Gray Matter Vulnerabilities Predict Longitudinal Development of Apathy in Huntington's Disease.

BACKGROUND: Apathy, a common neuropsychiatric disturbance in Huntington's disease (HD), is subserved by a complex neurobiological network. However, no study has yet employed a whole-brain approach to examine underlying regional vulnerabilities that may precipitate apathy changes over time. OBJECTIVES: To identify whole-brain gray matter volume (GMV) vulnerabilities that may predict longitudinal apathy development in HD. METHODS: Forty-five HD individuals (31 female) were scanned and evaluated for apathy and other neuropsychiatric features using the short-Problem Behavior Assessment for a maximum total of six longitudinal visits (including baseline). In order to identify regions where changes in GMV may describe changes in apathy, we performed longitudinal voxel-based morphometry (VBM) on those 33 participants with a magnetic resonance imaging (MRI) scan on their second visit at 18 ± 6 months follow-up (78 MRI datasets). We next employed a generalized linear mixed-effects model (N = 45) to elucidate whether initial and specific GMV may predict apathy development over time. RESULTS: Utilizing longitudinal VBM, we revealed a relationship between increases in apathy and specific GMV atrophy in the right middle cingulate cortex (MCC). Furthermore, vulnerability in the right MCC volume at baseline successfully predicted the severity and progression of apathy over time. CONCLUSIONS: This study highlights that individual differences in apathy in HD may be explained by variability in atrophy and initial vulnerabilities in the right MCC, a region implicated in action-initiation. These findings thus serve to facilitate the prediction of an apathetic profile, permitting targeted, time-sensitive interventions in neurodegenerative disease with potential implications in otherwise healthy populations. © 2021 International Parkinson and Movement Disorder Society.

Mapping connectivity fingerprints for presurgical evaluation of temporal lobe epilepsy.

BACKGROUND: Surgery may render temporal lobe epilepsy (TLE) patients seizure-free. However, TLE is a heterogenous entity and surgical prognosis varies between patients. Network-based biomarkers have been shown to be altered in TLE patients and hold promise for classifying TLE subtypes and improving pre-surgical prognosis. The aim of the present study is to investigate a network-based biomarker, the weighted degree of connectivity (wDC), on an individual level, and its relation to TLE subtypes and surgical prognosis. METHODS: Thirty unilateral TLE patients undergoing the same surgical procedure (anterior temporal resection) and 18 healthy controls were included. All patients were followed-up in the same center for a mean time of 6.85 years and classified as seizure-free (SF) and non seizure-free (non-SF). Using pre-surgical resting state functional MRI, whole brain wDC values for patients and controls were calculated. Then, we divided both temporal lobes in three Regions-of-interest (ROIs) -mesial, pole and lateral- as these areas are known to behave differently in seizure onset and propagation, delimiting different TLE profiles. The wDC values for the defined ROIs of each individual patient were compared with the healthy group. RESULTS: After surgery, 14 TLE patients remained SF. As a group, patients had higher wDC than controls in both the temporal pole (p < 0.05) as well as in the mesial regions (p < 0.002) of the to-be-resected temporal lobe. When comparing between SF and non-SF patients, a step-wise binary logistic regression model including all the ROIs, showed that having an increased wDC of the temporal pole (p < 0.05) and the mesial area (p < 0.05) of the to-be-resected temporal lobe was associated with seizure freedom long-term after surgery. CONCLUSIONS: This study provides a network-based presurgical biomarker that could pave the way towards personalized prediction. In patients with TLE undergoing anterior temporal resections, having an increased wDC at rest could be a signature of the epileptogenic area, and could help identifying those patients who would benefit most from surgery.

Reduced striato-cortical and inhibitory transcallosal connectivity in the motor circuit of Huntington's disease patients.

Huntington's disease (HD) is a neurodegenerative disorder which is primarily associated with striatal degeneration. However, the alterations in connectivity of this structure in HD have been underinvestigated. In this study, we analyzed the functional and structural connectivity of the left putamen, while participants performed a finger-tapping task. Using fMRI and DW-MRI, 30 HD gene expansion carriers (HDGEC) and 29 healthy participants were scanned. Psychophysiological interaction analysis and DTI-based tractography were employed to examine functional and structural connectivity, respectively. Manifest HDGEC exhibited a reduced functional connectivity of the left putamen with the left and the right primary sensorimotor areas (SM1). Based on this result, the inhibitory functional connectivity between the left SM1 and the right SM1 was explored, appearing to be also decreased. In addition, the tract connecting these areas (motor corpus callosum), and the tract connecting the left putamen with the left SM1 appeared disrupted in HDGEC compared to controls. Significant correlations were found between measures of functional and structural connectivity of the motor corpus callosum, showing a coupling of both types of alterations in this tract. The observed reduction of functional and structural connectivity was associated with worse motor scores, which highlights the clinical relevance of these results. Hum Brain Mapp 39:54-71, 2018. © 2017 Wiley Periodicals, Inc.

Neuroimaging as a tool to study the sources of phenotypic heterogeneity in Huntington's disease.

PURPOSE OF REVIEW: Huntington's disease is a neurodegenerative disorder characterized by a triad of motor, cognitive and psychiatric disturbances. There is great variability regarding the prominence and evolution of each type of clinical sign. One possible source of phenotypic heterogeneity could be the more prominent degeneration of specific brain circuits. The scope of this review is to highlight the most recent neuroimaging studies that have analysed the relationship between brain changes and motor, cognitive and psychiatric alterations in Huntington's disease. RECENT FINDINGS: The results from recent neuroimaging studies are heterogeneous. Although there is a great overlap between the different regions associated with each symptomatic domain, there is some degree of differentiation. For example, the motor network is associated with motor impairment, whereas the ventral striatum is especially involved in emotional deficits related with psychiatric problems. SUMMARY: Motor, cognitive and psychiatric impairments are associated with structural and functional brain biomarkers. However, the specificity of the regions involved remains unknown, because these studies focused on specific regions and symptoms. In order to tease apart the neural substrates that underlie the phenotypic heterogeneity in Huntington's disease, multivariate approaches combining brain and behavioural measures related to all symptomatic domains should be considered in the future.

Cocaine addiction is associated with abnormal prefrontal function, increased striatal connectivity and sensitivity to monetary incentives, and decreased connectivity outside the human reward circuit.

Cocaine addiction has been associated with increased sensitivity of the human reward circuit to drug-related stimuli. However, the capacity of non-drug incentives to engage this network is poorly understood. Here, we characterized the functional sensitivity to monetary incentives and the structural integrity of the human reward circuit in abstinent cocaine-dependent (CD) patients and their matched controls. We assessed the BOLD response to monetary gains and losses in 30 CD patients and 30 healthy controls performing a lottery task in a magnetic resonance imaging scanner. We measured brain gray matter volume (GMV) using voxel-based morphometry and white matter microstructure using voxel-based fractional anisotropy (FA). Functional data showed that, after monetary incentives, CD patients exhibited higher activation in the ventral striatum than controls. Furthermore, we observed an inverted BOLD response pattern in the prefrontal cortex, with activity being highest after unexpected high gains and lowest after losses. Patients showed increased GMV in the caudate and the orbitofrontal cortex, increased white matter FA in the orbito-striatal pathway but decreased FA in antero-posterior association bundles. Abnormal activation in the prefrontal cortex correlated with GMV and FA increases in the orbitofrontal cortex. While functional abnormalities in the ventral striatum were inversely correlated with abstinence duration, structural alterations were not. In conclusion, results suggest abnormal incentive processing in CD patients with high salience for rewards and punishments in subcortical structures but diminished prefrontal control after adverse outcomes. They further suggest that hypertrophy and hyper-connectivity within the reward circuit, to the expense of connectivity outside this network, characterize cocaine addiction.

Structural neuroplasticity in expert pianists depends on the age of musical training onset.

In the last decade, several studies have investigated the neuroplastic changes induced by long-term musical training. Here we investigated structural brain differences in expert pianists compared to non-musician controls, as well as the effect of the age of onset (AoO) of piano playing. Differences with non-musicians and the effect of sensitive periods in musicians have been studied previously, but importantly, this is the first time in which the age of onset of music-training was assessed in a group of musicians playing the same instrument, while controlling for the amount of practice. We recruited a homogeneous group of expert pianists who differed in their AoO but not in their lifetime or present amount of training, and compared them to an age-matched group of non-musicians. A subset of the pianists also completed a scale-playing task in order to control for performance skill level differences. Voxel-based morphometry analysis was used to examine gray-matter differences at the whole-brain level. Pianists showed greater gray matter (GM) volume in bilateral putamen (extending also to hippocampus and amygdala), right thalamus, bilateral lingual gyri and left superior temporal gyrus, but a GM volume shrinkage in the right supramarginal, right superior temporal and right postcentral gyri, when compared to non-musician controls. These results reveal a complex pattern of plastic effects due to sustained musical training: a network involved in reinforcement learning showed increased GM volume, while areas related to sensorimotor control, auditory processing and score-reading presented a reduction in the volume of GM. Behaviorally, early-onset pianists showed higher temporal precision in their piano performance than late-onset pianists, especially in the left hand. Furthermore, early onset of piano playing was associated with smaller GM volume in the right putamen and better piano performance (mainly in the left hand). Our results, therefore, reveal for the first time in a single large dataset of healthy pianists the link between onset of musical practice, behavioral performance, and putaminal gray matter structure. In summary, skill-related plastic adaptations may include decreases and increases in GM volume, dependent on an optimization of the system caused by an early start of musical training. We believe our findings enrich the plasticity discourse and shed light on the neural basis of expert skill acquisition.

Inducing a meditative state by artificial perturbations: A mechanistic understanding of brain dynamics underlying meditation.

Contemplative neuroscience has increasingly explored meditation using neuroimaging. However, the brain mechanisms underlying meditation remain elusive. Here, we implemented a mechanistic framework to explore the spatiotemporal dynamics of expert meditators during meditation and rest, and controls during rest. We first applied a model-free approach by defining a probabilistic metastable substate (PMS) space for each condition, consisting of different probabilities of occurrence from a repertoire of dynamic patterns. Moreover, we implemented a model-based approach by adjusting the PMS of each condition to a whole-brain model, which enabled us to explore in silico perturbations to transition from resting-state to meditation and vice versa. Consequently, we assessed the sensitivity of different brain areas regarding their perturbability and their mechanistic local-global effects. Overall, our work reveals distinct whole-brain dynamics in meditation compared to rest, and how transitions can be induced with localized artificial perturbations. It motivates future work regarding meditation as a practice in health and as a potential therapy for brain disorders.

Our work explores brain dynamics in a group of expert meditators and controls. First, we characterized meditation and rest with a repertoire of brain patterns, each with its distinct probability of occurrence. Then, we generated whole-brain models of each condition, which enabled us to artificially perturb the systems to induce transitions between rest and meditation. Our results open new avenues in meditation research as a practice in health and disease.

De novo depression following temporal lobe epilepsy surgery.

Surgical removal of the mesial temporal lobe can effectively treat drug-resistant epilepsy but may lead to mood disorders. This fact is of particular interest in patients without a prior psychiatric history. The study investigates the relationship between Temporal Lobe Epilepsy (TLE), mood disorders, and the functional connectivity of the Hippocampus (Hipp) and Nucleus Accumbens (NAcc). In this case control study, twenty-seven TLE patients and 18 control subjects participated, undergoing structural and functional magnetic resonance imaging (MRI) scans before and after surgery. Post-surgery, patients were categorized into those developing de novo depression (DnD) within the first year and those without depression (nD). Functional connectivity maps between NAcc and the whole brain were generated, and connectivity strength between the to-be-resected Hipp area and NAcc was compared. Within the first year post-surgery, 7 out of 27 patients developed DnD. Most patients (88.8 %) exhibited a significant reduction in NAcc-Hipp connectivity compared to controls. The DnD group showed notably lower connectivity values than the nD group, with statistically significant disparities. Receiver Operating Characteristic (ROC) curve analysis identified a potential biomarker threshold (Crawford-T value of -2.08) with a sensitivity of 0.83 and specificity of 0.76. The results suggest that functional connectivity patterns within the reward network could serve as a potential biomarker for predicting de novo mood disorders in TLE patients undergoing surgery. This insight may assist in identifying individuals at a higher risk of developing DnD after surgery, enhancing therapeutic guidance and clinical decision-making.

Disentangling the neurobiological bases of temporal impulsivity in Huntington's disease.

BACKGROUND: Despite its impact on daily life, impulsivity in Huntington's disease (HD) is understudied as a neuropsychiatric symptom. Our aim is to characterize temporal impulsivity in HD and to disentangle the white matter correlate associated with impulsivity. METHODS: Forty-seven HD individuals and 36 healthy controls were scanned and evaluated for temporal impulsivity using a delay-discounting (DD) task and complementary Sensitivity to Punishment and Sensitivity to Reward Questionnaire. Diffusion tensor imaging was employed to characterize the structural connectivity of three limbic tracts: the uncinate fasciculus (UF), the accumbofrontal tract (NAcc-OFC), and the dorsolateral prefrontal cortex connectig the caudate nucleus (DLPFC-cn). Multiple linear regression analyses were applied to analyze the relationship between impulsive behavior and white matter microstructural integrity. RESULTS: Our results revealed altered structural connectivity in the DLPC-cn, the NAcc-OFC and the UF in HD individuals. At the same time, the variability in structural connectivity of these tracts was associated with the individual differences in temporal impulsivity. Specifically, increased structural connectivity in the right NAcc-OFC and reduced connectivity in the left UF were associated with higher temporal impulsivity scores. CONCLUSIONS: The present findings highlight the importance of investigating the spectrum of temporal impulsivity in HD. As, while less prevalent than other psychiatric features, this symptom is still reported to significantly impact the quality of life of patients and caregivers. This study provides evidence that individual differences observed in temporal impulsivity may be explained by variability in limbic frontostriatal tracts, while shedding light on the role of sensitivity to reward in modulating impulsive behavior through the selection of immediate rewards.

Feedback-related brain potential activity complies with basic assumptions of associative learning theory.

Feedback-related negativity (FRN) is an ERP component that distinguishes positive from negative feedback. FRN has been hypothesized to be the product of an error signal that may be used to adjust future behavior. In addition, associative learning models assume that the trial-to-trial learning of cue-outcome mappings involves the minimization of an error term. This study evaluated whether FRN is a possible electrophysiological correlate of this error term in a predictive learning task where human subjects were asked to learn different cue-outcome relationships. Specifically, we evaluated the sensitivity of the FRN to the course of learning when different stimuli interact or compete to become a predictor of certain outcomes. Importantly, some of these cues were blocked by more informative or predictive cues (i.e., the blocking effect). Interestingly, the present results show that both learning and blocking affect the amplitude of the FRN component. Furthermore, independent analyses of positive and negative feedback event-related signals showed that the learning effect was restricted to the ERP component elicited by positive feedback. The blocking test showed differences in the FRN magnitude between a predictive and a blocked cue. Overall, the present results show that ERPs that are related to feedback processing correspond to the main predictions of associative learning models.

Brain oscillatory activity associated with task switching and feedback processing.

In this study, we sought to dissociate event-related potentials (ERPs) and the oscillatory activity associated with signals indicating feedback about performance (outcome-based behavioral adjustment) and the signals indicating the need to change or maintain a task set (rule-based behavioral adjustment). With this purpose in mind, we noninvasively recorded electroencephalographic signals, using a modified version of the Wisconsin card sorting task, in which feedback processing and task switching could be studied separately. A similar late positive component was observed for the switch and correct feedback signals on the first trials of a series, but feedback-related negativity was observed only for incorrect feedback. Moreover, whereas theta power showed a significant increase after a switch cue and after the first positive feedback of a new series, a selective frontal beta-gamma increase was observed exclusively in the first positive feedback (i.e., after the selection of the new rule). Importantly, for the switch cue, beta-alpha activity was suppressed rather than increased. This clear dissociation between the cue and feedback stimuli in task switching emphasizes the need to accurately study brain oscillatory activity to disentangle the role of different cognitive control processes.

Language learning under working memory constraints correlates with microstructural differences in the ventral language pathway.

The present study combined behavioral measures and diffusion tensor imaging to investigate the neuroanatomical basis of language learning in relation to phonological working memory (WM). Participants were exposed to simplified artificial languages under WM constraints. The results underscore the role of the rehearsal subcomponent of WM in successful speech segmentation and rule learning. Moreover, when rehearsal was blocked task performance was correlated to the white matter microstructure of the left ventral pathway connecting frontal and temporal language-related cortical areas through the extreme/external capsule. This ventral pathway may therefore play an important additional role in language learning when the main dorsal pathway-dependent rehearsal mechanisms are not available.

Meditation-induced effects on whole-brain structural and effective connectivity.

In the past decades, there has been a growing scientific interest in characterizing neural correlates of meditation training. Nonetheless, the mechanisms underlying meditation remain elusive. In the present work, we investigated meditation-related changes in functional dynamics and structural connectivity (SC). For this purpose, we scanned experienced meditators and control (naive) subjects using magnetic resonance imaging (MRI) to acquire structural and functional data during two conditions, resting-state and meditation (focused attention on breathing). In this way, we aimed to characterize and distinguish both short-term and long-term modifications in the brain's structure and function. First, to analyze the fMRI data, we calculated whole-brain effective connectivity (EC) estimates, relying on a dynamical network model to replicate BOLD signals' spatio-temporal structure, akin to functional connectivity (FC) with lagged correlations. We compared the estimated EC, FC, and SC links as features to train classifiers to predict behavioral conditions and group identity. Then, we performed a network-based analysis of anatomical connectivity. We demonstrated through a machine-learning approach that EC features were more informative than FC and SC solely. We showed that the most informative EC links that discriminated between meditators and controls involved several large-scale networks mainly within the left hemisphere. Moreover, we found that differences in the functional domain were reflected to a smaller extent in changes at the anatomical level as well. The network-based analysis of anatomical pathways revealed strengthened connectivity for meditators compared to controls between four areas in the left hemisphere belonging to the somatomotor, dorsal attention, subcortical and visual networks. Overall, the results of our whole-brain model-based approach revealed a mechanism underlying meditation by providing causal relationships at the structure-function level.

Verbal Learning and Longitudinal Hippocampal Network Connectivity in Temporal Lobe Epilepsy Surgery.

Introduction: Learning new verbal information can be impaired in 20-40% of patients after mesial temporal lobe resection. In recent years, understanding epilepsy as a brain network disease, and investigating the relationship between large-scale resting networks and cognition has led to several advances. Aligned studies suggest that it is the integrity of the hippocampal connectivity with these large-scale networks what is relevant for cognition, with evidence showing a functional and structural heterogeneity along the long axis hippocampus bilaterally. Objective: Our aim is to examine whether pre-operative resting-state connectivity along the long hippocampal axis is associated with verbal learning decline after anterior temporal lobe resection. Methods: Thirty-one patients with epilepsy who underwent an anterior temporal lobe resection were pre-surgically scanned at 3-tesla, and pre/post-surgery evaluated for learning deficits using the Rey Auditory Verbal Learning Task (RAVLT). Eighteen controls matched by age, gender and handedness were also scanned and evaluated with the RAVLT. We studied the functional connectivity along the (anterior/posterior) long axis hippocampal subregions and resting-state functionally-defined brain networks involved in learning [executive (EXE), dorsal attention (DAN) and default-mode (DMN) networks]. Functional connectivity differences between the two groups of patients (learning intact or with learning decline) and controls were investigated with MANOVA and discriminant analysis. Results: There were significant differences in the pattern of hippocampal connectivity among the groups. Regarding the anterior connectivity hippocampal pattern, our data showed an increase of connectivity in the pathological side with the DAN (p = 0.011) and the EXE (p = 0.008) when comparing learning-decline vs. learning-intact patients. Moreover, the non-pathological side showed an increase in the anterior connectivity pattern with the DAN (p = 0.027) between learning-decline vs. learning-intact patients. In contrast, the posterior hippocampus showed a reduction of connectivity in the learning-decline patients with the DMN, both in the pathological (p = 0.004) and the non-pathological sides (p = 0.036). Finally, the discriminant analysis based on the pre-operative connectivity pattern significantly differentiated the learning-decline patients from the other groups (p = 0.019). Conclusion: Our findings reveal bilateral connectivity disruptions along the longitudinal axis of the hippocampi with resting-state networks, which could be key to identify those patients at risk of verbal learning decline after epilepsy surgery.

Unifying turbulent dynamics framework distinguishes different brain states.

Significant advances have been made by identifying the levels of synchrony of the underlying dynamics of a given brain state. This research has demonstrated that non-conscious dynamics tend to be more synchronous than in conscious states, which are more asynchronous. Here we go beyond this dichotomy to demonstrate that different brain states are underpinned by dissociable spatiotemporal dynamics. We investigated human neuroimaging data from different brain states (resting state, meditation, deep sleep and disorders of consciousness after coma). The model-free approach was based on Kuramoto's turbulence framework using coupled oscillators. This was extended by a measure of the information cascade across spatial scales. Complementarily, the model-based approach used exhaustive in silico perturbations of whole-brain models fitted to these measures. This allowed studying of the information encoding capabilities in given brain states. Overall, this framework demonstrates that elements from turbulence theory provide excellent tools for describing and differentiating between brain states.

Delineating apathy profiles in Huntington's disease with the short-Lille Apathy Rating Scale.

INTRODUCTION: Apathy, a prevalent feature in neurological disorders including Huntington's disease (HD), is characterized by a reduction in goal-directed behavior across cognitive, auto-activation (i.e., self-activating thoughts/behavior), and emotional domains. Nonetheless, current diagnostic criteria are incapable of distinguishing multidimensional apathy profiles. Meanwhile, the short-Lille Apathy Rating Scale (LARS-s) bears potential as an operative diagnostic tool to disentangle apathy dimensions in clinical practice. The present study thereby examines the psychometric properties and factor structure of the LARS-s to tap into apathy profiles and their underlying neural correlates in HD. METHODS: Forty HD individuals were scanned and evaluated for apathy using the LARS-s, assessed for reliability and validity in HD, and the short-Problem Behavior Assessment (PBA-s). To study the dimensional structure of apathy, principal component analysis (PCA) of the LARS-s was implemented. Resulting factors were associated with gray matter volume through whole-brain voxel-based morphometry. RESULTS: The LARS-s demonstrated satisfactory psychometric properties, sharing convergent validity with PBA-s apathy and discriminant validity against depression. PCA resulted in three factors representative of apathy profiles across cognitive, auto-activation, and emotional domains. Anatomically, global apathy was significantly related with large-scale motor, cognitive, and limbic networks. Exploratory analyses of apathy profiles revealed correspondence between each factor and distinct cortical and subcortical nodes. CONCLUSION: The LARS-s is capable of capturing the multidimensional spectrum of apathy. At the same time, apathy profiles in HD are underpinned by functionally diverse neural networks. Such findings promote the continued study of apathy domains to pinpoint personalized therapeutic targets in neurologic disorders in addition to HD.

Microstructural brain differences predict functional hemodynamic responses in a reward processing task.

Many aspects of human behavior are driven by rewards, yet different people are differentially sensitive to rewards and punishment. In this study, we show that white matter microstructure in the uncinate/inferior fronto-occipital fasciculus, defined by fractional anisotropy values derived from diffusion tensor magnetic resonance images, correlates with both short-term (indexed by the fMRI blood oxygenation level-dependent response to reward in the nucleus accumbens) and long-term (indexed by the trait measure sensitivity to punishment) reactivity to rewards. Moreover, trait measures of reward processing were also correlated with reward-related functional activation in the nucleus accumbens. The white matter tract revealed by the correlational analysis connects the anterior temporal lobe with the medial and lateral orbitofrontal cortex and also supplies the ventral striatum. The pattern of strong correlations suggests an intimate relationship between white matter structure and reward-related behavior that may also play a role in a number of pathological conditions, such as addiction and pathological gambling.

Pramipexole modulates the neural network of reward anticipation.

Pramipexole is widely prescribed to treat Parkinson's disease. It has been found to cause impulse control disorders such as pathological gambling. To examine how pramipexole modulates the network of reward anticipation, we carried out a pharmacological functional magnetic resonance imaging study with a double-blind, within-subject design. During the anticipation of monetary rewards, pramipexole increased the activity of the nucleus accumbens (NAcc), enhanced the interaction between the NAcc and the anterior insula, but weakened the interaction between the NAcc and the prefrontal cortex. These results suggest that pramipexole may exaggerate incentive and affective responses to possible rewards, but reduce the top-down control of impulses, leading to an increase in impulsive behaviors. This imbalance between the prefrontal-striatum connectivity and the insula-striatum connectivity may represent the neural mechanism of pathological gambling caused by pramipexole.

The effects of COMT (Val108/158Met) and DRD4 (SNP -521) dopamine genotypes on brain activations related to valence and magnitude of rewards.

People's sensitivity to reinforcing stimuli such as monetary gains and losses shows a wide interindividual variation that might in part be determined by genetic differences. Because of the established role of the dopaminergic system in the neural encoding of rewards and negative events, we investigated young healthy volunteers being homozygous for either the Valine or Methionine variant of the catechol-O-methyltransferase (COMT) codon 158 polymorphism as well as homozygous for the C or T variant of the SNP -521 polymorphism of the dopamine D4 receptor. Participants took part in a gambling paradigm featuring unexpectedly high monetary gains and losses in addition to standard gains/losses of expected magnitude while undergoing functional magnetic resonance imaging at 3 T. Valence-related brain activations were seen in the ventral striatum, the anterior cingulate cortex, and the inferior parietal cortex. These activations were modulated by the COMT polymorphism with greater effects for valine/valine participants but not by the D4 receptor polymorphism. By contrast, magnitude-related effects in the anterior insula and the cingulate cortex were modulated by the D4 receptor polymorphism with larger responses for the CC variant. These findings emphasize the differential contribution of genetic variants in the dopaminergic system to various aspects of reward processing.

Music-supported therapy induces plasticity in the sensorimotor cortex in chronic stroke: a single-case study using multimodal imaging (fMRI-TMS).

PRIMARY OBJECTIVE: Music-Supported Therapy (MST) has been developed recently in order to improve the use of the affected upper extremity after stroke. This study investigated the neuroplastic mechanisms underlying effectiveness in a patient with chronic stroke. METHODS: MST uses musical instruments, a midi piano and an electronic drum set emitting piano sounds, to retrain fine and gross movements of the paretic upper extremity. Data are presented from a patient with a chronic stroke (20 months post-stroke) with residual right-sided hemiparesis who took part in 20 MST sessions over the course of 4 weeks. RESULTS: Post-therapy, a marked improvement of movement quality, assessed by 3D movement analysis, was observed. Moreover, functional magnetic resonance imaging (fMRI) of a sequential hand movement revealed distinct therapy-related changes in the form of a reduction of excess contralateral and ipsilateral activations. This was accompanied by changes in cortical excitability evidenced by transcranial magnetic stimulation (TMS). Functional MRI in a music listening task suggests that one of the effects of MST is the task-dependent coupling of auditory and motor cortical areas. CONCLUSIONS: The MST appears to be a useful neurorehabilitation tool in patients with chronic stroke and leads to neural reorganization in the sensorimotor cortex.