Elisa Scheller

Compensation in Preclinical Huntington's Disease: Evidence From the Track-On HD Study

Background Cognitive and motor task performance in premanifest Huntingtons disease (HD) gene-carriers is often within normal ranges prior to clinical diagnosis, despite loss of brain volume in regions involved in these tasks. This indicates ongoing compensation, with the brain maintaining function in the presence of neuronal loss. However, thus far, compensatory processes in HD have not been modeled explicitly. Using a new model, which incorporates individual variability related to structural change and behavior, we sought to identify functional correlates of compensation in premanifest-HD gene-carriers. Methods We investigated the modulatory effects of regional brain atrophy, indexed by structural measures of disease load, on the relationship between performance and brain activity (or connectivity) using task-based and resting-state functional MRI. Findings Consistent with compensation, as atrophy increased performance-related activity increased in the right parietal cortex during a working memory task. Similarly, increased functional coupling between the right dorsolateral prefrontal cortex and a left hemisphere network in the resting-state predicted better cognitive performance as atrophy increased. Such patterns were not detectable for the left hemisphere or for motor tasks. Interpretation Our findings provide evidence for active compensatory processes in premanifest-HD for cognitive demands and suggest a higher vulnerability of the left hemisphere to the effects of regional atrophy.

Differential effects of age on subcomponents of response inhibition

Inhibitory deficits contribute to cognitive decline in the aging brain. Separating subcomponents of response inhibition may help to resolve contradictions in the existing literature. A total of 49 healthy participants underwent functional magnetic resonance imaging (fMRI) while performing a Go/no-go-, a Simon-, and a Stop-signal task. Regression analyses were conducted to identify correlations of age and activation patterns. Imaging results revealed a differential effect of age on subcomponents of response inhibition. In a simple Go/no-go task (no spatial discrimination), aging was associated with increased activation of the core inhibitory network and parietal areas. In the Simon task, which required spatial discrimination, increased activation in additional inhibitory control regions was present. However, in the Stop-signal task, the most demanding of the three tasks, aging was associated with decreased activation. This suggests that older adults increasingly recruit the inhibitory network and, with increasing load, additional inhibitory regions. However, if inhibitory load exceeds compensatory capacity, performance declines in concert with decreasing activation. Thus, the present findings may refine current theories of cognitive aging.

Diagnostic features of emotional expressions are processed preferentially.

Diagnostic features of emotional expressions are differentially distributed across the face. The current study examined whether these diagnostic features are preferentially attended to even when they are irrelevant for the task at hand or when faces appear at different locations in the visual field. To this aim, fearful, happy and neutral faces were presented to healthy individuals in two experiments while measuring eye movements. In Experiment 1, participants had to accomplish an emotion classification, a gender discrimination or a passive viewing task. To differentiate fast, potentially reflexive, eye movements from a more elaborate scanning of faces, stimuli were either presented for 150 or 2000 ms. In Experiment 2, similar faces were presented at different spatial positions to rule out the possibility that eye movements only reflect a general bias for certain visual field locations. In both experiments, participants fixated the eye region much longer than any other region in the face. Furthermore, the eye region was attended to more pronouncedly when fearful or neutral faces were shown whereas more attention was directed toward the mouth of happy facial expressions. Since these results were similar across the other experimental manipulations, they indicate that diagnostic features of emotional expressions are preferentially processed irrespective of task demands and spatial locations. Saliency analyses revealed that a computational model of bottom-up visual attention could not explain these results. Furthermore, as these gaze preferences were evident very early after stimulus onset and occurred even when saccades did not allow for extracting further information from these stimuli, they may reflect a preattentive mechanism that automatically detects relevant facial features in the visual field and facilitates the orientation of attention towards them. This mechanism might crucially depend on amygdala functioning and it is potentially impaired in a number of clinical conditions such as autism or social anxiety disorders.

Attempted and successful compensation in preclinical and early manifest neurodegeneration - a review of task fMRI studies

Several models of neural compensation in healthy aging have been suggested to explain brain activity that aids to sustain cognitive function. Applying recently suggested criteria of “attempted” and “successful” compensation, we reviewed existing literature on compensatory mechanisms in preclinical Huntington’s disease (HD) and amnestic mild cognitive impairment (aMCI). Both disorders constitute early stages of neurodegeneration ideal for examining compensatory mechanisms and developing targeted interventions. We strived to clarify whether compensation criteria derived from healthy aging populations can be applied to early neurodegeneration. To concentrate on the close coupling of cognitive performance and brain activity, we exclusively addressed task fMRI studies. First, we found evidence for parallels in compensatory mechanisms between healthy aging and neurodegenerative disease. Several studies fulfilled criteria of attempted compensation, while reports of successful compensation were largely absent, which made it difficult to conclude on. Second, comparing working memory studies in preclinical HD and aMCI, we identified similar compensatory patterns across neurodegenerative disorders in lateral and medial prefrontal cortex. Such patterns included an inverted U-shaped relationship of neurodegeneration and compensatory activity spanning from preclinical to manifest disease. Due to the lack of studies systematically targeting all criteria of compensation, we propose an exemplary study design, including the manipulation of compensating brain areas by brain stimulation. Furthermore, we delineate the benefits of targeted interventions by non-invasive brain stimulation, as well as of unspecific interventions such as physical activity or cognitive training. Unambiguously detecting compensation in early neurodegenerative disease will help tailor interventions aiming at sustained overall functioning and delayed clinical disease onset.

Interregional compensatory mechanisms of motor functioning in progressing preclinical neurodegeneration

Understanding brain reserve in preclinical stages of neurodegenerative disorders allows determination of which brain regions contribute to normal functioning despite accelerated neuronal loss. Besides the recruitment of additional regions, a reorganisation and shift of relevance between normally engaged regions are a suggested key mechanism. Thus, network analysis methods seem critical for investigation of changes in directed causal interactions between such candidate brain regions. To identify core compensatory regions, fifteen preclinical patients carrying the genetic mutation leading to Huntingtons disease and twelve controls underwent fMRI scanning. They accomplished an auditory paced finger sequence tapping task, which challenged cognitive as well as executive aspects of motor functioning by varying speed and complexity of movements. To investigate causal interactions among brain regions a single Dynamic Causal Model (DCM) was constructed and fitted to the data from each subject. The DCM parameters were analysed using statistical methods to assess group differences in connectivity, and the relationship between connectivity patterns and predicted years to clinical onset was assessed in gene carriers. In preclinical patients, we found indications for neural reserve mechanisms predominantly driven by bilateral dorsal premotor cortex, which increasingly activated superior parietal cortices the closer individuals were to estimated clinical onset. This compensatory mechanism was restricted to complex movements characterised by high cognitive demand. Additionally, we identified task-induced connectivity changes in both groups of subjects towards pre- and caudal supplementary motor areas, which were linked to either faster or more complex task conditions. Interestingly, coupling of dorsal premotor cortex and supplementary motor area was more negative in controls compared to gene mutation carriers. Furthermore, changes in the connectivity pattern of gene carriers allowed prediction of the years to estimated disease onset in individuals. Our study characterises the connectivity pattern of core cortical regions maintaining motor function in relation to varying task demand. We identified connections of bilateral dorsal premotor cortex as critical for compensation as well as task-dependent recruitment of pre- and caudal supplementary motor area. The latter finding nicely mirrors a previously published general linear model-based analysis of the same data. Such knowledge about disease specific inter-regional effective connectivity may help identify foci for interventions based on transcranial magnetic stimulation designed to stimulate functioning and also to predict their impact on other regions in motor-associated networks.

Operationalizing compensation over time in neurodegenerative disease

In pre-clinical Huntingtons disease, normal behaviour is maintained despite neurodegeneration, suggesting a mechanism of compensation. Gregory, Long et al. present two mathematical models of compensation over time and their operationalisation for neuroimaging.

Large-scale brain network abnormalities in Huntington's disease revealed by structural covariance.

Huntingtons disease (HD) is a progressive neurodegenerative disorder that can be diagnosed with certainty decades before symptom onset. Studies using structural MRI have identified grey matter (GM) loss predominantly in the striatum, but also involving various cortical areas. So far, voxel‐based morphometric studies have examined each brain region in isolation and are thus unable to assess the changes in the interrelation of brain regions. Here, we examined the structural covariance in GM volumes in pre‐specified motor, working memory, cognitive flexibility, and social‐affective networks in 99 patients with manifest HD (mHD), 106 presymptomatic gene mutation carriers (pre‐HD), and 108 healthy controls (HC). After correction for global differences in brain volume, we found that increased GM volume in one region was associated with increased GM volume in another. When statistically comparing the groups, no differences between HC and pre‐HD were observed, but increased positive correlations were evident for mHD, relative to pre‐HD and HC. These findings could be explained by a HD‐related neuronal loss heterogeneously affecting the examined network at the pre‐HD stage, which starts to dominate structural covariance globally at the manifest stage. Follow‐up analyses identified structural connections between frontoparietal motor regions to be linearly modified by disease burden score (DBS). Moderator effects of disease load burden became significant at a DBS level typically associated with the onset of unequivocal HD motor signs. Together with existing findings from functional connectivity analyses, our data indicates a critical role of these frontoparietal regions for the onset of HD motor signs. Hum Brain Mapp 37:67–80, 2016.

Assessing parameter identifiability for dynamic causal modeling of fMRI data

Deterministic dynamic causal modeling (DCM) for fMRI data is a sophisticated approach to analyse effective connectivity in terms of directed interactions between brain regions of interest. To date it is difficult to know if acquired fMRI data will yield precise estimation of DCM parameters. Focusing on parameter identifiability, an important prerequisite for research questions on directed connectivity, we present an approach inferring if parameters of an envisaged DCM are identifiable based on information from fMRI data. With the freely available “attention to motion” dataset, we investigate identifiability of two DCMs and show how different imaging specifications impact on identifiability. We used the profile likelihood, which has successfully been applied in systems biology, to assess the identifiability of parameters in a DCM with specified scanning parameters. Parameters are identifiable when minima of the profile likelihood as well as finite confidence intervals for the parameters exist. Intermediate epoch duration, shorter TR and longer session duration generally increased the information content in the data and thus improved identifiability. Irrespective of biological factors such as size and location of a region, attention should be paid to densely interconnected regions in a DCM, as those seem to be prone to non-identifiability. Our approach, available in the DCMident toolbox, enables to judge if the parameters of an envisaged DCM are sufficiently determined by underlying data without priors as opposed to primarily reflecting the Bayesian priors in a SPM–DCM. Assessments with the DCMident toolbox prior to a study will lead to improved identifiability of the parameters and thus might prevent suboptimal data acquisition. Thus, the toolbox can be used as a preprocessing step to provide immediate statements on parameter identifiability.

Detection of motor changes in huntington's disease using dynamic causal modeling

Deficits in motor functioning are one of the hallmarks of Huntingtons disease (HD), a genetically caused neurodegenerative disorder. We applied functional magnetic resonance imaging (fMRI) and dynamic causal modeling (DCM) to assess changes that occur with disease progression in the neural circuitry of key areas associated with executive and cognitive aspects of motor control. Seventy-seven healthy controls, 62 pre-symptomatic HD gene carriers (preHD), and 16 patients with manifest HD symptoms (earlyHD) performed a motor finger-tapping fMRI task with systematically varying speed and complexity. DCM was used to assess the causal interactions among seven pre-defined regions of interest, comprising primary motor cortex, supplementary motor area (SMA), dorsal premotor cortex, and superior parietal cortex. To capture heterogeneity among HD gene carriers, DCM parameters were entered into a hierarchical cluster analysis using Wards method and squared Euclidian distance as a measure of similarity. After applying Bonferroni correction for the number of tests, DCM analysis revealed a group difference that was not present in the conventional fMRI analysis. We found an inhibitory effect of complexity on the connection from parietal to premotor areas in preHD, which became excitatory in earlyHD and correlated with putamen atrophy. While speed of finger movements did not modulate the connection from caudal to pre-SMA in controls and preHD, this connection became strongly negative in earlyHD. This second effect did not survive correction for multiple comparisons. Hierarchical clustering separated the gene mutation carriers into three clusters that also differed significantly between these two connections and thereby confirmed their relevance. DCM proved useful in identifying group differences that would have remained undetected by standard analyses and may aid in the investigation of between-subject heterogeneity.

Anodal tDCS Enhances Verbal Episodic Memory in Initially Low Performers

The left dorsolateral prefrontal cortex (DLPFC) is involved in encoding and retrieval of episodic memories, and thus, is frequently targeted in non-invasive brain stimulation paradigms, aiming for its functional modulation. Anodal transcranial direct current stimulation (tDCS), that boosts neuronal excitability in stimulated cortical areas, has been found to increase cognitive skills differentially, depending on the initial performance. We hypothesize that the benefit of tDCS on verbal episodic memory can be extrapolated from the participants’ baseline performance. In the present randomized, double-blind, parallel group study, healthy young adults (n = 43) received either real anodal or sham tDCS over their left DLPFC during the encoding phase of a verbal episodic memory task. Forty words were presented visually thrice with immediate vocal retrieval after each block and an additional delayed recall. We conducted a moderation analysis to test the modulating effect of initial episodic memory retrieval, adjusted for primacy and recency effects, on delayed recall under real or sham stimulation. Despite the absence of a significantly beneficial tDCS effect at the group level, we found that the number of remembered midlist words in the first retrieval significantly moderated the stimulation effect in such a way that initially low performers experienced the highest gain from real stimulation. These results suggest that anodal tDCS to the left DLPFC improves memory functions only so far. While only marginal stimulation-induced gains occur in cognitively unimpaired populations, greater stimulation benefits might be expected in individuals with clinically relevant deficiencies in the verbal episodic memory domain.