Motor dexterity and strength depend upon integrity of the attention-control system

The Relationship Between Reduced Hand Dexterity and Brain Structure Abnormality in Older Adults

BACKGROUND

Hand dexterity is affected by normal aging and neuroinflammatory processes in the brain. Understanding the relationship between hand dexterity and brain structure in neurotypical older adults may be informative about prodromal pathological processes, thus providing an opportunity for earlier diagnosis and intervention to improve functional outcomes.

METHODS

this study investigates the associations between hand dexterity and brain measures in neurotypical older adults (≥65 years) using the Nine-Hole Peg Test (9HPT) and magnetic resonance imaging (MRI).

RESULTS

Elastic net regularized regression revealed that reduced hand dexterity in dominant and non-dominant hands was associated with an enlarged volume of the left choroid plexus, the region implicated in neuroinflammatory and altered myelination processes, and reduced myelin content in the left frontal operculum, the region implicated in motor imagery, action production, and higher-order motor functions. Distinct neural mechanisms underlying hand dexterity in dominant and non-dominant hands included the differences in caudate and thalamic volumes as well as altered cortical myelin patterns in frontal, temporal, parietal, and occipital regions supporting sensorimotor and visual processing and integration, attentional control, and eye movements. Although elastic net identified more predictive features for the dominant vs. non-dominant hand, the feature stability was higher for the latter, thus indicating higher generalizability for the non-dominant hand model.

CONCLUSIONS

Our findings suggest that the 9HPT for hand dexterity might be a cost-effective screening tool for early detection of neuroinflammatory and neurodegenerative processes. Longitudinal studies are needed to validate our findings in a larger sample and explore the potential of hand dexterity as an early clinical marker.

Characterization of changes in the resting-state intrinsic network in patients with diabetic peripheral neuropathy

Diabetic peripheral neuropathy (DPN) is the most common complication of type 2 diabetes mellitus (T2DM) and is often accompanied by a variety of cognitive and emotional deficits, but the neurologic mechanisms underlying these deficits have not been fully elucidated. Therefore, this study aimed to use independent component analysis to explore the changes in the characteristics within the intrinsic network and to reveal patterns of interactions between networks in patients with DPN. Forty-one patients with T2DM who showed DPN, 37 patients with T2DM who did not show DPN (NDPN group), and 43 healthy controls (HC) underwent a neuropsychological assessment and resting-state functional magnetic resonance imaging examinations to examine the patterns of intra- and inter-network variations in the patients with T2DM at different clinical stages (with and without DPN). The relationships of intra- and inter-network functional connectivity (FC) with clinical/cognitive variables were also examined. In comparison with the NDPN group and HC, patients with DPN showed decreased FC within the visual network and sensorimotor network (SMN). Moreover, in comparison with the HC group, patients with DPN showed decreased FC within the anterior default mode network and increased FC within the basal ganglia network. Inter-network analysis showed decreased FC between the SMN and salience network in patients with DPN relative to the NDPN and HC groups. The decreased FC within the bilateral paracentral lobule (BA 6) of SMN was associated with Color Trails Test part 1 scores (r = -0.302, P = 0.007) and disease duration (r = -0.328, P = 0.003) in all patients with T2DM. In conclusion, the results revealed that patients with DPN have abnormal FC in multiple resting-state intrinsic networks in addition to the SMN, and that decreased FC between the SMN and salience network may be involved in the neural basis of abnormal sensorimotor function in patients with DPN.

Correlation of muscle strength, working memory, and activities of daily living in older adults

Objective

This study aims to investigate the relationship between muscle strength, working memory, and activities of daily living (ADL) in older adults. Additionally, it seeks to clarify the pathways and effects of working memory in mediating the relationship between muscle strength and ADL.

Methods

Using a cross-sectional study design, we recruited 245 older adults individuals from nursing homes. We collected data on grip strength, the 30-s sit-to-stand test, the N-back task, and ADL. The data were analyzed using independent sample t-tests, χ2 tests, correlation analysis, and structural equation modeling.

Results

Grip strength significantly influenced ADL (effect size = -0.175, 95% CI: -0.226 to -0.124). Grip strength also had a significant direct effect on ADL (effect size = -0.114, 95% CI: -0.161 to -0.067). The 1-back task correct rate significantly mediated the relationship between grip strength and ADL (effect size = 0.054, 95% CI: -0.084 to -0.029). The 30-s sit-to-stand test significantly impacted ADL (effect size = -0.280, 95% CI: -0.358 to -0.203). It also had a significant direct effect on ADL (effect size = -0.095, 95% CI: -0.183 to -0.007). The 1-back task correct rate significantly mediated the relationship between the 30-s sit-to-stand test and ADL (effect size = -0.166, 95% CI: -0.236 to -0.106).

Conclusion

There exists a strong correlation between muscle strength, working memory, and ADL. Increased muscle strength leads to better ADL performance and improved working memory tasks. Low cognitive load working memory tasks can mediate the relationship between muscle strength and ADL. Regular physical exercise can enhance muscle strength, slow down the decline of working memory, thereby maintaining or improving ADL in older adults.

Data-driven biomarkers better associate with stroke motor outcomes than theory-based biomarkers

Chronic motor impairments are a leading cause of disability after stroke. Previous studies have associated motor outcomes with the degree of damage to predefined structures in the motor system, such as the corticospinal tract. However, such theory-based approaches may not take full advantage of the information contained in clinical imaging data. The present study uses data-driven approaches to model chronic motor outcomes after stroke and compares the accuracy of these associations to previously-identified theory-based biomarkers. Using a cross-validation framework, regression models were trained using lesion masks and motor outcomes data from 789 stroke patients from the Enhancing NeuroImaging Genetics through Meta Analysis (ENIGMA) Stroke Recovery Working Group. Using the explained variance metric to measure the strength of the association between chronic motor outcomes and imaging biomarkers, we compared theory-based biomarkers, like lesion load to known motor tracts, to three data-driven biomarkers: lesion load of lesion-behaviour maps, lesion load of structural networks associated with lesion-behaviour maps, and measures of regional structural disconnection. In general, data-driven biomarkers had stronger associations with chronic motor outcomes accuracy than theory-based biomarkers. Data-driven models of regional structural disconnection performed the best of all models tested (R 2 = 0.210, P < 0.001), performing significantly better than the theory-based biomarkers of lesion load of the corticospinal tract (R 2 = 0.132, P < 0.001) and of multiple descending motor tracts (R 2 = 0.180, P < 0.001). They also performed slightly, but significantly, better than other data-driven biomarkers including lesion load of lesion-behaviour maps (R 2 = 0.200, P < 0.001) and lesion load of structural networks associated with lesion-behaviour maps (R 2 = 0.167, P < 0.001). Ensemble models - combining basic demographic variables like age, sex, and time since stroke - improved the strength of associations for theory-based and data-driven biomarkers. Combining both theory-based and data-driven biomarkers with demographic variables improved predictions, and the best ensemble model achieved R 2 = 0.241, P < 0.001. Overall, these results demonstrate that out-of-sample associations between chronic motor outcomes and data-driven imaging features, particularly when lesion data is represented in terms of structural disconnection, are stronger than associations between chronic motor outcomes and theory-based biomarkers. However, combining both theory-based and data-driven models provides the most robust associations.

The influence of eight cognitive training regimes upon cognitive screening tool performance in post-stroke survivors: a network meta-analysis

Background

Traditional meta-analysis offers only direct comparative evidence. The optimal cognitive training for poststroke cognitive impairment (PSCI) remains largely undetermined.

Objectives

This study aims to assess and compare the effectiveness of selected cognitive training methods for PSCI patients and to identify and rank the most effective intervention programs.

Methods

Searches were conducted in PubMed, Embase, Cochrane Library, Web of science, China National Knowledge Infrastructure, China Science and Technology Journal Database, Wanfang Database, and China Biomedical Database for randomized controlled trials up to September 30, 2023. Two researchers independently performed literature screening, data extraction, and quality assessment. Network meta-analysis was utilized to synthesize the main findings. The primary outcome focused on the intervention's impact on subjective cognitive function, with secondary outcomes including effects on activities of daily living, motor function, and functional independence. This study is registered with PROSPERO (CRD42023463282).

Results

Fifty eligible randomized controlled trials were identified, revealing eight distinct interventions. These interventions collectively demonstrate efficacy in enhancing cognition. Traditional cognitive training significantly improves overall cognitive function, daily living function, motor function, and functional independence. In Loewenstein Occupational Therapy Cognitive Assessment, Barthel Index, Fugl-Meyer Assessment, and Functional Independence Measure scales, a combination of computer-based and traditional cognitive training outperformed the conventional control group MD = 29.97 (95%CI: 16.3, 44.2), MD = 18.67 (95%CI: 9.78, 27.45), MD = 28.76 (95%CI: 5.46, 51.79) and MD = 42.2 (95%CI: 5.25, 78.99). In the MMSE scale, virtual reality cognitive training combined with traditional training was most effective MD = 8.01 (95%CI: 3.6, 12.4). On the MoCA scale, the combination of exercise and cognitive training showed superior results MD = 6.68 (95%CI: 2.55, 10.78). Only the combined computer-based and traditional cognitive training, as well as traditional cognitive training alone, significantly enhanced functional independence, with no notable differences in other pairwise interventions.

Conclusion

The network meta-analysis suggests that augmenting traditional training with other modalities may enhance overall effectiveness. Specifically, interventions incorporating computer-based cognitive training appear to surpass other methods in improving cognition, daily living function, motor skills, and functional independence. The findings of this network meta-analysis provide evidence-based guidance for clinical decision-making.

Systematic Review Registration

https://www.crd.york.ac.uk/PROSPERO/, identifier in PROSPERO (CRD42023463282).

Increased dual-task interference during upper limb movements in stroke exceeding that found in aging - a systematic review and meta-analysis

Objective

To determine whether dual-task interference during upper limb tasks is increased in patients after stroke compared to healthy older subjects and to compare magnitude of stroke-induced change in interference to that explained by aging.

Methods

We conducted a systematic literature search in MEDLINE, CINAHL, Google Scholar and PEDro databases up to October 2023 for studies on upper limb dual-tasks in stroke and elderly healthy subjects. Eleven upper limb dual-task studies in stroke patients and 11 studies in healthy older subjects were identified and systematically reviewed. A meta-analysis was performed on seven stroke studies and on five studies in healthy older subjects that included control groups.

Results

Most stroke studies investigated proximal arm movements with kinematic measures, but few studies evaluated manual dexterity. In contrast, studies in healthy older subjects used more distal (finger tapping) tasks. The meta-analysis showed that stroke patients had on average a 19% (CI 95% = 1.0-37.3) increase in dual-task interference compared to age-matched healthy controls (Z = 2.06, p = 0.04). Older healthy subjects showed greater dual-task interference compared to younger subjects (19% greater, CI 95% = 6.5-31.2, Z = 2.98, p = 0.003).

Conclusion

Meta-analysis revealed an increase in dual-task interference during upper limb movements in stroke patients, exceeding age-related changes, supporting the presence of subclinical impairments in divided attention post-stroke that may impede motor recovery.

Bimanual coordinated motor skill learning in patients with a chronic cerebellar stroke

Cerebellar strokes induce coordination disorders that can affect activities of daily living. Evidence-based neurorehabilitation programs are founded on motor learning principles. The cerebellum is a key neural structure in motor learning. It is unknown whether and how well chronic cerebellar stroke individuals (CCSIs) can learn to coordinate their upper limbs through bimanual motor skill learning. The aim was to determine whether CCSIs could achieve bimanual skill learning through a serious game with the REAplan® robot and to compare CCSIs with healthy individuals (HIs). Over three consecutive days, sixteen CCSIs and eighteen HIs were trained on an asymmetric bimanual coordination task ("CIRCUIT" game) with the REAplan® robot, allowing quantification of speed, accuracy and coordination. The primary outcomes were the bimanual speed/accuracy trade-off (BiSAT) and bimanual coordination factor (BiCo). They were also evaluated on a bimanual REACHING task on Days 1 and 3. Correlation analyses between the robotic outcomes and clinical scale scores were computed. Throughout the sessions, BiSAT and BiCo improved during the CIRCUIT task in both HIs and CCSIs. On Day 3, HIs and CCSIs showed generalization of BiSAT, BiCo and transferred to the REACHING task. There was no significant between-group difference in progression. Four CCSIs and two HIs were categorized as "poor learners" according to BiSAT and/or BiCo. Increasing age correlated with reduced BiSAT but not BiCo progression. Over three days of training, HIs and CCSIs improved, retained, generalized and transferred a coordinated bimanual skill. There was no between-group difference, suggesting plastic compensation in CCSIs. Clinical trial NCT04642599 approved the 24th of November 2020.

Discrepant changes in structure-function coupling in dancers and musicians

Dance and music are well known to improve sensorimotor skills and cognitive functions. To reveal the underlying mechanism, previous studies focus on the brain plastic structural and functional effects of dance and music training. However, the discrepancy training effects on brain structure-function relationship are still blurred. Thus, proficient dancers, musicians, and controls were recruited in this study. The graph signal processing framework was employed to quantify the region-level and network-level relationship between brain function and structure. The results showed the increased coupling strength of the right ventromedial putamen in the dance and music groups. Distinctly, enhanced coupling strength of the ventral attention network, increased coupling strength of the right inferior frontal gyrus opercular area, and increased function connectivity of coupling function signal between the right and left middle frontal gyrus were only found in the dance group. Besides, the dance group indicated enhanced coupling function connectivity between the left inferior parietal lobule caudal area and the left superior parietal lobule intraparietal area compared with the music groups. The results might illustrate dance and music training's discrepant effect on the structure-function relationship of the subcortical and cortical attention networks. Furthermore, dance training seemed to have a greater impact on these networks.

Higher handgrip strength is linked to higher salience ventral attention functional network segregation in older adults

Converging evidence suggests that handgrip strength is linked to cognition in older adults, and this may be subserved by shared age-related changes in brain function and structure. However, the interplay among handgrip strength, brain functional connectivity, and cognitive function remains poorly elucidated. Hence, our study sought to examine these relationships in 148 community-dwelling older adults. Specifically, we examined functional segregation, a measure of functional brain organization sensitive to ageing and cognitive decline, and its associations with handgrip strength and cognitive function. We showed that higher handgrip strength was related to better processing speed, attention, and global cognition. Further, higher handgrip strength was associated with higher segregation of the salience/ventral attention network, driven particularly by higher salience/ventral attention intra-network functional connectivity of the right anterior insula to the left posterior insula/frontal operculum and right midcingulate/medial parietal cortex. Importantly, these handgrip strength-related inter-individual differences in salience/ventral attention network functional connectivity were linked to cognitive function, as revealed by functional decoding and brain-cognition association analyses. Our findings thus highlight the importance of the salience/ventral attention network in handgrip strength and cognition, and suggest that inter-individual differences in salience/ventral attention network segregation and intra-network connectivity could underpin the handgrip strength-cognition relationship in older adults.

Don't plan, just do it: Cognitive and sensorimotor contributions to manual dexterity

Manual dexterity is referred to as the skill to perform fine motor movements and it has been assumed to be associated to the cognitive domain, as well as the sensorimotor one. In this work, we investigated with functional near-infrared spectroscopy the cortical activations elicited by the execution of the 9-HPT, i.e., a standard test evaluating manual dexterity in which nine pegs were taken, placed into and then removed from nine holes on a board as quickly as possible. For comparison, we proposed a new active control task mainly involving the sensorimotor domain, in which the pegs must be placed and removed using the same single hole (1-HPT). Behaviorally, we found two distinct groups based on the difference between the execution time of the 9-HPT and the 1-HPT (ΔHPT). Cortical areas belonging to the network controlling reaching and grasping movements were active in both groups; however, participants showing a large ΔHPT presented significantly higher activation in prefrontal cortical areas (right BA10 and BA11) during 9-HPT and 1-HPT performance with respect to the participants with a small ΔHPT, who showed a deactivation in BA10. Unexpectedly, we observed a significant linear relationship between ΔHPT and right BA10 activity. This suggested that participants performing the 9-HPT more slowly than the 1-HPT recruited prefrontal areas implicitly exploiting the cognitive skills of planning, perhaps in search of a motor strategy to solve the test activating attentional and cognitive control processes, but this resulted not efficient and instead increased the time to accomplish a manual dexterity task.

Substructure of the brain's Cingulo-Opercular network

The Cingulo-Opercular network (CON) is an executive network of the human brain that regulates actions. CON is composed of many widely distributed cortical regions that are involved in top-down control over both lower-level (i.e., motor) and higher-level (i.e., cognitive) functions, as well as in processing of painful stimuli. Given the topographical and functional heterogeneity of the CON, we investigated whether subnetworks within the CON support separable aspects of action control. Using precision functional mapping (PFM) in 15 participants with > 5 hours of resting state functional connectivity (RSFC) and task data, we identified three anatomically and functionally distinct CON subnetworks within each individual. These three distinct subnetworks were linked to Decisions, Actions, and Feedback (including pain processing), respectively, in convergence with a meta-analytic task database. These Decision, Action and Feedback subnetworks represent pathways by which the brain establishes top-down goals, transforms those goals into actions, implemented as movements, and processes critical action feedback such as pain.

Mechanisms and neuroanatomy of response selection in tool and non-tool action tasks: Evidence from left-hemisphere stroke

The ability to select between potential actions is central to the complex process of tool use. After left hemisphere stroke, individuals with limb apraxia make more hand action errors when gesturing the use of tools with conflicting hand actions for grasping-to-move and use (e.g., screwdriver) relative to tools that are grasped-to-move and used with the same hand action (e.g., hammer). Prior research indicates that this grasp-use interference effect is driven by abnormalities in the competitive action selection process. The goal of this project was to determine whether common mechanisms and neural substrates support the competitive selection of task-appropriate responses in both tool and non-tool domains. If so, the grasp-use interference effect in a tool use gesturing task should be correlated with response interference effects in the classic Eriksen flanker and Simon tasks, and at least partly overlapping neural regions should subserve the 3 tasks. Sixty-four left hemisphere stroke survivors (33 with apraxia) participated in the tool- and non-tool interference tasks and underwent T1 anatomical MRI. There were robust grasp-use interference effects (grasp-use conflict test) and response interference effects (Eriksen flanker and Simon tasks), but these effects were not correlated. Lesion-symptom mapping analyses showed that lesions to the left inferior parietal lobule, ventral premotor cortex, and insula were associated with grasp-use interference. Lesions to the left inferior parietal lobule, postcentral gyrus, insula, caudate, and putamen were associated with response interference in the Eriksen flanker task. Lesions to the left caudate and putamen were also associated with response interference in the Simon task. Our results suggest that the selection of hand posture for tool use is mediated by distinct cognitive mechanisms and partly distinct neuroanatomic substrates from those mapping a stimulus to an appropriate motor response in non-tool domains.

Data-driven biomarkers outperform theory-based biomarkers in predicting stroke motor outcomes

Chronic motor impairments are a leading cause of disability after stroke. Previous studies have predicted motor outcomes based on the degree of damage to predefined structures in the motor system, such as the corticospinal tract. However, such theory-based approaches may not take full advantage of the information contained in clinical imaging data. The present study uses data-driven approaches to predict chronic motor outcomes after stroke and compares the accuracy of these predictions to previously-identified theory-based biomarkers. Using a cross-validation framework, regression models were trained using lesion masks and motor outcomes data from 789 stroke patients (293 female/496 male) from the ENIGMA Stroke Recovery Working Group (age 64.9±18.0 years; time since stroke 12.2±0.2 months; normalised motor score 0.7±0.5 (range [0,1]). The out-of-sample prediction accuracy of two theory-based biomarkers was assessed: lesion load of the corticospinal tract, and lesion load of multiple descending motor tracts. These theory-based prediction accuracies were compared to the prediction accuracy from three data-driven biomarkers: lesion load of lesion-behaviour maps, lesion load of structural networks associated with lesion-behaviour maps, and measures of regional structural disconnection. In general, data-driven biomarkers had better prediction accuracy - as measured by higher explained variance in chronic motor outcomes - than theory-based biomarkers. Data-driven models of regional structural disconnection performed the best of all models tested (R2 = 0.210, p < 0.001), performing significantly better than predictions using the theory-based biomarkers of lesion load of the corticospinal tract (R2 = 0.132, p< 0.001) and of multiple descending motor tracts (R2 = 0.180, p < 0.001). They also performed slightly, but significantly, better than other data-driven biomarkers including lesion load of lesion-behaviour maps (R2 =0.200, p < 0.001) and lesion load of structural networks associated with lesion-behaviour maps (R2 =0.167, p < 0.001). Ensemble models - combining basic demographic variables like age, sex, and time since stroke - improved prediction accuracy for theory-based and data-driven biomarkers. Finally, combining both theory-based and data-driven biomarkers with demographic variables improved predictions, and the best ensemble model achieved R2 = 0.241, p < 0.001. Overall, these results demonstrate that models that predict chronic motor outcomes using data-driven features, particularly when lesion data is represented in terms of structural disconnection, perform better than models that predict chronic motor outcomes using theory-based features from the motor system. However, combining both theory-based and data-driven models provides the best predictions.

Thalamo-cortical and cerebello-cortical functional connectivity in development

The thalamus is a critical relay center for neural pathways involving sensory, motor, and cognitive functions, including cortico-striato-thalamo-cortical and cortico-ponto-cerebello-thalamo-cortical loops. Despite the importance of these circuits, their development has been understudied. One way to investigate these pathways in human development in vivo is with functional connectivity MRI, yet few studies have examined thalamo-cortical and cerebello-cortical functional connectivity in development. Here, we used resting-state functional connectivity to measure functional connectivity in the thalamus and cerebellum with previously defined cortical functional networks in 2 separate data sets of children (7-12 years old) and adults (19-40 years old). In both data sets, we found stronger functional connectivity between the ventral thalamus and the somatomotor face cortical functional network in children compared with adults, extending previous cortico-striatal functional connectivity findings. In addition, there was more cortical network integration (i.e. strongest functional connectivity with multiple networks) in the thalamus in children than in adults. We found no developmental differences in cerebello-cortical functional connectivity. Together, these results suggest different maturation patterns in cortico-striato-thalamo-cortical and cortico-ponto-cerebellar-thalamo-cortical pathways.

Association of Brain Age, Lesion Volume, and Functional Outcome in Patients With Stroke

BACKGROUND AND OBJECTIVES

Functional outcomes after stroke are strongly related to focal injury measures. However, the role of global brain health is less clear. In this study, we examined the impact of brain age, a measure of neurobiological aging derived from whole-brain structural neuroimaging, on poststroke outcomes, with a focus on sensorimotor performance. We hypothesized that more lesion damage would result in older brain age, which would in turn be associated with poorer outcomes. Related, we expected that brain age would mediate the relationship between lesion damage and outcomes. Finally, we hypothesized that structural brain resilience, which we define in the context of stroke as younger brain age given matched lesion damage, would differentiate people with good vs poor outcomes.

METHODS

We conducted a cross-sectional observational study using a multisite dataset of 3-dimensional brain structural MRIs and clinical measures from the ENIGMA Stroke Recovery. Brain age was calculated from 77 neuroanatomical features using a ridge regression model trained and validated on 4,314 healthy controls. We performed a 3-step mediation analysis with robust mixed-effects linear regression models to examine relationships between brain age, lesion damage, and stroke outcomes. We used propensity score matching and logistic regression to examine whether brain resilience predicts good vs poor outcomes in patients with matched lesion damage.

RESULTS

We examined 963 patients across 38 cohorts. Greater lesion damage was associated with older brain age (β = 0.21; 95% CI 0.04-0.38, p = 0.015), which in turn was associated with poorer outcomes, both in the sensorimotor domain (β = -0.28; 95% CI -0.41 to -0.15, p < 0.001) and across multiple domains of function (β = -0.14; 95% CI -0.22 to -0.06, p < 0.001). Brain age mediated 15% of the impact of lesion damage on sensorimotor performance (95% CI 3%-58%, p = 0.01). Greater brain resilience explained why people have better outcomes, given matched lesion damage (odds ratio 1.04, 95% CI 1.01-1.08, p = 0.004).

DISCUSSION

We provide evidence that younger brain age is associated with superior poststroke outcomes and modifies the impact of focal damage. The inclusion of imaging-based assessments of brain age and brain resilience may improve the prediction of poststroke outcomes compared with focal injury measures alone, opening new possibilities for potential therapeutic targets.

Effects of motor imagery based brain-computer interface on upper limb function and attention in stroke patients with hemiplegia: a randomized controlled trial

BACKGROUND

Seeking positive and comprehensive rehabilitation methods after stroke is an urgent problem to be solved, which is very important to improve the dysfunction of stroke. The aim of this study was to investigate the effects of motor imagery-based brain-computer interface training (MI-BCI) on upper limb function and attention in stroke patients with hemiplegia.

METHODS

Sixty stroke patients with impairment of upper extremity function and decreased attention were randomly assigned to the control group (CR group) or the experimental group (BCI group) in a 1:1 ratio. Patients in the CR group received conventional rehabilitation. Patients in the BCI group received 20 min of MI-BCI training five times a week for 3 weeks (15 sessions) in addition to conventional rehabilitation. The primary outcome measures were the changes in Fugl-Meyer Motor Function Assessment of Upper Extremities (FMA-UE) and Attention Network Test (ANT) from baseline to 3 weeks.

RESULTS

About 93% of the patients completed the allocated training. Compared with the CR group, among those in the BCI group, FMA-UE was increased by 8.0 points (95%CI, 5.0 to 10.0; P < 0.001). Alert network response time (32.4ms; 95%CI, 58.4 to 85.6; P < 0.001), orienting network response (5.6ms; 95%CI, 29.8 to 55.8; P = 0.010), and corrects number (8.0; 95%CI, 17.0 to 28.0; P < 0.001) also increased in the BCI group compared with the CR group. Additionally, the executive control network response time (- 105.9ms; 95%CI, - 68.3 to - 23.6; P = 0.002), the total average response time (- 244.8ms; 95%CI, - 155.8 to - 66.2; P = 0.002), and total time (- 122.0ms; 95%CI, - 80.0 to - 35.0; P = 0.001) were reduced in the BCI group compared with the CR group.

CONCLUSION

MI-BCI combined with conventional rehabilitation training could better enhance upper limb motor function and attention in stroke patients. This training method may be feasible and suitable for individuals with stroke.

TRIAL REGISTRATION

This study was registered in the Chinese Clinical Trial Registry with Portal Number ChiCTR2100050430(27/08/2021).

The Role of Extra-motor Networks in Upper Limb Motor Performance Post-stroke

BACKGROUND

Motor improvement post-stroke may happen even if resting state functional connectivity between the ipsilesional and contralesional components of the sensorimotor network is not fully recovered. Therefore, we investigated which extra-motor networks might support upper limb motor gains in response to treatment post-stroke.

METHODS

Both resting state functional connectivity and upper limb capacity were measured prior to and after an 8-week intervention of task-specific training in 29 human participants [59.24 ± (SD) 10.40 yrs., 12 females and 17 males] with chronic stroke. The sensorimotor and five extra-motor networks were defined: default mode, frontoparietal, cingulo-opercular, dorsal attention network, and salience networks. The Network Level Analysis toolbox was used to identify network pairs whose connectivities were enriched in connectome-behavior relationships.

RESULTS

Mean upper limb capacity score increased 5.45 ± (SD) 5.55 following treatment. Baseline connectivity of some motor but mostly extra-motor network interactions of cingulo-opercular and default-mode networks were predictive of upper limb capacity following treatment. Also, changes in connectivity for extra-motor interactions of salience with default mode, cingulo-opercular, and dorsal attention networks were correlated with gains in upper limb capacity.

CONCLUSIONS

These connectome-behavior patterns suggest larger involvement of cingulo-opercular networks in prediction of treatment response and of salience networks in maintenance of improved skilled behavior. These results support our hypothesis that cognitive networks may contribute to recovery of motor performance after stroke and provide additional insights into the neural correlates of intensive training.

Hand Dexterity Is Associated with the Ability to Resolve Perceptual and Cognitive Interference in Older Adults: Pilot Study

The relationship between hand dexterity and inhibitory control across the lifespan is underexplored. In this pilot study, we examined inhibitory control using a modified Simon task. During the task, participants were presented with right- and left-pointing arrows located either on the right or the left parts of the screen. In the congruent trials, the arrow location and direction matched. In the incongruent trials, they mismatched, thus creating cognitive interference. In 50% of trials, the arrow presentation was accompanied by a task-irrelevant but environmentally meaningful sound that created perceptual interference. Hand dexterity was measured with the 9-hole peg test. Significantly faster reaction time (RT) on the modified Simon task (p < 0.001) was observed in younger adults, trials with concurrent sound stimuli, and congruent trials. Older adults who reported recent falls had greater difficulty resolving cognitive interference than older adults without recent falls. Hand dexterity significantly moderated the effect of sound on RT, but only in the group of older individuals. Interestingly, older individuals with reduced hand dexterity benefited from concurrent sounds more than those with better hand dexterity. Our findings suggest that task-irrelevant but environmentally meaningful sounds may increase alertness and enhance stimulus perception and recognition, thus improving motor performance in older individuals.

High intra-task and low inter-task correlations of motor skills in humans creates an individualized behavioural pattern

Our motor system allows us to generate an enormous breadth of voluntary actions, but it remains unclear whether and how much motor skill translates across tasks. For example, if an individual is good at gross motor control, are they also good at fine motor control? Previous research about the generalization across motor skills has been equivocal. Here, we compare human performance across five different motor skills. High correlation between task measures would suggest a certain level of underlying sensorimotor ability that dictates performance across all task types. Low correlation would suggest specificity in abilities across tasks. Performance on a reaching task, an object-hitting task, a bimanual coordination task, a rapid motion task and a target tracking task, was examined twice in a cohort of 25 healthy individuals. Across the cohort, we found relatively high correlations for different spatial and temporal parameters within a given task (16-53% of possible parameter pairs were significantly correlated, with significant r values ranging from 0.53 to 0.97) but relatively low correlations across different tasks (2.7-4.4% of possible parameter pairs were significantly correlated, with significant r values ranging from 0.53-0.71). We performed a cluster analysis across all individuals using 76 performance measures across all tasks for the two repeat testing sessions and demonstrated that repeat tests were commonly grouped together (16 of 25 pairs were grouped next to each other). These results highlight that individuals have different abilities across motor tasks, and that these patterns are consistent across time points.

Brain electrical microstate features as biomarkers of a stable motor output

Objective.The aim of the present study was to elucidate the brain dynamics underlying the maintenance of a constant force level exerted during a visually guided isometric contraction task by optimizing a predictive multivariate model based on global and spectral brain dynamics features.Approach.Electroencephalography (EEG) was acquired in 18 subjects who were asked to press a bulb and maintain a constant force level, indicated by a bar on a screen. For intervals of 500 ms, we calculated an index of force stability as well as indices of brain dynamics: microstate metrics (duration, occurrence, global explained variance, directional predominance) and EEG spectral amplitudes in the theta, low alpha, high alpha and beta bands. We optimized a multivariate regression model (partial least square (PLS)) where the microstate features and the spectral amplitudes were the input variables and the indexes of force stability were the output variables. The issues related to the collinearity among the input variables and to the generalizability of the model were addressed using PLS in a nested cross-validation approach.Main results.The optimized PLS regression model reached a good generalizability and succeeded to show the predictive value of microstates and spectral features in inferring the stability of the exerted force. Longer duration and higher occurrence of microstates, associated with visual and executive control networks, corresponded to better contraction performances, in agreement with the role played by the visual system and executive control network for visuo-motor integration.Significance.A combination of microstate metrics and brain rhythm amplitudes could be considered as biomarkers of a stable visually guided motor output not only at a group level, but also at an individual level. Our results may play an important role for a better understanding of the motor control in single trials or in real-time applications as well as in the study of motor control.

Hand dexterity, daily functioning and health-related quality of life in kidney transplant recipients

Impaired interplay between sensory and motor function may be an important, often overlooked cause of the decreased daily functioning and impaired health-related quality of life (HRQoL) of kidney transplant recipients (KTR). We assessed this interplay using a hand dexterity test, and investigated its potential associations with daily functioning and HRQoL among KTR enrolled at the TransplantLines Biobank and Cohort Study. A total of 309 KTR (58% male, mean age 56 ± 13 years) at median 4 [IQR: 1-11] years after transplantation were included. Impaired hand dexterity, as defined by a test performance slower than the 95th percentile of an age- and sex-specific reference population, was observed in 71 (23%) KTR. Worse hand dexterity was independently associated with worse performance on almost all measures of physical capacity, activities of daily living and societal participation. Finally, hand dexterity was independently associated with physical HRQoL (standardized beta - 0.22, 95%CI - 0.34 to - 0.09, P < 0.001). In conclusion, impaired interplay between sensory and motor function, as assessed by hand dexterity, is prevalent among KTR. In addition, poor hand dexterity was associated with impaired daily functioning and limited physical HRQoL. Impaired interplay between sensory and motor function may be therefore an important, hitherto overlooked, phenomenon in KTR.

Brain Mapping of Behavioral Domains Using Multi-Scale Networks and Canonical Correlation Analysis

Simultaneous mapping of multiple behavioral domains into brain networks remains a major challenge. Here, we shed some light on this problem by employing a combination of machine learning, structural and functional brain networks at different spatial resolutions (also known as scales), together with performance scores across multiple neurobehavioral domains, including sensation, motor skills, and cognition. Provided by the Human Connectome Project, we make use of three cohorts: 640 participants for model training, 160 subjects for validation, and 200 subjects for model performance testing thus enhancing prediction generalization. Our modeling consists of two main stages, namely dimensionality reduction in brain network features at multiple scales, followed by canonical correlation analysis, which determines an optimal linear combination of connectivity features to predict multiple behavioral performance scores. To assess the differences in the predictive power of each modality, we separately applied three different strategies: structural unimodal, functional unimodal, and multimodal, that is, structural in combination with functional features of the brain network. Our results show that the multimodal association outperforms any of the unimodal analyses. Then, to answer which human brain structures were most involved in predicting multiple behavioral scores, we simulated different synthetic scenarios in which in each case we completely deleted a brain structure or a complete resting state network, and recalculated performance in its absence. In deletions, we found critical structures to affect performance when predicting single behavioral domains, but this occurred in a lesser manner for prediction of multi-domain behavior. Overall, our results confirm that although there are synergistic contributions between brain structure and function that enhance behavioral prediction, brain networks may also be mutually redundant in predicting multidomain behavior, such that even after deletion of a structure, the connectivity of the others can compensate for its lack in predicting behavior.

Functional connectivity drives stroke recovery: shifting the paradigm from correlation to causation

Stroke is a leading cause of disability, with deficits encompassing multiple functional domains. The heterogeneity underlying stroke poses significant challenges in the prediction of post-stroke recovery, prompting the development of neuroimaging-based biomarkers. Structural neuroimaging measurements, particularly those reflecting corticospinal tract injury, are well-documented in the literature as potential biomarker candidates of post-stroke motor recovery. Consistent with the view of stroke as a 'circuitopathy', functional neuroimaging measures probing functional connectivity may also prove informative in post-stroke recovery. An important step in the development of biomarkers based on functional neural network connectivity is the establishment of causality between connectivity and post-stroke recovery. Current evidence predominantly involves statistical correlations between connectivity measures and post-stroke behavioural status, either cross-sectionally or serially over time. However, the advancement of functional connectivity application in stroke depends on devising experiments that infer causality. In 1965, Sir Austin Bradford Hill introduced nine viewpoints to consider when determining the causality of an association: (i) strength; (ii) consistency; (iii) specificity; (iv) temporality; (v) biological gradient; (vi) plausibility; (vii) coherence; (viii) experiment; and (ix) analogy. Collectively referred to as the Bradford Hill Criteria, these points have been widely adopted in epidemiology. In this review, we assert the value of implementing Bradford Hill's framework to stroke rehabilitation and neuroimaging. We focus on the role of neural network connectivity measurements acquired from task-oriented and resting-state functional MRI, EEG, magnetoencephalography and functional near-infrared spectroscopy in describing and predicting post-stroke behavioural status and recovery. We also identify research opportunities within each Bradford Hill tenet to shift the experimental paradigm from correlation to causation.

Evidence of Motor Skill Learning in Acute Stroke Patients Without Lesions to the Thalamus and Internal Capsule

Background:

It is currently unknown whether motor skill learning (MSkL) with the paretic upper limb is possible during the acute phase after stroke and whether lesion localization impacts MSkL. Here, we investigated MSkL in acute (1–7 days post) stroke patients compared with healthy individuals (HIs) and in relation to voxel-based lesion symptom mapping.

Methods:

Twenty patients with acute stroke and 35 HIs were trained over 3 consecutive days on a neurorehabilitation robot measuring speed, accuracy, and movement smoothness variables. Patients used their paretic upper limb and HI used their nondominant upper limb on an MSkL task involving a speed/accuracy trade-off. Generalization was evaluated on day 3. All patients underwent a 3-dimensional magnetic resonance imaging used for VSLM.

Results:

Most patients achieved MSkL demonstrated by day-to-day retention and generalization of the newly learned skill on day 3. When comparing raw speed/accuracy trade-off values, HI achieved larger MSkL than patients. However, relative speed/accuracy trade-off values showed no significant differences in MSkL between patients and HI on day 3. In patients, MSkL progression correlated with acute motor and cognitive impairments. The voxel-based lesion symptom mapping showed that acute vascular damage to the thalamus or the posterior limb of the internal capsule reduced MSkL.

Conclusions:

Despite worse motor performance for acute stroke patients compared with HI, most patients were able to achieve MSkL with their paretic upper limb. Damage to the thalamus and posterior limb of the internal capsule, however, reduced MSkL. These data show that MSkL could be implemented into neurorehabilitation during the acute phase of stroke, particularly for patients without lesions to the thalamus and posterior limb of the internal capsule.

Registration:

URL: https://www.clinicaltrials.gov ; Unique identifier: NCT01519843.

GripAble: An accurate, sensitive and robust digital device for measuring grip strength

Introduction

Grip strength is a reliable biomarker of overall health and physiological well-being. It is widely used in clinical practice as an outcome measure. This paper demonstrates the measurement characteristics of GripAble, a wireless mobile handgrip device that measures grip force both isometrically and elastically-resisted for assessment and training of hand function.

Methods

A series of bench tests were performed to evaluate GripAble's grip force measurement accuracy and sensitivity. Measurement robustness was evaluated through repeated drop tests interwoven with error verification test phases.

Results

GripAble's absolute measurement error at the central position was under 0.81 and 1.67 kg (95^th percentiles; N = 47) when measuring elastically and isometrically, respectively, providing similar or better accuracy than the industry-standard Jamar device. Sensitivity was measured as 0.062 ± 0.015 kg (mean ± std; 95^th percentiles: [0.036, 0.089] kg; N = 47), independent of the applied force. There was no significant performance degradation following impact from 30 drops from a height >1.5 m.

Conclusion

GripAble is an accurate and reliable grip strength dynamometer. It is highly sensitive and robust, which in combination with other novel features (e.g. portability, telerehabilitation and digital data tracking) enable broad applicability in a range of clinical caseloads and environments.

Cingulo-Opercular and Frontoparietal Network Control of Effort and Fatigue in Mild Traumatic Brain Injury

Neural substrates of fatigue in traumatic brain injury (TBI) are not well understood despite the considerable burden of fatigue on return to productivity. Fatigue is associated with diminishing performance under conditions of high cognitive demand, sense of effort, or need for motivation, all of which are associated with cognitive control brain network integrity. We hypothesize that the pathophysiology of TBI results in damage to diffuse cognitive control networks, disrupting coordination of moment-to-moment monitoring, prediction, and regulation of behavior. We investigate the cingulo-opercular (CO) and frontoparietal (FP) networks, which are engaged to sustain attention for task and maintain performance. A total of 61 individuals with mild TBI and 42 orthopedic control subjects participated in functional MRI during performance of a constant effort task requiring altering the amount of effort (25, 50, or 75% of maximum effort) utilized to manually squeeze a pneumostatic bulb across six 30-s trials. Network-based statistics assessed within-network organization and fluctuation with task manipulations by group. Results demonstrate small group differences in network organization, but considerable group differences in the evolution of task-related modulation of connectivity. The mild TBI group demonstrated elevated CO connectivity throughout the task with little variation in effort level or time on task (TOT), while CO connectivity diminished over time in controls. Several interregional CO connections were predictive of fatigue in the TBI group. In contrast, FP connectivity fluctuated with task manipulations and predicted fatigue in the controls, but connectivity fluctuations were delayed in the mild traumatic brain injury (mTBI) group and did not relate to fatigue. Thus, the mTBI group's hyper-connectivity of the CO irrespective of task demands, along with hypo-connectivity and delayed peak connectivity of the FP, may allow for attainment of task goals, but also contributes to fatigue. Findings are discussed in relation to performance monitoring of prediction error that relies on internal cues from sensorimotor feedback during task performance. Delay or inability to detect and respond to prediction errors in TBI, particularly evident in bilateral insula-temporal CO connectivity, corresponds to day-to-day fatigue and fatigue during task performance.

Modernising grip dynamometry: Inter-instrument reliability between GripAble and Jamar

INTRODUCTION

Maximum grip strength (MGS) is a reliable biomarker of overall health and physiological well-being. Therefore, an accurate and reliable measurement device is vital for ensuring the validity of the MGS assessment. This paper presents GripAble, a mobile hand grip device for the assessment of MGS. GripAble's performance was evaluated using an inter-instrument reliability test against the widely used Jamar PLUS+ dynamometer.

METHODS

MGS data from sixty-three participants (N = 63, median (IQR) age = 29.0 (29.5) years, 33 M/30 F) from both hands using GripAble and Jamar PLUS+ were collected and compared. Intraclass correlation (ICC), regression, and Bland and Altman analysis were performed to evaluate the inter-instrument reliability and relationship in MGS measurements between GripAble and Jamar PLUS+ .

RESULTS

GripAble demonstrates good-to-excellent inter-instrument reliability to the Jamar PLUS+ with ICC3,1 = 0.906 (95% CI [0.87-0.94]). GripAble's MGS measurement is equivalent to 69% (95% CI [0.67-0.71]%) of Jamar PLUS+'s measurement. There is a proportional difference in mean MGS between the two devices, with the difference in MGS between GripAble and Jamar PLUS+ increasing with MGS.

CONCLUSION

The GripAble is a reliable tool for measuring grip strength. However, the MGS readings from GripAble and Jamar PLUS+ should not be interchanged for serial measurements of the same patient, nor be translated directly from one device to the other. A new normative MGS data using GripAble will be collected and accessed through the software for immediate comparison to age and gender-matched subpopulations.

Coherent neural oscillations inform early stroke motor recovery

Neural oscillations may contain important information pertaining to stroke rehabilitation. This study examined the predictive performance of electroencephalography‐derived neural oscillations following stroke using a data‐driven approach. Individuals with stroke admitted to an inpatient rehabilitation facility completed a resting‐state electroencephalography recording and structural neuroimaging around the time of admission and motor testing at admission and discharge. Using a lasso regression model with cross‐validation, we determined the extent of motor recovery (admission to discharge change in Functional Independence Measurement motor subscale score) prediction from electroencephalography, baseline motor status, and corticospinal tract injury. In 27 participants, coherence in a 1–30 Hz band between leads overlying ipsilesional primary motor cortex and 16 leads over bilateral hemispheres predicted 61.8% of the variance in motor recovery. High beta (20–30 Hz) and alpha (8–12 Hz) frequencies contributed most to the model demonstrating both positive and negative associations with motor recovery, including high beta leads in supplementary motor areas and ipsilesional ventral premotor and parietal regions and alpha leads overlying contralesional temporal–parietal and ipsilesional parietal regions. Electroencephalography power, baseline motor status, and corticospinal tract injury did not significantly predict motor recovery during hospitalization (R² = 0–6.2%). Findings underscore the relevance of oscillatory synchronization in early stroke rehabilitation while highlighting contributions from beta and alpha frequency bands and frontal, parietal, and temporal–parietal regions overlooked by traditional hypothesis‐driven prediction models.

The relevance of signal timing in human-robot collaborative manipulation

To achieve a seamless human-robot collaboration, it is crucial that robots express their intentions without perturbating or interrupting the task that a human partner is performing at that moment. Although it has not received much attention so far, this issue is important when robots assist humans in physical and manipulation tasks. The main question addressed here is whether there is a more appropriate time to inform a human partner that a robot is requesting to pass them an object. This question is posed in a reference scenario where human individuals are involved in a continuous pick-and-place task that cannot be interrupted. Our findings showed that providing a cue at the beginning of a reach-to-grasp movement could severely interfere with the ongoing human action, increasing the number of errors made by humans, slowing down and degrading the smoothness of their arm movement, and deflecting their gaze. These disruptive interferences strongly decreased, until they disappeared, when the robot provided the cue to the human partners shortly after the participants picked up an object, identifying this as the best signaling timing. The results of this work showed how the signaling timing may have a decisive influence on the performances of the human-robot teamwork and contribute to understanding the mechanisms underpinning the phenomenon of cognitive-motor interference in humans.

Disorganized resting-state functional connectivity between the dorsal attention network and intrinsic networks in Parkinson's disease with freezing of gait

Freezing of gait (FOG) is a common and complex manifestation of Parkinson's disease (PD) and is associated with impairment of attention. The purpose of this study was to evaluate the functional network connectivity (FNc) changes between the dorsal attention network (DAN) and the other seven intrinsic networks relevant to attention, visual-spatial, executive and motor functions in PD with or without FOG. Forty-three idiopathic PD patients (21 with FOG [FOG+] versus 22 without FOG [FOG-]) and 18 healthy controls (HC) were recruited in this study. The data-driven independent component analysis (ICA) method was used to extract and analyze the above-mentioned resting-state networks (RSNs). Compared with FOG-, FOG+ displayed decreased positive connectivity between the DAN and medial visual network (mVN) and sensory-motor network (SMN) and increased negative connectivity between the DAN and default mode network (DMN). The within-network connectivity in the SMN and visual networks were decreased, whereas the connectivity within DMN was increased significantly in FOG+. Correlation analysis showed that the clock drawing test (CDT) scores were positively correlated with the functional connectivity of mVN (r = 0.573, p = 0.008) and lateral visual network (lVN) (r = 0.510, p = 0.022), the Timed Up and Go Test (TUG) duration were negatively correlated with the connectivity of SMN (r = -0.629, p = 0.003), and the Frontal Assessment Battery (FAB) scores were negatively correlated with the connectivity of DMN in FOG+. Functional connectivity was changed in multiple intra-networks in patients with FOG. Inordinate inter-network connectivity between the DAN and other intrinsic networks may partly contribute to the mechanism of freezing.

A cortical injury model in a non-human primate to assess execution of reach and grasp actions: implications for recovery after traumatic brain injury

BACKGROUND

Technological advances in developing experimentally controlled models of traumatic brain injury (TBI) are prevalent in rodent models and these models have proven invaluable in characterizing temporal changes in brain and behavior after trauma. To date no long-term studies in non-human primates (NHPs) have been published using an experimentally controlled impact device to follow behavioral performance over time.

NEW METHOD

We have employed a controlled cortical impact (CCI) device to create a focal contusion to the hand area in primary motor cortex (M1) of three New World monkeys to characterize changes in reach and grasp function assessed for 3 months after the injury.

RESULTS

The CCI destroyed most of M1 hand representation reducing grey matter by 9.6 mm³, 12.9 mm³, and 15.5 mm³ and underlying corona radiata by 7.4 mm³, 6.9 mm³, and 5.6 mm³ respectively. Impaired motor function was confined to the hand contralateral to the injury. Gross hand-use was only mildly affected during the first few days of observation after injury while activity requiring skilled use of the hand was impaired over three months.

COMPARISON WITH EXISTING METHOD(S)

This study is unique in establishing a CCI model of TBI in an NHP resulting in persistent impairments in motor function evident in volitional use of the hand.

CONCLUSIONS

Establishing an NHP model of TBI is essential to extend current rodent models to the complex neural architecture of the primate brain. Moving forward this model can be used to investigate novel therapeutic interventions to improve or restore impaired motor function after trauma.

A Bayesian optimization approach for rapidly mapping residual network function in stroke

Post-stroke cognitive and linguistic impairments are debilitating conditions, with limited therapeutic options. Domain-general brain networks play an important role in stroke recovery and characterizing their residual function with functional MRI has the potential to yield biomarkers capable of guiding patient-specific rehabilitation. However, this is challenging as such detailed characterization requires testing patients on multitudes of cognitive tasks in the scanner, rendering experimental sessions unfeasibly lengthy. Thus, the current status quo in clinical neuroimaging research involves testing patients on a very limited number of tasks, in the hope that it will reveal a useful neuroimaging biomarker for the whole cohort. Given the great heterogeneity among stroke patients and the volume of possible tasks this approach is unsustainable. Advancing task-based functional MRI biomarker discovery requires a paradigm shift in order to be able to swiftly characterize residual network activity in individual patients using a diverse range of cognitive tasks. Here, we overcome this problem by leveraging neuroadaptive Bayesian optimization, an approach combining real-time functional MRI with machine-learning, by intelligently searching across many tasks, this approach rapidly maps out patient-specific profiles of residual domain-general network function. We used this technique in a cross-sectional study with 11 left-hemispheric stroke patients with chronic aphasia (four female, age ± standard deviation: 59 ± 10.9 years) and 14 healthy, age-matched control subjects (eight female, age ± standard deviation: 55.6 ± 6.8 years). To assess intra-subject reliability of the functional profiles obtained, we conducted two independent runs per subject, for which the algorithm was entirely reinitialized. Our results demonstrate that this technique is both feasible and robust, yielding reliable patient-specific functional profiles. Moreover, we show that group-level results are not representative of patient-specific results. Whereas controls have highly similar profiles, patients show idiosyncratic profiles of network abnormalities that are associated with behavioural performance. In summary, our study highlights the importance of moving beyond traditional 'one-size-fits-all' approaches where patients are treated as one group and single tasks are used. Our approach can be extended to diverse brain networks and combined with brain stimulation or other therapeutics, thereby opening new avenues for precision medicine targeting a diverse range of neurological and psychiatric conditions.

Effects of Different Types of Exercise Training on Fine Motor Skills and Testosterone Concentration in Adolescents: A Cluster Randomized Controlled Trial

We sought to compare the effect of two types of exercise training on fine motor skills and to establish their association with the salivary testosterone. Research participants, 135 adolescents (68 adolescent females; mean age = 12.76, SD = 0.85) were assigned into three groups: coordinative exercise (CE), cardiovascular exercise (CVE), and the control group (CON). Fine motor skills were assessed with a drawing trail test and salivary testosterone concentration was measured before and after 10 weeks of intervention. There were no significant changes in fine motor skills and testosterone concentration after either CE or CVE training. However, a significant positive correlation between post-test fine motor skills and post-test testosterone concentration was found after the CVE training. One type of exercise training cannot be singled out as more effective for fine motor skills and testosterone activity. Nevertheless, our results showed a relationship between fine motor skills and testosterone concentration after the CVE training. Thus, the type of exercise training is important in the exercise-induced testosterone effect on fine motor skills.

Precision Functional Mapping of the Subcortex and Cerebellum

Human functional brain networks can be reliably characterized within individuals using precision functional mapping. This approach entails the collection of large quantities of functional magnetic resonance imaging (fMRI) data from each individual subject. Studies employing precision functional mapping in the cerebral cortex have found that individuals manifest unique representations of functional brain networks around a central tendency described by previous group average approaches. We recently extended precision functional mapping to the subcortex and cerebellum, which has revealed several novel organizational principles within these structures. Here, we detail these principles and provide insights into how precision functional mapping of subcortical structures and the cerebellum may become clinically translatable.

Recovery and Prediction of Bimanual Hand Use After Stroke

OBJECTIVE

To determine similarities and differences in key predictors of recovery of bimanual hand use and unimanual motor impairment after stroke.

METHOD

In this prospective longitudinal study, 89 patients with first-ever stroke with arm paresis were assessed at 3 weeks and 3 and 6 months after stroke onset. Bimanual activity performance was assessed with the Adult Assisting Hand Assessment Stroke (Ad-AHA), and unimanual motor impairment was assessed with the Fugl-Meyer Assessment (FMA). Candidate predictors included shoulder abduction and finger extension measured by the corresponding FMA items (FMA-SAFE; range 0-4) and sensory and cognitive impairment. MRI was used to measure weighted corticospinal tract lesion load (wCST-LL) and resting-state interhemispheric functional connectivity (FC).

RESULTS

Initial Ad-AHA performance was poor but improved over time in all (mild-severe) impairment subgroups. Ad-AHA correlated with FMA at each time point (r > 0.88, p < 0.001), and recovery trajectories were similar. In patients with moderate to severe initial FMA, FMA-SAFE score was the strongest predictor of Ad-AHA outcome (R ² = 0.81) and degree of recovery (R ² = 0.64). Two-point discrimination explained additional variance in Ad-AHA outcome (R ² = 0.05). Repeated analyses without FMA-SAFE score identified wCST-LL and cognitive impairment as additional predictors. A wCST-LL >5.5 cm³ strongly predicted low to minimal FMA/Ad-AHA recovery (≤10 and 20 points respectively, specificity = 0.91). FC explained some additional variance to FMA-SAFE score only in unimanual recovery.

CONCLUSION

Although recovery of bimanual activity depends on the extent of corticospinal tract injury and initial sensory and cognitive impairments, FMA-SAFE score captures most of the variance explained by these mechanisms. FMA-SAFE score, a straightforward clinical measure, strongly predicts bimanual recovery.

CLINICALTRIALSGOV IDENTIFIER

NCT02878304.

CLASSIFICATION OF EVIDENCE

This study provides Class I evidence that the FMA-SAFE score predicts bimanual recovery after stroke.

Tracking whole-brain connectivity dynamics in the resting-state fMRI with post-facial paralysis synkinesis

BACKGROUND

Resting-state functional magnetic resonance imaging (rs-fMRI) is widely applied to explore abnormal functional connectivity (FC) in patients with post-facial paralysis synkinesis (PFPS). However, most studies considered steady spatial-temporal signal interactions between distinct brain regions during the period of scanning.

OBJECTIVE

In this study, we aim to investigate abnormal dynamic functional connectivity (dFC) in PFPS patients.

METHODS

We enrolled 31 PFPS patients and 19 healthy controls. All participants underwent rs-fMRI. Sliding windows approach was applied to construct dFC matrices. Next, these matrices were clustered into distinct states using the k-means clustering algorithm.

RESULTS

We found that it was not the dFC patterns, but rather the temporal properties including the mean dwell time (MDT) and occurrence frequencies, that showed a significant difference between PFPS patients and healthy controls. Two randomly clustered dFC states were recognized for both groups. Among them, State 1 showed significantly lower connectivity compared to State 2 in patients group. Compared to healthy controls, the duration spent by the PFPS patients in the state with lower connectivity significantly increased and is positively correlated with the better facial function.

CONCLUSIONS

In conclusion, aberrant dFC is a fundamental feature of brain dysfunction in PFPS patients, which is associated with the facial nerve function. These findings may contribute to a better understanding of the abnormal brain reorganization mechanisms in PFPS patients.

Cognitive Demands Influence Upper Extremity Motor Performance During Recovery From Acute Stroke

OBJECTIVE

To test the hypothesis that cognitive demands influence motor performance during recovery from acute stroke, we tested patients with acute stroke on 2 motor tasks with different cognitive demands and related task performance to cognitive impairment and neuroanatomic injury.

METHODS

We assessed the contralesional and ipsilesional upper extremities of a cohort of 50 patients with weakness after unilateral acute ischemic stroke at 3 time points with 2 tasks: the Box & Blocks Test, a task with greater cognitive demand, and Grip Strength, a simple and ballistic motor task. We compared performance on the 2 tasks, related motor performance to cognitive dysfunction, and used voxel-based lesion symptom mapping to determine neuroanatomic sites associated with motor performance.

RESULTS

Consistent across contralesional and ipsilesional upper extremities and most pronounced immediately after stroke, Box & Blocks scores were significantly more impaired than Grip Strength scores. The presence of cognitive dysfunction significantly explained up to 33% of variance in Box & Blocks performance but was not associated with Grip Strength performance. While Grip Strength performance was associated with injury largely restricted to sensorimotor regions, Box & Blocks performance was associated with broad injury outside sensorimotor structures, particularly the dorsal anterior insula, a region known to be important for complex cognitive function.

CONCLUSIONS

Together, these results suggest that cognitive demands influence upper extremity motor performance during recovery from acute stroke. Our findings emphasize the integrated nature of motor and cognitive systems and suggest that it is critical to consider cognitive demands during motor testing and neurorehabilitation after stroke.

Stay or go? Neuronal activity in medial frontal cortex during a voluntary tactile preference task in head-fixed mice

The decision to move is influenced by sensory, attentional, and motivational cues. One such cue is the quality of the tactile input, with noxious or unpleasant sensations causing an animal to move away from the cue. Processing of painful and unpleasant sensation in the cortex involves multiple brain regions, although the specific role of the brain areas involved in voluntary, rather than reflexive movement away from unpleasant stimuli is not well understood. Here, we focused on the medial subdivision of secondary motor cortex, which is proposed to link sensory and contextual cues to motor action, and tested its role in controlling voluntary movement in the context of an aversive tactile cue. We designed a novel, 3D-printed tactile platform consisting of innocuous (grid) and mildly noxious (spiked) surfaces (50:50 % of total area), which enabled monitoring neuronal activity in the medial frontal cortex by two-photon imaging during a sensory preference task in head-fixed mice. We found that freely moving mice spent significantly less time on a spiked-surface, and that this preference was eliminated by administration of a local anesthetic. At the neuronal level, individual neurons were differentially modulated specific to the tactile surface encountered. At the population level, the neuronal activity was analyzed in relation to the events where mice chose to "stop-on" or "go-from" a specific tactile surface and when they "switched" surfaces without stopping. Notably, each of these three scenarios showed population activity that differed significantly between the grid and spiked tactile surfaces. Collectively, these data provide evidence that tactile quality is encoded within medial frontal cortex. The task pioneered in this study provides a valuable tool to better evaluate mouse models of nociception and pain, using a voluntary task that allows simultaneous recording of preference and choice.

The effect of dual-task conditions on gait and balance performance in children with cerebral palsy: A systematic review and meta-analysis of observational studies

Dual-task conditions are commonly experienced in daily routines. The aim of the present systematic review is to investigate the effect of dual-task conditions on gait and balance performance in children with cerebral palsy (CP) and to perform meta-analyses where applicable. Five databases, "ProQuest", "PubMed", "OTSeeker", "Scopus", and "PEDro" from the incipient date of databases up to Aug 24, 2020 were searched for studies focusing on the effects of dual-task conditions on gait and balance performance in children with CP. After removing irrelevant articles and applying inclusion and exclusion criteria, nine articles were included in the present systematic review and meta-analysis. The results of the meta-analysis showed that walking speed was slower during dual-task conditions compared to single-task conditions in children with CP (WMD = -0.29 m/s, 95% CI = -0.34, -0.24, P ≤ 0.001) and walking speed decreased in children with CP during dual-task conditions in comparison with the typical development (TD) control group (WMD = -0.19 m/s, 95% CI = -0.23 to -0.15, P ≤ 0.001). The results of subgroup analysis based on the type of task indicated that adding concurrent tasks to walking degrades walking speed under varied dual-task conditions. Additionally, theoretical synthesis of the literature demonstrated that other gait and balance variables are changed by performing cognitive and motor secondary tasks differently. Although these changes may be compensatory strategies to retain their stability, there was not sufficient evidence to reach a firm conclusion. Research gaps and recommendations for future studies are discussed.

Decreased functional connectivity within the salience network after two-week morning bright light exposure in individuals with sleep disturbances: a preliminary randomized controlled trial

BACKGROUND

Bright light (BL) exposure is a safe non-pharmacological intervention for sleep disturbances. However, the functional brain correlates underlying the effects of bright light exposure need to be further clarified. As alterations in the salience network were reported in individuals with sleep disturbances, we have investigated whether bright light exposure may improve sleep quality by altering functional connectivity in this network.

METHODS

In the current study, 30 individuals with sleep disturbances were randomly assigned to one of the two interventions for two weeks: (1) 1 h of bright light (10,000 lux) exposure (BL-exposed group) and (2) 1 h of dim light (<300 lux) exposure (DL-exposed group). Sleep characteristics and functional connectivity in the salience network were assessed by sleep diary and resting-state functional magnetic resonance imaging, respectively, as outcome measures at before and after the intervention.

RESULTS

After two weeks of the intervention, the BL-exposed group showed greater improvement with respect to sleep efficiency (t = 2.27, p = 0.03) and sleep latency (t = -2.40, p = 0.03) as compared to the DL-exposed group. In addition, functional connectivity decreased in the cluster that encompasses the right anterior insular and the frontal opercular regions in the salience network (uncorrected p < 0.001, cluster size>100 mm³) in the BL-exposed group. Decreased functional connectivity in the cluster was associated with decreased sleep latency in the BL-exposed group (β = 0.54, p = 0.01).

CONCLUSIONS

Our results suggest that bright light exposure may improve sleep quality in individuals with sleep disturbances by modulating functional connectivity in the salience network.

CLINICAL TRIAL REGISTRATION

https://cris.nih.go.kr/cris; KCT0002607.

Predictors of Arm Nonuse in Chronic Stroke: A Preliminary Investigation

Background. Nonuse (NU) after stroke is characterized by failure to use the contralesional arm despite adequate capacity. It has been suggested that NU is a consequence of the greater effort and/or attention required to use the affected limb, but such accounts have not been directly tested, and we have poor understanding of the predictors of NU. Objective. We aimed to provide preliminary evidence regarding demographic, neuropsychological (ie, apraxia, attention/arousal, neglect), and psychological (ie, self-efficacy) factors that may influence NU in chronic stroke. Methods. Twenty chronic stroke survivors with mild to moderate sensory-motor impairment characterized by the Upper-Extremity Fugl-Meyer (UEFM) were assessed for NU with a modified version of the Actual Amount of Use Test (AAUT), which measures the disparity between amount of use in spontaneous versus forced conditions. Participants were also assessed with measures of limb apraxia, spatial neglect, attention/arousal, and self-efficacy. Using stepwise multiple regression, we determined which variables predicted AAUT NU scores. Results. Scores on the UEFM as well as attention/arousal predicted the degree of NU (P < .05). Attention/arousal predicted NU above and beyond UEFM (P < .05). Conclusions. The results are consistent with the importance of attention and engagement necessary to fully incorporate the paretic limb into daily activities. Larger-scale studies that include additional behavioral (eg, sensation, proprioception, spasticity, pain, mental health, motivation) and neuroanatomical measures (eg, lesion volume and white matter connectivity) will be important for future investigations.

Motor improvement estimation and task adaptation for personalized robot-aided therapy: a feasibility study

BACKGROUND

In the past years, robotic systems have become increasingly popular in upper limb rehabilitation. Nevertheless, clinical studies have so far not been able to confirm superior efficacy of robotic therapy over conventional methods. The personalization of robot-aided therapy according to the patients' individual motor deficits has been suggested as a pivotal step to improve the clinical outcome of such approaches.

METHODS

Here, we present a model-based approach to personalize robot-aided rehabilitation therapy within training sessions. The proposed method combines the information from different motor performance measures recorded from the robot to continuously estimate patients' motor improvement for a series of point-to-point reaching movements in different directions. Additionally, it comprises a personalization routine to automatically adapt the rehabilitation training. We engineered our approach using an upper-limb exoskeleton. The implementation was tested with 17 healthy subjects, who underwent a motor-adaptation paradigm, and two subacute stroke patients, exhibiting different degrees of motor impairment, who participated in a pilot test undergoing rehabilitative motor training.

RESULTS

The results of the exploratory study with healthy subjects showed that the participants divided into fast and slow adapters. The model was able to correctly estimate distinct motor improvement progressions between the two groups of participants while proposing individual training protocols. For the two pilot patients, an analysis of the selected motor performance measures showed that both patients were able to retain the improvements gained during training when reaching movements were reintroduced at a later stage. These results suggest that the automated training adaptation was appropriately timed and specifically tailored to the abilities of each individual.

CONCLUSIONS

The results of our exploratory study demonstrated the feasibility of the proposed model-based approach for the personalization of robot-aided rehabilitation therapy. The pilot test with two subacute stroke patients further supported our approach, while providing encouraging results for the applicability in clinical settings. Trial registration This study is registered in ClinicalTrials.gov (NCT02770300, registered 30 March 2016, https://clinicaltrials.gov/ct2/show/NCT02770300).

Force control predicts fine motor dexterity in high-functioning stroke survivors

BACKGROUND AND PURPOSE

High-functioning stroke survivors with mild to moderate motor impairments show greater functional autonomy in activities of daily living, and often return to work or prior activities. Increased functional independence necessitates dexterous use of hands to execute tasks such as typing, using a phone, and driving. Despite the absence of any pronounced motor impairments, high-functioning individuals with stroke report challenges in performing skilled manual tasks. Two prominent motor deficits that limit functional performance after stroke are decline in strength and force control. Here, we quantify the deficits in fine motor dexterity in high-functioning stroke survivors and determine the relative contribution of strength and force control to fine motor dexterity.

METHODS

Fifteen high-functioning participants with stroke (upper-limb Fugl-Meyer score ≥43/66) and 15 controls performed following tasks with the paretic and non-dominant hands respectively: i) Nine-hole peg pest, ii) maximum voluntary contraction and iii) dynamic force tracking with isometric finger flexion.

RESULTS

High-functioning stroke participants required greater time to complete the pegboard task, showed reduced finger strength, and increased force variability relative to the controls. Importantly, the time to complete pegboard task in high-functioning stroke participants was explained by finger force variability, not strength.

DISCUSSION AND CONCLUSIONS

High-functioning stroke survivors show persistent deficits in fine motor dexterity, finger strength, and force control. The ability to modulate forces (control) contributes to fine motor dexterity in high-functioning stroke survivors. Interventions to improve fine motor dexterity in these individuals should include the assessment and training of force control.

Integrative and Network-Specific Connectivity of the Basal Ganglia and Thalamus Defined in Individuals

The basal ganglia, thalamus, and cerebral cortex form an interconnected network implicated in many neurological and psychiatric illnesses. A better understanding of cortico-subcortical circuits in individuals will aid in development of personalized treatments. Using precision functional mapping-individual-specific analysis of highly sampled human participants-we investigated individual-specific functional connectivity between subcortical structures and cortical functional networks. This approach revealed distinct subcortical zones of network specificity and multi-network integration. Integration zones were systematic, with convergence of cingulo-opercular control and somatomotor networks in the ventral intermediate thalamus (motor integration zones), dorsal attention and visual networks in the pulvinar, and default mode and multiple control networks in the caudate nucleus. The motor integration zones were present in every individual and correspond to consistently successful sites of deep brain stimulation (DBS; essential tremor). Individually variable subcortical zones correspond to DBS sites with less consistent treatment effects, highlighting the importance of PFM for neurosurgery, neurology, and psychiatry.

Factors Influencing Manipulation of a Familiar Object in Patients With Limb Apraxia After Stroke

Previous studies have shown that hand actions to visual objects are affected both by perceptual factors and by action goals. Our aim was to study how these processes affected hand actions in chronic stroke patients, based on whether they had limb apraxia. Twenty-two left hemisphere, chronic stroke patients were measured on neuropsychological tasks of limb apraxia, which was identified in a subgroup of 10 patients. All patients underwent testing on a separate task of making simple reach and grasp actions to a cup. Their performance was compared to a group of 18 healthy age-matched volunteers. Participants were instructed to grasp the top or bottom of a cup to either lift or turn it over so as to end with a hand position that was either comfortable or uncomfortable. This task tested the influence of the compatibility of hand–cup orientation, as well as goals driven by the end-state comfort of the hand, on action selection for object manipulation. Participants’ performance was measured in terms of error rates, and speed of initiation and reaching (movement time) to the object. The patients’ performance was significantly delayed, and error rates increased when reaching to grasp a cup under conditions of poor compatibility and end-state comfort. The subgroup of patients with apraxia showed a decreased influence of compatibility of hand interaction with the cup, with increased error rates and delayed response times, compared to patients with no apraxia and healthy volunteers. This is despite the fact they did not display significant deficits on neuropsychological tasks of real object use. The study shows that patients with apraxia have difficulties in selecting elements of object-directed actions, pertaining to both habitual and goal-directed factors.

Relationship Between Motor Capacity of the Contralesional and Ipsilesional Hand Depends on the Side of Stroke in Chronic Stroke Survivors With Mild-to-Moderate Impairment

There is growing evidence that after a stroke, sensorimotor deficits in the ipsilesional hand are related to the degree of impairment in the contralesional upper extremity. Here, we asked if the relationship between the motor capacities of the two hands differs based on the side of stroke. Forty-two pre-morbidly right-handed chronic stroke survivors (left hemisphere damage, LHD = 21) with mild-to-moderate paresis performed distal items of the Wolf Motor Function Test (dWMFT). We found that compared to RHD, the relationship between contralesional arm impairment (Upper Extremity Fugl-Meyer, UEFM) and ipsilesional hand motor capacity was stronger (R L H D 2 = 0.42;R R H D 2 < 0.01; z = 2.12; p = 0.03) and the slope was steeper (t = -2.03; p = 0.04) in LHD. Similarly, the relationship between contralesional dWMFT and ipsilesional hand motor capacity was stronger (R L H D 2 = 0.65;R R H D 2 = 0.09; z = 2.45; p = 0.01) and the slope was steeper (t = 2.03; p = 0.04) in LHD compared to RHD. Multiple regression analysis confirmed the presence of an interaction between contralesional UEFM and side of stroke (β3 = 0.66 ± 0.30; p = 0.024) and between contralesional dWMFT and side of stroke (β3 = -0.51 ± 0.34; p = 0.05). Our findings suggest that the relationship between contra- and ipsi-lesional motor capacity depends on the side of stroke in chronic stroke survivors with mild-to-moderate impairment. When contralesional impairment is more severe, the ipsilesional hand is proportionally slower in those with LHD compared to those with RHD.

Recovery and Prediction of Dynamic Precision Grip Force Control After Stroke

Background and Purpose- Dexterous object manipulation, requiring generation and control of finger forces, is often impaired after stroke. This study aimed to describe recovery of precision grip force control after stroke and to determine clinical and imaging predictors of 6-month performance. Methods- Eighty first-ever stroke patients with varying degrees of upper limb weakness were evaluated at 3 weeks, 3 months, and 6 months after stroke. Twenty-three healthy individuals of comparable age were also studied. The Strength-Dexterity test was used to quantify index finger and thumb forces during compression of springs of varying length in a precision grip. The coordination between finger forces (CorrForce), along with Dexterity-score and Repeatability-score, was calculated. Anatomical magnetic resonance imaging was used to calculate weighted corticospinal tract lesion load (wCST-LL). Results- CorrForce, Dexterity-score, and Repeatability-score in the affected hand were dramatically lower at each time point compared with the less-affected hand and the control group, even in patients with mild motor impairment according to Fugl-Meyer assessment. Improved performance over time occurred in CorrForce and Dexterity-score but not in Repeatability-score. The Fugl-Meyer assessment hand subscale, sensory function, and wCST-LL best predicted CorrForce and Dexterity-score status at 6 months (R²=0.56 and 0.87, respectively). wCST-LL explained substantial variance in CorrForce (R²=0.34) and Dexterity-score (R²=0.50) at 6 months; two-point discrimination and Fugl-Meyer score accounted for considerable additional variance. Absence of recovery in CorrForce was predicted by wCST-LL >4 cc and in Dexterity-score by wCST-LL >6 cc. Conclusions- Findings highlight persisting deficits in the ability to grasp and control finger forces after stroke. wCST-LL was the strongest predictor of performance at 6 months, but early two-point discrimination and Fugl-Meyer score had substantial additional predictive value. Registration- URL: https://www.clinicaltrials.gov. Unique identifier: NCT02878304.

Inferential Integrity and Attention

How should we define inferential reasoning in high-level cognition? Can non-conscious representations guide or even determine high-level cognition? If so, what are the properties of such non-conscious representations? Two contemporary debates on high-level cognition center on these issues. The first concerns the possibility of cognitive penetration, or the degree and extent to which high-level cognition influences or determines low-level cognition. The second focuses on the epistemic status of conscious cognition, and on whether or not non-conscious cognition could play a similar, albeit not as fundamental, justificatory role as conscious cognition. This latter issue is at the heart of the question concerning the epistemic status of conscious awareness. This paper focuses on the epistemic standard required for inference, or inferential reasoning, to count as justificatory. The debates on the epistemic status of consciousness and cognitive penetration typically assume such a standard because high-level cognition is associated with rationality, inferentially structured thought, and the epistemic responsibility one has for the conclusions drawn through one’s inferences. The paper proposes an account of inferential-attention that explains how cognitive penetration of non-phenomenally conscious cognition and perception is possible, and why there are unconscious processes that should be considered as essential components of high-level cognition. Sections “Defining Inference” and “Accuracy Constraints: The Agency-First Account of Inference” provide a theoretical framework for understanding the multiple criteria that an adequate account of inference and rational thought must satisfy. Sections “Attention: High- and Low-Level Inferential Cognition in Various Domains” and “Advantages Concerning Rule-Following and Rationality: Not Necessarily-Phenomenal Inferential Reasoning” articulate the inferential-attention account and explain how it meets the descriptive and normative criteria for epistemic responsibility and rationality. In particular, section “Attention: High- and Low-Level Inferential Cognition in Various Domains” defends an agential interpretation of inferential-attention, which offers a resolution of the tension between conservative or consciousness-based approaches to inference and liberal approaches that allow for types of unconscious or subdoxastic processes. An agency condition on inference explains how inference is a psychological process under the control of the agent, and at the same time, it satisfies the normative condition that an inference should be responsive to reasons or evidence by being cognitively available for personal level assessment and evaluation. The key is to identify this kind of epistemic agency with attention. Section “Advantages Concerning Rule-Following and Rationality: Not Necessarily-Phenomenal Inferential Reasoning” compares this inferential-attention account with an influential agential account of inference based on conscious intuition, and it argues that the former account is preferable. This section also demonstrates the significance of inferential-attention in higher cognition, even when it is non-phenomenally conscious.

Three Distinct Sets of Connector Hubs Integrate Human Brain Function

Control over behavior is enabled by the brain's control networks, which interact with lower-level sensory motor and default networks to regulate their functions. Such interactions are facilitated by specialized "connector hub" regions that interconnect discrete networks. Previous work has treated hubs as a single category of brain regions, although their unitary nature is dubious when examined in individual brains. Here we investigated the nature of hubs by using fMRI to characterize individual-specific hub regions in two independent datasets. We identified three separable sets of connector hubs that integrate information between specific brain networks. These three hub categories occupy different positions within the brain's network structure; they affect networks differently when artificially lesioned, and they are differentially engaged during cognitive and motor task performance. This work suggests a model of brain organization in which different connector hubs integrate control functions and enable top-down control of separate processing streams.