Population-wide cerebellar growth models of children and adolescents.

In the past, the cerebellum has been best known for its crucial role in motor function. However, increasingly more findings highlight the importance of cerebellar contributions in cognitive functions and neurodevelopment. Using a total of 7240 neuroimaging scans from 4862 individuals, we describe and provide detailed, openly available models of cerebellar development in childhood and adolescence (age range: 6-17 years), an important time period for brain development and onset of neuropsychiatric disorders. Next to a traditionally used anatomical parcellation of the cerebellum, we generated growth models based on a recently proposed functional parcellation. In both, we find an anterior-posterior growth gradient mirroring the age-related improvements of underlying behavior and function, which is analogous to cerebral maturation patterns and offers evidence for directly related cerebello-cortical developmental trajectories. Finally, we illustrate how the current approach can be used to detect cerebellar abnormalities in clinical samples.

Biallelic PAX5 mutations cause hypogammaglobulinemia, sensorimotor deficits, and autism spectrum disorder.

The genetic causes of primary antibody deficiencies and autism spectrum disorder (ASD) are largely unknown. Here, we report a patient with hypogammaglobulinemia and ASD who carries biallelic mutations in the transcription factor PAX5. A patient-specific Pax5 mutant mouse revealed an early B cell developmental block and impaired immune responses as the cause of hypogammaglobulinemia. Pax5 mutant mice displayed behavioral deficits in all ASD domains. The patient and the mouse model showed aberrant cerebellar foliation and severely impaired sensorimotor learning. PAX5 deficiency also caused profound hypoplasia of the substantia nigra and ventral tegmental area due to loss of GABAergic neurons, thus affecting two midbrain hubs, controlling motor function and reward processing, respectively. Heterozygous Pax5 mutant mice exhibited similar anatomic and behavioral abnormalities. Lineage tracing identified Pax5 as a crucial regulator of cerebellar morphogenesis and midbrain GABAergic neurogenesis. These findings reveal new roles of Pax5 in brain development and unravel the underlying mechanism of a novel immunological and neurodevelopmental syndrome.

Individual differences in error-related frontal midline theta activity during visuomotor adaptation.

Post-feedback frontal midline EEG activity has been found to correlate with error magnitude during motor adaptation. However, the role of this neuronal activity remains to be elucidated. It has been hypothesized that post-feedback frontal midline activity may represent a prediction error, which in turn may be directly related to the adaptation process or to an unspecific orienting response. To address these hypotheses, we replicated a previous visuomotor adaptation experiment with very small perturbations, likely to invoke implicit adaptation, in a new group of 60 participants and combined it with EEG recordings. We found error-related peaks in the frontal midline electrodes in the time domain. However, these were best understood as modulations of frontal midline theta activity (FMT, 4-8 Hz). Trial-level differences in FMT correlated with error magnitude. This correlation was robust even for very small errors as well as in the absence of imposed perturbations, indicating that FMT does not depend on explicit or strategic re-aiming. Within participants, trial-level differences in FMT were not related to between-trial error corrections. Between participants, individual differences in FMT-error-sensitivity did not predict differences in adaptation rate. Taken together, these results imply that FMT does not drive implicit motor adaptation. Finally, individual differences in FMT-error-sensitivity negatively correlate to motor execution noise. This suggests that FMT reflects saliency: larger execution noise means a larger standard deviation of errors so that a fixed error magnitude is less salient. In conclusion, this study suggests that frontal midline theta activity represents a saliency signal and does not directly drive motor adaptation.

Computerised patient-specific prediction of the recovery profile of upper limb capacity within stroke services: the next step.

INTRODUCTION: Predicting upper limb capacity recovery is important to set treatment goals, select therapies and plan discharge. We introduce a prediction model of the patient-specific profile of upper limb capacity recovery up to 6 months poststroke by incorporating all serially assessed clinical information from patients. METHODS: Model input was recovery profile of 450 patients with a first-ever ischaemic hemispheric stroke measured using the Action Research Arm Test (ARAT). Subjects received at least three assessment sessions, starting within the first week until 6 months poststroke. We developed mixed-effects models that are able to deal with one or multiple measurements per subject, measured at non-fixed time points. The prediction accuracy of the different models was established by a fivefold cross-validation procedure. RESULTS: A model with only ARAT time course, finger extension and shoulder abduction performed as good as models with more covariates. For the final model, cross-validation prediction errors at 6 months poststroke decreased as the number of measurements per subject increased, from a median error of 8.4 points on the ARAT (Q1-Q3:1.7-28.1) when one measurement early poststroke was used, to 2.3 (Q1-Q3:1-7.2) for seven measurements. An online version of the recovery model was developed that can be linked to data acquisition environments. CONCLUSION: Our innovative dynamic model can predict real-time, patient-specific upper limb capacity recovery profiles up to 6 months poststroke. The model can use all available serially assessed data in a flexible way, creating a prediction at any desired moment poststroke, stand-alone or linked with an electronic health record system.

Predicting Upper Limb Motor Impairment Recovery after Stroke: A Mixture Model.

OBJECTIVE: Spontaneous recovery is an important determinant of upper extremity recovery after stroke and has been described by the 70% proportional recovery rule for the Fugl-Meyer motor upper extremity (FM-UE) scale. However, this rule is criticized for overestimating the predictability of FM-UE recovery. Our objectives were to develop a longitudinal mixture model of FM-UE recovery, identify FM-UE recovery subgroups, and internally validate the model predictions. METHODS: We developed an exponential recovery function with the following parameters: subgroup assignment probability, proportional recovery coefficient r k , time constant in weeks τ k , and distribution of the initial FM-UE scores. We fitted the model to FM-UE measurements of 412 first-ever ischemic stroke patients and cross-validated endpoint predictions and FM-UE recovery cluster assignment. RESULTS: The model distinguished 5 subgroups with different recovery parameters ( r1 = 0.09, τ1 = 5.3, r2 = 0.46, τ2 = 10.1, r3 = 0.86, τ3 = 9.8, r4 = 0.89, τ4 = 2.7, r5 = 0.93, τ5 = 1.2). Endpoint FM-UE was predicted with a median absolute error of 4.8 (interquartile range [IQR] = 1.3-12.8) at 1 week poststroke and 4.2 (IQR = 1.3-9.8) at 2 weeks. Overall accuracy of assignment to the poor (subgroup 1), moderate (subgroups 2 and 3), and good (subgroups 4 and 5) FM-UE recovery clusters was 0.79 (95% equal-tailed interval [ETI] = 0.78-0.80) at 1 week poststroke and 0.81 (95% ETI = 0.80-0.82) at 2 weeks. INTERPRETATION: FM-UE recovery reflects different subgroups, each with its own recovery profile. Cross-validation indicates that FM-UE endpoints and FM-UE recovery clusters can be well predicted. Results will contribute to the understanding of upper limb recovery patterns in the first 6 months after stroke. ANN NEUROL 2020;87:383-393 Ann Neurol 2020;87:383-393.

TMS motor mapping: Comparing the absolute reliability of digital reconstruction methods to the golden standard.

BACKGROUND: Changes in transcranial magnetic stimulation motor map parameters can be used to quantify plasticity in the human motor cortex. The golden standard uses a counting analysis of motor evoked potentials (MEPs) acquired with a predefined grid. Recently, digital reconstruction methods have been proposed, allowing MEPs to be acquired with a faster pseudorandom procedure. However, the reliability of these reconstruction methods has never been compared to the golden standard. OBJECTIVE: To compare the absolute reliability of the reconstruction methods with the golden standard. METHODS: In 21 healthy subjects, both grid and pseudorandom acquisition were performed twice on the first day and once on the second day. The standard error of measurement was calculated for the counting analysis and the digital reconstructions. RESULTS: The standard error of measurement was at least equal using digital reconstructions. CONCLUSION: Pseudorandom acquisition and digital reconstruction can be used in intervention studies without sacrificing reliability.

Individual Differences in Motor Noise and Adaptation Rate Are Optimally Related.

Individual variations in motor adaptation rate were recently shown to correlate with movement variability or "motor noise" in a forcefield adaptation task. However, this finding could not be replicated in a meta-analysis of adaptation experiments. Possibly, this inconsistency stems from noise being composed of distinct components that relate to adaptation rate in different ways. Indeed, previous modeling and electrophysiological studies have suggested that motor noise can be factored into planning noise, originating from the brain, and execution noise, stemming from the periphery. Were the motor system optimally tuned to these noise sources, planning noise would correlate positively with adaptation rate, and execution noise would correlate negatively with adaptation rate, a phenomenon familiar in Kalman filters. To test this prediction, we performed a visuomotor adaptation experiment in 69 subjects. Using a novel Bayesian fitting procedure, we succeeded in applying the well-established state-space model of adaptation to individual data. We found that adaptation rate correlates positively with planning noise (ß = 0.44; 95% HDI = [0.27 0.59]) and negatively with execution noise (ß = -0.39; 95% HDI = [-0.50 -0.30]). In addition, the steady-state Kalman gain calculated from planning and execution noise correlated positively with adaptation rate (r = 0.54; 95% HDI = [0.38 0.66]). These results suggest that motor adaptation is tuned to approximate optimal learning, consistent with the "optimal control" framework that has been used to explain motor control. Since motor adaptation is thought to be a largely cerebellar process, the results further suggest the sensitivity of the cerebellum to both planning noise and execution noise.

Cerebellar transcranial direct current stimulation interacts with BDNF Val66Met in motor learning.

BACKGROUND: Cerebellar transcranial direct current stimulation has been reported to enhance motor associative learning and motor adaptation, holding promise for clinical application in patients with movement disorders. However, behavioral benefits from cerebellar tDCS have been inconsistent. OBJECTIVE: Identifying determinants of treatment success is necessary. BDNF Val66Met is a candidate determinant, because the polymorphism is associated with motor skill learning and BDNF is thought to mediate tDCS effects. METHODS: We undertook two cerebellar tDCS studies in subjects genotyped for BDNF Val66Met. Subjects performed an eyeblink conditioning task and received sham, anodal or cathodal tDCS (N = 117, between-subjects design) or a vestibulo-ocular reflex adaptation task and received sham and anodal tDCS (N = 51 subjects, within-subjects design). Performance was quantified as a learning parameter from 0 to 100%. We investigated (1) the distribution of the learning parameter with mixture modeling presented as the mean (M), standard deviation (S) and proportion (P) of the groups, and (2) the role of BDNF Val66Met and cerebellar tDCS using linear regression presented as the regression coefficients (B) and odds ratios (OR) with equally-tailed intervals (ETIs). RESULTS: For the eyeblink conditioning task, we found distinct groups of learners (MLearner = 67.2%; SLearner = 14.7%; PLearner = 61.6%) and non-learners (MNon-learner = 14.2%; SNon-learner = 8.0%; PNon-learner = 38.4%). Carriers of the BDNF Val66Met polymorphism were more likely to be learners (OR = 2.7 [1.2 6.2]). Within the group of learners, anodal tDCS supported eyeblink conditioning in BDNF Val66Met non-carriers (B = 11.9% 95%ETI = [0.8 23.0]%), but not in carriers (B = 1.0% 95%ETI = [-10.2 12.1]%). For the vestibulo-ocular reflex adaptation task, we found no effect of BDNF Val66Met (B = -2.0% 95%ETI = [-8.7 4.7]%) or anodal tDCS in either carriers (B = 3.4% 95%ETI = [-3.2 9.5]%) or non-carriers (B = 0.6% 95%ETI = [-3.4 4.8]%). Finally, we performed additional saccade and visuomotor adaptation experiments (N = 72) to investigate the general role of BDNF Val66Met in cerebellum-dependent learning and found no difference between carriers and non-carriers for both saccade (B = 1.0% 95%ETI = [-8.6 10.6]%) and visuomotor adaptation (B = 2.7% 95%ETI = [-2.5 7.9]%). CONCLUSIONS: The specific role for BDNF Val66Met in eyeblink conditioning, but not vestibulo-ocular reflex adaptation, saccade adaptation or visuomotor adaptation could be related to dominance of the role of simple spike suppression of cerebellar Purkinje cells with a high baseline firing frequency in eyeblink conditioning. Susceptibility of non-carriers to anodal tDCS in eyeblink conditioning might be explained by a relatively larger effect of tDCS-induced subthreshold depolarization in this group, which might increase the spontaneous firing frequency up to the level of that of the carriers.

The Role of the BDNF Val66Met Polymorphism in Recovery of Aphasia After Stroke.

BACKGROUND: Brain-derived neurotrophic factor (BDNF) is assumed to play a role in mediating neuroplasticity after stroke. Carriers of the function-limiting Val66Met (rs6265) single nucleotide polymorphism (SNP) may have a downregulation in BDNF secretion, which may lead to a poorer prognosis after stroke compared to noncarriers in motor learning and motor function recovery. The present study investigates whether this polymorphism may also affect the recovery of poststroke aphasia (ie, language impairment). OBJECTIVE: To study the influence of the BDNF Val66Met polymorphism on the recovery of poststroke aphasia. METHODS: We included 53 patients with poststroke aphasia, all participating in an inpatient rehabilitation program with speech and language therapy. All patients were genotyped for the Val66Met SNP and subdivided into carriers (at least one Met allele) and noncarriers (no Met allele). Primary outcome measures included the improvement over rehabilitation time on the Amsterdam-Nijmegen Everyday Language Test (ANELT) and the Boston Naming Test (BNT). RESULTS: The outcome measures showed a large variability in the improvement scores on both the ANELT and BNT. There was no significant difference between noncarriers and carriers in the primary outcome measures. CONCLUSION: This study investigated the effect of the BDNF Val66Met polymorphism on clinical recovery of poststroke aphasia. In contrast to earlier studies describing a reducing effect of this polymorphism on motor function recovery after stroke, the present study does not support a reduction in language recovery for carriers compared to noncarriers with poststroke aphasia.

BDNF Val66Met but not transcranial direct current stimulation affects motor learning after stroke.

BACKGROUND: tDCS is a non-invasive neuromodulation technique that has been reported to improve motor skill learning after stroke. However, the contribution of tDCS to motor skill learning has only been investigated in a small number of studies. In addition, it is unclear if tDCS effects are mediated by activity-dependent BDNF release and dependent on timing of tDCS relative to training. OBJECTIVE: Investigate the role of activity-dependent BDNF release and timing of tDCS relative to training in motor skill learning. METHODS: Double-blind, between-subjects randomized controlled trial of circuit tracing task improvement (ΔMotor skill) in 80 chronic stroke patients who underwent tDCS and were genotyped for BDNF Val66Met. Patients received either short-lasting tDCS (20 min) during training (short-lasting online group), long-lasting tDCS (10 min-25 min break - 10 min) one day before training (long-lasting offline group), short-lasting tDCS one day before training (short-lasting offline group), or sham tDCS. ΔMotor skill was defined as the skill difference on the circuit tracing task between day one and day nine of the study. RESULTS: Having at least one BDNF Met allele was found to diminish ΔMotor skill (ßBDNF,Met = -0.217 95%HDI = [-0.431 -0.0116]), indicating activity-dependent BDNF release is important for motor skill learning after stroke. However, none of the tDCS protocols affected ΔMotor skill (ßShort-lasting,online = 0.0908 95%HDI = [-0.227 0.403]; ßLong-lasting,offline = 0.0242 95%HDI = [-0.292 0.349]; ßShort-lasting,offline = -0.108 95%HDI = [-0.433 0.210]). CONCLUSION: BDNF Val66Met is a determinant of motor skill learning after stroke and could be important for prognostic models. tDCS does not modulate motor skill learning in our study and might be less effective than previously assumed.