Altered brain connectivity in hyperkinetic movement disorders: A review of resting-state fMRI.

BACKGROUND: Hyperkinetic movement disorders (HMD) manifest as abnormal and uncontrollable movements. Despite reported involvement of several neural circuits, exact connectivity profiles remain elusive. OBJECTIVES: Providing a comprehensive literature review of resting-state brain connectivity alterations using resting-state fMRI (rs-fMRI). We additionally discuss alterations from the perspective of brain networks, as well as correlations between connectivity and clinical measures. METHODS: A systematic review was performed according to PRISMA guidelines and searching PubMed until October 2022. Rs-fMRI studies addressing ataxia, chorea, dystonia, myoclonus, tics, tremor, and functional movement disorders (FMD) were included. The standardized mean difference was used to summarize findings per region in the Automated Anatomical Labeling atlas for each phenotype. Furthermore, the activation likelihood estimation meta-analytic method was used to analyze convergence of significant between-group differences per phenotype. Finally, we conducted hierarchical cluster analysis to provide additional insights into commonalities and differences across HMD phenotypes. RESULTS: Most articles concerned tremor (51), followed by dystonia (46), tics (19), chorea (12), myoclonus (11), FMD (11), and ataxia (8). Altered resting-state connectivity was found in several brain regions: in ataxia mainly cerebellar areas; for chorea, the caudate nucleus; for dystonia, sensorimotor and basal ganglia regions; for myoclonus, the thalamus and cingulate cortex; in tics, the basal ganglia, cerebellum, insula, and frontal cortex; for tremor, the cerebello-thalamo-cortical circuit; finally, in FMD, frontal, parietal, and cerebellar regions. Both decreased and increased connectivity were found for all HMD. Significant spatial convergence was found for dystonia, FMD, myoclonus, and tremor. Correlations between clinical measures and resting-state connectivity were frequently described. CONCLUSION: Key brain regions contributing to functional connectivity changes across HMD often overlap. Possible increases and decreases of functional connections of a specific region emphasize that HMD should be viewed as a network disorder. Despite the complex interplay of physiological and methodological factors, this review serves to gain insight in brain connectivity profiles across HMD phenotypes.

A resting-state fMRI pattern of spinocerebellar ataxia type 3 and comparison with 18F-FDG PET.

Spinocerebellar ataxia type 3 (SCA3) is a rare genetic neurodegenerative disease. The neurobiological basis of SCA3 is still poorly understood, and up until now resting-state fMRI (rs-fMRI) has not been used to study this disease. In the current study we investigated (multi-echo) rs-fMRI data from patients with genetically confirmed SCA3 (n = 17) and matched healthy subjects (n = 16). Using independent component analysis (ICA) and subsequent regression with bootstrap resampling, we identified a pattern of differences between patients and healthy subjects, which we coined the fMRI SCA3 related pattern (fSCA3-RP) comprising cerebellum, anterior striatum and various cortical regions. Individual fSCA3-RP scores were highly correlated with a previously published 18F-FDG PET pattern found in the same sample (rho = 0.78, P = 0.0003). Also, a high correlation was found with the Scale for Assessment and Rating of Ataxia scores (r = 0.63, P = 0.007). No correlations were found with neuropsychological test scores, nor with levels of grey matter atrophy. Compared with the 18F-FDG PET pattern, the fSCA3-RP included a more extensive contribution of the mediofrontal cortex, putatively representing changes in default network activity. This rs-fMRI identification of additional regions is proposed to reflect a consequence of the nature of the BOLD technique, enabling measurement of dynamic network activity, compared to the more static 18F-FDG PET methodology. Altogether, our findings shed new light on the neural substrate of SCA3, and encourage further validation of the fSCA3-RP to assess its potential contribution as imaging biomarker for future research and clinical use.

Next move in movement disorders (NEMO): developing a computer-aided classification tool for hyperkinetic movement disorders.

INTRODUCTION: Our aim is to develop a novel approach to hyperkinetic movement disorder classification, that combines clinical information, electromyography, accelerometry and video in a computer-aided classification tool. We see this as the next step towards rapid and accurate phenotype classification, the cornerstone of both the diagnostic and treatment process. METHODS AND ANALYSIS: The Next Move in Movement Disorders (NEMO) study is a cross-sectional study at Expertise Centre Movement Disorders Groningen, University Medical Centre Groningen. It comprises patients with single and mixed phenotype movement disorders. Single phenotype groups will first include dystonia, myoclonus and tremor, and then chorea, tics, ataxia and spasticity. Mixed phenotypes are myoclonus-dystonia, dystonic tremor, myoclonus ataxia and jerky/tremulous functional movement disorders. Groups will contain 20 patients, or 40 healthy participants. The gold standard for inclusion consists of interobserver agreement on the phenotype among three independent clinical experts. Electromyography, accelerometry and three-dimensional video data will be recorded during performance of a set of movement tasks, chosen by a team of specialists to elicit movement disorders. These data will serve as input for the machine learning algorithm. Labels for supervised learning are provided by the expert-based classification, allowing the algorithm to learn to predict what the output label should be when given new input data. Methods using manually engineered features based on existing clinical knowledge will be used, as well as deep learning methods which can detect relevant and possibly new features. Finally, we will employ visual analytics to visualise how the classification algorithm arrives at its decision. ETHICS AND DISSEMINATION: Ethical approval has been obtained from the relevant local ethics committee. The NEMO study is designed to pioneer the application of machine learning of movement disorders. We expect to publish articles in multiple related fields of research and patients will be informed of important results via patient associations and press releases.

Further Evidence that Habitual Consumption of Sucralose with, but Not without, Carbohydrate Alters Glucose Metabolism.

In this letter, Dalenberg et al. provide a point-by-point response to the critique offered by Kahn and Sievenpiper. They also offer new evidence to support their original finding from a study they conducted in mice.

The chronnectome as a model for Charcot's 'dynamic lesion' in functional movement disorders.

This exploratory study set out to investigate dynamic functional connectivity (dFC) in patients with jerky and tremulous functional movement disorders (JT-FMD). The focus in this work is on dynamic brain states, which represent distinct dFC patterns that reoccur in time and across subjects. Resting-state fMRI data were collected from 17 patients with JT-FMD and 17 healthy controls (HC). Symptom severity was measured using the Clinical Global Impression-Severity scale. Depression and anxiety were measured using the Beck Depression Inventory (BDI) and Beck Anxiety Inventory (BAI), respectively. Independent component analysis was used to extract functional brain components. After computing dFC, dynamic brain states were determined for every subject using k-means clustering. Compared to HC, patients with JT-FMD spent more time in a state that was characterized predominantly by increasing medial prefrontal, and decreasing posterior midline connectivity over time. They also tended to visit this state more frequently. In addition, patients with JT-FMD transitioned significantly more often between different states compared to HC, and incorporated a state with decreasing medial prefrontal, and increasing posterior midline connectivity in their attractor, i.e., the cyclic patterns of state transitions. Altogether, this is the first study that demonstrates altered functional brain network dynamics in JT-FMD that may support concepts of increased self-reflective processes and impaired sense of agency as driving factors in FMD.

No evidence for an association between obesity and milkshake liking.

BACKGROUND: Prevailing models of obesity posit that hedonic signals override homeostatic mechanisms to promote overeating in today's food environment. What researchers mean by "hedonic" varies considerably, but most frequently refers to an aggregate of appetitive events including incentive salience, motivation, reinforcement, and perceived pleasantness. Here we define hedonic as orosensory pleasure experienced during eating and set out to test whether there is a relationship between adiposity and the perceived pleasure of a palatable and energy-dense milkshake. METHODS: The perceived liking, wanting, and intensity of two palatable and energy-dense milkshakes were assessed using the Labeled Hedonic Scale (1), visual analog scale (VAS), and Generalized Labeled Magnitude Scale (2) in 110 individuals ranging in body mass index (BMI) from 19.3 to 52.1 kg/m2. Waist circumference, waist-hip ratio, and percent body fat were also measured. Importantly, unlike the majority of prior studies, we attempted to standardize internal state by instructing participants to arrive to the laboratory neither hungry nor full and at least 1-h fasted. Data were analyzed with general linear and linear mixed effects models (GLMs). Hunger ratings were also examined prior to hedonic measurement and included as covariates in our analyses. RESULTS: We identified a significant association between ratings of hunger and milkshake liking and wanting. By contrast, we found no evidence for a relationship between any measure of adiposity and ratings of milkshake liking, wanting, or intensity. CONCLUSIONS: We conclude that adiposity is not associated with the pleasure experienced during consumption of our energy-dense and palatable milkshakes. Our results provide further evidence against the hypothesis that heightened hedonic signals drive weight gain.

Short-Term Consumption of Sucralose with, but Not without, Carbohydrate Impairs Neural and Metabolic Sensitivity to Sugar in Humans.

There is a general consensus that overconsumption of sugar-sweetened beverages contributes to the prevalence of obesity and related comorbidities such as type 2 diabetes (T2D). Whether a similar relationship exists for no- or low-calorie "diet" drinks is a subject of intensive debate and controversy. Here, we demonstrate that consuming seven sucralose-sweetened beverages with, but not without, a carbohydrate over 10 days decreases insulin sensitivity in healthy human participants, an effect that correlates with reductions in midbrain, insular, and cingulate responses to sweet, but not sour, salty, or savory, taste as assessed with fMRI. Taste perception was unaltered and consuming the carbohydrate alone had no effect. These findings indicate that consumption of sucralose in the presence of a carbohydrate rapidly impairs glucose metabolism and results in longer-term decreases in brain, but not perceptual sensitivity to sweet taste, suggesting dysregulation of gut-brain control of glucose metabolism.

A Brief Neuropsychological Battery for Measuring Cognitive Functions Associated with Obesity.

OBJECTIVE: Although ample evidence links obesity to cognitive dysfunction, the trajectory of cognitive change, the underlying mechanisms, and the involvement of related factors, such as metabolic disease and diet, remain unclear. To support further investigations of BMI and cognition, this study aimed to create a concise test battery to be used in future trials. METHODS: Twenty neurocognitive measures were regressed on BMI in the Human Connectome Project Healthy Young Adult S1200 data release by using linear mixed models and by adjusting for major confounders. Measures were then identified by using least absolute shrinkage and selection operator regression analysis to select tests most strongly associated with BMI. To guide further test selection, the explained variance for each variable was visualized in the final model. RESULTS: BMI was negatively associated with seven neurocognitive measures. Variable selection yielded a model that included years of education and, in order of model weight, delay discounting, the relational task, the Penn Progressive Matrices test, the oral reading recognition test, the Variable Short Penn Line Orientation test, and the Penn Word Memory test. CONCLUSIONS: This research resulted in an approximate 40-minute test battery for the BMI-cognition relationship in young adults that can be used in trials investigating the interrelationship between obesity and cognitive performance.

Valence processing differs across stimulus modalities.

Although it is often assumed that valence processing in the prefrontal cortex (PFC) is similar for stimuli originating from different sensory modalities, evidence supporting this view is lacking. To address this, we recruited 20 male participants and used a delayed-response fMRI design to test whether perceived pleasantness of flavors and images is similarly processed in the PFC. As predicted, significant correlations were observed between image and flavor pleasantness ratings, and PFC response to these stimuli; however, these responses were spatially different, with flavor pleasantness reflected in more ventrally located PFC regions than image pleasantness. These results indicate that, contrary to the general assumption of a singular circuit representing pleasantness, distinct PFC circuits are recruited depending upon stimulus modality. We argue that the ventral-dorsal distinction may be attributed to a difference in proximal versus distal stimulus representations.

Flavor pleasantness processing in the ventral emotion network.

The ventral emotion network-encompassing the amygdala, insula, ventral striatum, and ventral regions of the prefrontal cortex-has been associated with the identification of emotional significance of perceived external stimuli and the production of affective states. Functional magnetic resonance imaging (fMRI) studies investigating chemosensory stimuli have associated parts of this network with pleasantness coding. In the current study, we independently analyzed two datasets in which we measured brain responses to flavor stimuli in young adult men. In the first dataset, participants evaluated eight regular off the shelf drinking products while participants evaluated six less familiar oral nutritional supplements (ONS) in the second dataset. Participants provided pleasantness ratings 20 seconds after tasting. Using independent component analysis (ICA) and mixed effect models, we identified one brain network in the regular products dataset that was associated with flavor pleasantness. This network was very similar to the ventral emotion network. Although we identified an identical network in the ONS dataset using ICA, we found no linear relation between activation of any network and pleasantness scores within this dataset. Our results indicate that flavor pleasantness is processed in a network encompassing amygdala, ventral prefrontal, insular, striatal and parahippocampal regions for familiar drinking products. For more unfamiliar ONS products the association is not obvious, which could be related to the unfamiliarity of these products.

Functional specialization of the male insula during taste perception.

The primary gustatory area is located in the insular cortex. Although the insular cortex has been the topic of multiple parcellation studies, its functional specialization regarding taste processing received relatively little attention. Studies investigating the brain response to taste suggested that the insular cortex is involved in processing multiple characteristics of a taste stimulus, such as its quality, intensity, and pleasantness. In the current functional magnetic resonance study, younger and older adult male subjects were exposed to four basic tastes in five increasing concentrations. We applied a data-driven analysis to obtain insular response maps, which showed that the insular cortex processes the presence of taste, its corresponding pleasantness, as well as its concentration. More specifically, the left and right insular cortices are differentially engaged in processing the aforementioned taste characteristics: representations of the presence of a taste stimulus as well as its corresponding pleasantness dominate in the left insular cortex, whereas taste concentration processing dominates in the right insular cortex. These results were similar across both age groups. Our results fit well within previous cytoarchitectural studies and show insular lateralization in processing different aspects of taste stimuli in men.

Neural processing of basic tastes in healthy young and older adults - an fMRI study.

Ageing affects taste perception as shown in psychophysical studies, however, underlying structural and functional mechanisms of these changes are still largely unknown. To investigate the neurobiology of age-related differences associated with processing of basic tastes, we measured brain activation (i.e. fMRI-BOLD activity) during tasting of four increasing concentrations of sweet, sour, salty, and bitter tastes in young (average 23 years of age) and older (average 65 years of age) adults. The current study highlighted age-related differences in taste perception at the different higher order brain areas of the taste pathway. We found that the taste information delivered to the brain in young and older adults was not different, as illustrated by the absence of age effects in NTS and VPM activity. Our results indicate that multisensory integration changes with age; older adults showed less brain activation to integrate both taste and somatosensory information. Furthermore, older adults directed less attention to the taste stimulus; therefore attention had to be reallocated by the older individuals in order to perceive the tastes. In addition, we considered that the observed age-related differences in brain activation between taste concentrations in the amygdala reflect its involvement in processing both concentration and pleasantness of taste. Finally, we state the importance of homeostatic mechanisms in understanding the taste quality specificity in age related differences in taste perception.

Differences in cognitive aging: typology based on a community structure detection approach.

The current study investigated the extent and patterns of cognitive variability in younger and older adults. An important novelty of this study is the use of graph-based community structure detection analysis to map performance in a mixed population of 79 young and 76 older adults, without separating the age groups a-priori. We identified six subgroups, with distinct patterns of neuropsychological performance. The stability of the identified subgroups was confirmed by employing a cross-validation support vector machine based analysis. The majority of these subgroups comprised either young or older adults, confirming the expected role of aging in cognitive performance. In addition, we identified a subgroup of young and older adults who performed at a similar cognitive level of overall good cognitive performance with slightly decreased processing speed. This result showed that older age is not necessarily associated with general lower cognitive performance and that being young is not necessarily associated with superior cognitive performance. Moreover, cognitively better performing elderly had a significantly higher level of education attainment and higher crystallized intelligence than the other elderly, which suggests that older adults with higher cognitive reserve may be able to cope better with age-related neurobiological change.

Evoked emotions predict food choice.

In the current study we show that non-verbal food-evoked emotion scores significantly improve food choice prediction over merely liking scores. Previous research has shown that liking measures correlate with choice. However, liking is no strong predictor for food choice in real life environments. Therefore, the focus within recent studies shifted towards using emotion-profiling methods that successfully can discriminate between products that are equally liked. However, it is unclear how well scores from emotion-profiling methods predict actual food choice and/or consumption. To test this, we proposed to decompose emotion scores into valence and arousal scores using Principal Component Analysis (PCA) and apply Multinomial Logit Models (MLM) to estimate food choice using liking, valence, and arousal as possible predictors. For this analysis, we used an existing data set comprised of liking and food-evoked emotions scores from 123 participants, who rated 7 unlabeled breakfast drinks. Liking scores were measured using a 100-mm visual analogue scale, while food-evoked emotions were measured using 2 existing emotion-profiling methods: a verbal and a non-verbal method (EsSense Profile and PrEmo, respectively). After 7 days, participants were asked to choose 1 breakfast drink from the experiment to consume during breakfast in a simulated restaurant environment. Cross validation showed that we were able to correctly predict individualized food choice (1 out of 7 products) for over 50% of the participants. This number increased to nearly 80% when looking at the top 2 candidates. Model comparisons showed that evoked emotions better predict food choice than perceived liking alone. However, the strongest predictive strength was achieved by the combination of evoked emotions and liking. Furthermore we showed that non-verbal food-evoked emotion scores more accurately predict food choice than verbal food-evoked emotions scores.

Dealing with consumer differences in liking during repeated exposure to food; typical dynamics in rating behavior.

Consumers show high interindividual variability in food liking during repeated exposure. To investigate consumer liking during repeated exposure, data is often interpreted on a product level by averaging results over all consumers. However, a single product may elicit inconsistent behaviors in consumers; averaging will mix and hide possible subgroups of consumer behaviors, leading to a misinterpretation of the results. To deal with the variability in consumer liking, we propose to use clustering on data from consumer-product combinations to investigate the nature of the behavioral differences within the complete dataset. The resulting behavioral clusters can then be used to describe product acceptance. To test this approach we used two independent data sets in which young adults were repeatedly exposed to drinks and snacks, respectively. We found that five typical consumer behaviors existed in both datasets. These behaviors differed both in the average level of liking as well as its temporal dynamics. By investigating the distribution of a single product across typical consumer behaviors, we provide more precise insight in how consumers divide in subgroups based on their product liking (i.e. product modality). This work shows that taking into account and using interindividual differences can unveil information about product acceptance that would otherwise be ignored.

Pupil dilation co-varies with memory strength of individual traces in a delayed response paired-associate task.

Studies on cognitive effort have shown that pupil dilation is a reliable indicator of memory load. However, it is conceivable that there are other sources of effort involved in memory that also affect pupil dilation. One of these is the ease with which an item can be retrieved from memory. Here, we present the results of an experiment in which we studied the way in which pupil dilation acts as an online marker for memory processing during the retrieval of paired associates while reducing confounds associated with motor responses. Paired associates were categorized into sets containing either 4 or 7 items. After learning the paired associates once, pupil dilation was measured during the presentation of the retrieval cue during four repetitions of each set. Memory strength was operationalized as the number of repetitions (frequency) and set-size, since having more items per set results in a lower average recency. Dilation decreased with increased memory strength, supporting the hypothesis that the amplitude of the evoked pupillary response correlates positively with retrieval effort. Thus, while many studies have shown that "memory load" influences pupil dilation, our results indicate that the task-evoked pupillary response is also sensitive to the experimentally manipulated memory strength of individual items. As these effects were observed well before the response had been given, this study also suggests that pupil dilation can be used to assess an item's memory strength without requiring an overt response.