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Introduction: Increased motor fatigability is a symptom of many neuromuscular and neurodegenerative disorders. However, it is difficult to pinpoint pathological motor fatigability, since the phenomena has not yet been fully characterized in the healthy population. In this study, we investigate how motor fatigability differs across age. Given that many disorders involve supraspinal components, we characterize motor fatigability with a paradigm that has previously been associated with supraspinal mechanisms. Finger tapping at maximal speed results in a rapid decrease in movement speed, which is a measure of motor fatigability. Methods: We collected finger tapping data in a field experiment from the general population with a smartphone app, and we investigated age differences in maximal tapping speed, as well as the decrease in tapping speed for the index, middle, and little fingers. Results: We found that the maximal tapping speed differed significantly between young (18-30 years, n = 194) and aged (50-70 years, n = 176), whereas the fatigability-induced relative decrease in movement speed did not differ between the age groups (average decrease: 17.0% ± 6.9% (young) vs. 16.5% ± 7.5% (aged) decrease). Furthermore, tapping speed and motor fatigability depended on which finger was used. Discussion: These findings might relate to dexterity, with more dexterous movements being more resistant to fatigue. In this study, we provide a characterization of motor fatigability in the general population which can be used as a comparison for clinical populations in the future. [ABSTRACT FROM AUTHOR]

Autism spectrum disorders (ASD) are a set of complex neurodevelopmental disorders for which there is currently no targeted therapeutic approach. It is thought that alterations of genes regulating migration and synapse formation during development affect neural circuit formation and result in aberrant connectivity within distinct circuits that underlie abnormal behaviors. However, it is unknown whether deviant developmental trajectories are circuit-specific for a given autism risk-gene. We used MRI to probe changes in functional and structural connectivity from childhood to adulthood in Fragile-X (Fmr1-/y) and contactin-associated (CNTNAP2-/-) knockout mice. Young Fmr1-/y mice (30 days postnatal) presented with a robust hypoconnectivity phenotype in corticocortico and corticostriatal circuits in areas associated with sensory information processing, which was maintained until adulthood. Conversely, only small differences in hippocampal and striatal areas were present during early postnatal development in CNTNAP2-/- mice, while major connectivity deficits in prefrontal and limbic pathways developed between adolescence and adulthood. These findings are supported by viral tracing and electron micrograph approaches and define 2 clearly distinct connectivity endophenotypes within the autism spectrum. We conclude that the genetic background of ASD strongly influences which circuits are most affected, the nature of the phenotype, and the developmental time course of the associated changes.

The second iteration of the Autism Brain Imaging Data Exchange (ABIDE II) aims to enhance the scope of brain connectomics research in Autism Spectrum Disorder (ASD). Consistent with the initial ABIDE effort (ABIDE I), that released 1112 datasets in 2012, this new multisite open-data resource is an aggregate of resting state functional magnetic resonance imaging (MRI) and corresponding structural MRI and phenotypic datasets. ABIDE II includes datasets from an additional 487 individuals with ASD and 557 controls previously collected across 16 international institutions. The combination of ABIDE I and ABIDE II provides investigators with 2156 unique cross-sectional datasets allowing selection of samples for discovery and/or replication. This sample size can also facilitate the identification of neurobiological subgroups, as well as preliminary examinations of sex differences in ASD. Additionally, ABIDE II includes a range of psychiatric variables to inform our understanding of the neural correlates of co-occurring psychopathology; 284 diffusion imaging datasets are also included. It is anticipated that these enhancements will contribute to unraveling key sources of ASD heterogeneity.

Transcranial direct current stimulation (tDCS) may facilitate neuroplasticity but with a limited effect when administered while patients with stroke are at rest. Muscle-computer interface (MCI) training is a promising approach for training patients with stroke even if they cannot produce overt movements. However, using tDCS to enhance MCI training has not been investigated. We combined bihemispheric tDCS with MCI training of the paretic wrist and examined the effect of this intervention in patients with chronic stroke. A crossover, double-blind, randomized trial was conducted. Twenty-six patients with chronic stroke performed MCI wrist training for three consecutive days at home while receiving either real tDCS or sham tDCS in counterbalanced order and separated by at least 8 mo. The primary outcome measure was the Fugl-Meyer Assessment Upper Extremity Scale (FMA-UE) that was measured 1 wk before training, on the first training day, on the last training day, and 1 wk after training. There was neither a significant difference in the baseline FMA-UE score between groups nor between intervention periods. Patients improved 3.9 ± 0.6 points in FMA-UE score when receiving real tDCS, and 1.0 ± 0.7 points when receiving sham tDCS (P = 0.003). In addition, patients also showed continuous improvement in their motor control of the MCI tasks over the training days. Our study showed that the training paradigm could lead to functional improvement in patients with chronic stroke. We argue that appropriate MCI training in combination with bihemispheric tDCS could be a useful adjuvant for neurorehabilitation in patients with stroke. NEW & NOTEWORTHY: Bihemispheric tDCS combined with a novel MCI training for motor control of wrist extensor can improve upper limb function especially a training-specific effect on the wrist movement in patients with chronic stroke. The training regimen can be personalized with adjustments made daily to accommodate the functional change throughout the intervention. This demonstrates that bihemispheric tDCS with MCI training could complement conventional poststroke neurorehabilitation. [ABSTRACT FROM AUTHOR]