Multimodal connectivity of motor learning-related dorsal premotor cortex

Symmetry in Frontal But Not Motor and Somatosensory Cortical Projections

The neocortex and striatum are topographically organized for sensory and motor functions. While sensory and motor areas are lateralized for touch and motor control, respectively, frontal areas are involved in decision-making, where lateralization of function may be less important. This study contrasted the topographic precision of cell-type-specific ipsilateral and contralateral cortical projections while varying the injection site location in transgenic mice of both sexes. While sensory cortical areas had strongly topographic outputs to the ipsilateral cortex and striatum, they were weaker and not as topographically precise to contralateral targets. The motor cortex had somewhat stronger projections but still relatively weak contralateral topography. In contrast, frontal cortical areas had high degrees of topographic similarity for both ipsilateral and contralateral projections to the cortex and striatum. Corticothalamic organization is mainly ipsilateral, with weaker, more medial contralateral projections. Corticostriatal computations might integrate input outside closed basal ganglia loops using contralateral projections, enabling the two hemispheres to act as a unit to converge on one result in motor planning and decision-making.

Brain functional characterization of response-code conflict in dual-tasking and its modulation by age

Crosstalk between conflicting response codes contributes to interference in dual-tasking, an effect exacerbated in advanced age. Here, we investigated (i) brain activity correlates of such response-code conflicts, (ii) activity modulations by individual dual-task performance and related cognitive abilities, (iii) task-modulated connectivity within the task network, and (iv) age-related differences in all these aspects. Young and older adults underwent fMRI while responding to the pitch of tones through spatially mapped speeded button presses with one or two hands concurrently. Using opposing stimulus-response mappings between hands, we induced conflict between simultaneously activated response codes. These response-code conflicts elicited activation in key regions of the multiple-demand network. While thalamic and parietal areas of the conflict-related network were modulated by attentional, working-memory and task-switching abilities, efficient conflict resolution in dual-tasking mainly relied on increasing supplementary motor activity. Older adults showed non-compensatory hyperactivity in left superior frontal gyrus, and higher right premotor activity was modulated by working-memory capacity. Finally, connectivity between premotor or parietal seed regions and the conflict-sensitive network was neither conflict-specific nor age-sensitive. Overall, resolving dual-task response-code conflict recruited substantial parts of the multiple-demand network, whose activity and coupling, however, were only little affected by individual differences in task performance or age.

Neurofunctional correlates of a neurorehabilitation system based on eye movements in chronic stroke impairment levels: A pilot study

INTRODUCTION

Rehabilitation after a stroke is widely considered fundamental to improve secondary functional impairments. Accessible methods based on motor learning, motor transfer and virtual environments are necessary to help to improve stroke patients' quality of life.

OBJECTIVES

Continuing the line of our previous studies, this work investigated the effect of our new and innovative game-based virtual reality training using the control of virtual objects with gaze in three chronic stroke survivors.

METHODS

All participants performed an eye-controlled virtual training task for 4 weeks. Pre- and post-training evaluation were carried out with the Fugl-Meyer Assessment for upper extremity scale as well as performing a tracking task inside an MRI scanner with a MRI-compatible eye-tracker or a joystick.

RESULTS

Neural results for each participant show the increase of activity in the motor cortex, basal ganglia and cerebellum for both effectors (hand or eye).

CONCLUSION

These promising results have a potential application as a new game-based neurorehabilitation approach to enhance the motor activity of stroke patients.

Rethinking recovery in adolescent concussions: Network-level functional connectivity alterations associated with motor deficits

Adolescents who are clinically recovered from concussion continue to show subtle motor impairment on neurophysiological and behavioral measures. However, there is limited information on brain-behavior relationships of persistent motor impairment following clinical recovery from concussion. We examined the relationship between subtle motor performance and functional connectivity of the brain in adolescents with a history of concussion, status post-symptom resolution, and subjective return to baseline. Participants included 27 adolescents who were clinically recovered from concussion and 29 never-concussed, typically developing controls (10-17 years); all participants were examined using the Physical and Neurologic Examination of Subtle Signs (PANESS). Functional connectivity between the default mode network (DMN) or dorsal attention network (DAN) and regions of interest within the motor network was assessed using resting-state functional magnetic resonance imaging (rsfMRI). Compared to controls, adolescents clinically recovered from concussion showed greater subtle motor deficits as evaluated by the PANESS and increased connectivity between the DMN and left lateral premotor cortex. DMN to left lateral premotor cortex connectivity was significantly correlated with the total PANESS score, with more atypical connectivity associated with more motor abnormalities. This suggests that altered functional connectivity of the brain may underlie subtle motor deficits in adolescents who have clinically recovered from concussion. More investigation is required to understand the persistence and longer-term clinical relevance of altered functional connectivity and associated subtle motor deficits to inform whether functional connectivity may serve as an important biomarker related to longer-term outcomes after clinical recovery from concussion.

Risk-taking in the human brain: An activation likelihood estimation meta-analysis of the balloon analog risk task (BART)

The Balloon Analog Risk Task (BART) is increasingly used to assess risk-taking behavior and brain function. However, the brain networks underlying risk-taking during the BART and its reliability remain controversial. Here, we combined the activation likelihood estimation (ALE) meta-analysis with both task-based and task-free functional connectivity (FC) analysis to quantitatively synthesize brain networks involved in risk-taking during the BART, and compared the differences between adults and adolescents studies. Based on 22 pooled publications, the ALE meta-analysis revealed multiple brain regions in the reward network, salience network, and executive control network underlying risk-taking during the BART. Compared with adult risk-taking, adolescent risk-taking showed greater activation in the insula, putamen, and prefrontal regions. The combination of meta-analytic connectivity modeling with task-free FC analysis further confirmed the involvement of the reward, salience, and cognitive control networks in the BART. These findings demonstrate the core brain networks for risk-taking during the BART and support the utility of the BART for future neuroimaging and developmental research.

Motor training-related brain reorganization in patients with cerebellar degeneration

Cerebellar degeneration progressively impairs motor function. Recent research showed that cerebellar patients can improve motor performance with practice, but the optimal feedback type (visual, proprioceptive, verbal) for such learning and the underlying neuroplastic changes are unknown. Here, patients with cerebellar degeneration (N = 40) and age‐ and sex‐matched healthy controls (N = 40) practiced single‐joint, goal‐directed forearm movements for 5 days. Cerebellar patients improved performance during visuomotor practice, but a training focusing on either proprioceptive feedback, or explicit verbal feedback and instruction did not show additional benefits. Voxel‐based morphometry revealed that after training gray matter volume (GMV) was increased prominently in the visual association cortices of controls, whereas cerebellar patients exhibited GMV increase predominantly in premotor cortex. The premotor cortex as a recipient of cerebellar efferents appears to be an important hub in compensatory remodeling following damage of the cerebro‐cerebellar motor system.

The neural signatures of social hierarchy-related learning and interaction: A coordinate- and connectivity-based meta-analysis

Numerous neuroimaging studies have investigated the neural mechanisms of two mutually independent yet closely related cognitive processes aiding humans to navigate complex societies: social hierarchy-related learning (SH-RL) and social hierarchy-related interaction (SH-RI). To integrate these heterogeneous results into a more fine-grained and reliable characterization of the neural basis of social hierarchy, we combined coordinate-based meta-analyses with connectivity and functional decoding analyses to understand the underlying neuropsychological mechanism of SH-RL and SH-RI. We identified the anterior insula and temporoparietal junction (dominance detection), medial prefrontal cortex (information updating and computation), and intraparietal sulcus region, amygdala, and hippocampus (social hierarchy representation) as consistent activated brain regions for SH-RL, but the striatum, amygdala, and hippocampus associated with reward processing for SH-RI. Our results provide an overview of the neural architecture of the neuropsychological processes underlying how we understand, and interact within, social hierarchy.

Motor sequence learning in patients with ideomotor apraxia: Effects of long-term training

Recent studies show that limb apraxia is a quite frequent, yet often underdiagnosed, higher motor impairment following stroke. Because it adversely affects every-day life and personal independence, successful rehabilitation of apraxia is essential for personal well-being. Nevertheless, evidence of long-term efficacy of training schemes and generalization to untrained actions is still scarce. One possible reason for the tendency of this neurological disorder to persist may be a deficit in planning, conceptualisation and storage of complex motor acts. This pilot study aims at investigating explicit motor learning in apractic stroke patients. In particular, we addressed the ability of apractic patients to learn and to retain new explicit sequential finger movements across 10 training sessions over a 3-week interval. Nine stroke patients with ideomotor apraxia in its chronic stage participated in a multi-session training regimen and were included in data analyses. Patients performed an explicit finger sequence learning task (MSLT - motor sequence learning task), which is a well-established paradigm to investigate motor learning and memory processes. Patients improved task performance in terms of speed and accuracy across sessions. Specifically, they showed a noticeable reduction in the mean time needed to perform a correct sequence and the number of erroneous sequences. We found also a trend for improved performance at the Goldenberg apraxia test protocol: "imitation of meaningless hand and finger gestures" relative to when assessed before the MSLT training. Patients with ideomotor apraxia demonstrated the ability to acquire and maintain a novel sequence of movements; and, this training was associated with hints towards improvement of apraxia symptoms.

The Myelin Content of the Human Precentral Hand Knob Reflects Interindividual Differences in Manual Motor Control at the Physiological and Behavioral Level

The primary motor cortex hand area (M1_HAND) and adjacent dorsal premotor cortex (PMd) form the so-called motor hand knob in the precentral gyrus. M1_HAND and PMd are critical for dexterous hand use and are densely interconnected via corticocortical axons, lacking a sharp demarcating border. In 24 young right-handed volunteers, we performed multimodal mapping to delineate the relationship between structure and function in the right motor hand knob. Quantitative structural magnetic resonance imaging (MRI) at 3 tesla yielded regional R1 maps as a proxy of cortical myelin content. Participants also underwent functional MRI (fMRI). We mapped task-related activation and temporal precision, while they performed a visuomotor synchronization task requiring visually cued abduction movements with the left index or little finger. We also performed sulcus-aligned transcranial magnetic stimulation of the motor hand knob to localize the optimal site (hotspot) for evoking a motor evoked potential (MEP) in two intrinsic hand muscles. Individual motor hotspot locations varied along the rostrocaudal axis. The more rostral the motor hotspot location in the precentral crown, the longer were corticomotor MEP latencies. “Hotspot rostrality” was associated with the regional myelin content in the precentral hand knob. Cortical myelin content also correlated positively with task-related activation of the precentral crown and temporal precision during the visuomotor synchronization task. Together, our results suggest a link among cortical myelination, the spatial cortical representation, and temporal precision of finger movements. We hypothesize that the myelination of cortical axons facilitates neuronal integration in PMd and M1_HAND and, hereby, promotes the precise timing of movements.

SIGNIFICANCE STATEMENT Here we used magnetic resonance imaging and transcranial magnetic stimulation of the precentral motor hand knob to test for a link among cortical myelin content, functional corticomotor representations, and manual motor control. A higher myelin content of the precentral motor hand knob was associated with more rostral corticomotor presentations, with stronger task-related activation and a higher precision of movement timing during a visuomotor synchronization task. We propose that a high precentral myelin content enables fast and precise neuronal integration in M1 (primary motor cortex) and dorsal premotor cortex, resulting in higher temporal precision during dexterous hand use. Our results identify the degree of myelination as an important structural feature of the neocortex that is tightly linked to the function and behavior supported by the cortical area.

The emerging neuroscience of social punishment: Meta-analytic evidence

Social punishment (SOP)-third-party punishment (TPP) and second-party punishment (SPP)-sanctions norm-deviant behavior. The hierarchical punishment model (HPM) posits that TPP is an extension of SPP and both recruit common processes engaging large-scale domain-general brain networks. Here, we provided meta-analytic evidence to the HPM by combining the activation likelihood estimation approach with connectivity analyses and hierarchical clustering analyses. Although both forms of SOP engaged the dorsolateral prefrontal cortex and bilateral anterior insula (AI), a functional differentiation also emerged with TPP preferentially engaging social cognitive regions (temporoparietal junction) and SPP affective regions (AI). Further, although both TPP and SPP recruit domain-general networks (salience, default-mode, and central-executive networks), some specificity in network organization was observed. By revealing differences and commonalities of the neural networks consistently activated by different types of SOP, our findings contribute to a better understanding of the neuropsychological mechanisms of social punishment behavior--one of the most peculiar human behaviors.

Paired Associative Stimulation Rewired: A Novel Paradigm to Modulate Resting-State Intracortical Connectivity

Recent neuroimaging research has demonstrated that resting-state intracortical connectivity (i.e., the shared communication between two brain regions) can serve as a robust predictor of motor performance and learning. Theoretically, direct modulation of resting-state intracortical connectivity within the motor system could then improve motor performance and learning. However, previous neuromodulation techniques such as repetitive Transcranial Magnetic Stimulation may be limited in the capacity to modulate targeted intracortical connectivity. Paired Associative Stimulation (PAS) has shown efficacy in facilitating connectivity primarily between the central and peripheral nervous system based on the neuroplasticity mechanism of Spike Timing Dependent Plasticity. It may therefore be plausible for a reconfigured corticocortical PAS paradigm to modulate resting-state intracortical connectivity using a dual stimulator methodology over specific cortical nodes. However, potential theoretical and technological considerations of such a paradigm first need to be addressed prior to application for the purposes of manipulating motor behavior. We posit a corticocortical PAS paradigm used in conjunction with resting-state electroencephalography to demonstrate efficacy of potentiating motor learning associated resting-state intracortical connectivity within the human brain. Here we provide a precise PAS/EEG experimental design, details on data analysis, recommendations for maintaining scientific rigor, and preliminary proof of principle within a single-subject.

Neurofunctional correlates of eye to hand motor transfer

This work investigates the transfer of motor learning from the eye to the hand and its neural correlates by using functional magnetic resonance imaging (fMRI) and a sensorimotor task consisting of the continuous tracking of a virtual target. In pretraining evaluation, all the participants (experimental and control group) performed the tracking task inside an MRI scanner using their right hand and a joystick. After which, the experimental group practiced an eye-controlled version of the task for 5 days using an eye tracking system outside the MRI environment. Post-training evaluation was done 1 week after the first scanning session, where all the participants were scanned again while repeating the manual pretraining task. Behavioral results show that the training in the eye-controlled task produced a better performance not only in the eye-controlled modality (motor learning) but also in the hand-controlled modality (motor transfer). Neural results indicate that eye to hand motor transfer is supported by the motor cortex, the basal ganglia and the cerebellum, which is consistent with previous research focused on other effectors. These results may be of interest in neurorehabilitation to activate the motor systems and help in the recovery of motor functions in stroke or movement disorder patients.

CBPtools: a Python package for regional connectivity-based parcellation

Regional connectivity-based parcellation (rCBP) is a widely used procedure for investigating the structural and functional differentiation within a region of interest (ROI) based on its long-range connectivity. No standardized software or guidelines currently exist for applying rCBP, making the method only accessible to those who develop their own tools. As such, there exists a discrepancy between the laboratories applying the procedure each with their own software solutions, making it difficult to compare and interpret the results. Here, we outline an rCBP procedure accompanied by an open source software package called CBPtools. CBPtools is a Python (version 3.5+) package that allows users to run an extensively evaluated rCBP analysis workflow on a given ROI. It currently supports two modalities: resting-state functional connectivity and structural connectivity based on diffusion-weighted imaging, along with support for custom connectivity matrices. Analysis parameters are customizable and the workflow can be scaled to a large number of subjects using a parallel processing environment. Parcellation results with corresponding validity metrics are provided as textual and graphical output. Thus, CBPtools provides a simple plug-and-play, yet customizable way to conduct rCBP analyses. By providing an open-source software we hope to promote reproducible and comparable rCBP analyses and, importantly, make the rCBP procedure readily available. Here, we demonstrate the utility of CBPtools using a voluminous data set on an average compute-cluster infrastructure by performing rCBP on three ROIs prominently featured in parcellation literature.

Acquisition of chopstick-operation skills with the non-dominant hand and concomitant changes in brain activity

Despite their common use as eating utensils in East Asia, chopsticks require complex fine motor-skills for adequate operation and are thus most frequently used with the dominant hand; however, the effect of training time on the proficiency of using chopsticks with the non-dominant hand, as well as the brain activity underlying changes in skill, remain unclear. This study characterised the effect of time spent training in chopstick operation with the non-dominant hand on chopstick-use proficiency and the related brain activity to obtain data that may help individuals who are obliged to change handedness due to neurological disease to learn to use their non-dominant hand in performing daily activities. Thirty-two healthy right-handed students were randomly allocated to training (n = 16) or control (n = 16) groups; the former received 6 weeks of training in chopstick use with their non-dominant (left) hand, and the latter received none. After training, significant improvements in the execution speed and smoothness of upper extremity joints were observed in the training group. Moreover, left dorsolateral prefrontal cortex activity significantly decreased, and bilateral premotor cortex activity significantly increased across training. These results indicated that 6 weeks of chopstick training with the non-dominant hand effectively improved chopstick operation.

Reciprocal intralimb transfer of skilled isometric force production

Motor control theories propose that the same motor plans can be employed by different effectors (e.g., the hand and arm). Skills learned with one effector can therefore "transfer" to others, which has potential applications in clinical situations. However, evidence from adaptation suggests this effect is not reciprocal; learning can be generalized from proximal to distal effectors (e.g., arm to hand), but not from distal to proximal effectors (e.g., hand to arm). We propose that skill learning may not follow the same pattern, because it relies on multiple learning processes beyond error detection and correction. Participants learned a skill task involving the production of isometric forces. We assessed their ability to perform the task with the hand and arm. One group then trained to perform the task using only their hand, whereas a second group trained using only their arm. In a final assessment, we found that participants who trained with either effector improved their skill in performing the task with both their hand and arm. There was no change in a control group that did not train between assessments, indicating that gains were related to the training, not the multiple assessments. These results indicate that in contrast to adaptation, motor skills can generalize from both proximal to distal effectors and from distal to proximal effectors. We propose this is due to differences in the processes underlying skill acquisition as compared with adaptation. NEW & NOTEWORTHY Prior research indicates that motor learning transfers from proximal to distal effectors, but not vice versa. However, this work focused on adapting existing behavior; we questioned whether different results would occur during learning of new motor skills. We found that the benefits of training on a skill task with either the hand or arm transferred across both effectors. This highlights important differences between adaptation and skill learning, and may allow therapeutic benefits for patients with impairments in specific effectors.

Differential impact of reward and punishment on functional connectivity after skill learning

Reward and punishment shape behavior, but the mechanisms underlying their effect on skill learning are not well understood. Here, we tested whether the functional connectivity of premotor cortex (PMC), a region known to be critical for learning of sequencing skills, is altered after training when reward or punishment is given during training. Resting-state fMRI was collected in two experiments before and after participants trained on either a serial reaction time task (SRTT; n = 36) or force-tracking task (FTT; n = 36) with reward, punishment, or control feedback. In each experiment, training-related change in PMC functional connectivity was compared across feedback groups. In both tasks, we found that reward and punishment differentially affected PMC functional connectivity. On the SRTT, participants trained with reward showed an increase in functional connectivity between PMC and cerebellum as well as PMC and striatum, while participants trained with punishment showed an increase in functional connectivity between PMC and medial temporal lobe connectivity. After training on the FTT, subjects trained with control and reward showed increases in PMC connectivity with parietal and temporal cortices after training, while subjects trained with punishment showed increased PMC connectivity with ventral striatum. While the results from the two experiments overlapped in some areas, including ventral pallidum, temporal lobe, and cerebellum, these regions showed diverging patterns of results across the two tasks for the different feedback conditions. These findings suggest that reward and punishment strongly influence spontaneous brain activity after training, and that the regions implicated depend on the task learned.

Structural Covariance Analysis Reveals Differences Between Dancers and Untrained Controls

Dancers and musicians differ in brain structure from untrained individuals. Structural covariance (SC) analysis can provide further insight into training-associated brain plasticity by evaluating interregional relationships in gray matter (GM) structure. The objectives of the present study were to compare SC of cortical thickness (CT) between expert dancers, expert musicians and untrained controls, as well as to examine the relationship between SC and performance on dance- and music-related tasks. A reduced correlation between CT in the left dorsolateral prefrontal cortex (DLPFC) and mean CT across the whole brain was found in the dancers compared to the controls, and a reduced correlation between these two CT measures was associated with higher performance on a dance video game task. This suggests that the left DLPFC is structurally decoupled in dancers and may be more strongly affected by local training-related factors than global factors in this group. This work provides a better understanding of structural brain connectivity and training-induced brain plasticity, as well as their interaction with behavior in dance and music.

Age-Dependent Modulations of Resting State Connectivity Following Motor Practice

Recent work in young adults has demonstrated that motor learning can modulate resting state functional connectivity. However, evidence for older adults is scarce. Here, we investigated whether learning a bimanual tracking task modulates resting state functional connectivity of both inter- and intra-hemispheric regions differentially in young and older individuals, and whether this has behavioral relevance. Both age groups learned a set of complex bimanual tracking task variants over a 2-week training period. Resting-state and task-related functional magnetic resonance imaging scans were collected before and after training. Our analyses revealed that both young and older adults reached considerable performance gains. Older adults even obtained larger training-induced improvements relative to baseline, but their overall performance levels were lower than in young adults. Short-term practice resulted in a modulation of resting state functional connectivity, leading to connectivity increases in young adults, but connectivity decreases in older adults. This pattern of age differences occurred for both inter- and intra-hemispheric connections related to the motor network. Additionally, long-term training-induced increases were observed in intra-hemispheric connectivity in the right hemisphere across both age groups. Overall, at the individual level, the long-term changes in inter-hemispheric connectivity correlated with training-induced motor improvement. Our findings confirm that short-term task practice shapes spontaneous brain activity differentially in young and older individuals. Importantly, the association between changes in resting state functional connectivity and improvements in motor performance at the individual level may be indicative of how training shapes the short-term functional reorganization of the resting state motor network for improvement of behavioral performance.

Definition and characterization of an extended multiple-demand network

Neuroimaging evidence suggests that executive functions (EF) depend on brain regions that are not closely tied to specific cognitive demands but rather to a wide range of behaviors. A multiple-demand (MD) system has been proposed, consisting of regions showing conjoint activation across multiple demands. Additionally, a number of studies defining networks specific to certain cognitive tasks suggest that the MD system may be composed of a number of sub-networks each subserving specific roles within the system. We here provide a robust definition of an extended MDN (eMDN) based on task-dependent and task-independent functional connectivity analyses seeded from regions previously shown to be convergently recruited across neuroimaging studies probing working memory, attention and inhibition, i.e., the proposed key components of EF. Additionally, we investigated potential sub-networks within the eMDN based on their connectional and functional similarities. We propose an eMDN network consisting of a core whose integrity should be crucial to performance of most operations that are considered higher cognitive or EF. This then recruits additional areas depending on specific demands.

Neural coupling between contralesional motor and frontoparietal networks correlates with motor ability in individuals with chronic stroke

Movement is traditionally viewed as a process that involves motor brain regions. However, movement also implicates non-motor regions such as prefrontal and parietal cortex, regions whose integrity may thus be important for motor recovery after stroke. Importantly, focal brain damage can affect neural functioning within and between distinct brain networks implicated in the damage. The aim of this study is to investigate how resting state connectivity (rs-connectivity) within and between motor and frontoparietal networks are affected post-stroke in correlation with motor outcome. Twenty-seven participants with chronic stroke with unilateral upper limb deficits underwent motor assessments and magnetic resonance imaging. Participants completed the Chedoke-McMaster Stroke Assessment as a measure of arm (CMSA-Arm) and hand (CMSA-Hand) impairment and the Action Research Arm Test (ARAT) as a measure of motor function. We used a seed-based rs-connectivity approach defining the motor (seed=contralesional primary motor cortex (M1)) and frontoparietal (seed=contralesional dorsolateral prefrontal cortex (DLPFC)) networks. We analyzed the rs-connectivity within each network (intra-network connectivity) and between both networks (inter-network connectivity), and performed correlations between: a) intra-network connectivity and motor assessment scores; b) inter-network connectivity and motor assessment scores. We found: a) Participants with high rs-connectivity within the motor network (between M1 and supplementary motor area) have higher CMSA-Hand stage (z=3.62, p=0.003) and higher ARAT score (z=3.41, p=0.02). Rs-connectivity within the motor network was not significantly correlated with CMSA-Arm stage (z=1.83, p>0.05); b) Participants with high rs-connectivity within the frontoparietal network (between DLPFC and mid-ventrolateral prefrontal cortex) have higher CMSA-Hand stage (z=3.64, p=0.01). Rs-connectivity within the frontoparietal network was not significantly correlated with CMSA-Arm stage (z=0.93, p=0.03) or ARAT score (z=2.53, p=0.05); and c) Participants with high rs-connectivity between motor and frontoparietal networks have higher CMSA-Hand stage (r_s=0.54, p=0.01) and higher ARAT score (r_s=0.54, p=0.009). Rs-connectivity between the motor and frontoparietal networks was not significantly correlated with CMSA-Arm stage (r_s=0.34, p=0.13). Taken together, the connectivity within and between the motor and frontoparietal networks correlate with motor outcome post-stroke. The integrity of these regions may be important for an individual's motor outcome. Motor-frontoparietal connectivity may be a potential biomarker of motor recovery post-stroke.

Motor control of handwriting in the developing brain: A review

This review focuses on the acquisition of writing motor aspects in adults, and in 5-to 12-year-old children without learning disabilities. We first describe the behavioural aspects of adult writing and dominant models based on the notion of motor programs. We show that handwriting acquisition is characterized by the transition from reactive movements programmed stroke-by-stroke in younger children, to an automatic control of the whole trajectory when the motor programs are memorized at about 10 years old. Then, we describe the neural correlates of adult writing, and the changes that could occur with learning during childhood. The acquisition of a new skill is characterized by the involvement of a network more restricted in space and where neural specificity is increased in key regions. The cerebellum and the left dorsal premotor cortex are of fundamental importance in motor learning, and could be at the core of the acquisition of handwriting.

Connectome-Wide Phenotypical and Genotypical Associations in Focal Dystonia

Isolated focal dystonia is a debilitating movement disorder of unknown pathophysiology. Early studies in focal dystonias have pointed to segregated changes in brain activity and connectivity. Only recently has the notion that dystonia pathophysiology may lie in abnormalities of large-scale brain networks appeared in the literature. Here, we outline a novel concept of functional connectome-wide alterations that are linked to dystonia phenotype and genotype. Using a neural community detection strategy and graph theoretical analysis of functional MRI data in human patients with the laryngeal form of dystonia (LD) and healthy controls (both males and females), we identified an abnormally widespread hub formation in LD, which particularly affected the primary sensorimotor and parietal cortices and thalamus. Left thalamic regions formed a delineated functional community that highlighted differences in network topology between LD patients with and without family history of dystonia. Conversely, marked differences in the topological organization of parietal regions were found between phenotypically different forms of LD. The interface between sporadic genotype and adductor phenotype of LD yielded four functional communities that were primarily governed by intramodular hub regions. Conversely, the interface between familial genotype and abductor phenotype was associated with numerous long-range hub nodes and an abnormal integration of left thalamus and basal ganglia. Our findings provide the first comprehensive atlas of functional topology across different phenotypes and genotypes of focal dystonia. As such, this study constitutes an important step toward defining dystonia as a large-scale network disorder, understanding its causative pathophysiology, and identifying disorder-specific markers.SIGNIFICANCE STATEMENT The architecture of the functional connectome in focal dystonia was analyzed in a large population of patients with laryngeal dystonia. Breaking with the empirical concept of dystonia as a basal ganglia disorder, we discovered large-scale alterations of neural communities that are significantly influenced by the disorder's clinical phenotype and genotype.

Multimodal connectivity-based parcellation reveals a shell-core dichotomy of the human nucleus accumbens

The subdifferentiation of the nucleus accumbens (NAc) has been extensively studied using neuroanatomy and histochemistry, yielding a well-accepted dichotomic shell/core architecture that reflects dissociable roles, such as in reward and aversion, respectively. However, in vivo parcellation of these structures in humans has been rare, potentially impairing future research into the structural and functional characteristics and alterations of putative NAc subregions. Here, we used three complementary parcellation schemes based on tractography, task-independent functional connectivity, and task-dependent co-activation to investigate the regional differentiation within the NAc. We found that a 2-cluster solution with shell-like and core-like subdivisions provided the best description of the data and was consistent with the earlier anatomical shell/core architecture. The consensus clusters from this optimal solution, which was based on the three schemes, were used as the final parcels for the subsequent connection analyses. The resulting connectivity patterns presented inter-hemispheric symmetry, convergence and divergence across the modalities, and, most importantly, clearly distinct patterns between the two subregions. This convergent connectivity patterns also confirmed the connections in animal models, supporting views that the two subregions could have antagonistic roles in some circumstances. Finally, the identified parcels should be helpful in further neuroimaging studies of the NAc. Hum Brain Mapp 38:3878-3898, 2017. © 2017 Wiley Periodicals, Inc.

Motor Learning in Stroke: Trained Patients Are Not Equal to Untrained Patients With Less Impairment

BACKGROUND AND OBJECTIVE

Stroke rehabilitation assumes motor learning contributes to motor recovery, yet motor learning in stroke has received little systematic investigation. Here we aimed to illustrate that despite matching levels of performance on a task, a trained patient should not be considered equal to an untrained patient with less impairment.

METHODS

We examined motor learning in healthy control participants and groups of stroke survivors with mild-to-moderate or moderate-to-severe motor impairment. Participants performed a series of isometric contractions of the elbow flexors to navigate an on-screen cursor to different targets, and trained to perform this task over a 4-day period. The speed-accuracy trade-off function (SAF) was assessed for each group, controlling for differences in self-selected movement speeds between individuals.

RESULTS

The initial SAF for each group was proportional to their impairment. All groups were able to improve their performance through skill acquisition. Interestingly, training led the moderate-to-severe group to match the untrained (baseline) performance of the mild-to-moderate group, while the trained mild-to-moderate group matched the untrained (baseline) performance of the controls. Critically, this did not make the two groups equivalent; they differed in their capacity to improve beyond this matched performance level. Specifically, the trained groups had reached a plateau, while the untrained groups had not.

CONCLUSIONS

Despite matching levels of performance on a task, a trained patient is not equal to an untrained patient with less impairment. This has important implications for decisions both on the focus of rehabilitation efforts for chronic stroke, as well as for returning to work and other activities.

Behavior, sensitivity, and power of activation likelihood estimation characterized by massive empirical simulation

Given the increasing number of neuroimaging publications, the automated knowledge extraction on brain-behavior associations by quantitative meta-analyses has become a highly important and rapidly growing field of research. Among several methods to perform coordinate-based neuroimaging meta-analyses, Activation Likelihood Estimation (ALE) has been widely adopted. In this paper, we addressed two pressing questions related to ALE meta-analysis: i) Which thresholding method is most appropriate to perform statistical inference? ii) Which sample size, i.e., number of experiments, is needed to perform robust meta-analyses? We provided quantitative answers to these questions by simulating more than 120,000 meta-analysis datasets using empirical parameters (i.e., number of subjects, number of reported foci, distribution of activation foci) derived from the BrainMap database. This allowed to characterize the behavior of ALE analyses, to derive first power estimates for neuroimaging meta-analyses, and to thus formulate recommendations for future ALE studies. We could show as a first consequence that cluster-level family-wise error (FWE) correction represents the most appropriate method for statistical inference, while voxel-level FWE correction is valid but more conservative. In contrast, uncorrected inference and false-discovery rate correction should be avoided. As a second consequence, researchers should aim to include at least 20 experiments into an ALE meta-analysis to achieve sufficient power for moderate effects. We would like to note, though, that these calculations and recommendations are specific to ALE and may not be extrapolated to other approaches for (neuroimaging) meta-analysis.

Multi-Modal Imaging of Neural Correlates of Motor Speed Performance in the Trail Making Test

The assessment of motor and executive functions following stroke or traumatic brain injury is a key aspect of impairment evaluation and used to guide further therapy. In clinical routine, such assessments are largely dominated by pen-and-paper tests. While these provide standardized, reliable, and ecologically valid measures of the individual level of functioning, rather little is yet known about their neurobiological underpinnings. Therefore, the aim of this study was to investigate brain regions and their associated networks that are related to upper extremity motor function, as quantified by the motor speed subtest of the trail making test (TMT-MS). Whole-brain voxel-based morphometry and whole-brain tract-based spatial statistics were used to investigate the association between TMT-MS performance with gray-matter volume (GMV) and white-matter integrity, respectively. While results demonstrated no relationship to local white-matter properties, we found a significant correlation between TMT-MS performance and GMV of the lower bank of the inferior frontal sulcus, a region associated with cognitive processing, as indicated by assessing its functional profile by the BrainMap database. Using this finding as a seed region, we further examined and compared networks as reflected by resting state connectivity, meta-analytic connectivity modeling, structural covariance, and probabilistic tractography. While differences between the different approaches were observed, all approaches converged on a network comprising regions that overlap with the multiple-demand network. Our data therefore indicate that performance may primarily depend on executive function, thus suggesting that motor speed in a more naturalistic setting should be more associated with executive rather than primary motor function. Moreover, results showed that while there were differences between the approaches, a convergence indicated that common networks can be revealed across highly divergent methods.