Functional Magnetic Resonance Imaging in Huntington's Disease

CHAPTER TEN

Functional Magnetic Resonance Imaging in Huntington’s Disease Sarah Gregory, Rachael I. Scahill1 Huntington’s Disease Research Centre, UCL Institute of Neurology, London, United Kingdom 1 Corresponding author: e-mail address: [email protected]

Contents 1. Introduction 1.1 Huntington’s Disease 1.2 Functional MRI 1.3 Task-Based fMRI 1.4 Resting State fMRI 2. Task fMRI Studies in Huntington’s Disease 3. Resting State fMRI Studies in Huntington’s Disease 4. Conclusions Acknowledgment References

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Abstract Huntington’s disease is an inherited neurodegenerative condition characterized by motor dysfunction, cognitive impairment and neuropsychiatric disturbance. The effects of the underlying pathology on brain morphology are relatively well understood. Numerous structural Magnetic Resonance Imaging (MRI) studies have demonstrated macrostructural change with widespread striatal and cortical atrophy and microstructural white matter loss in premanifest and manifest HD gene carriers. However, disease effects on brain function are less well characterized. Functional MRI provides an opportunity to examine differences in brain activity either in response to a particular task or in the brain at rest. There is increasing evidence that HD gene carriers exhibit altered activation patterns and functional connectivity between brain regions in response to the neurodegenerative process. Here we review the growing literature in this area and critically evaluate the utility of this imaging modality.

International Review of Neurobiology, Volume 142 ISSN 0074-7742 https://doi.org/10.1016/bs.irn.2018.09.013

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1. INTRODUCTION 1.1 Huntington’s Disease Huntington’s disease (HD) is an inherited neurodegenerative disease which typically manifests in middle age with a triad of symptoms: motor dysfunction, cognitive impairment and neuropsychiatric disturbance. Individuals with a parent affected by the disease have a 50% risk of inheriting the faulty gene and diagnostic and predictive genetic testing is available. The prevalence of HD in the United Kingdom is estimated to be approximately 12.3 per 100,000 (Evans et al., 2013). There are currently no disease-modifying treatments available for Huntington’s disease but there are a number of promising therapeutic approaches in development and clinical trials are ongoing (Rodrigues & Wild, 2018). The genetic mutation results in expansion of a CAG trinucleotide repeat sequence on chromosome 4, causing production of the mutant huntingtin protein (mHTT). The length of the expansion is inversely proportional to the age of onset and it is possible to estimate the age at which symptoms are likely to appear (Langbehn et al., 2010). Although ubiquitously expressed, the effects of mHTT are most prominent in the gray and white matter of the brain. Both post-mortem and in vivo structural imaging have revealed disease-related atrophy focused in the subcortical regions and degeneration of white matter (Tabrizi et al., 2009, 2011; Vonsattel et al., 1985). As symptoms start to develop there is increasing involvement of the cortical regions (Tabrizi et al., 2011). Structural MRI has revealed volumetric brain changes in gene carriers many years before disease onset (Aylward et al., 2000; Paulsen et al., 2006; Tabrizi et al., 2009); these changes most likely represent not only neuronal loss but also axonal degeneration, demyelination and dendritic pruning prior to cell death. Alongside this structural damage it is likely that neuronal function is also compromised early on in the disease process. At the cellular level there are reductions in the number of neurotransmitter receptors. For example, Positron Emission Tomography (PET) studies have shown reduced dopamine receptors in early and premanifest HD (Pavese et al., 2003, 2010). There are a range of pathogenic processes such as disruption of gene expression, decreased energy production and impaired glutamate release that can lead to synaptic dysfunction (reviewed by Tyebji & Hannan, 2017). Structural neuronal damage and impaired synaptic transmission inevitably disrupt large scale networks within the brain and consequently

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communication between brain regions starts to break down. In the earliest stages of premanifest disease alternative brain networks may be accessed to compensate for this structural damage so that function can be maintained to a certain extent. Eventually these compensatory networks fail and disease symptoms start to manifest themselves. Functional MRI (fMRI) provides a powerful tool to study these networks within the brain and help to elucidate the impact of toxic mHTT on brain function.

1.2 Functional MRI Functional MRI (fMRI) is an imaging technique used primarily in observational studies to investigate brain activity while performing a specific task (task-based fMRI) or during a period of rest (resting state activity). It is used routinely in healthy populations to investigate normal function and in clinical cohorts to understand changes in function related to pathology and disease progression. fMRI utilizes the neurovascular coupling of neural activity and blood flow (Blood Oxygen Level-Dependent; BOLD) to obtain an indirect measure of neuronal activity in response to performing a task or a function. Small increases in brain activity cause increased metabolic activity, which leads to regional increases in blood flow (hemodynamic response). This causes a local shift in the ratio of oxygenated to deoxygenated blood, enabling the measurement of the BOLD fMRI signal. As this signal is an indirect measure of neuronal activity, a derived hemodynamic response function is convolved with the predicted neuronal response and temporally matched to different aspects of a task or network activity. fMRI uses rapid gradient echo planar imaging (EPI) as this facilitates the acquisition of the large number of images necessary to detect the subtle changes in the BOLD signal. Once acquired, the fMRI images are processed using standard imaging software and a pipeline that includes realignment of all EPI images across a time series; co-registration of the EPI images to a high resolution structural image to improve anatomical specificity; normalization into standard space (for group level comparisons) and smoothing to improve the ratio of signal to noise. The resultant data can then be used for most types of analyses for both task-based and resting state fMRI data (in some cases, not all these steps are required).

1.3 Task-Based fMRI Task-based fMRI is used to investigate the spatial distribution of brain activity (the neurovascular response) associated with a particular task or function.

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This can nominally be tested using two types of experimental design: blocked and event-related. Blocked designs are used for basic betweencondition comparisons. Experimental stimuli are presented over long epochs, interspersed with baseline rest epochs and due to the large number of stimuli presented consecutively have a robust signal. Event-related designs conversely measure activity of interest across much shorter, discrete intervals and are therefore more flexible. However, as the measured signal is necessarily weaker, a high number of trials per condition are required. Typically task fMRI analysis involves identifying group differences in activation on a voxel-by-voxel basis, performed within customized neuroimaging software such as Statistical Parametric Mapping (Friston, 2007).

1.4 Resting State fMRI In the absence of a task, resting state fMRI analyses focus on network connectivity; measuring connectivity between regions within networks that are generally congruous with those identified when performing a task or function. Functional connectivity is essentially a descriptive measure which examines the temporal correlations between regional activity across the brain or in specific networks using analysis techniques such as seed-based connectivity, Independent Component Analyses and functional connectomics. Functional connectivity, however, does not measure causality. Effective connectivity can be used to test the causal effects of activity between regions using techniques such as Structural Equation modeling and Dynamic Causal Modeling (Friston, Harrison, & Penny, 2003). It should be noted that while pre-processing of resting state fMRI data is comparable to that of task-based, resting state data are considerably noisier as the low frequency fluctuations that comprise resting state data (and the absence of contrasts which in task-based fMRI eliminate a proportion of the noise) incorporate significant non-neuronal or physiological signals, which require further post-processing to remove. This can be done by including measured cardiac and respiratory signals that are recorded during the scanning session or adjusting the data for this noise by using proxy time series of non-neuronal noise extracted white matter and CSF. Seed-based analyses and independent component analysis are both used to investigate whole-brain network activity. Seed-based analysis is partly hypothesis-driven looking at the correlation between activity within a specific, pre-defined region and that across the rest of the brain. In choosing a specific seed region, such as the primary motor cortex, the nature of the

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behavior of the associated network(s) can then be examined. Independent component analysis, alternatively is a purely data-driven approach whereby the signals within the fMRI data are separated into orthogonal components each of which represent a set of temporally correlated data comprising maps depicting either functional networks or noise. Finally, functional connectomics uses either a hypothesis-driven or purely datadriven approach to investigate whole-brain connectivity and is traditionally analyzed using graph theory metrics. The brain is parcellated into a number of regions using a pre-specified atlas and connections between every set of regions are calculated to produce a large connectivity matrix. Data decomposition is generally performed on these data to enable interpretation. Alternatively, empirical evidence can be used to limit the number of connections that form the basis for the analysis once the matrices have been produced. There are a number of techniques available which can be used to measure effective connectivity within resting state networks. A technique which is being increasingly applied to rsfMRI data is Dynamic Causal Modeling, which can be used to infer the underlying causal effects of regions within a particular network. This requires pre-selecting the most biologicallyplausible regions within a network that are also relevant for a particular question or clinical phenotype. The neuronal activity within each region is modeled and directed connections between these regions are estimated. Again, these connectivity parameters can be analyzed using data reduction techniques or at the group level.

2. TASK FMRI STUDIES IN HUNTINGTON’S DISEASE Many studies have shown differences in activation patterns in both premanifest and manifest HD participants in comparison to healthy controls (see Table 1 for summary of studies). Activation may be elevated or reduced and this varies not only according to disease stage but also the task being presented and the regions of the brain being examined. Consequently there may appear to be inconsistencies between studies and interpretation is often complex. The motor system has been examined using a finger tapping task with varying levels of speed and complexity (Kl€ oppel et al., 2009). Fifteen premanifest gene carriers without motor impairment and 12 healthy controls performed button presses in time with a metronome, following a prelearnt sequence. The gene carriers showed increased activation in the left caudal

Table 1 Task fMRI Studies in HD Publication Design

Domı´nguez et al. (2017)

Cohort

Executive function shifting 29 controls 35 preHD response set task with 18 symp-HD 30 months follow-up

Findings

No longitudinal changes in preHD and controls. Symp-HD showed increasing deactivation in the anterior cingulate, striatum and DMN. Decline in activation in right DLPFC associated with impaired executive functioning and behavioral dysregulation in gene carriers

Georgiou-Karistianis Simon interference task et al. (2007)

17 controls 20 symp-HD

Hyperactivation in manifest HD compared with controls and additional recruitment of frontal and parietal regions

Georgiou-Karistianis N-BACK WM memory et al. (2013) task with 18 months follow-up (1-BACK and 0-BACK only)

23 controls 27 preHD 17 symp-HD

PreHD showed increases in activation over time in 1-BACK compared with 0-BACK. Longitudinal increases in activation in DLPFC compared with controls

Georgiou-Karistianis N-BACK WM memory et al. (2014) task

32 controls 35 preHD 23 symp-HD

Reduced activation in combined gene carrier group with greater involvement in 2-BACK condition. Symp-HD increased activation in DLPFC for 1-BACK but decreased activation in DLPFC for 2-BACK

Gray et al. (2013)

Executive function shifting 35 controls response set task and 35 preHD 30 symp-HD association with neuropsychiatric symptoms

Little difference in activation between preHD and controls. Symp-HD both hyper and hypoactivation in PFC; larger differences associated with greater cognitive load. Deactivation in PFC associated with greater neuropsychiatric disturbance

Hennenlotter et al. (2004)

Facial recognition of disgust

Controls showed task-related activation in the left dorsal anterior insula and putamen. No activation in the preHD

9 controls 9 preHD

Kl€ oppel et al. (2009) Motor finger tapping task 12 controls with variation in speed and 15 preHD complexity

Increased activation in SMA in preHD. Closest to onset showed increased activation in SMA and superior parietal regions and decreased activity in rostral SMA

Kl€ oppel et al. (2015)a Motor finger tapping task 111 controls 106 No significant disease effects in motor task. Increased with variation in speed and preHD 22 symp- activation in response to WM task as atrophy increased, suggesting compensation complexity and N-BACK HD WM task Malejko et al. (2014) Reward task

18 controls 14 pre/symp

Gene carriers showed increased activation in the ventral striatum and orbitofrontal cortex

Novak et al. (2012)

14 controls 16 preHD

PreHD deactivation in three functional networks and increased activity in frontal regions

7 controls 14 preHD

Hypoactivation in subcortical structures in preHD close to onset, hyperactivation in anterior cingulate and preSMA in preHD far from onset

Facial emotion processing

Paulsen et al. (2004) Time discrimination task

Poudel et al. (2015)

32 controls N-BACK WM task and 35 preHD association with neuropsychiatric symptoms

In preHD close to onset deactivation associated with OCD and depressive symptoms. In further from onset only association with depressive symptoms during 2-BACK condition

Poudel et al. (2015)

N-BACK WM task with 30 month follow-up

No longitudinal change in controls or symp-HD but preHD showed progressive increases in activation in both conditions. Longitudinal change in functional connectivity between DLPFC and caudate associated with DBS and estimated years to onset

20 controls 22 preHD 11 symp-HD

Continued

Table 1 Task fMRI Studies in HD—cont’d Publication Design

Cohort

Findings

Reading et al. (2004) Letter interference task

6 controls 7 preHD

PreHD showed reduced activation in the left anterior cingulate compared with controls

Saft et al. (2008)

Auditory processing task

34 controls 18 preHD 16 symp-HD

Symp-HD and preHD far from onset showed increased activation in subcortical structures. PreHD close to onset showed hypoactivation

Saft et al. (2013)

Cartoon mentalizing task

30 controls 26 preHD

No differences in activation between preHD and controls in response to task

Unschuld et al. (2012)

Stroop interference task and association with depressive symptoms

52 controls 32 preHD

Activity in the ventromedial PFC correlated with depressive symptoms and strength of association greater with increasing CAG repeat length

Unschuld et al. (2013)

Tower of London executive task with different levels of complexity

52 controls 41 preHD 12 symp-HD

Combined gene carrier group showed reduction in connectivity between the medial PFC and left premotor region. Task complexity moderated reduction in connectivity

Van den Stock et al. Mood induction task (2015)

20 controls 20 preHD

PreHD showed increased activation in response to anger in the pulvinar, cingulate and somatosensory regions

Verbal WM task Wolf, Vasic, Scho, Landwehrmeyer, and Ecker (2007)

16 controls 16 preHD

Decreased activation in DLPFC in preHD compared with controls. Increased activation in those closest to onset in left inferior parietal and right superior frontal regions

Wolf et al. (2008a)

Verbal WM task

16 controls 16 preHD

PreHD showed disruption of the frontostriatal and frontoparietal networks

Wolf et al. (2008b)

Verbal WM task

16 controls 16 preHD

Decreased functional connectivity in the DLPFC associated with increasing WM load

Verbal WM task Wolf, Vasic, Sch€ onfeldt-Lecuona, Ecker, and Landwehrmeyer (2009)

16 controls 12 symp-HD

Reduced activation in dorso and ventrolateral PFC and inferior parietal region in symp-HD compared with controls

Wolf et al. (2011)

Verbal WM task with 24 month follow-up

13 controls 13 preHD

No evidence of change in activation over time in either group

Wolf, Sambataro, et al. (2012)

Alertness task

18 controls 18 preHD

Increased functional connectivity within the DMN in preHD compared with controls

Wolf, Gr€ on, et al. (2012)

Alertness task

18 controls 18 preHD

PreHD close to onset showed deactivation of the frontostriatal and striatal regions

Wolf, Sambataro, Vasic, Wolf, et al. (2014)

Verbal WM task with 24 month follow-up

13 controls 13 preHD

Lower functional connectivity in the task-negative posterior cingulate and higher functional connectivity in the left anterior PFC in preHD. Higher connectivity in dorsal cingulate over time in preHD

Zimbelman et al. (2007)

Time reproduction task

13 controls 26 preHD

PreHD far from onset showed reduced activation in anterior cingulate and increased activation in several regions. PreHD close to onset showed decreased activation in the left putamen, SMA, left insula and right inferior frontal gyrus

preHD, premanifest gene carriers; symp-HD, manifest HD patients; DMN, default mode network; DLPFC, dorsolateral prefrontal cortex; WM, working memory; PFC, prefrontal cortex; SMA, supplementary motor area; OCD, obsessive compulsive disorder; DBS, disease burden score. a Multi-site study.

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Fig. 1 Areas displaying differential activations with group membership for a finger tapping task. The plot below depicts condition specific activations compared with rest for indicated voxels in arbitrary units. Error bars represent one SEM, activations are displayed at P < 0.01; uncorrected (voxel extent ¼ 50). Figure reproduced from Kloppel, S., Draganski, B., Siebner, H. R., Tabrizi, S. J., Weiller, C., & Frackowiak, R. S. J. (2009). Functional compensation of motor function in pre-symptomatic Huntingtons disease. Brain, 132(6), 1624–1632. http://doi.org/10.1093/brain/awp081 courtesy of Oxford University Press.

supplementary motor area with all conditions (see Fig. 1). There was greater activation in the supplementary motor area and superior parietal regions with increasing speed in those approaching onset. Conversely, there was decreased activation in the rostral supplementary motor area with increasing complexity in those closest to disease onset. The left superior parietal lobe showed increasing activation with increasing complexity and the right superior parietal showed reduced activation in all conditions except the most demanding. This study demonstrates the complex patterns of both hyper- and hypoactivation which can characterize the premanifest phase of the disease.

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When a similar motor task was employed in a larger multi-site premanifest cohort, no significant disease effects could be detected (Kl€ oppel et al., 2015). It is possible that the inclusion of data from four different sites introduced a degree of variability that masked the real signal, although the earlier study did not correct for multiple comparisons and it is possible that disease effects were not actually that strong. This same multi-site cohort also performed a working memory task, the N-BACK, where participants are shown a sequence of stimuli and asked to recall either the previous stimulus (1-BACK) or the one before that (2-BACK). Premanifest gene carriers showed increased performance-related activity in response to the task as atrophy increased. It was suggested that this increased activation was a compensatory response to ongoing structural atrophy in order to maintain performance. Other investigators have also demonstrated a disease-related effect on activation in response to the N-BACK test in both premanifest and early HD participants compared with controls (Georgiou-Karistianis et al., 2014). A number of regions including the inferior frontal gyrus, anterior insula and the striatum showed reduced activation across the combined whole group of gene carriers, with more extensive involvement in the 2-BACK condition. Examination of the separate groups revealed differential patterns with the symptomatic group showing increased activation in the dorsolateral prefrontal cortex for the 1-BACK but decreased activation in this region for the 2-BACK condition. When these participants were followed up longitudinally interestingly there were no differences between early HD and controls (Poudel et al., 2013) but the premanifest cohort showed progressive increase in activation in the dorsolateral prefrontal cortex and frontal regions over 18 months (Georgiou-Karistianis et al., 2013) and over 30 months (Poudel et al., 2013) during the 1-BACK test and also increased activation in the striatum and temporal cortex in the 2-BACK (Poudel et al., 2013). There was decreased functional connectivity between the dorsolateral prefrontal cortex and the caudate in both conditions in the premanifest cohort and longitudinal change was associated with disease burden and estimated years to disease onset. Another study investigating a verbal working memory task showed decreased activation in the dorsolateral prefrontal cortex at higher cognitive load in 16 premanifest gene carriers compared with 16 controls (Wolf et al., 2007). Those closest to estimated disease onset showed increased activation in the left inferior parietal lobe and right superior frontal gyrus. Two year follow-up of 13 gene carriers and 13 controls from the original cohort

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replicated the finding of decreased activation of the dorsolateral prefrontal cortex, although there was no evidence of progressive reduction over this time period (Wolf et al., 2011). Functional connectivity analysis of the cross-sectional dataset suggested that premanifest gene carriers showed disruption of the frontostriatal and frontoparietal networks (Wolf et al., 2008a). Decreased functional connectivity in the dorsolateral prefrontal cortex was also associated with increased working memory load (Wolf et al., 2008b). When this verbal working memory task was applied in an early HD cohort, compared with controls, they showed large areas of reduced activation including the dorso and ventrolateral prefrontal cortex and inferior parietal regions, after controlling for atrophy (Wolf et al., 2009). Although the authors excluded incorrectly performed trials, the patients were slower and less accurate for all working memory loads, and this needs to be taken into consideration when interpreting activation patterns. Task-negative networks can also reveal interesting alterations in activity patterns. Wolf, Sambataro, Vasic, Wolf, et al. (2014) demonstrated lower functional connectivity in the posterior cingulate and higher functional connectivity in the left anterior prefrontal cortex in premanifest gene carriers compared with controls using the same verbal working memory task. When followed up over 2 years the premanifest cohort showed higher connectivity in the dorsal cingulate over time and these differences were inversely correlated with change in motor score. Cognitive systems involved in executive function have been probed using an fMRI study of the Tower of London test with different levels of complexity (Unschuld et al., 2013). Compared with 52 controls, a group of 12 early HD and 41 premanifest HD showed a task-related reduction in connectivity between the medial prefrontal cortex and the left premotor region; connectivity reduction was moderated by task complexity. Cognitive flexibility has been investigated using a shifting response set task (Gray et al., 2013). There was very little difference between premanifest gene carriers and controls. However, the symptomatic HD patients exhibited a complex pattern of both increased and decreased prefrontal activation compared with controls and premanifest gene carriers. Deactivation was associated with increasing cognitive challenge. When the same cohort were followed up over a period of 30 months there were no longitudinal changes in activity related to the shifting response set task in either the controls or the premanifest gene carrier groups. In contrast, the symptomatic HD group showed greater reduction in activity over time in the anterior cingulate, striatum and in regions from the default mode network (Domı´nguez et al., 2017).

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Paulsen et al. (2004) found differences in activation across the premanifest phase using a time discrimination task in a small cohort. Participants were presented with two tones separated by 1200 ms and after a 1 s delay another comparison pair of tones. They had to estimate whether the time interval was shorter or longer than the first. They found that those close to estimated disease onset had reduced activation in the subcortical structures compared with controls in response to the task. Those far from onset had intermediate activation between controls and those close to onset in these regions. However, those far from onset appeared to have hyperactivation in the anterior cingulate and presupplementary motor area and the authors suggest that this may represent a compensatory mechanism. Using an expanded cohort from the same study, Zimbelman et al. (2007) explored another time discrimination task. They used a block design to alternate between three conditions: first participants were asked to tap their finger in response to a pulse, next to continue tapping at the same rate but without the auditory cue and the third condition was a rest phase. In contrast to the findings by Paulsen et al., those far from onset displayed reduced activation in the anterior cingulate. This cohort also showed increased activation in several regions including the left sensorimotor, left medial frontal and left precentral gyrus. The close to onset group showed decreased activation in the left putamen, supplementary motor area, left insula and right inferior frontal gyrus. The contrast between these two studies which had several participants in common illustrates how task design can influence results, even when the task is interrogating a very similar function. Emotional processing is known to be impaired early on in Huntington’s disease (Tabrizi et al., 2009). One early study investigated activation in response to facial expressions of disgust in a small group of premanifest gene carriers and controls (Hennenlotter et al., 2004). In healthy controls, processing of disgust was associated with significant activation of the left dorsal anterior insula and putamen; there was no significant activation in this region in the gene carriers. However, this premanifest cohort already seemed to be exhibiting behavioral impairment in emotional processing which is likely to have impacted the results. Another study (Novak et al., 2012) examined response to facial expressions in 14 controls and 16 premanifest gene carriers where there were no behavioral group differences in out-of-scanner testing of emotional processing. The premanifest cohort exhibited reduced neural activity in three partially separable functional networks as well as increased activity in frontal regions, in particular the middle frontal gyri.

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Huntington’s disease patients also exhibit attentional deficits and this function was probed in an alertness task where participants were instructed to press a button in response to the appearance of a cross on a screen (Wolf, Gr€ on, et al., 2012). Using a block design participants first had to respond to a cross presented at random time intervals and in the second condition the appearance of the cross was preceded by an auditory cue. Premanifest gene carriers closer to disease onset showed reduced activation in the right frontostriatal and striatal regions. There was also lower functional connectivity in the motor regions and lower activity in the putamen. Using the same task these authors identified increased connectivity within the default mode network and they suggest that this network may remain active in order to maintain cognitive performance in premanifest gene carriers (Wolf, Sambataro, et al., 2012). Attentional deficits are also evident in interference tasks. For example, one early study found that premanifest gene carriers showed reduced activation in the anterior cingulate region in response to an interference task presenting large letters made up of small letters (Reading et al., 2004). Using a Simon interference task with congruent and incongruent stimuli, another study demonstrated that manifest HD patients have large areas of hyperactivation compared with controls and additionally recruited frontal and parietal regions (Georgiou-Karistianis et al., 2007). There have also been functional MRI studies showing disease-related activation differences in response to a range of other tasks such as auditory processing (Saft et al., 2008), reward (Malejko et al., 2014) and a mood induction task (Van den Stock et al., 2015). However, no differences were found between premanifest gene carriers in controls in terms of brain activity in response to a mentalizing task (Saft et al., 2013). A number of studies have related brain activity to HD symptoms, most often neuropsychiatric disturbances. For example, the IMAGE-HD study (Poudel et al., 2015) examined how obsessive compulsive disorder and depressive symptoms affected brain activity when performing the N-BACK working memory task. In 18 close to onset premanifest gene carriers obsessive compulsive disorder and depressive symptoms were associated with decreased activity. This was evident in both the 1-BACK and 2-BACK conditions. However, in those furthest from onset there was no association between obsessive compulsive disorder and brain activity and depressive symptoms correlated with decreased activity only when there was greater cognitive load, i.e., in the 2-BACK condition. Another study found depressive symptoms correlated with activation of the ventromedial prefrontal cortex during

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the Stroop interference task (Unschuld et al., 2012). The strength of this correlation was greater with longer CAG repeat lengths. Reduced prefrontal activation in symptomatic HD patients in response to the attentional control shifting response set task was associated with increased neuropsychiatric disturbance including pathological impulses, disinhibition and depression (Gray et al., 2013). When followed up over 30 months a combined group of premanifest and symptomatic gene carriers showed a decline in activation in the right dorsolateral prefrontal cortex and putamen which was associated with impaired executive functioning and behavioral dysregulation (Domı´nguez et al., 2017).

3. RESTING STATE FMRI STUDIES IN HUNTINGTON’S DISEASE Resting State fMRI has been increasingly used to examine functional networks in HD populations over the past 5 years. This has focused mainly on functional connectivity using seed-based and independent component analysis approaches, with a recent increase in those studies looking at the entire connectome (see Table 2 for summary of studies). Table 2 Resting State fMRI Studies in HD Publication Design Cohort

Findings

Reduced connectivity within the medial visual network for pre and manifest HD; reduced connectivity in the DMN and executive networks in HD only

Dumas et al. (2013)

ICA

28 controls 28 preHD 20 symp-HD

Espinoza et al. (2018)a

ICA

Reduced within-putaminal and 73 controls putaminal-insular connectivity 183 preHD (23 converted) (correlated with worsening motor and cognitive performance). Reduced local visual connectivity, but increased long-range frontooccipital connectivity

Gargouri et al. (2016)

Connectomics 18 controls 24 preHD 18 symp-HD

Reduced global efficiency and network robustness in the somatosensory cortex in symp-HD, but not preHD. No longitudinal changes Continued

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Table 2 Resting State fMRI Studies in HD—cont’d Publication Design Cohort Findings

94 preHD 16 symp-HD

Gregory et al. (2018)a

Seed-based connectivity DCM

Harrington et al. (2015)

Connectomics 16 controls 48 preHD

Kl€ oppel et al. (2015)a

Seed-based connectivity DCM

Liu et al. (2016) ALFF

Global cognition associated with increased effective connectivity between the left and right DLPFC and motor performance associated with increased connectivity between the left and right premotor cortex-evidence of longitudinal compensation Reduced connectivity in hub regions. Functional segregation maintained locally and globally, but reduction in long-range frontostriatal and frontoparietal connectivity as disease burden increased

111 controls Compensation in the right hemisphere with increased 128 preHD (22 converted) functional coupling between the right DLPFC and the left cognitive network to predict better cognitive performance, despite neuronal loss 26 controls 10 symp-HD

Reduced LFF in precuneus and increased LFF in the temporal gyrus both correlating with worsening cognitive performance

McColgan, Gregory, et al. (2017)a

Connectomics 66 controls 64 preHD

Strong structural connectivity predicts reduced functional connectivity in preHD (and vice-versa), while connectivity in anterior brain regions was higher than that posteriorly

McColgan, Razi, et al. (2017)

Connectomics 94 controls 92 preHD

Depression correlates with increased connectivity in both the DMN and basal ganglia

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Table 2 Resting State fMRI Studies in HD—cont’d Publication Design Cohort Findings

M€ uller et al. (2016)

Seed-based connectivity

32 controls 34 symp-HD

Reduced connectivity between M1 and insula, as part of the motor network, correlating with motor scores; reduced connectivity within basal ganglia and between basal ganglia and insula

Odish et al. (2015)

ICA

17 controls 22 preHD

No change in connectivity over 3 years in preHD

Poudel et al. (2014)

ICA

18 controls 25 preHD 23 symp-HD

Reduced connectivity in DAN (correlating with worse cognitive performance) and executive function network in symp-HD. PreHD showed reduced connectivity in DAN and sensorimotor network

Quarantelli et al. (2013)

Seed-based connectivity

22 controls 26 symp-HD

Reduced positive correlation between PCC and VM PFC (corr. with Stroop test performance), right DM PFC and right inferior parietal cortex; and reduced negative correlation with bilateral inferior parietal cortex. Increased correlation with mid occipital gyrus

Sa´nchezSeed-based Castan˜eda et al. connectivity (2017)

10 symp-HD

Increased connectivity somatosensory and DFN that was reduced following treatment with Pridopidine (four tested for treatment effects)

ICA Wolf, Sambataro, Vasic, Depping, et al. (2014)

20 controls 21 symp-HD

Increased connectivity in SMA (corr. with worsening motor performance), bilateral caudate and inferior and middle frontal cortices (corr. with improved cognitive performance). Reduced connectivity in parietal and frontal regions in different RSNs Continued

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Table 2 Resting State fMRI Studies in HD—cont’d Publication Design Cohort Findings

Wolf, Sambataro, Vasic, Baldas, et al. (2014)

ICA

20 controls 20 symp-HD

Reduced connectivity in the left lower fusiform gyrus correlating with higher disease burden and poorer cognitive performance

Wolf et al. (2015)

Seed-based connectivity

20 controls 20 symp-HD

Reduced connectivity between right cerebellar region and increased coupling with the paracentral gyrus (correlating with DBS and clinical motor scores), precuneus and right inferior frontal/insula

Werner et al. (2014)

ICA

19 controls 17 symp-HD

Increased widespread shortrange connectivity esp. in motor and parietal regions, correlating with motor impairment; and striatal, thalamic and frontal regions, correlating with worsening function. Long-range connectivity was reduced

ICA, independent component analysis; preHD, premanifest gene carriers; symp-HD, manifest HD patients; DMN, default mode network; DCM, dynamic causal modeling; DLPFC, dorsolateral prefrontal cortex; ALFF, amplitude of low frequency fluctuations; DAN, dorsal attention network; PCC, posterior cingulate cortex; VM, ventromedial; PFC, prefrontal cortex; DM, dorsomedial; SMA, supplementary motor area; RSN, resting state network; DBS, disease burden score. a Multi-site study.

Studies using a seed-based approach have tended to focus on networks related to the HD phenotype, such as motor and cognitive, plus the default mode network (DMN), a “task-negative” network that becomes more active when the brain is at rest, and which, although not specifically relevant to HD, has been shown to be affected early on in other neurodegenerative disorders, in particular Alzheimer’s disease. As such, one of the earliest studies in manifest HD gene carriers used the posterior cingulate cortex—a central region within the DMN—as a seed of interest, showing reduced connectivity between the posterior cingulate cortex and both the ventromedial and dorsomedial prefrontal cortices (the former correlating

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with Stroop test performance) and the inferior parietal cortex, all key regions within the DMN, suggesting abnormal connectivity when the brain is at rest (Quarantelli et al., 2013). However, another study using the posterior cingulate cortex as a seed region for the DMN and the supplementary motor area as a seed region for the somatosensory network showed an aberrant network-wide increase in connectivity in HD that preceded volume loss and that was reduced in four patients undergoing Pridopidine treatment (Sa´nchez-Castan˜eda et al., 2017). The motor network has shown equally complex patterns in manifest HD, using seedbased approaches, with reduced connectivity between the primary motor cortex (M1) and insula, correlating with clinical motor scores; within the basal ganglia and between the basal ganglia and the insula (M€ uller et al., 2016) and between the cerebellum and paracentral gyrus correlating with disease burden and clinical motor scores (Wolf et al., 2015). It should be noted that many of these studies adjusted for cortical and/or subcortical volume. This, however, had little effect on the results indicating that changes in connectivity were independent of neuronal loss. Independent component analysis has been used more commonly in resting state studies of HD populations. Given the lack of conclusive evidence in terms of resting state changes when using seed-based analysis, a datadriven approach that interrogates all networks may prove more useful in trying to understand functional changes in HD—at least in the first instance. However, similarly to the seed-based studies, the evidence is still somewhat mixed with manifest HD cohorts demonstrating both increases and decreases in connectivity across a series of networks, often with conflicting correlations with behavior. Reduced connectivity between frontal and motor cortex and a region in the medial visual network was evident in both manifest and premanifest HD groups, with additional connectivity reductions in the deep grey matter and occipital cortex for manifest HD only (Dumas et al., 2013). Similarly reduced visual connectivity in the lower fusiform gyrus correlated with both disease burden and symbol digit modalities test (SDMT) performance, suggesting an impact of reduced connectivity within the visual network on visual function (Wolf, Sambataro, Vasic, Depping, et al., 2014). There was also reduced connectivity in the dorsal attention network, correlating with worsening cognitive function, abnormal connectivity between the posterior putamen and superior parietal cortex and the frontal executive network—differences that were not evident in premanifest groups—and also in the DMN (Dumas et al., 2013; Poudel et al., 2014). Furthermore, reduced

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amplitude of low frequency fluctuations (ALFF) in the right precuneus and angular gyrus correlated with reduced cognitive performance in the Stroop and SDMT (Liu et al., 2016). However, the same studies also detected concomitant increases in frontoparietal coupling—part of the network putatively associated with attention—compared to premanifest HD (Poudel et al., 2014), while increased ALFF in the temporal gyrus correlated with worsening cognitive performance (Liu et al., 2016). This complex picture was also evident in another study using the independent component analysis approach, which despite revealing some decreases in frontal connectivity within specific networks, did also show increases in supplementary motor area and the inferior and middle frontal gyri, which correlated with worsening motor and improved cognitive performance, respectively (Wolf, Sambataro, Vasic, Baldas, et al., 2014). Furthermore, increased connectivity in motor and parietal cortices correlated with motor impairment, and increased striatal, frontal, thalamic and insular connectivity correlated with worsening function; long-range connections between parietal regions were reduced (Werner et al., 2014). Premanifest HD groups displayed similar reductions in connectivity with a decrease of within-putaminal and putamen-insula connectivity as CAG length increased, the latter correlated with motor and cognitive performance, while visual networks showed increasing fronto-occipital connectivity as CAG increased, but reductions in local visual cortex with increasing CAG length (Espinoza et al., 2018). Premanifest gene carriers also showed reduced connectivity in the somatosensory cortex and dorsal attention network, the former of which correlated with motor performance (Poudel et al., 2014). Only one study has directly analyzed functional connectivity in this way over time, and over a 3 year period using independent component analysis found no change in connectivity within a premanifest HD cohort; this could represent genuine absence of alterations in connectivity or more likely, an inability to detect subtle change in a slowly progressing disease, particularly during the early stages (Odish et al., 2015). Recently, there has been a movement toward using connectomic approaches which allow examination of connectivity between parcellated regions across the whole-brain and which can subsequently be analyzed using graph theory. In this way, premanifest gene carriers were shown to exhibit reduced connectivity between highly connected “rich club” regions—hub areas that are key to the integration of diverse processing.

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Functional segregation, i.e., the grouping of distinct pockets of neurons that work together to facilitate a function, was essentially maintained both locally and globally (Harrington et al., 2015). Network-based statistics also showed a reduction in long-range frontostriatal and frontoparietal connectivity as disease burden increased; a finding which strongly correlated with the rich club findings and is suggestive of the mediation of executive control. Another study that used graph theory to analyze the connectome with over 182 regions showed reduced path length (marker of global efficiency) and clustering/betweenness centrality (markers of network robustness) in the somatosensory cortex, while degree (the number of connections) was increased in all networks (Gargouri et al., 2016). There were no equivalent changes in premanifest HD, however, despite connectivity reductions in the hub regions of both the somatosensory and associative networks (and which were no longer even detectable in HD). There were also no longitudinal changes, again raising the question of whether this represented a genuine absence of change, or the inability of the technique to detect such subtle effects. Finally, strong structural connectivity was shown to predict reduced functional connectivity in preHD (and vice versa), while connectivity in anterior brain regions was higher than that posteriorly, indicating a gradient effect of pathology (McColgan, Gregory, et al., 2017). Furthermore, in the same cohort, depression correlated with increased connectivity in both the DMN and basal ganglia (McColgan, Razi, et al., 2017) (Fig. 2). Finally, a subset of studies has used resting state fMRI in conjunction with task-based fMRI to examine compensatory effects in HD. Compensation is the process purported to underlie the maintenance of normal performance in neurodegeneration populations despite the presence of pathology. Using a model which characterizes changes in brain activity and behavior in the presence of neuronal loss, a cross-sectional analysis of premanifest HD showed that as atrophy increased, functional coupling between the right dorsolateral prefrontal cortex and the left cognitive network predicted better cognitive performance; this was not the case in the motor network (Kl€ oppel et al., 2015). Following from this, longitudinal compensation in the same cohort showed that maintained global cognition was associated with increased effective connectivity between the left and right dorsolateral prefrontal cortex, a central region in cognitive processing, while maintained motor performance was associated with increased connectivity between the left and right premotor cortex (Gregory et al., 2018).

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Fig. 2 Functional regulation analysis. For each brain region in the average control network, correlations were performed against the strength of functional connection to all other 75 regions in the network (where a functional connection was present) and average group differences (preHD minus controls) in these functional connections. Upregulation is defined as a positive correlation (stronger control connections show greater increases in preHD), whereas downregulation is defined as a negative correlation (stronger control connections show greater decreases in preHD). Brain regions that show significant positive (green) and negative (purple) correlations are highlighted. The size of the sphere represents the number of structural connections (thus largest spheres indicate hub brain regions). Figure reproduced from McColgan, P., Gregory, S., Razi, A., Seunarine, K. K., Gargouri, F., Durr, A., et al. (2017). White matter predicts functional connectivity in premanifest Huntington’s disease. Annals of Clinical and Translational Neurology, 4(2), 106–118. https://doi.org/10.1002/acn3.384.

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4. CONCLUSIONS This review of functional MRI has demonstrated that both task and rsfMRI show sensitivity to disease effects in HD. Task fMRI aims to identify whether gene carriers increase activation in the same regions as healthy controls and/or access alternative networks in order to maintain performance for a given task. Variability in task performance can confound activation patterns so most studies ensure that behavioral performance is matched between gene carriers and healthy controls, even applying an accuracy threshold if necessary (Gray et al., 2013). For this reason task fMRI may prove more useful during the premanifest phase prior to the onset of widespread functional deficits. Resting state fMRI can potentially avoid the issue of variability in task performance by examining activation patterns at rest. Consistency of acquisition and in particular instructions given to participants is vital for both types of study to minimize inter-individual variability and to date there are relatively few multi-site studies which have succeeded in standardizing across different centers (Espinoza et al., 2018; Kl€ oppel et al., 2015; McColgan, Gregory, et al., 2017; McColgan, Razi, et al., 2017). In some cases findings from small single site studies have not been entirely replicated in larger cohorts (Paulsen et al., 2004; Zimbelman et al., 2007) or across multiple sites (Kl€ oppel et al., 2009, 2015). The clinical utility of fMRI is still to be established and currently it remains predominantly a research tool. Although sensitive to subtle disease effects, its power to discriminate between groups is relatively weak. While one study demonstrated discrimination using motor sequence tapping and irritability tasks (Abdulkadir et al., 2013), Vives-Gilabert et al., using functional connectivity metrics for classification, showed only chance-level accuracy (Vives-Gilabert et al., 2013). There is, however, considerable interest in rsfMRI in clinical trials and this modality is already being used as an exploratory endpoint in a number of ongoing studies, since it has the advantage of avoiding impaired behavioral performance and therefore can be applied across the spectrum of HD as long as patients are able to tolerate scanning. Advances in acquisition and further standardization across multiple sites as well as results from ongoing clinical trials will help us to evaluate its future clinical application.

ACKNOWLEDGMENT R.S. and S.G. are supported by a Wellcome Trust Collaborative Award (200181/Z/15/Z).

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