Abnormal synchrony of resting state networks in premanifest and symptomatic Huntington disease: the IMAGE-HD study

Evolution of aberrant brain-wide spatiotemporal dynamics of resting-state networks in a Huntington's disease mouse model

BACKGROUND

Huntington's disease (HD) is marked by irreversible loss of neuronal function for which currently no availability for disease-modifying treatment exists. Advances in the understanding of disease progression can aid biomarker development, which in turn can accelerate therapeutic discovery.

METHODS

We characterised the progression of altered dynamics of whole-brain network states in the zQ175DN mouse model of HD using a dynamic functional connectivity (FC) approach to resting-state fMRI and identified quasi-periodic patterns (QPPs) of brain activity constituting the most prominent resting-state networks.

RESULTS

The occurrence of the normative QPPs, as observed in healthy controls, was reduced in the HD model as the phenotype progressed. This uncovered progressive cessation of synchronous brain activity with phenotypic progression, which is not observed with the conventional static FC approaches. To better understand the potential underlying cause of the observed changes in these brain states, we further assessed how mutant huntingtin (mHTT) protein deposition affects astrocytes and pericytes - one of the most important effectors of neurovascular coupling, along phenotypic progression. Increased cell-type dependent mHTT deposition was observed at the age of onset of motor anomalies, in the caudate putamen, somatosensory and motor cortex, regions that are prominently involved in HD pathology as seen in humans.

CONCLUSION

Our findings provide meaningful insights into the development and progression of altered functional brain dynamics in this HD model and open new avenues in assessing the dynamics of whole brain states, through QPPs, in clinical HD research.

HIGHLIGHTS

Hyperactivity in the LCN-linked regions within short QPPs observed before motor impairment onset. DMLN QPP presents a progressive decrease in DMLN activity and occurrence along HD-like phenotype development. Breakdown of the LCN DMLN state flux at motor onset leads to a subsequent absence of the LCN DMLN QPP at an advanced HD-like stage.

Functional and structural gradients reveal atypical hierarchical organization of Parkinson's disease

Parkinson's disease (PD) patients exhibit deficits in primary sensorimotor and higher-order executive functions. The gradient reflects the functional spectrum in sensorimotor-associated areas of the brain. We aimed to determine whether the gradient is disrupted in PD patients and how this disruption is associated with treatment outcome. Seventy-six patients (mean age, 59.2 ± 12.4 years [standard deviation], 44 women) and 34 controls participants (mean age, 58.1 ± 10.0 years [standard deviation], 19 women) were evaluated. We explored functional and structural gradients in PD patients and control participants. Patients were followed during 2 weeks of multidisciplinary intensive rehabilitation therapy (MIRT). The Unified Parkinson's Disease Rating Scale Part III (UPDRS-III) was administered to patients before and after treatment. We investigated PD-related alterations in the principal functional and structural gradients. We further used a support vector machine (SVM) and correlation analysis to assess the classification ability and treatment outcomes related to PD gradient alterations, respectively. The gradients showed significant differences between patients and control participants, mainly in somatosensory and visual networks involved in primary function, and higher-level association networks (dorsal attentional network (DAN) and default mode network (DMN)) related to motor control and execution. On the basis of the combined functional and structural gradient features of these networks, the SVM achieved an accuracy of 91.2% in discriminating patients from control participants. Treatment reduced the gradient difference. The altered gradient exhibited a significant correlation with motor improvement and was mainly distributed across the visual network, DAN and DMN. This study revealed damage to gradients in the brain characterized by sensorimotor and executive control deficits in PD patients. The application of gradient features to neurological disorders could lead to the development of potential diagnostic and treatment markers for PD.

Transmission-selective muscle pathology induced by the active propagation of mutant huntingtin across the human neuromuscular synapse

Neuron-to-neuron transmission of aggregation-prone, misfolded proteins may potentially explain the spatiotemporal accumulation of pathological lesions in the brains of patients with neurodegenerative protein-misfolding diseases (PMDs). However, little is known about protein transmission from the central nervous system to the periphery, or how this propagation contributes to PMD pathology. To deepen our understanding of these processes, we established two functional neuromuscular systems derived from human iPSCs. One was suitable for long-term high-throughput live-cell imaging and the other was adapted to a microfluidic system assuring that connectivity between motor neurons and muscle cells was restricted to the neuromuscular junction. We show that the Huntington's disease (HD)-associated mutant HTT exon 1 protein (mHTTEx1) is transmitted from neurons to muscle cells across the human neuromuscular junction. We found that transmission is an active and dynamic process that starts before aggregate formation and is regulated by synaptic activity. We further found that transmitted mHTTEx1 causes HD-relevant pathology at both molecular and functional levels in human muscle cells, even in the presence of the ubiquitous expression of mHTTEx1. In conclusion, we have uncovered a causal link between mHTTEx1 synaptic transmission and HD pathology, highlighting the therapeutic potential of blocking toxic protein transmission in PMDs.

Subthalamic nucleus shows opposite functional connectivity pattern in Huntington's and Parkinson's disease

Huntington's and Parkinson's disease are two movement disorders representing mainly opposite states of the basal ganglia inhibitory function. Despite being an integral part of the cortico-subcortico-cortical circuitry, the subthalamic nucleus function has been studied at the level of detail required to isolate its signal only through invasive studies in Huntington's and Parkinson's disease. Here, we tested whether the subthalamic nucleus exhibited opposite functional signatures in early Huntington's and Parkinson's disease. We included both movement disorders in the same whole-brain imaging study, and leveraged ultra-high-field 7T MRI to achieve the very fine resolution needed to investigate the smallest of the basal ganglia nuclei. Eleven of the 12 Huntington's disease carriers were recruited at a premanifest stage, while 16 of the 18 Parkinson's disease patients only exhibited unilateral motor symptoms (15 were at Stage I of Hoehn and Yahr off medication). Our group comparison interaction analyses, including 24 healthy controls, revealed a differential effect of Huntington's and Parkinson's disease on the functional connectivity at rest of the subthalamic nucleus within the sensorimotor network, i.e. an opposite effect compared with their respective age-matched healthy control groups. This differential impact in the subthalamic nucleus included an area precisely corresponding to the deep brain stimulation 'sweet spot'-the area with maximum overall efficacy-in Parkinson's disease. Importantly, the severity of deviation away from controls' resting-state values in the subthalamic nucleus was associated with the severity of motor and cognitive symptoms in both diseases, despite functional connectivity going in opposite directions in each disorder. We also observed an altered, opposite impact of Huntington's and Parkinson's disease on functional connectivity within the sensorimotor cortex, once again with relevant associations with clinical symptoms. The high resolution offered by the 7T scanner has thus made it possible to explore the complex interplay between the disease effects and their contribution on the subthalamic nucleus, and sensorimotor cortex. Taken altogether, these findings reveal for the first time non-invasively in humans a differential, clinically meaningful impact of the pathophysiological process of these two movement disorders on the overall sensorimotor functional connection of the subthalamic nucleus and sensorimotor cortex.

Longitudinal investigation of changes in resting-state co-activation patterns and their predictive ability in the zQ175 DN mouse model of Huntington's disease

Huntington's disease (HD) is a neurodegenerative disorder caused by expanded (≥ 40) glutamine-encoding CAG repeats in the huntingtin gene, which leads to dysfunction and death of predominantly striatal and cortical neurons. While the genetic profile and clinical signs and symptoms of the disease are better known, changes in the functional architecture of the brain, especially before the clinical expression becomes apparent, are not fully and consistently characterized. In this study, we sought to uncover functional changes in the brain in the heterozygous (HET) zQ175 delta-neo (DN) mouse model at 3, 6, and 10 months of age, using resting-state functional magnetic resonance imaging (RS-fMRI). This mouse model shows molecular, cellular and circuitry alterations that worsen through age. Motor function disturbances are manifested in this model at 6 and 10 months of age. Specifically, we investigated, longitudinally, changes in co-activation patterns (CAPs) that are the transient states of brain activity constituting the resting-state networks (RSNs). Most robust changes in the temporal properties of CAPs occurred at the 10-months time point; the durations of two anti-correlated CAPs, characterized by simultaneous co-activation of default-mode like network (DMLN) and co-deactivation of lateral-cortical network (LCN) and vice-versa, were reduced in the zQ175 DN HET animals compared to the wild-type mice. Changes in the spatial properties, measured in terms of activation levels of different brain regions, during CAPs were found at all three ages and became progressively more pronounced at 6-, and 10 months of age. We then assessed the cross-validated predictive power of CAP metrics to distinguish HET animals from controls. Spatial properties of CAPs performed significantly better than the chance level at all three ages with 80% classification accuracy at 6 and 10 months of age.

Aberrant resting-state brain activity in Huntington's disease: A voxel-based meta-analysis

Introduction

Functional neuroimaging could provide abundant information of underling pathophysiological mechanisms of the clinical triad including motor, cognitive and psychiatric impairment in Huntington's Disease (HD).

Methods

We performed a voxel-based meta-analysis using anisotropic effect size-signed differential mapping (AES-SDM) method.

Results

6 studies (78 symptomatic HD, 102 premanifest HD and 131 healthy controls) were included in total. Altered resting-state brain activity was primarily detected in the bilateral medial part of superior frontal gyrus, bilateral anterior cingulate/paracingulate gyrus, left insula, left striatum, right cortico-spinal projections area, right inferior temporal gyrus area, right thalamus, right cerebellum and right gyrus rectus area. Premanifest and symptomatic HD patients showed different alterative pattern in the subgroup analyses.

Discussion

The robust and consistent abnormalities in the specific brain regions identified in the current study could help to understand the pathophysiology of HD and explore reliable neuroimaging biomarkers for monitoring disease progression, or even predicting the onset of premanifest HD patients.

Genetically encoded cell-death indicators (GEDI) to detect an early irreversible commitment to neurodegeneration

Cell death is a critical process that occurs normally in health and disease. However, its study is limited due to available technologies that only detect very late stages in the process or specific death mechanisms. Here, we report the development of a family of fluorescent biosensors called genetically encoded death indicators (GEDIs). GEDIs specifically detect an intracellular Ca²⁺ level that cells achieve early in the cell death process and that marks a stage at which cells are irreversibly committed to die. The time-resolved nature of a GEDI delineates a binary demarcation of cell life and death in real time, reformulating the definition of cell death. We demonstrate that GEDIs acutely and accurately report death of rodent and human neurons in vitro, and show that GEDIs enable an automated imaging platform for single cell detection of neuronal death in vivo in zebrafish larvae. With a quantitative pseudo-ratiometric signal, GEDIs facilitate high-throughput analysis of cell death in time-lapse imaging analysis, providing the necessary resolution and scale to identify early factors leading to cell death in studies of neurodegeneration.

Cell death is a critical process in health and disease, yet available markers record later stages of cell death once a cell has already begun to decompose. Here the authors show the use of a genetically encoded calcium indicator that demarcates an irreversible stage of cell death earlier than previously possible.

Multiparametric magnetic resonance imaging and positron emission tomography findings in neurodegenerative diseases: Current status and future directions

Neurodegenerative diseases (NDDs) are characterized by progressive neuronal loss, leading to dementia and movement disorders. NDDs broadly include Alzheimer's disease, frontotemporal lobar degeneration, parkinsonian syndromes, and prion diseases. There is an ever-increasing prevalence of mild cognitive impairment and dementia, with an accompanying immense economic impact, prompting efforts aimed at early identification and effective interventions. Neuroimaging is an essential tool for the early diagnosis of NDDs in both clinical and research settings. Structural, functional, and metabolic imaging modalities, including magnetic resonance imaging (MRI) and positron emission tomography (PET), are widely available. They show encouraging results for diagnosis, monitoring, and treatment response evaluation. The current review focuses on the complementary role of various imaging modalities in relation to NDDs, the qualitative and quantitative utility of newer MRI techniques, novel radiopharmaceuticals, and integrated PET/MRI in the setting of NDDs.

Robustness of connectome harmonics to local gray matter and long-range white matter connectivity changes

Recently, it has been proposed that the harmonic patterns emerging from the brain's structural connectivity underlie the resting state networks of the human brain. These harmonic patterns, termed connectome harmonics, are estimated as the Laplace eigenfunctions of the combined gray and white matters connectivity matrices and yield a connectome-specific extension of the well-known Fourier basis. However, it remains unclear how topological properties of the combined connectomes constrain the precise shape of the connectome harmonics and their relationships to the resting state networks. Here, we systematically study how alterations of the local and long-range connectivity matrices affect the spatial patterns of connectome harmonics. Specifically, the proportion of local gray matter homogeneous connectivity versus long-range white-matter heterogeneous connectivity is varied by means of weight-based matrix thresholding, distance-based matrix trimming, and several types of matrix randomizations. We demonstrate that the proportion of local gray matter connections plays a crucial role for the emergence of wide-spread, functionally meaningful, and originally published connectome harmonic patterns. This finding is robust for several different cortical surface templates, mesh resolutions, or widths of the local diffusion kernel. Finally, using the connectome harmonic framework, we also provide a proof-of-concept for how targeted structural changes such as the atrophy of inter-hemispheric callosal fibers and gray matter alterations may predict functional deficits associated with neurodegenerative conditions.

Resting-state connectivity stratifies premanifest Huntington's disease by longitudinal cognitive decline rate

Patient stratification is critical for the sensitivity of clinical trials at early stages of neurodegenerative disorders. In Huntington’s disease (HD), genetic tests make cognitive, motor and brain imaging measurements possible before symptom manifestation (pre-HD). We evaluated pre-HD stratification models based on single visit resting-state functional MRI (rs-fMRI) data that assess observed longitudinal motor and cognitive change rates from the multisite Track-On HD cohort (74 pre-HD, 79 control participants). We computed longitudinal performance change on 10 tasks (including visits from the preceding TRACK-HD study when available), as well as functional connectivity density (FCD) maps in single rs-fMRI visits, which showed high test-retest reliability. We assigned pre-HD subjects to subgroups of fast, intermediate, and slow change along single tasks or combinations of them, correcting for expectations based on aging; and trained FCD-based classifiers to distinguish fast- from slow-progressing individuals. For robustness, models were validated across imaging sites. Stratification models distinguished fast- from slow-changing participants and provided continuous assessments of decline applicable to the whole pre-HD population, relying on previously-neglected white matter functional signals. These results suggest novel correlates of early deterioration and a robust stratification strategy where a single MRI measurement provides an estimate of multiple ongoing longitudinal changes.

Aberrant brain network connectivity in presymptomatic and manifest Huntington's disease: A systematic review

Resting‐state functional magnetic resonance imaging (rs‐fMRI) has the potential to shed light on the pathophysiological mechanisms of Huntington's disease (HD), paving the way to new therapeutic interventions. A systematic literature review was conducted in three online databases according to PRISMA guidelines, using keywords for HD, functional connectivity, and rs‐fMRI. We included studies investigating connectivity in presymptomatic (pre‐HD) and manifest HD gene carriers compared to healthy controls, implementing seed‐based connectivity, independent component analysis, regional property, and graph analysis approaches. Visual network showed reduced connectivity in manifest HD, while network/areas underpinning motor functions were consistently altered in both manifest HD and pre‐HD, showing disease stage‐dependent changes. Cognitive networks underlying executive and attentional functions showed divergent anterior–posterior alterations, possibly reflecting compensatory mechanisms. The involvement of these networks in pre‐HD is still unclear. In conclusion, aberrant connectivity of the sensory‐motor network is observed in the early stage of HD while, as pathology spreads, other networks might be affected, such as the visual and executive/attentional networks. Moreover, sensory‐motor and executive networks exhibit hyper‐ and hypo‐connectivity patterns following different spatiotemporal trajectories. These findings could potentially help to implement future huntingtin‐lowering interventions.

Network spread determines severity of degeneration and disconnection in Huntington's disease

Trans-neuronal propagation of mutant huntingtin protein contributes to the organised spread of cortico-striatal degeneration and disconnection in Huntington's disease (HD). We investigated whether the network diffusion model, which models transneuronal spread as diffusion of pathological proteins via the brain connectome, can determine the severity of neural degeneration and disconnection in HD. We used structural magnetic resonance imaging (MRI) and high-angular resolution diffusion weighted imaging (DWI) data from symptomatic Huntington's disease (HD) (N = 26) and age-matched healthy controls (N = 26) to measure neural degeneration and disconnection in HD. The network diffusion model was used to test whether disease spread, via the human brain connectome, is a viable mechanism to explain the distribution of pathology across the brain. We found that an eigenmode identified in the healthy human brain connectome Laplacian matrix, accurately predicts the cortico-striatal spatial pattern of degeneration in HD. Furthermore, the spread of neural degeneration from sub-cortical brain regions, including the accumbens and thalamus, generates a spatial pattern which represents the typical neurodegenerative characteristics in HD. The white matter connections connecting the nodes with the highest amount of disease factors, when diffusion based disease spread is initiated from the striatum, were found to be most vulnerable to disconnection in HD. These findings suggest that trans-neuronal diffusion of mutant huntingtin protein across the human brain connectome may explain the pattern of gray matter degeneration and white matter disconnection that are hallmarks of HD.

Cognitive Behavior Classification From Scalp EEG Signals

Electroencephalography (EEG) has become increasingly valuable outside of its traditional use in neurology. EEG is now used for neuropsychiatric diagnosis, neurological evaluation of traumatic brain injury, neurotherapy, gaming, neurofeedback, mindfulness, and cognitive enhancement training. The trend to increase the number of EEG electrodes, the development of novel analytical methods, and the availability of large data sets has created a data analysis challenge to find the "signal of interest" that conveys the most information about ongoing cognitive effort. Accordingly, we compare three common types of neural synchrony measures that are applied to EEG-power analysis, phase locking, and phase-amplitude coupling to assess which analytical measure provides the best separation between EEG signals that were recorded, while healthy subjects performed eight cognitive tasks-Hopkins Verbal Learning Test and its delayed version, Stroop Test, Symbol Digit Modality Test, Controlled Oral Word Association Test, Trail Marking Test, Digit Span Test, and Benton Visual Retention Test. We find that of the three analytical methods, phase-amplitude coupling, specifically theta (4-7 Hz)-high gamma (70-90 Hz) obtained from frontal and parietal EEG electrodes provides both the largest separation between the EEG during cognitive tasks and also the highest classification accuracy between pairs of tasks. We also find that phase-locking analysis provides the most distinct clustering of tasks based on their utilization of long-term memory. Finally, we show that phase-amplitude coupling is the least sensitive to contamination by intense jaw-clenching muscle artifact.

Dynamic functional network connectivity in Huntington's disease and its associations with motor and cognitive measures

Dynamic functional network connectivity (dFNC) is an expansion of traditional, static FNC that measures connectivity variation among brain networks throughout scan duration. We used a large resting-state fMRI (rs-fMRI) sample from the PREDICT-HD study (N = 183 Huntington disease gene mutation carriers [HDgmc] and N = 78 healthy control [HC] participants) to examine whole-brain dFNC and its associations with CAG repeat length as well as the product of scaled CAG length and age, a variable representing disease burden. We also tested for relationships between functional connectivity and motor and cognitive measurements. Group independent component analysis was applied to rs-fMRI data to obtain whole-brain resting state networks. FNC was defined as the correlation between RSN time-courses. Dynamic FNC behavior was captured using a sliding time window approach, and FNC results from each window were assigned to four clusters representing FNC states, using a k-means clustering algorithm. HDgmc individuals spent significantly more time in State-1 (the state with the weakest FNC pattern) compared to HC. However, overall HC individuals showed more FNC dynamism than HDgmc. Significant associations between FNC states and genetic and clinical variables were also identified. In FNC State-4 (the one that most resembled static FNC), HDgmc exhibited significantly decreased connectivity between the putamen and medial prefrontal cortex compared to HC, and this was significantly associated with cognitive performance. In FNC State-1, disease burden in HDgmc participants was significantly associated with connectivity between the postcentral gyrus and posterior cingulate cortex, as well as between the inferior occipital gyrus and posterior parietal cortex.

Novel Imaging Biomarkers for Huntington's Disease and Other Hereditary Choreas

PURPOSE OF THE REVIEW

Imaging biomarkers for neurodegenerative disorders are primarily developed with the goal to aid diagnosis, to monitor disease progression, and to assess the efficacy of disease-modifying therapies in support to clinical outcomes that may either show limited sensitivity or need extended time for their evaluation. This article will review the most recent concepts and findings in the field of neuroimaging applied to Huntington's disease and Huntington-like syndromes. Emphasis will be given to the discussion of potential pharmacodynamic biomarkers for clinical trials in Huntington's disease (HD) and of neuroimaging tools that can be used as diagnostic biomarkers in HD-like syndromes.

RECENT FINDINGS

Several magnetic resonance (MR) and positron emission tomography (PET) molecular imaging tools have been identified as potential pharmacodynamic biomarkers and others are in the pipeline after preclinical validation. MRI and 18F-fluorodeoxyglucose PET can be considered useful supportive diagnostic tools for the differentiation of other HD-like syndromes. New trials in HD have the primary goal to lower mutant huntingtin (mHTT) protein levels in the brain in order to reduce or alter the progression of the disease. MR and PET molecular imaging markers have been developed as tools to monitor disease progression and to evaluate treatment outcomes of disease-modifying trials in HD. These markers could be used alone or in combination for detecting structural and pharmacodynamic changes potentially associated with the lowering of mHTT.

Resting-state connectivity in neurodegenerative disorders: Is there potential for an imaging biomarker?

Biomarkers in whichever modality are tremendously important in diagnosing of disease, tracking disease progression and clinical trials. This applies in particular for disorders with a long disease course including pre-symptomatic stages, in which only subtle signs of clinical progression can be observed. Magnetic resonance imaging (MRI) biomarkers hold particular promise due to their relative ease of use, cost-effectiveness and non-invasivity. Studies measuring resting-state functional MR connectivity have become increasingly common during recent years and are well established in neuroscience and related fields. Its increasing application does of course also include clinical settings and therein neurodegenerative diseases. In the present review, we critically summarise the state of the literature on resting-state functional connectivity as measured with functional MRI in neurodegenerative disorders. In addition to an overview of the results, we briefly outline the methods applied to the concept of resting-state functional connectivity. While there are many different neurodegenerative disorders cumulatively affecting a substantial number of patients, for most of them studies on resting-state fMRI are lacking. Plentiful amounts of papers are available for Alzheimer's disease (AD) and Parkinson's disease (PD), but only few works being available for the less common neurodegenerative diseases. This allows some conclusions on the potential of resting-state fMRI acting as a biomarker for the aforementioned two diseases, but only tentative statements for the others. For AD, the literature contains a relatively strong consensus regarding an impairment of the connectivity of the default mode network compared to healthy individuals. However, for AD there is no considerable documentation on how that alteration develops longitudinally with the progression of the disease. For PD, the available research points towards alterations of connectivity mainly in limbic and motor related regions and networks, but drawing conclusions for PD has to be done with caution due to a relative heterogeneity of the disease. For rare neurodegenerative diseases, no clear conclusions can be drawn due to the few published results. Nevertheless, summarising available data points towards characteristic connectivity alterations in Huntington's disease, frontotemporal dementia, dementia with Lewy bodies, multiple systems atrophy and the spinocerebellar ataxias. Overall at this point in time, the data on AD are most promising towards the eventual use of resting-state fMRI as an imaging biomarker, although there remain issues such as reproducibility of results and a lack of data demonstrating longitudinal changes. Improved methods providing more precise classifications as well as resting-state network changes that are sensitive to disease progression or therapeutic intervention are highly desirable, before routine clinical use could eventually become a reality.

Whole-Brain Connectivity in a Large Study of Huntington's Disease Gene Mutation Carriers and Healthy Controls

Huntington's disease (HD) is an inherited brain disorder characterized by progressive motor, cognitive, and behavioral dysfunctions. It is caused by abnormally large trinucleotide cytosine-adenine-guanine (CAG) repeat expansions on exon 1 of the Huntingtin gene. CAG repeat length (CAG-RL) inversely correlates with an earlier age of onset. Region-based studies have shown that HD gene mutation carrier (HDgmc) individuals (CAG-RL ≥36) present functional connectivity alterations in subcortical (SC) and default mode networks. In this analysis, we expand on previous HD studies by investigating associations between CAG-RL and connectivity in the whole brain, as well as between CAG-dependent connectivity and motor and cognitive performances. We used group-independent component analysis on resting-state functional magnetic resonance imaging scans of 261 individuals (183 HDgmc and 78 healthy controls) from the PREDICT-HD study, to obtain whole-brain resting state networks (RSNs). Regression analysis was applied within and between RSNs connectivity (functional network connectivity [FNC]) to identify CAG-RL associations. Connectivity within the putamen RSN is negatively correlated with CAG-RL. The FNC between putamen and insula decreases with increasing CAG-RL, and also shows significant associations with motor and cognitive measures. The FNC between calcarine and middle frontal gyri increased with CAG-RL. In contrast, FNC in other visual (VIS) networks declined with increasing CAG-RL. In addition to observed effects in SC areas known to be related to HD, our study identifies a strong presence of alterations in VIS regions less commonly observed in previous reports and provides a step forward in understanding FNC dysfunction in HDgmc.

Cognitive dysfunction in Huntington's disease: mechanisms and therapeutic strategies beyond BDNF

One of the main focuses in Huntington's disease (HD) research, as well as in most neurodegenerative diseases, is the development of new therapeutic strategies, as currently there is no treatment to delay or prevent the progression of the disease. Neuronal dysfunction and neuronal death in HD are caused by a combination of interrelated pathogenic processes that lead to motor, cognitive and psychiatric symptoms. Understanding how mutant huntingtin impacts on a plethora of cellular functions could help to identify new molecular targets. Although HD has been classically classified as a neurodegenerative disease affecting voluntary movement, lately cognitive dysfunction is receiving increased attention as it is very invalidating for patients. Thus, an ambitious goal in HD research is to find altered molecular mechanisms that contribute to cognitive decline. In this review, we have focused on those findings related to corticostriatal and hippocampal cognitive dysfunction in HD, as well as on the underlying molecular mechanisms, which constitute potential therapeutic targets. These include alterations in synaptic plasticity, transcriptional machinery and neurotrophic and neurotransmitter signaling.

Functional neuroimaging and chorea: a systematic review

Chorea is a hyperkinetic movement disorder consisting of involuntary irregular, flowing movements of the trunk, neck or face. Although Huntington’s disease is the most common cause of chorea in adults, chorea can also result from many other neurodegenerative, metabolic, and autoimmune conditions. While the pathophysiology of these different conditions is quite variable, recent advances in functional imaging have enabled the development of new methods for analysis of brain activity and neuronal dysfunction. In this paper we review the growing body of functional imaging data that has been performed in chorea syndromes and identify particular trends, which can be used to better understand the underlying network changes within the basal ganglia. While it can be challenging to identify whether changes are primary, secondary, or compensatory, identification of these trends can ultimately be useful in diagnostic testing and treatment in many of the conditions that cause chorea.

Resting-state connectivity and modulated somatomotor and default-mode networks in Huntington disease

AIMS

To analyze brain functional connectivity in the somatomotor and default-mode networks (DMNs) of patients with Huntington disease (HD), its relationship with gray matter (GM) volume loss, and functional changes after pridopidine treatment.

METHODS

Ten patients and ten untreated controls underwent T1-weighted imaging and resting-state functional magnetic resonance imaging (fMRI); four patients were also assessed after 3 months of pridopidine treatment (90 mg/d). The seed-based functional connectivity patterns from the posterior cingulate cortex and the supplementary motor area (SMA), considered cortical hubs of the DMN and somatomotor networks, respectively, were computed. FMRIB Software Library voxel-based morphometry measured GM volume.

RESULTS

Patients had GM volume decrease in all cortical and subcortical areas of the somatomotor network with preservation of the SMA, and increased somatomotor and DMN connectivity. In DMN structures, functional connectivity impairment preceded volume loss. Pridopidine reduced the intensity of these aberrant connections.

CONCLUSION

The abnormal connectivity of the somatomotor and DMN observed in HD patients may represent an early dysfunction marker, as it preceded volume loss in DMN. Pridopidine reduced connectivity of these networks in all four treated patients, suggesting that connectivity is sensitive to treatment response.

Intact sensory-motor network structure and function in far from onset premanifest Huntington's disease

Structural and functional changes attributable to the neurodegenerative process in Huntington's disease (HD) may be evident in HTT CAG repeat expansion carriers before the clinical manifestations of HD. It remains unclear, though, how far from motor onset a consistent signature of the neurodegenerative process in HD can be detected. Twelve far from onset preHD and 22 age-matched healthy control participants underwent volumetric structural magnetic resonance imaging (MRI), diffusion tensor imaging (DTI), and resting-state functional MRI (11 preHD, 22 controls) as well as electrophysiological measurements (12 preHD, 13 controls). There were no significant differences in white matter macro- and microstructure between far from onset preHD participants and controls. Functional connectivity in a basal ganglia-thalamic and motor networks, all measures of the motor efferent and sensory afferent pathways as well as sensory-motor integration were also similar in far from onset preHD and controls. With the methods used in far from onset preHD sensory-motor neural macro- or micro-structure and brain function were similar to healthy controls. This suggests that any observable structural and functional change in preHD nearer to onset, or in manifest HD, at least using comparable techniques such as in this study, most likely reflects an ongoing neurodegenerative process.

White matter predicts functional connectivity in premanifest Huntington's disease

Objectives

The distribution of pathology in neurodegenerative disease can be predicted by the organizational characteristics of white matter in healthy brains. However, we have very little evidence for the impact these pathological changes have on brain function. Understanding any such link between structure and function is critical for understanding how underlying brain pathology influences the progressive behavioral changes associated with neurodegeneration. Here, we demonstrate such a link between structure and function in individuals with premanifest Huntington's.

Methods

Using diffusion tractography and resting state functional magnetic resonance imaging to characterize white matter organization and functional connectivity, we investigate whether characteristic patterns of white matter organization in the healthy human brain shape the changes in functional coupling between brain regions in premanifest Huntington's disease.

Results

We find changes in functional connectivity in premanifest Huntington's disease that link directly to underlying patterns of white matter organization in healthy brains. Specifically, brain areas with strong structural connectivity show decreases in functional connectivity in premanifest Huntington's disease relative to controls, while regions with weak structural connectivity show increases in functional connectivity. Furthermore, we identify a pattern of dissociation in the strongest functional connections between anterior and posterior brain regions such that anterior functional connectivity increases in strength in premanifest Huntington's disease, while posterior functional connectivity decreases.

Interpretation

Our findings demonstrate that organizational principles of white matter underlie changes in functional connectivity in premanifest Huntington's disease. Furthermore, we demonstrate functional antero–posterior dissociation that is in keeping with the caudo–rostral gradient of striatal pathology in HD.

Striatal morphology correlates with frontostriatal electrophysiological motor processing in Huntington's disease: an IMAGE-HD study

BACKGROUND

Huntington's disease (HD) causes progressive atrophy to the striatum, a critical node in frontostriatal circuitry. Maintenance of motor function is dependent on functional connectivity of these premotor, motor, and dorsolateral frontostriatal circuits, and structural integrity of the striatum itself. We aimed to investigate whether size and shape of the striatum as a measure of frontostriatal circuit structural integrity was correlated with functional frontostriatal electrophysiological neural premotor processing (contingent negative variation, CNV), to better understand motoric structure-function relationships in early HD.

METHODS

Magnetic resonance imaging (MRI) scans and electrophysiological (EEG) measures of premotor processing were obtained from a combined HD group (12 presymptomatic, 7 symptomatic). Manual segmentation of caudate and putamen was conducted with subsequent shape analysis. Separate correlational analyses (volume and shape) included covariates of age, gender, intracranial volume, and time between EEG and MRI.

RESULTS

Right caudate volume correlated with early CNV latency over frontocentral regions and late CNV frontally, whereas right caudate shape correlated with early CNV latency centrally. Left caudate volume correlated with early CNV latency over centroparietal regions and late CNV frontally. Right and left putamen volumes correlated with early CNV latency frontally, and right and left putamen shape/volume correlated with parietal CNV slope.

CONCLUSIONS

Timing (latency) and pattern (slope) of frontostriatal circuit-mediated premotor functional activation across scalp regions were correlated with abnormalities in structural integrity of the key frontostriatal circuit component, the striatum (size and shape). This was accompanied by normal reaction times, suggesting it may be undetected in regular tasks due to preserved motor "performance." Such differences in functional activation may reflect atrophy-based frontostriatal circuitry despecialization and/or compensatory recruitment of additional brain regions.

Longitudinal changes in functional connectivity of cortico-basal ganglia networks in manifests and premanifest huntington's disease

Huntington's disease (HD) is a genetic neurological disorder resulting in cognitive and motor impairments. We evaluated the longitudinal changes of functional connectivity in sensorimotor, associative and limbic cortico-basal ganglia networks. We acquired structural MRI and resting-state fMRI in three visits one year apart, in 18 adult HD patients, 24 asymptomatic mutation carriers (preHD) and 18 gender- and age-matched healthy volunteers from the TRACK-HD study. We inferred topological changes in functional connectivity between 182 regions within cortico-basal ganglia networks using graph theory measures. We found significant differences for global graph theory measures in HD but not in preHD. The average shortest path length (L) decreased, which indicated a change toward the random network topology. HD patients also demonstrated increases in degree k, reduced betweeness centrality bc and reduced clustering C. Changes predominated in the sensorimotor network for bc and C and were observed in all circuits for k. Hubs were reduced in preHD and no longer detectable in HD in the sensorimotor and associative networks. Changes in graph theory metrics (L, k, C and bc) correlated with four clinical and cognitive measures (symbol digit modalities test, Stroop, Burden and UHDRS). There were no changes in graph theory metrics across sessions, which suggests that these measures are not reliable biomarkers of longitudinal changes in HD. preHD is characterized by progressive decreasing hub organization, and these changes aggravate in HD patients with changes in local metrics. HD is characterized by progressive changes in global network interconnectivity, whose network topology becomes more random over time. Hum Brain Mapp 37:4112-4128, 2016. © 2016 Wiley Periodicals, Inc.

Early grey matter changes in structural covariance networks in Huntington's disease

Background

Progressive subcortical changes are known to occur in Huntington's disease (HD), a hereditary neurodegenerative disorder. Less is known about the occurrence and cohesion of whole brain grey matter changes in HD.

Objectives

We aimed to detect network integrity changes in grey matter structural covariance networks and examined relationships with clinical assessments.

Methods

Structural magnetic resonance imaging data of premanifest HD (n = 30), HD patients (n = 30) and controls (n = 30) was used to identify ten structural covariance networks based on a novel technique using the co-variation of grey matter with independent component analysis in FSL. Group differences were studied controlling for age and gender. To explore whether our approach is effective in examining grey matter changes, regional voxel-based analysis was additionally performed.

Results

Premanifest HD and HD patients showed decreased network integrity in two networks compared to controls. One network included the caudate nucleus, precuneous and anterior cingulate cortex (in HD p < 0.001, in pre-HD p = 0.003). One other network contained the hippocampus, premotor, sensorimotor, and insular cortices (in HD p < 0.001, in pre-HD p = 0.023). Additionally, in HD patients only, decreased network integrity was observed in a network including the lingual gyrus, intracalcarine, cuneal, and lateral occipital cortices (p = 0.032). Changes in network integrity were significantly associated with scores of motor and neuropsychological assessments. In premanifest HD, voxel-based analyses showed pronounced volume loss in the basal ganglia, but less prominent in cortical regions.

Conclusion

Our results suggest that structural covariance might be a sensitive approach to reveal early grey matter changes, especially for premanifest HD.

•

Identification of anatomical networks in Huntington's disease (HD).

•

Independent component analysis was used to examine structural covariance networks.

•

HD patients showed changes in subcortical and cortical covariance networks.

•

A network-based approach is sensitive to reveal early grey matter changes.

Abnormal Electrophysiological Motor Responses in Huntington's Disease: Evidence of Premanifest Compensation

Background

Huntington's disease (HD) causes progressive motor dysfunction through characteristic atrophy. Changes to neural structure begin in premanifest stages yet individuals are able to maintain a high degree of function, suggesting involvement of supportive processing during motor performance. Electroencephalography (EEG) enables the investigation of subtle impairments at the neuronal level, and possible compensatory strategies, by examining differential activation patterns. We aimed to use EEG to investigate neural motor processing (via the Readiness Potential; RP), premotor processing and sensorimotor integration (Contingent Negative Variation; CNV) during simple motor performance in HD.

Methods

We assessed neural activity associated with motor preparation and processing in 20 premanifest (pre-HD), 14 symptomatic HD (symp-HD), and 17 healthy controls. Participants performed sequential tapping within two experimental paradigms (simple tapping; Go/No-Go). RP and CNV potentials were calculated separately for each group.

Results

Motor components and behavioural measures did not distinguish pre-HD from controls. Compared to controls and pre-HD, symp-HD demonstrated significantly reduced relative amplitude and latency of the RP, whereas controls and pre-HD did not differ. However, early CNV was found to significantly differ between control and pre-HD groups, due to enhanced early CNV in pre-HD.

Conclusions

For the first time, we provide evidence of atypical activation during preparatory processing in pre-HD. The increased activation during this early stage of the disease may reflect ancillary processing in the form of recruitment of additional neural resources for adequate motor preparation, despite atrophic disruption to structure and circuitry. We propose an early adaptive compensation mechanism in pre-HD during motor preparation.

Network topology and functional connectivity disturbances precede the onset of Huntington's disease

Cognitive, motor and psychiatric changes in prodromal Huntington's disease have nurtured the emergent need for early interventions. Preventive clinical trials for Huntington's disease, however, are limited by a shortage of suitable measures that could serve as surrogate outcomes. Measures of intrinsic functional connectivity from resting-state functional magnetic resonance imaging are of keen interest. Yet recent studies suggest circumscribed abnormalities in resting-state functional magnetic resonance imaging connectivity in prodromal Huntington's disease, despite the spectrum of behavioural changes preceding a manifest diagnosis. The present study used two complementary analytical approaches to examine whole-brain resting-state functional magnetic resonance imaging connectivity in prodromal Huntington's disease. Network topology was studied using graph theory and simple functional connectivity amongst brain regions was explored using the network-based statistic. Participants consisted of gene-negative controls (n = 16) and prodromal Huntington's disease individuals (n = 48) with various stages of disease progression to examine the influence of disease burden on intrinsic connectivity. Graph theory analyses showed that global network interconnectivity approximated a random network topology as proximity to diagnosis neared and this was associated with decreased connectivity amongst highly-connected rich-club network hubs, which integrate processing from diverse brain regions. However, functional segregation within the global network (average clustering) was preserved. Functional segregation was also largely maintained at the local level, except for the notable decrease in the diversity of anterior insula intermodular-interconnections (participation coefficient), irrespective of disease burden. In contrast, network-based statistic analyses revealed patterns of weakened frontostriatal connections and strengthened frontal-posterior connections that evolved as disease burden increased. These disturbances were often related to long-range connections involving peripheral nodes and interhemispheric connections. A strong association was found between weaker connectivity and decreased rich-club organization, indicating that whole-brain simple connectivity partially expressed disturbances in the communication of highly-connected hubs. However, network topology and network-based statistic connectivity metrics did not correlate with key markers of executive dysfunction (Stroop Test, Trail Making Test) in prodromal Huntington's disease, which instead were related to whole-brain connectivity disturbances in nodes (right inferior parietal, right thalamus, left anterior cingulate) that exhibited multiple aberrant connections and that mediate executive control. Altogether, our results show for the first time a largely disease burden-dependent functional reorganization of whole-brain networks in prodromal Huntington's disease. Both analytic approaches provided a unique window into brain reorganization that was not related to brain atrophy or motor symptoms. Longitudinal studies currently in progress will chart the course of functional changes to determine the most sensitive markers of disease progression.

Neuroanatomical Visualization of the Impaired Striatal Connectivity in Huntington's Disease Mouse Model

Huntington's disease (HD) is a movement disorder characterized by the early selective degeneration of striatum. For motor control, the striatum receives excitatory inputs from multiple brain regions and projects the information to other basal ganglia nuclei. Despite the pathological importance of the striatal degeneration in HD, there are little anatomical data that show impaired striatal connectivity in HD. For the anatomical mapping of the striatum, we injected here a neurotracer DiD to the dorsal striatum of HD mouse model (YAC128). Compared with littermate controls, the number of the traced inputs to the striatum was reduced dramatically in YAC128 mice at 12 months of age suggesting massive destruction of the striatal connections. Basal ganglia inputs were significantly damaged in HD mice by showing 61 % decrease in substantia nigra pars compacta, 85% decrease in thalamic centromedian nucleus, and 55% decrease in thalamic parafascicular nucleus. Cortical inputs were also greatly decreased by 43% in motor cortex, 48% in somatosensory cortex, and 72% in visual cortex. Besides the known striatal connections, the neurotracer DiD also traced inputs from amygdala and the amygdala inputs were decreased by 68% in YAC128 mice. Considering the role of amygdala in emotion processing, the impairment in amygdalostriatal connectivity strongly suggests that emotional disturbances could occur in HD mice. Indeed, open-field tests further indicated that YAC128 mice exhibited changes in emotional behaviors related to symptoms of depression and anxiety. Although onset of HD is clinically determined on the basis of motor abnormality, emotional deficits are also common features of the disease. Therefore, our anatomical connectivity mapping of the striatum provides a new insight to interpret brain dysfunction in HD.

Recent imaging advances in neurology

Over the recent years, the application of neuroimaging techniques such as magnetic resonance imaging (MRI) and positron emission tomography (PET) has considerably advanced the understanding of complex neurological disorders. PET is a powerful molecular imaging tool, which investigates the distribution and binding of radiochemicals attached to biologically relevant molecules; as such, this technique is able to give information on biochemistry and metabolism of the brain in health and disease. MRI uses high intensity magnetic fields and radiofrequency pulses to provide structural and functional information on tissues and organs in intact or diseased individuals, including the evaluation of white matter integrity, grey matter thickness and brain perfusion. The aim of this article is to review the most recent advances in neuroimaging research in common neurological disorders such as movement disorders, dementia, epilepsy, traumatic brain injury and multiple sclerosis, and to evaluate their contribution in the diagnosis and management of patients.

Functional connectivity modeling of consistent cortico-striatal degeneration in Huntington's disease

Huntington's disease (HD) is a progressive neurodegenerative disorder characterized by a complex neuropsychiatric phenotype. In a recent meta-analysis we identified core regions of consistent neurodegeneration in premanifest HD in the striatum and middle occipital gyrus (MOG). For early manifest HD convergent evidence of atrophy was most prominent in the striatum, motor cortex (M1) and inferior frontal junction (IFJ). The aim of the present study was to functionally characterize this topography of brain atrophy and to investigate differential connectivity patterns formed by consistent cortico-striatal atrophy regions in HD. Using areas of striatal and cortical atrophy at different disease stages as seeds, we performed task-free resting-state and task-based meta-analytic connectivity modeling (MACM). MACM utilizes the large data source of the BrainMap database and identifies significant areas of above-chance co-activation with the seed-region via the activation-likelihood-estimation approach. In order to delineate functional networks formed by cortical as well as striatal atrophy regions we computed the conjunction between the co-activation profiles of striatal and cortical seeds in the premanifest and manifest stages of HD, respectively. Functional characterization of the seeds was obtained using the behavioral meta-data of BrainMap. Cortico-striatal atrophy seeds of the premanifest stage of HD showed common co-activation with a rather cognitive network including the striatum, anterior insula, lateral prefrontal, premotor, supplementary motor and parietal regions. A similar but more pronounced co-activation pattern, additionally including the medial prefrontal cortex and thalamic nuclei was found with striatal and IFJ seeds at the manifest HD stage. The striatum and M1 were functionally connected mainly to premotor and sensorimotor areas, posterior insula, putamen and thalamus. Behavioral characterization of the seeds confirmed that experiments activating the MOG or IFJ in conjunction with the striatum were associated with cognitive functions, while the network formed by M1 and the striatum was driven by motor-related tasks. Thus, based on morphological changes in HD, we identified functionally distinct cortico-striatal networks resembling a cognitive and motor loop, which may be prone to early disruptions in different stages of the disease and underlie HD-related cognitive and motor symptom profiles. Our findings provide an important link between morphometrically defined seed-regions and corresponding functional circuits highlighting the functional and ensuing clinical relevance of structural damage in HD.

•

Pre-HD atrophy seeds showed common functional co-activation with a cognitive network.

•

Modeling of manifest-HD seeds delineated a segregation of a cognitive and motor loop.

•

Behavioral decoding of atrophy seeds confirmed functional segregation of networks.

•

Based on morphometric changes in HD distinct corticostriatal networks were identified.

•

Findings depict functional and ensuing clinical relevance of structural damage in HD.

Volumetric analysis of the hypothalamus in Huntington Disease using 3T MRI: the IMAGE-HD Study

Huntington disease (HD) is a fatal neurodegenerative disorder caused by an expanded CAG repeat in the huntingtin gene. Non-motor symptoms and signs such as psychiatric disturbances, sleep problems and metabolic dysfunction are part of the disease manifestation. These aspects may relate to changes in the hypothalamus, an area of the brain involved in the regulation of emotion, sleep and metabolism. Neuropathological and imaging studies using both voxel-based morphometry (VBM) of magnetic resonance imaging (MRI) as well as positron emission tomography (PET) have demonstrated pathological changes in the hypothalamic region during early stages in symptomatic HD. In this investigation, we aimed to establish a robust method for measurements of the hypothalamic volume in MRI in order to determine whether the hypothalamic dysfunction in HD is associated with the volume of this region. Using T1-weighted imaging, we describe a reproducible delineation procedure to estimate the hypothalamic volume which was based on the same landmarks used in histologically processed postmortem hypothalamic tissue. Participants included 36 prodromal HD (pre-HD), 33 symptomatic HD (symp-HD) and 33 control participants who underwent MRI scanning at baseline and 18 months follow-up as part of the IMAGE-HD study. We found no evidence of cross-sectional or longitudinal changes between groups in hypothalamic volume. Our results suggest that hypothalamic pathology in HD is not associated with volume changes.

The role of resting state networks in focal neocortical seizures

Objective

The role of resting state functional networks in epilepsy is incompletely understood. While some pathologic diagnoses have been shown to have maintained but altered resting state connectivity, others have implicated resting state connectivity in disease progression. However little is known about how these resting state networks influence the behavior of a focal neocortical seizure.

Methods

Using data taken from invasively monitored patients with intractable focal neocortical epilepsy, we evaluated network connectivity (as determined by oscillatory covariance of the slow cortical potential (<0.5 Hz)) as it relates to neocortical seizure foci both in the interictal and ictal states.

Results

Similar to what has been shown in the past for sleep and anesthesia, electophysiologic resting state networks that are defined by this slow cortical potential covariance maintain their topographic correlation structure throughout an ictal event. Moreover, in the context of focal epilepsy in which the seizure has a specific site of onset, seizure propagation is not chaotic or random. Rather, the seizure (reflected by an elevation of high frequency power) preferentially propagates along the network that contains the seizure onset zone.

Significance

Taken together, these findings further undergird the fundamental role of resting state networks, provide novel insights into the network-influenced behavior of seizures, and potentially identify additional targets for surgical disconnection including informing the location for the completion of multiple subpial transections (MSPTs).

Functional connectivity of primary motor cortex is dependent on genetic burden in prodromal Huntington disease

Subtle changes in motor function have been observed in individuals with prodromal Huntington disease (prHD), but the underlying neural mechanisms are not well understood nor is the cumulative effect of the disease (disease burden) on functional connectivity. The present study examined the resting-state functional magnetic resonance imaging (rs-fMRI) connectivity of the primary motor cortex (M1) in 16 gene-negative (NEG) controls and 48 gene-positive prHD participants with various levels of disease burden. The results showed that the strength of the left M1 connectivity with the ipsilateral M1 and somatosensory areas decreased as disease burden increased and correlated with motor symptoms. Weakened M1 connectivity within the motor areas was also associated with abnormalities in long-range connections that evolved with disease burden. In this study, M1 connectivity was decreased with visual centers (bilateral cuneus), but increased with a hub of the default mode network (DMN; posterior cingulate cortex). Changes in connectivity measures were associated with worse performance on measures of cognitive-motor functioning. Short- and long-range functional connectivity disturbances were also associated with volume loss in the basal ganglia, suggesting that weakened M1 connectivity is partly a manifestation of striatal atrophy. Altogether, the results indicate that the prodromal phase of HD is associated with abnormal interhemispheric interactions among motor areas and disturbances in the connectivity of M1 with visual centers and the DMN. These changes may, respectively, contribute to increased motor symptoms, visuomotor integration problems, and deficits in the executive control of movement as individuals approach a manifest diagnosis.

Longitudinal resting state fMRI analysis in healthy controls and premanifest Huntington's disease gene carriers: a three-year follow-up study

BACKGROUND

We previously demonstrated that in the premanifest stage of Huntington's disease (preHD), a reduced functional connectivity exists compared to healthy controls. In the current study, we look at possible changes in functional connectivity occurring longitudinally over a period of 3 years, with the aim of assessing the potential usefulness of this technique as a biomarker for disease progression in preHD.

METHODS

Twenty-two preHD and 17 healthy control subjects completed resting state functional magnetic resonance imaging (fMRI) scans in two visits with 3 years in between. Differences in resting state connectivity were examined for eight networks of interest using FSL with three different analysis types: a dual regression method, region of interest approach, and an independent component analysis. To evaluate a possible combined effect of gray matter volume change and the change in blood oxygenation level dependent signal, the analysis was performed with and without voxel-wise correction for gray matter volume. To evaluate possible correlations between functional connectivity change and the predicted time to disease onset, the preHD group was classed as preHD-A if ≥10.9 years and preHD-B if <10.9 years from predicted disease onset. Possible correlations between burden of pathology score and functional connectivity change in preHD were also assessed. Finally, longitudinal change in whole brain and striatal volumetric measures was assessed in the studied cohort.

RESULTS

Longitudinal analysis of the resting state-fMRI (RS-fMRI) data revealed no differences in the degree of connectivity change between the groups over a period of 3 years, though a significantly higher rate of striatal atrophy was found in the preHD group compared to controls in the same period.

DISCUSSION

Based on the results found in this study, the provisional conclusion is that RS-fMRI lacks sensitivity in detecting changes in functional connectivity in HD gene carriers prior to disease manifestation over a 3-year follow-up period.

Neuroimaging in Huntington’s disease

Huntington’s disease (HD) is a progressive and fatal neurodegenerative disorder caused by an expanded trinucleotide CAG sequence in huntingtin gene (HTT) on chromosome 4. HD manifests with chorea, cognitive and psychiatric symptoms. Although advances in genetics allow identification of individuals carrying the HD gene, much is still unknown about the mechanisms underlying the development of overt clinical symptoms and the transitional period between premanifestation and manifestation of the disease. HD has no cure and patients rely only in symptomatic treatment. There is an urgent need to identify biomarkers that are able to monitor disease progression and assess the development and efficacy of novel disease modifying drugs. Over the past years, neuroimaging techniques such as magnetic resonance imaging (MRI) and positron emission tomography (PET) have provided important advances in our understanding of HD. MRI provides information about structural and functional organization of the brain, while PET can detect molecular changes in the brain. MRI and PET are able to detect changes in the brains of HD gene carriers years ahead of the manifestation of the disease and have also proved to be powerful in assessing disease progression. However, no single technique has been validated as an optimal biomarker. An integrative multimodal imaging approach, which combines different MRI and PET techniques, could be recommended for monitoring potential neuroprotective and preventive therapies in HD. In this article we review the current neuroimaging literature in HD.

The multi-modal Australian ScienceS Imaging and Visualization Environment (MASSIVE) high performance computing infrastructure: applications in neuroscience and neuroinformatics research

The Multi-modal Australian ScienceS Imaging and Visualization Environment (MASSIVE) is a national imaging and visualization facility established by Monash University, the Australian Synchrotron, the Commonwealth Scientific Industrial Research Organization (CSIRO), and the Victorian Partnership for Advanced Computing (VPAC), with funding from the National Computational Infrastructure and the Victorian Government. The MASSIVE facility provides hardware, software, and expertise to drive research in the biomedical sciences, particularly advanced brain imaging research using synchrotron x-ray and infrared imaging, functional and structural magnetic resonance imaging (MRI), x-ray computer tomography (CT), electron microscopy and optical microscopy. The development of MASSIVE has been based on best practice in system integration methodologies, frameworks, and architectures. The facility has: (i) integrated multiple different neuroimaging analysis software components, (ii) enabled cross-platform and cross-modality integration of neuroinformatics tools, and (iii) brought together neuroimaging databases and analysis workflows. MASSIVE is now operational as a nationally distributed and integrated facility for neuroinfomatics and brain imaging research.