Behavioral/Cognitive Distinct Modulations in Sensorimotor Postmovement and Foreperiod ␤-Band Activities Related to Error Salience Processing and Sensorimotor Adaptation

International audienceIn a recent study, Tan et al. (2014a,b) showed that the increase in ␤-power typically observed after a movement above sensorimotor regions (␤-rebound) is attenuated when movement-execution errors are induced by visual perturbations. Moreover, akin to sensorimo-tor adaptation, the effect depended on the context in which the errors are experienced. Thus the ␤-rebound attenuation might relate to neural processes involved in trial-to-trial adaptive mechanisms. In two EEG experiments with human participants, along with the ␤-rebound, we examine ␤-activity during the preparation of reaches immediately following perturbed movements. In the first experiment , we show that both foreperiod and postmovement ␤-activities are parametrically modulated by the sizes of kinematic errors produced by unpredictable mechanical perturbations (force field) independent of their on-line corrections. In the second experiment, we contrast two types of reach errors: movement-execution errors that trigger trial-to-trial adaptive mechanisms and goal errors that do not elicit sensorimotor adaptation. Movement-execution errors were induced by mechanical or visual perturbations, whereas goal errors were caused by unexpected displacements of the target at movement initiation. Interestingly, foreperiod and postmovement ␤-activities exhibit contrasting patterns, pointing to important functional differences of their underlying neuronal activity. While both types of reach errors attenuate the postmovement ␤-rebound, only the kinematic errors that trigger trial-to-trial motor-command updates influenced ␤-activity during the foreperiod. These findings suggest that the error-related modulation of the ␤-rebound may reflect salience processing , independent of sensorimotor adaptation. In contrast, modulations in the foreperiod ␤-power might relate to the motor-command adjustments activated after movement-execution errors are experienced

Neurophysiological Correlates of Trait Impulsivity in Parkinson's Disease.

BACKGROUND Impulsivity is common in people with Parkinson's disease (PD), with many developing impulsive compulsive behavior disorders (ICB). Its pathophysiological basis remains unclear. OBJECTIVES We aimed to investigate local field potential (LFP) markers of trait impulsivity in PD and their relationship to ICB. METHODS We recorded subthalamic nucleus (STN) LFPs in 23 PD patients undergoing deep brain stimulation implantation. Presence and severity of ICB were assessed by clinical interview and the Questionnaire for Impulsive-Compulsive Disorders in PD-Rating Scale (QUIP-RS), whereas trait impulsivity was estimated with the Barratt Impulsivity Scale (BIS-11). Recordings were obtained during the off dopaminergic states and the power spectrum of the subthalamic activity was analyzed using Fourier transform-based techniques. Assessment of each electrode contact localization was done to determine the topography of the oscillatory activity recorded. RESULTS Patients with (n = 6) and without (n = 17) ICB had similar LFP spectra. A multiple regression model including QUIP-RS, BIS-11, and Unified PD Rating Scale-III scores as regressors showed a significant positive correlation between 8-13 Hz power and BIS-11 score. The correlation was mainly driven by the motor factor of the BIS-11, and was irrespective of the presence or absence of active ICB. Electrode contact pairs with the highest α power, which also correlated most strongly with BIS-11, tended to be more ventral than contact pairs with the highest beta power, which localize to the dorsolateral motor STN. CONCLUSIONS Our data suggest a link between α power and trait impulsivity in PD, irrespective of the presence and severity of ICB. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society

Combining Multimodal Biomarkers to Guide Deep Brain Stimulation Programming in Parkinson Disease

BACKGROUND Deep brain stimulation (DBS) programming of multicontact DBS leads relies on a very time-consuming manual screening procedure, and strategies to speed up this process are needed. Beta activity in subthalamic nucleus (STN) local field potentials (LFP) has been suggested as a promising marker to index optimal stimulation contacts in patients with Parkinson disease. OBJECTIVE In this study, we investigate the advantage of algorithmic selection and combination of multiple resting and movement state features from STN LFPs and imaging markers to predict three relevant clinical DBS parameters (clinical efficacy, therapeutic window, side-effect threshold). MATERIALS AND METHODS STN LFPs were recorded at rest and during voluntary movements from multicontact DBS leads in 27 hemispheres. Resting- and movement-state features from multiple frequency bands (alpha, low beta, high beta, gamma, fast gamma, high frequency oscillations [HFO]) were used to predict the clinical outcome parameters. Subanalyses included an anatomical stimulation sweet spot as an additional feature. RESULTS Both resting- and movement-state features contributed to the prediction, with resting (fast) gamma activity, resting/movement-modulated beta activity, and movement-modulated HFO being most predictive. With the proposed algorithm, the best stimulation contact for the three clinical outcome parameters can be identified with a probability of almost 90% after considering half of the DBS lead contacts, and it outperforms the use of beta activity as single marker. The combination of electrophysiological and imaging markers can further improve the prediction. CONCLUSION LFP-guided DBS programming based on algorithmic selection and combination of multiple electrophysiological and imaging markers can be an efficient approach to improve the clinical routine and outcome of DBS patients

Electrophysiological differences between upper and lower limb movements in the human subthalamic nucleus

OBJECTIVE Functional processes in the brain are segregated in both the spatial and spectral domain. Motivated by findings reported at the cortical level in healthy participants we test the hypothesis in the basal ganglia of Parkinson's disease patients that lower frequency beta band activity relates to motor circuits associated with the upper limb and higher beta frequencies with lower limb movements. METHODS We recorded local field potentials (LFPs) from the subthalamic nucleus using segmented "directional" DBS leads, during which patients performed repetitive upper and lower limb movements. Movement-related spectral changes in the beta and gamma frequency-ranges and their spatial distributions were compared between limbs. RESULTS We found that the beta desynchronization during leg movements is characterised by a strikingly greater involvement of higher beta frequencies (24-31 Hz), regardless of whether this was contralateral or ipsilateral to the limb moved. The spatial distribution of limb-specific movement-related changes was evident at higher gamma frequencies. CONCLUSION Limb processing in the basal ganglia is differentially organised in the spectral and spatial domain and can be captured by directional DBS leads. SIGNIFICANCE These findings may help to refine the use of the subthalamic LFPs as a control signal for adaptive DBS and neuroprosthetic devices

Electrophysiological correlates of movement-execution errors and sensorimotor adaptation

Chez l’humain, les corrélats EEG du système de supervision de l’action ont largement été explorés dans le cadre de travaux sur la prise de décision, mettant en évidence plusieurs potentiels évoqués caractéristiques du traitement des erreurs de sélection de l'action. Typiquement, les tâches employées impliquent des réponses motrices élémentaires et l’évaluation des performances est de nature catégorielle. En contraste, l'EEG n'a que rarement été associée à des tâches motrices plus complexes, dans lesquelles les erreurs d'exécution du mouvement correspondent à des événements spatio-temporels variant en amplitude de manière continue. Pour explorer les corrélats EEG du traitement des erreurs d’exécution du mouvement nous avons enregistré l'activité cérébrale de participants engagés dans des tâches d'adaptation visuomotrice impliquant des perturbations mécaniques ou visuelles.Dans une première étude, nous avons identifié une négativité fronto-centrale sensible à la taille des erreurs cinématiques. Sa forte similitude avec la négativité liée au feedback (FRN), classiquement associée aux erreurs de prédiction de la récompense (EPR) suggère que le traitement des erreurs de prédiction sensorielles recrute des processus neuronaux communs à celui des EPR. Dans une seconde étude, nous avons exploré la sensibilité de l'activité oscillatoire β aux erreurs cinématiques. Nous avons ainsi mis en évidence deux patrons de modulation distincts. Alors que la modulation du rebond β post-mouvement serait liée à la saillance des erreurs cinématiques indépendamment de l’adaptation sensorimotrice, la modulation de la puissance β pré-mouvement semble être le reflet de mécanismes adaptatifs.In humans, EEG correlates of performance monitoring have been extensively investigated in relation to decision-making theories. Event-related potentials correlates of error processing have been well documented using choice reaction-time tasks in which very simple motor responses are required. In these tasks, errors concern inappropriate action selection only and the evaluation of the performance is discrete (e.g. failure or success). In contrast, EEG activity has been much less examined in more complex motor tasks in which inaccurate movement-execution produces errors that vary continuously in magnitude. Our goal was to explore EEG correlates of movement-error processing and sensorimotor adaptation. In this purpose, we recorded EEG while volunteers performed reaching movements under mechanically or visually perturbed conditions. In a first study, we identified a fronto-central negativity whose amplitude was modulated by the size of movement errors. This potential presents great similarities with the Feedback Related Negativity (FRN), a potential often assumed to reflect reward-prediction errors (RPE). These findings suggest that the processing of movement-execution errors, corresponding to sensory-prediction errors, and the processing of RPE involve a shared neural network. In a second study we assessed β-power sensitivity to errors and found two clearly distinct patterns of β-band modulation. Our results suggest that the postmovement β-power may reflect error-salience processing independent of sensorimotor adaptation whereas modulations in the foreperiod may directly relate to the motor-command adjustments activated after movement-execution errors are experienced

Modulation of Beta Bursts in the Subthalamic Nucleus Predicts Motor Performance

Considerable evidence suggests a role of beta-band oscillations in voluntary movements. However, most of the studies linking beta power to motor performance are based on data averaged across trials that ignore the fast dynamics of oscillatory activity and trial-to-trial variations in motor responses. Recently, emphasis has shifted from the functional implications of the mean beta power to the presence and nature of episodic bursts of beta activity. Here we test the hypothesis that beta bursts, though short in duration in more physiological state, may help explain spontaneous variations in motor behavior of human adults at the single-trial level. To this end, we recorded local field potential activity from the subthalamic nucleus of parkinsonian patients of both genders whose motor behavior had been normalized as far as possible through treatment with the dopamine prodrug, levodopa. We found that beta bursts present in a time-limited window well before movement onset in the contralateral subthalamic nucleus reduce the peak velocity of that movement and that this effect is further amplified by the amplitude of the burst. Additionally, prolonged reaction times are observed when bursts occur immediately after the GO cue. Together, these results suggest that the modulation of the timing and amplitude of beta bursts might serve to dynamically adapt motor performance. These results offer new insight in the pathology of Parkinson's disease, and suggest that beta bursts whose presence and nature are modulated by context may have a physiological role in modulating behavior

Balance between competing spectral states in subthalamic nucleus is linked to motor impairment in Parkinson's disease.

Exaggerated bursts of activity at frequencies in the low beta band are a well-established phenomenon in the subthalamic nucleus (STN) of patients with Parkinson's disease. However, such activity is only moderately correlated with motor impairment. Here we test the hypothesis that beta bursts are just one of several dynamic states in the STN local field potential (LFP) in Parkinson's disease, and that together these different states predict motor impairment with high fidelity. LFPs were recorded in 32 patients (64 hemispheres) undergoing deep brain stimulation surgery targeting the STN. Recordings were performed following overnight withdrawal of anti-parkinsonian medication, and after administration of levodopa. LFPs were analysed using Hidden Markov Modelling to identify transient spectral states with frequencies under 40 Hz. Findings in the low beta frequency band were similar to those previously reported; levodopa reduced occurrence rate and duration of low beta states, and the greater the reductions, the greater the improvement in motor impairment. However, additional LFP states were distinguished in the theta, alpha and high beta bands, and these behaved in an opposite manner. They were increased in occurrence rate and duration by levodopa, and the greater the increases, the greater the improvement in motor impairment. In addition, levodopa favoured the transition of low beta states to other spectral states. When all LFP states and corresponding features were considered in a multivariate model it was possible to predict 50% of the variance in patients' hemibody impairment OFF medication, and in the change in hemibody impairment following levodopa. This only improved slightly if signal amplitude or gamma band features were also included in the multivariate model. In addition, it compares with a prediction of only 16% of the variance when using beta bursts alone. We conclude that multiple spectral states in the STN LFP have a bearing on motor impairment, and that levodopa-induced shifts in the balance between these states can predict clinical change with high fidelity. This is important in suggesting that some states might be upregulated to improve parkinsonism and in suggesting how LFP feedback can be made more informative in closed-loop deep brain stimulation systems

Balance between competing spectral states in Subthalamic nucleus is linked to motor impairment in Parkinson’s Disease

Exaggerated bursts of activity at frequencies in the low beta band are a well-established phenomenon in the subthalamic nucleus (STN) of patients with Parkinson’s disease. However, such activity is only moderately correlated with motor impairment. Here we test the hypothesis that beta bursts are just one of several dynamic states in the STN local field potential (LFP) in Parkinson’s disease, and that together these different states predict motor impairment with high fidelity. LFPs were recorded in 32 patients (64 hemispheres) undergoing deep brain stimulation surgery targeting the STN. Recordings were performed following overnight withdrawal of anti-parkinsonian medication, and after administration of levodopa. LFPs were analysed using Hidden Markov Modelling to identify transient spectral states with frequencies under 40Hz. Findings in the low beta frequency band were similar to those previously reported; levodopa reduced occurrence rate and duration of low beta states, and the greater the reductions, the greater the improvement in motor impairment. However, additional LFP states were distinguished in the theta, alpha and high beta bands, and these behaved in an opposite manner. They were increased in occurrence rate and duration by levodopa, and the greater the increases, the greater the improvement in motor impairment. In addition, levodopa favoured the transition of low beta states to other spectral states. When all LFP states and corresponding features were considered in a multivariate model it was possible to predict 50% of the variance in patients’ hemibody impairment OFF medication, and in the change in hemibody impairment following levodopa. This only improved slightly if signal amplitude or gamma band features were also included in the multivariate model. In addition, it compares with a prediction of only 16% of the variance when using beta bursts alone. We conclude that multiple spectral states in the STN LFP have a bearing on motor impairment, and that levodopa-induced shifts in the balance between these states can predict clinical change with high fidelity. This is important in suggesting that some states might be upregulated to improve parkinsonism and in suggesting how LFP feedback can be made more informative in closed-loop deep brain stimulation systems

Beta burst coupling across the motor circuit in Parkinson's disease

Exaggerated activity in the beta band (13-35 Hz) is a hallmark of basal ganglia signals in patients with Parkinson's disease (PD). Beta activity however is not constantly elevated, but comes in bursts. In previous work we showed that the longer beta bursts are maintained, the more the oscillatory synchronisation within the subthalamic nucleus (STN) increases, which is posited to limit the information coding capacity of local circuits. Accordingly, a higher incidence of longer bursts correlates positively with clinical impairment, while the opposite is true for short, more physiological bursts. Here, we test the hypothesis that beta bursts not only indicate local synchronisation within the STN, but also phasic coupling across the motor network and hence entail an even greater restriction of information coding capacity in patients with PD. Local field potentials from the subthalamic nucleus and EEG over the motor cortex area were recorded in nine PD patients after temporary lead externalization after surgery for deep brain stimulation and overnight withdrawal of levodopa. Beta bursts were defined as periods exceeding the 75th percentile of signal amplitude and the coupling between bursts was considered using two distinct measurements, first the % overlapping (%OVL) as a feature of the amplitude coupling and secondly the phase synchrony index (PSI) to measure the phase coupling between regions. %OVL between STN and cortex and between the left and the right STN was higher than expected between the regions than if they had been independent. Similarly, PSI was higher during bursts as opposed to non-bursts periods. In addition, %OVL was greater for long compared to short bursts. Our results support the hypothesis that beta bursts involve long-range coupling between structures in the basal ganglia-cortical network. The impact of this is greater during long as opposed to short duration beta bursts. Accordingly, we posit that episodes of simultaneously elevated coupling across multiple structures in the basal ganglia-cortical circuit further limit information coding capacity and may have further impact upon motor impairment