0.36, p=6.12 x 10(-6)). Atrophy of these structures also correlated with 1) T2 hyperintense lesion volumes (thalamus: r=-0.56, p=9.96 x 10(-9); caudate nucleus: r=-0.31, p=3.10 x 10(-3); putamen: r=-0.50, p=6.06 x 10(-7)), 2) T1 hypointense lesion volumes (thalamus: r=-0.61, p=2.29 x 10(-10); caudate nucleus: r=-0.35, p=9.51 x 10(-4); putamen: r=-0.43, p=3.51 x 10(-5)), and 3) normalized CSF volume (thalamus: r=-0.66, p=3.55 x 10(-12); caudate nucleus: r=-0.52, p=2.31 x 10(-7), and putamen: r=-0.66, r=2.13 x 10(-12)). More severe atrophy was observed mainly in thalamus at higher EDSS. These studies appear to suggest a link between the white matter damage and DGM atrophy in MS.