Neural Mechanisms underlying Bimanual Coordination in Healthy and Stroke Individuals and Application of Non-Invasive Brain Stimulation: A Scoping Review

Neural Mechanisms underlying Bimanual Coordination in Healthy and Stroke Individuals and Application of Non-Invasive Brain Stimulation: A Scoping Review | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Neural Mechanisms underlying Bimanual Coordination in Healthy and Stroke Individuals and Application of Non-Invasive Brain Stimulation: A Scoping Review Jingyi Wu, Jiaqi LI, Patrick Wai-Hang Kwong, Jack Jiaqi Zhang, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3975753/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Post-stroke dysfunction in bimanual coordination causes decreased independence in activities of daily living. Past studies and reviews have reported the neural mechanisms underlying bilateral movements with an independent goal (BMIG) in healthy adults; however, those underlying bilateral movements with a common goal (BMCG) remain unclear. The purpose of this study is twofold: to review the neural mechanisms underlying upper-limb BMCG in healthy and stroke individuals, compared with BMIG and rest, and to determine the effects of non-invasive brain stimulation (NIBS) on improving BMCG in healthy and stroke individuals. Methods We conducted a literature search in the PubMed, Embase, Medline vis EBSCO, and Web of Science databases. Two authors independently screened the studies, extracted data, and qualitatively synthesized the studies. Results Fifteen studies were included. Of these studies, nine focused on brain activation underlying BMCG, and seven focused on the effects of NIBS on BMCG. In healthy individuals, three brain activation patterns underlying different BMCGs were identified. When healthy individuals performed BMCG and BMIG, the main differences observed were increased activation in the right superior temporal cortex and bilateral secondary somatosensory cortex. Compared with healthy controls, stroke patients demonstrated increased involvement of the unaffected cortical areas and decreased positive neural coupling between the primary motor cortex (M1) and supplementary motor area in the affected hemisphere during BMCG. Excitatory stimulation applied over the ipsilateral M1 and the contralateral dorsal premotor cortex may improve the performance of BMCG in stroke patients with mild and severe impairments, respectively. Conclusion Stroke patients may be compensatorily recruited with more brain areas to execute the BMCG tasks compared to healthy individuals. The improvement of BMCG in stroke is because of the improvement of general motor impairment rather than a specific effect on BMCG. Systematic Review Registration This review was registered on Inplasy.com (INPLASY202350080) Hand Motor Skills Disorders Neurovascular Coupling Physical Functional Performance Stroke Non-invasive brain stimulation Figures Figure 1 Figure 2 Figure 3 Background According to the 2021 Global Burden of Disease study, stroke is not only a leading cause of the loss of disability-adjusted life years, but also one of the most widespread adult-onset neurological disabilities worldwide [ 1 , 2 ]. Among stroke survivors, dysfunction in the upper extremities is the most common complication, which leads to difficulty in completing occupational activities [ 3 , 4 ]. Performing most activities of daily living (ADLs), including playing musical instruments, working with tools, and performing some household chores, considerably depends on the cooperation and coordination of bilateral upper extremities. Patients with coordination deficits in bilateral upper extremities have increased difficulty in performing certain ADLs [ 5 , 6 ]. Most relevant studies focused on the affected limbs, with the aim of promoting independence in ADLs through the improvement of motor function in the hemiplegic limb [ 7 – 9 ]. However, functional bilateral abilities are not as simple but involve a combination of one-handed motor skills. Exploring unilateral dysfunction alone cannot aid in determining the extent of bilateral upper-limb deficits. Similarly, resolving upper-limb impairment does not engender improvements in bilateral cooperative movement [ 10 ]. Therefore, exploring changes in neural activities underlying the bilateral upper-limb coordination in patients with stroke is warranted. Upper-limb bimanual coordination involves an interrelationship between the spatial and temporal domains for accomplishing a clear goal (i.e., common goal and independent goal). On the basis of the spatiotemporal feature, theoretically based classes of bilateral coordination can be obtained; for example, bilateral upper-limb movements can be either symmetric and asymmetric driven by either a common goal or an independent goal [ 11 ]. The main characteristics of symmetric movements are temporal and spatial coupling and the simultaneous engagement of homologous muscles. In contrast, asymmetric movements are mainly characterized by different relative phases of movement and spatial uncoupling. According to the theory of egocentric and allocentric constraints, asymmetrical movements are less accurate and stable than symmetrical movements [ 12 ]. In a psychophysical experiment in healthy adults, as the anti-phase movement frequency increases the tendency towards symmetrical movements becomes stronger, leading to the eventual transition of movements from being anti-phase to being in-phase [ 13 ]. The way in which a person perceives the goal of a specific task (i.e., independent or common) can also affect bimanual coordination, particularly in terms of determining bimanual movements of the upper limbs [ 14 , 15 ]. According to task characteristics, bimanual movements can be divided into two categories: bilateral movements with an independent goal (BMIG) and bilateral movements with a common goal (BMCG). Each category can be further divided into two classes, and they are the symmetric independent goal (e.g., reaching forward to grab two different objects) and asymmetric independent goal (e.g. using one hand to draw a circle and the other to draw a line); symmetric common goal (e.g. reaching forward to grasp the same object) and asymmetric common goal (e.g. opening a bottle cap; folding a towel or clothes) [ 11 ]. Importantly, ADLs completed using bilateral upper limbs typically involve either a symmetric or an asymmetric common goal. Many studies explored the relevant kinematic and neural mechanisms underlying deficits in bimanual coordination in patients with stroke, with the aim of improving independence in ADL. Some studies investigated the distinction in neural mechanisms during unilateral movement versus bilateral movement, and the findings revealed that bimanual activities exhibited heightened interhemispheric interactions compared to unilateral movement [ 16 , 17 ]. Kim et al. reviewed 17 studies, including a total of 103 patients with stroke and 90 healthy individuals [ 18 ]. The authors concluded that the patients performing both symmetric and asymmetric BMCG appeared to have major coordination deficits in the kinematic and kinetic domains. However, during symmetrical BMIG, no considerable impairment in coordination was observed in the patients compared with healthy individuals. Moreover, patients with stroke demonstrated a longer pickup time while reaching for a box using both hands than healthy individuals. During an asymmetric task, where one hand is used to open the drawer and the other presses the button, patients demonstrated a longer delay than control individuals [ 5 ]. Another review suggested that an extended cortical network, including the sensorimotor cortex, supplementary motor area (SMA), cingulate cortex, dorsal premotor cortex (PMd), and posterior parietal cortex, is involved in normal bilateral movements [ 19 ]. De Oliveira et al. proposed a classical bilateral movement model of three theories: generalized motor program, intermanual crosstalk model, and dynamic systems approach to explain and attempt to predict the neural basis of in-phase and anti-phase bimanual behavior [ 20 ]. Subsequent clinical trials have confirmed the presence of changes in neural activities [ 17 , 21 , 22 ]. A functional magnetic resonance imaging (fMRI)-based study reported higher activation of the right dorsal lateral prefrontal cortex (DLPFC) during temporal uncoupling movements than during symmetrical movements [ 23 ]. Van Dun et al. used activation likelihood estimation to quantify and synthetically analysed the differences between all in-phase, anti-phase, and out-of-phase bilateral movements; they found that the anterior cerebellar vermis played a vital role during anti-phase and out-of-phase movements, whereas the posterior cerebellar vermis played a vital role during out-of-phase movements [ 24 ]. The extent and areas of activation during BMCG were partly determined based on the differences in the motor and task characteristics. However, no studies reviewed the neural mechanism of BMCG in healthy individuals and stroke patients. Non-invasive brain stimulation (NIBS) is a modern technique for stroke rehabilitation in which abnormal brain activity is increased or reduced for physical function improvement. In general, NIBS comprises transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS) [ 25 , 26 ]. Regarding unilateral motor impairment, decreased excitability of the impaired hemisphere and imbalanced interhemispheric inhibition (IHI) after stroke are the main reasons underlying poor motor function recovery [ 27 , 28 ]. The disturbed neural network involving PMC and cerebellum and disturbed interhemispheric interaction between SMA and M1 were the primary reasons for poor recovery in bimanual coordination compared to unilateral movement [ 17 , 29 ]. When applied to the ipsilesional primary motor cortex (M1), high-frequency repetitive TMS (rTMS) could effectively enhance the motor function recovery of the paretic upper limbs. Still, whether it leads to any improvement in bimanual coordination through acting in motor-related areas is unclear [ 30 ]. The development of novel brain modulation techniques aimed at improving bimanual coordination and filling the gap between impaired neurological assessment and advanced training of coordinated bilateral movements is ongoing. Recent neuroimaging experiments have clarified neural activity changes underlying BMCG in healthy individuals and patients with stroke. Moreover, many studies used advanced NIBS to enhance bimanual coordination (i.e., BMIG and BMCG). However, most of these studies are limited by a small sample size; furthermore, high variability has been noted across different studies. Therefore, a scoping review with a qualitative synthesis of the literature on BMCG–related neural activity in healthy and stroke patients and the effects of NIBS on BMCG improvement is warranted. In the current scoping review, we thus carry three main objectives. First, we identify the brain areas consistently activated during BMCG in healthy individuals, compared to BMIG and rest. Second, we investigate differences in brain activity between patients with stroke and healthy individuals during BMCG. Third, we provide a comprehensive summary of advanced NIBS applied in both neurologically intact individuals and patients with stroke for the improvement of their BMCG. Methods This review was carried out by conforming to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines [ 31 ] and was already registered on Inplasy.com (INPLASY202350080). Database Search We searched PubMed, Embase, Medline via EBSCO, and Web of Science databases for relevant articles published from inception until 1 February 2023. We used the following search terms: stroke, CVA, hemiplegia, cerebrovascular accidents, cerebrovascular disorder, paresis, healthy individuals, healthy participants, healthy subjects, normal volunteer, bilateral coordination, bimanual coordination, cooperative, bimanual cooperative, coordination, symmetric, asymmetric, out-of-phase, upper limb, upper extremities, upper limbs, upper extremity, hand, hands; functional imaging, fMRI, functional magnetic resonance imaging, brain imaging, MRI, EEG, electromyography, near-infrared spectrometry, NIRS, TMS, and transcranial magnetic stimulation. Our search strategy is detailed in Table S1 . Study Selection Criteria According to the PICOS principle, we included studies on neural changes that met the following criteria: studies that recruited adult participants diagnosed as having a stroke, healthy individuals, or both [population (P)]; studies that compared BMCG with other types of movement [intervention (I)]; and studies that described at least one outcome assessing upper-limb neural functions, such as TMS-EMG, electroencephalography (EEG), and fMRI [outcomes (O)]. We excluded studies that (1) recruited patients with primary neurological diseases other than stroke; (2) were published in dissertations or books or as conference abstracts without access to their full papers; (3) included only symmetric and asymmetric BMIG; (4) focused on infants, children, or adolescents; and (5) were not published in the English language. Among all articles on neural mechanisms of bimanual coordination, we selected studies on NIBS aimed at enhancing BMCG according to the PICOS principle. Specifically, we included studies on NIBS that met the following inclusion criteria: studies that recruited adult participants diagnosed as having stroke, healthy subjects, or both (P) and those that employed NIBS or experimental paradigms such as rTMS, theta burst stimulation (TBS), tDCS, and transcranial alternating current stimulation (tACS) to improve BMCG (I). However, we excluded studies that (1) did not employ NIBS to promote BMCG; (2) recruited patients without a diagnosis of stroke or included infants, children, and adolescents; (4) were published as research protocols, conference proceedings, or conference abstracts; and (5) were not published in the English language. Data Extraction After identifying relevant studies, two authors (JYW and JQL) independently extracted the following information from each article: (1) the first author and publication year; (2) patient characteristics (i.e., age, time since stroke onset, and initial impairment level) and the characteristics of healthy individuals (i.e., age and handedness); (3) the NIBS used for both the groups, including the intervention type and duration and measurement details; (4) the modalities used for functional neuroimaging, EEG, or both; and (5) the outcome data, including brain activation and functional connectivity. Any disagreements between the two authors were resolved through discussion with the third author (WHK). Outcome Measurement Assessment BMCG and BMIG induced differential activation patterns in each brain region as measured by fMRI in separate brain regions of interest or the whole brain. Functional connectivity is evaluated using the task-based fMRI. This method tests how different brain regions interact during a specific task. EEG is another technique to measure the change of inter/intra-cortical connectivity through electrodes covering interested brain areas. Activation Pattern Identification All statistical analyses were performed using SPSS 26.0 (SPSS Inc., Chicago, USA). We used hierarchical clustering analysis with Ward’s model to classify BMCG into different groups according to the specific activated brain regions in each study. To discover the specific brain activation patterns during BMCG, we used K-means clustering—an unsupervised machine learning algorithm—with the number of groups as the K value (i.e., the number of clusters). The algorithm first assigned data points to random groups and then estimated the group centres. The studies were iteratively grouped according to the distance between each data point and the group centres; this was repeated until no change occurred in the grouped studies from the previous iteration. Finally, one-way analysis of variance (ANOVA) was used to compare differences in activation patterns among the clusters. Results Study Characteristics In the initial search, we retrieved 2735 articles. We then removed duplicates and screened the remaining 1875 articles. Out of these articles, we excluded 1782 articles because they were irrelevant (n = 1765), reviews or meta-analyses (n = 10), or conference abstracts (n = 7). Next, we screened the full text of the remaining 93 articles. Out of these, 78 articles were excluded for the following reasons: they did not employ fMRI in healthy individuals or fMRI or electroencephalography (EEG) for comparing outcomes between patients with stroke and healthy individuals (n = 17), they used unclear experimental designs in terms of whether BMCG (n = 56) were involved, they reported improved bimanual coordination without the use of NIBS (n = 5). Finally, this scoping review included 15 studies. Out of these, nine studies aimed at the neurological mechanism of BMCG involving 144 healthy individuals and 24 patients with stroke and seven studies aimed at the effect of NIBS involving 184 and 31 healthy and stroke population. One study either reported neurological mechanism of BMCG and the effect of NIBS on BMCG. Figure 1 illustrates our study selection flowchart. Brain Activation Patterns in Healthy Individuals After they were subjected to hierarchical cluster analysis using Ward’s method, five studies (six units) were found to report brain activities associated with BMCG [ 32 – 36 ]. On the basis of the different activated brain regions, the brain activation patterns underlying BMCG could be divided into three clusters. The resulting dendrogram presented in Fig. 2 provides the clusters that reflect the three brain activation patterns. The results of the K-means cluster analysis of these studies corroborated those of the hierarchical cluster analysis (Table I). The ‘familiar’ and ‘unfamiliar’ BMCG-related neural activities were reported in healthy adults using an imitation task paradigm of familiar and unfamiliar actions. The specific brain activation patterns of the three clusters are presented in Figure. 3. Cluster I [ 32 , 34 ] pertained to the brain activation pattern underlying BMCG in healthy individuals, which comprised the bilateral interior parietal cortex (IPC), M1, inferior temporal cortex (ITC), superior frontal cortex (SFC), cerebellum, medial occipital cortex (MOC), the primary somatosensory cortex (S1), medial frontal cortex (MFC), superior parietal cortex (SPC), right inferior frontal cortex (IFC), intraparietal sulcus (IPS), precuneus, ventral premotor cortex (PMv), superior temporal cortex (STC), anterior cingulate cortex (ACC), DLPFC, medial temporal cortex (MTC), orbitofrontal cortex (OFC), and angular gyrus, left PMd and basal ganglia (Fig. S1 a). Cluster II [ 36 ] pertained to the brain activation patterns for the imitation of familiar movements involving the bilateral wrists and hands, which included the medial prefrontal cortex (PFC) and cerebellum in the right hemisphere and the SFC, middle cingulate cortex (MCC), angular gyrus, and precuneus in the left hemisphere, bilateral STC, S1, and cuneus (Fig. S1 b). Cluster III [ 33 , 35 ] mainly reflected the brain activation pattern for BMCG with wrist joint, which comprised the bilateral cerebellum, M1, S1, SMA, premotor cortex (PMC), thalamus, the secondary somatosensory cortex (S2), ACC, posterior cingulate cortex (PCC), basal ganglia, cuneus, parietal and frontal opercular cortex (FPO), supramarginal gyrus, lateral PFC (PFl), ventral PMC (PMv) and dorsal PMC (PMd), the right MTC, and left insular cortex (Fig. S1 c). Differences among the activation patterns were found to be significant ( P = 0.001). Table 1 K-means cluster analysis distribution Reference Cluster Distance Koeneke 2004 1 2.000 Hanawa 2016a 2 0.000 Hanawa 2016b 1 2.449 Dietz 2013 3 1.803 Duque 2010 1 2.449 Puttemans 2005 3 1.803 a: Familiar BMCG for healthy subjects; b: Unfamiliar BMCG for healthy subjects. Familiarity refers to the subjects seeing the action many times, whereas non-familiarity refers to the action that looks difficult to perform for the subjects. Major Differences of Brain Activation Between BMCG and BMIG in Healthy Individuals Four studies have investigated differences in brain activation between BMCG and BMIG in healthy individuals [ 34 , 35 , 37 , 38 ]. Specifically, Duque et al. and Ullen et al. used fMRI to investigate the differences in brain activation between bilateral hand movements with a given speed ratio and bilateral hand movements without a given speed ratio [ 34 , 37 ]. The findings of the former demonstrated that BMCG involves a greater activation in the right SMA, M1, and STC than BMIG. In contrast, the latter indicated that BMCG has a greater activation in bilateral STC, right IPS, and middle preSMA. Another two studies comparing bilateral wrist movement with simulating open-and-close bottles and bilateral wrist pro-and supination movement indicate that bilateral S2 are sensitive to BMCG [ 35 , 38 ]. In addition, one of the two studies, bilateral S1, left insular cortex, cerebellum, and right posterior thalamus may also be responsible for BMCG, as activity in these areas significantly increases during BMCG than BMIG [ 35 ]. Major Differences of Brain Activation of BMCG Between Patients with Stroke and Healthy Individuals Two studies reported differences in activated brain areas and functional connectivity (FC) between healthy individuals and patients with stroke [ 39 , 40 ]. Schrafl-Altermatt et al. [ 40 ] found that when the affected arm was stimulated during BMCG, the somatosensory evoked potential amplitude ratio was higher (indicating more contralateral hemisphere involvement) in patients with stroke (1.23 ± 028) than in healthy individuals (0.99 ± 0.44). Grefkes et al. [ 39 ] demonstrated that healthy individuals had significantly increased inhibitory of FC among the bilateral M1, PMC, and SMA and positive interaction within the hemisphere. In contrast, stroke patients showed reduced positive neural coupling between the ipsilateral SMA and ipsilateral M1 and decreased inhibitory FC between bilateral SMA and between contralateral SMA and ipsilateral M1 than healthy individuals. Finally, impairments in BMCG in patients with stroke were associated with low coupling strength from the ipsilateral SMA to the ipsilateral M1 (Pearson’s r = 0.62, P < 0.05). Tables S2 present the characteristics of all included studies on neural changes. Non-Invasive Brain Stimulation in Healthy Individuals Targeting the BMCG Five studies reported the effects of NIBS on BMCG in healthy individuals. In particular, anodal tDCS (1.5 mA, for 15-min stimulation) on the cerebellum when performing two-hand coordinated movements improved skill acquisition (i.e., error time reduction); by contrast, the consolidation of adapting learning of tasks (off-line learning) was enhanced when tDCS (1.5 mA, for 15-min stimulation) was administered before the performance of two-hand coordinated movements [ 41 ]. A study by Duque et al. found significantly increased hand error in BMCG in healthy individuals after virtual lesion over the right STC inducing by 18 min of 10-Hz rTMS trains compared with no train [ 34 ]. In addition, 10-Hz TMS applied over the left PMd (110% rest motor threshold, 5 pulses) enhanced bilateral hand motor speed and accuracy during BMCG [ 42 ]. However, in-phase or out-of-phase beta-tACS (2 mA, for 20-min stimulation) or sham tACS over the bilateral M1 led to no learning-related changes [ 43 ]. Similarly, 10-Hz and 20-Hz tACS (1 mA, for 20-min stimulation) and sham tACS over the left IPC did not result in differences in bimanual coordination improvement [ 44 ]. Table S3 present the characteristics of all included studies on NIBS. Non-Invasive Brain Stimulation in Patients with Stroke targeting the BMCG Two studies reported the effects of NIBS on BMCG in stroke patients. Compared with sham stimulation, anodal tDCS (1 mA, for 30-min conditioning) over the cM1 did not lead to enhancement in bimanual motor skill learning and generalization (i.e. applying learned motor skills to other tasks) in chronic stroke patients with mild and moderate impairment [ 45 ]. In addition, 5-Hz rTMS (70% of active motor threshold, 1200 pulses) over the cPMd or iM1 led to enhanced two-arm temporal coordination: stimulation over the iM1 increased bimanual coordination in patients with mild impairment and strong IHI from the contralateral to the ipsilateral M1, and stimulation over the cPMd increased bimanual coordination in those with severe impairment and weak IHI [ 29 ]. Discussion The review concluded that a general bimanual network was activated when healthy subjects underwent different types of BMCG, which consisted of the bilateral M1, SMA, cerebellum, and S1. Secondly, previous studies showed that increased unimpaired hemisphere involvement and decreased positive neural coupling between the ipsilateral SMA and the ipsilateral M1 were the major differences in neural patterns between patients with stroke and healthy individuals who performed BMCG. Thirdly, excitatory NIBS applied over the left PMd and the bilateral cerebellum led to a positive influence on BMCG in healthy individuals, whereas applied over the bilateral M1 and the left IPC, they did not induce a positive effect on BMCG in healthy subjects. Finally, stroke patients with mild impairment benefited from excitatory stimulation of the ipsilateral M1, and those with severe impairment benefited from stimulation of the contralateral PMd in terms of improvement in BMIG. In contrast, chronic stroke patients with mild to moderate impairment did not benefit from excitatory stimulation of the contralateral M1 in terms of improvement in BMCG. Regarding the findings of the general bimanual network, a study examining the effects of NIBS on healthy individuals to improve BMCG showed that excitatory stimulation over the cerebellum resulted in positive changes in bimanual coordination [ 41 ]. This aligns with our findings that all patterns activate the cerebellum during BMCG (Fig. 3 ), suggesting that the anterior and posterior cerebellar vermis are involved in spatial and temporal control during complex bimanual tasks. Additionally, Dietz et al. identified a neural network related to BMCG, primarily involving bilateral M1, SMA, and cerebellum [ 46 ]. However, our results indicate significant extra-activation on the bilateral S1 compared to Dietz et al.’s findings [ 46 ]. More precisely, sensory information, such as proprioceptive and cutaneous sensory input, predominantly contributes to motor learning and control. Moreover, functional goal-oriented tasks (i.e., reaching out and grasping a ball) elicit higher activation in S1 than non-functional movements [ 47 – 49 ]. This implies that bilateral S1 plays a pivotal role in BMCG, especially in activities demanding purposeful movements and the integration of sensory input to enhance coordinated actions involving both upper limbs or hands. Our hierarchical cluster analysis revealed three distinct activation patterns within the brain regions when various BMCG tasks were performed. Notably, Cluster I was only associated with the execution of an object manipulation task performed while participants observed a computer screen. Object manipulation necessitates intricate fine motor control and the concurrent operation of two sensory systems—namely, proprioception and somatic sensation. Signals originating from tactile and proprioceptive fibers, which innervate the skin and muscles of the hand, are conveyed to the S1 through the ventro-postero-lateral nucleus of the thalamus and the cuneate nucleus in the brainstem. [ 50 ]. This observation is consistent with our results that the IPC in the bilateral hemispheres was more significantly activated in Cluster I than in Cluster II. In addition, visual information regarding the cursor’s location helped foster a proper motion plan. Specialised circuits in the primary visual cortex located in the occipital lobe can aid in achieving this visuomotor transformation through the posterior parietal cortex, PMd, and PMv. Therefore, our results indicated that the BMCG in Cluster I led to the significant activation of the bilateral MOC, right PMv, and left PMd compared to Cluster II and III [ 50 , 51 ]. The complexity of BMCG varied between Clusters II and III, specifically in terms of relative phase, temporal aspects (relative interlimb frequency), and spatial elements (direction and amplitude). In contrast to the tasks in Cluster II, those in Cluster III exhibited increased complexity across all these domains. Two studies investigating age-related changes in the brain highlighted that complex bimanual motor tasks led to heightened activities in the PFC and primary M1 in both hemispheres [ 21 , 52 ]. Debaere et al. proposed a positive association between spatiotemporal complexity of bilateral movements and activation in the SPC, SMA, and thalamus in both hemispheres. Additionally, they suggested that the movement frequency of bimanual tasks were positively associated mainly with activities in the bilateral CMC, PMC, and thalamus [ 53 ]. This partly aligns with our findings that complex bilateral movements activate the bilateral M1, PMC, thalamus, CMC, and PFC (Fig. 3 .). However, in contrast to the findings of Debaere et al., our results demonstrated that the bimanual movements of different complexities led to significant activation of the bilateral SMA. Notably, augmented activities in the SPC in the bilateral hemispheres were observed during relatively simple bilateral tasks but not during relatively complex bilateral tasks; this outcome may be related to the neural mechanism of imitation [ 54 ]. The primary distinction between Cluster II and Clusters I and III lies in the level of familiarity that healthy subjects have with BMCG. Specifically, when healthy participants were learning a new bilateral task, bilateral M1 and SMA exhibited the most pronounced activation and the most extensive network of functional connectivity [ 55 , 56 ]. In addition, some studies indicated that the cerebellum plays a crucial role in the motor learning network by facilitating SMA to M1 communication, which means that the communication between the cerebellum and motor cortical areas is vital for motor learning [ 57 , 58 ]. These findings support our discovery of a cortical-striato-cerebellar network involved in motor learning, specifically bilateral M1, SMA, and the left cerebellum, which undergoes modulation changes when healthy individuals attempt an innovative bilateral task. However, we also observed increased activation in the right MTC when healthy individuals performed a novel BMCG task, which may be associated with the neural mechanisms underlying explicit and implicit motor learning processes. Previous research has shown that improved activation in the MTC is associated with increased cognitive demand during the learning and execution of new tasks [ 59 , 60 ]. The key contrast observed between BMCG and BMIG in healthy individuals during a hand activity with a specific speed ratio was the enhanced activation in the right STC. Specifically, when engaging in a hand activity with a given fixed rhythm, there were generally greater demands in spatial and temporal aspects compared to activities without rhythm. Previous studies have highlighted the dominant role of the right hemisphere for spatial representation and attention, particularly in the STC [ 61 , 62 ]. Heightened activation of the right STC may contribute to the proficient execution of BMCG by enabling constant monitoring of the spatial positions of both hands in healthy individuals. Our observation aligns with a study on the impact of NIBS, supporting the notion that stimulating the right STC actively enhances bimanual coordination performance, thereby promoting awareness of the spatial locations of both hands [ 63 ]. When examining task-oriented activities, it became evident that the disparity between BMCG and BMIG in healthy individuals resulted in excessive activation of bilateral S2. This can be attributed to the fact that S2 is responsible for merging sensory input from both hands, an essential requirement for coordinating movements between the two sides during cooperative actions rather than non-cooperative ones [ 35 , 64 ]. Interestingly, our findings are in agreement with the research conducted by Michels et al., which also revealed similar outcomes, indicating that younger individuals exhibit heightened activation in bilateral S2 when performing task-specific BMCG as opposed to BMIG [ 65 ]. These findings support our assertion that bilateral S2 is critical in task-based BMCG in healthy individuals. The primary neural distinctions observed between stroke patients and healthy individuals performing BMCG included heightened engagement of the unaffected hemisphere and reduced positive neural connectivity between the ipsilateral SMA and the ipsilateral M1. Neural coupling during BMCG is achieved through the exchange of information from each hand to both the hemispheres through the corpus callosum while producing effective FC between specific sensorimotor areas, resulting in the appropriate control of bimanual coordination [ 35 ]. Compared with healthy individuals, stroke patients who received nerve stimulation of the affected hand when performing BMCG demonstrated increased engagement of the unaffected hemisphere, which may involve S2 activation. The S2 acts as an integration area for sensory input from the right hand, left hand, or both hands, and it is significantly activated after stimulation [ 22 , 66 ]. In addition, the bilateral S2 is more activated in BMCG (i.e., bottle opening and closing) than in non-cooperative movements [ 65 ]. In other words, increased bilateral S2 activation aids in performing BMCG in patients with stroke compared with that in healthy individuals. Another finding of this review is that an imbalance in inter-hemispheric inhibition arises from diminished neural coupling between the ipsilateral M1 and the contralateral SMA and between bilateral SMA, disrupting the neural functions and leading to their overactivation. Balanced interhemispheric coupling is crucial for the coordination of bilateral patterns [ 67 ]. This imbalance in inter-hemispheric inhibition results in impaired coordination. In addition, underactivation in ipsilateral M1 induced by decreased positive neural coupling between ipsilateral M1 and ipsilateral SMA that negatively affected BMCG in stroke patients closely aligned with our results of excitatory NIBS applied over the ipsilateral M1 improved BMCG in stroke patients with mild impairment. We observed differences among the effects of NIBS on healthy individuals for improving BMCG. This difference was due to the distinction in the stimulation sites, outcome measures, and ceiling effect among the included studies. First, excitatory stimulation over the cerebellum induced positive change in bimanual coordination because the anterior and posterior cerebellar vermis perform spatial and temporal control during complex bimanual tasks [ 24 ]; this is consistent with our result that all types of activation patterns activate the cerebellum during BMCG. Moreover, virtual lesions over the right STC disrupted bimanual coordination performance because the right STC is mainly responsible for spatial awareness and exploration associated with both object- and spatial-related information, which aid in fostering the spatial location of the two hands [ 63 ]. Second, compared with sham stimulation, excitatory stimulation over the bilateral M1 did not trigger a positive effect in terms of bilateral task performance (i.e., error rate and movement time). This may have been due to the stimulation frequency used; specifically, beta may not be the optimal stimulation frequency for motor learning compared with the other frequencies (e.g., gamma and alpha) [ 68 ]. This may be due to beta-tACS increasing beta in the M1 by entrain endogenous beta rhythms and causing cortical reorganisation associated with motor learning. Third, healthy individuals aged 18–30 years have great bimanual coordination, which may have led to a ceiling effect (where the effects of 10- and 20-Hz tACS were indistinguishable), leaving only little room for significant enhancement after tACS. Similar findings were found in some other studies on healthy individuals [ 69 , 70 ]. The effects of NIBS applied in the M1 for improving BMCG are highly dependent on the impairment levels of patients with stroke. This is consistent with the bimodal recovery model - mild impairment needs a re-establishment of IHI, while severe impairment needs contralesional compensation [ 52 ]. Specifically, stimulation over the M1 on the impaired hemisphere than on the unimpaired hemisphere led to significant improvement in bimanual coordination in stroke patients with mild impairment. This is because, compared with other impairment levels, stimulation over the ipsilateral M1 leads to a great response, which is positively associated with motor recovery [ 71 , 72 ], which is also consistent with our findings that reduced positive neural coupling between ipsilateral M1 and ipsilateral SMA was observed when performed BMCG in stroke patients compared with healthy individuals (Table S2 ). However, stroke patients with severe impairment did not benefit from simulation over the ipsilateral M1 because strong transcallosal inhibition from the unaffected hemisphere to the affected hemisphere reduced patient response to NIBS [ 28 ]. They may benefit from stimulation over the contralateral PMd. This is because the contralateral PMd compensatorily supports the general motor functions in severe stroke patients and can trigger more facilitatory and less inhibitory effects on the ipsilateral M1 than in those with other impairment levels [ 73 , 74 ]. Thus, we guess the improvement of BMCG in stroke is because of the improvement of general motor impairment rather than a specific effect on BMCG. The difference in effect between individuals with healthy and stroke also supports this statement that excitatory stimulation over the M1 is ineffective, whereas, over the PMC and cerebellum, it is effective in healthy individuals. Limitations This review has some limitations. The quantitative outcomes and changes in neural activities during BMCG in healthy individuals and patients with stroke still need to be clarified due to the limited number and the heterogeneity of the included studies on outcome measurement. Thus, a meta-analysis of neuroimaging data has not been performed, and the result cannot be generalized to the whole population. Potential factors, such as differences in measurement methods, targeted areas, and definitions of bimanual coordination tasks, among the included studies rendered the detection of the brain areas involved in bimanual coordination in patients with stroke difficult. Studies identifying differences in brain activation between patients with stroke and healthy individuals during BMCG targeting the whole brain, and not only areas of interest (e.g., bilateral M1), are warranted. Furthermore, both internal and external factors influence bimanual coordination performance. However, our review primarily focuses on external factors, precisely task complexity, while internal factors, including age, gender, and inherent motor skills, remain to be thoroughly investigated [ 75 ]. Future research This study is intended to serve as a foundation for future research, pinpointing potential areas for the application of NIBS for improving the BMCG in stroke patients. It is proposed that future research can concentrate on cerebellum, STC, premotor, and ITC. Although NIBS has shown potential in enhancing BMCG in stroke patients through its influence on neural plasticity and brain regions, the existing findings are still insufficient. Further investigation is needed to understand how neural activation patterns during BMCG evolve over time in post-stroke recovery. This could be achieved through a series of longitudinal studies, offering valuable insights into the dynamic changes in brain function and bimanual coordination at different stages of rehabilitation. Conclusions During BMCG, three activation patterns mainly occur in the brain of a healthy individual. In healthy individuals, there are noticeable differences in brain activation patterns between BMCG and BMIG, with specific brain areas (i.e., the right STC and bilateral S2) showing increased activation. The differences noted between healthy individuals and those with stroke are associated with increased unaffected cortical areas engagement and poor positive neural coupling between the ipsilateral SMA and the ipsilateral M1. Excitatory NIBS may effectively enhance BMCG when applied to the M1 in the affected hemisphere in stroke patients with mild impairment and the PMd in the unaffected hemisphere in stroke patients with severe impairment, whereas stimulation over the contralateral M1 does not induce a positive effect in terms of BMCG in chronic stroke patients with mild to moderate impairment. This review allows researchers and clinicians to understand better the neural bases behind BMCG in daily lives among individuals with health and stroke, whereas how to effectively apply patient-specific NIBS for improving BMCG after stroke needs to be further studied. Abbreviations ADL Activities of daily living BMIG Bilateral movements with an independent goal BMCG Bilateral movements with a common goal SMA Supplementary motor area PMd Dorsal premotor cortex fMRI Functional magnetic resonance imaging DLPFC Dorsal lateral prefrontal cortex NIBS Non-invasive brain stimulation TMS Transcranial magnetic stimulation tDCS Transcranial direct current stimulation IHI Imbalanced interhemispheric inhibition M1 Primary motor cortex EEG Electroencephalography TBS Theta burst stimulation tACS Transcranial alternating current stimulation IPC Interior parietal cortex ITC Inferior temporal cortex SFC Superior frontal cortex MOC Medial occipital cortex S1 Primary somatosensory cortex MFC Medial frontal cortex SPC Superior parietal cortex IFC Inferior frontal cortex IPS Intraparietal sulcus PMv Ventral premotor cortex STC Superior temporal cortex ACC Anterior cingulate cortex MTC Medial temporal cortex OFC Orbitofrontal cortex PFC Prefrontal cortex MCC Middle cingulate cortex PMC Premotor cortex PCC Posterior cingulate cortex FPO Parietal and frontal opercular cortex PFl Lateral prefrontal cortex, PMv Ventral premotor cortex PMd Dorsal premotor cortex Declarations Ethics approval and consent to participate Not Applicable Consent for publication Not Applicable Availability of data and materials The study utilized publicly available datasets, and the findings of the study are detailed in the article and/or supplementary materials. Competing interests The authors have no competing interests to declare that are relevant to the content of this article. Funding This work was supported by the Hong Kong Polytechnic University (grant No. P0042680). Authors' contributions Conceptualization: [KWH, AS, and JYW]; Methodology: [JYW and JQL]; Formal analysis and investigation: [JYW and KWH]; Writing - original draft preparation: [JYW, AS, JJQZ, and KWH]; Writing - review and editing: [KWH and AS]; Funding acquisition: [KWH]; Supervision: [KWH and AS]. Acknowledgements None References Mboi N, Murty Surbakti I, Trihandini I, Elyazar I, Houston Smith K, Bahjuri Ali P et al. On the road to universal health care in Indonesia, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet (London, England). 2018;392(10147):581–91. 10.1016/S0140-6736(18)30595-6 . Feigin VL, Stark BA, Johnson CO, Roth GA, Bisignano C, Abady GG, et al. 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Al-Azhar Med J. 2020;49(2):651–66. Swinnen SP, Gooijers J. Bimanual coordination. Brain mapping: an encyclopedic reference. 2015;2:475 – 82. 10.1016%2Fb978-0-12-397025-1.00030-0. Supplementary Files PRISMAChecklist.docx Supplementarymaterial.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3975753","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":295505239,"identity":"bd0026c7-74fb-436a-a880-ec76ab02ea46","order_by":0,"name":"Jingyi Wu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2klEQVRIiWNgGAWjYBACAxiDXwJMScgQoYWZsQHEkJzBAGJI8BCvxeAGWAsDYS3m7P3HH3xgOJy4+Xbz8Uc3aix4GNgPH92AT4tlz2HGxhlALdvuHEtszjkGdBhPWtoNvA67kczYzMNwO3HbjRzD5hw2oBYJHjP8Wu4/Zmz+A9SyeQZIyz9itNxgZmxmAGrZIAHUkttGhBbLnmTDmT0M/41n3EhLnJ3bJ8HDRsgv5uwHH3z4wZAm2z8j+cDnnG91cvzsh4/h1QIGjP+QOGwElY+CUTAKRsEoIAgA0o1J2v2Eot0AAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0001-7391-7547","institution":"The Hong Kong Polytechnic University","correspondingAuthor":true,"prefix":"","firstName":"Jingyi","middleName":"","lastName":"Wu","suffix":""},{"id":295505240,"identity":"934f55c9-01df-484b-b3e5-1b1de6d3c4d6","order_by":1,"name":"Jiaqi LI","email":"","orcid":"","institution":"The Hong Kong Polytechnic University","correspondingAuthor":false,"prefix":"","firstName":"Jiaqi","middleName":"","lastName":"LI","suffix":""},{"id":295505241,"identity":"5aba0d27-b56e-4007-944e-90bce470ba27","order_by":2,"name":"Patrick Wai-Hang Kwong","email":"","orcid":"https://orcid.org/0000-0002-1834-5715","institution":"The Hong Kong Polytechnic University","correspondingAuthor":false,"prefix":"","firstName":"Patrick","middleName":"Wai-Hang","lastName":"Kwong","suffix":""},{"id":295505242,"identity":"2bf1131d-0d5d-4c06-9a2f-f38f71837772","order_by":3,"name":"Jack Jiaqi Zhang","email":"","orcid":"","institution":"The Hong Kong Polytechnic University","correspondingAuthor":false,"prefix":"","firstName":"Jack","middleName":"Jiaqi","lastName":"Zhang","suffix":""},{"id":295505243,"identity":"dd75afc9-12a0-4e72-a961-9a4db98f1133","order_by":4,"name":"Ananda Sidarta","email":"","orcid":"","institution":"Nanyang Technological University","correspondingAuthor":false,"prefix":"","firstName":"Ananda","middleName":"","lastName":"Sidarta","suffix":""}],"badges":[],"createdAt":"2024-02-21 13:51:29","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3975753/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3975753/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":55769051,"identity":"7d593691-04e6-47c5-94e8-f2a8daf07f79","added_by":"auto","created_at":"2024-05-02 20:40:29","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":227491,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart of the literature search in this review.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-3975753/v1/0566b0e9461a819db63e61e3.png"},{"id":55769056,"identity":"fe1eea05-7c02-4a5e-bb33-a6a30f51d078","added_by":"auto","created_at":"2024-05-02 20:40:30","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":249949,"visible":true,"origin":"","legend":"\u003cp\u003eDendrogram of brain activation patterns underlying BMCG in healthy subjects (a: Familiar BMCG for healthy subjects; b: Unfamiliar BMCG for healthy subjects. Familiarity refers to the subjects seeing the action many times, whereas non-familiarity refers to the action that looks difficult to perform for the subjects.)\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-3975753/v1/b63f12eda5624684142fd02e.png"},{"id":55769052,"identity":"56bca819-610a-4aca-b529-256525ee25ff","added_by":"auto","created_at":"2024-05-02 20:40:29","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":209725,"visible":true,"origin":"","legend":"\u003cp\u003eBrain activation patterns of every cluster during BMCG in healthy subjects (bi: bilateral; IPC: inferior parietal cortex; r: right; IFC: inferior frontal cortex; M1: primary motor cortex; ITC: inferior temporal cortex; l: light; SFC: superior frontal cortex; SPC: superior parietal cortex; S1: posterior central gyrus; IPS: intraparietal sulcus; MOC: medial occipital cortex; MFC: medial frontal cortex; SPC: superior parietal cortex; SMA: supplementary motor area; PMv: ventral premotor cortex; PMd: dorsal premotor cortex; STC: superior temporal cortex; ACC: anterior cingulate cortex; DLPFC: dorsal lateral prefrontal cortex; MTC: medial temporal cortex; OFC: orbitofrontal cortex; PFC: prefrontal cortex; MCC: middle cingulate cortex; PMC: premotor cortex; S2: the secondary somatosensory cortex; PCC: posterior cingulate cortex; PMv: ventral premotor cortex; PMd: dorsal premotor cortex; PFl: lateral prefrontal cortex; FPO: frontal and parietal opercular.)\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-3975753/v1/60e14a1e93a0ca0d4720529a.jpeg"},{"id":65384108,"identity":"7152785f-2048-4600-95bd-51d54c482c09","added_by":"auto","created_at":"2024-09-26 19:01:39","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1253636,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3975753/v1/309ca81a-0833-4aef-9cf7-1cded552b6ff.pdf"},{"id":55769823,"identity":"987248a8-9631-4bac-8fea-3c2ec0566e6e","added_by":"auto","created_at":"2024-05-02 20:48:30","extension":"docx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":58640,"visible":true,"origin":"","legend":"","description":"","filename":"PRISMAChecklist.docx","url":"https://assets-eu.researchsquare.com/files/rs-3975753/v1/1a5582b4dc673f2a58571ac3.docx"},{"id":55769055,"identity":"738b6a3d-b94c-46e5-997e-ee2ec616a1b5","added_by":"auto","created_at":"2024-05-02 20:40:30","extension":"docx","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":511695,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-3975753/v1/0cff95360e3dbe654c8a0021.docx"}],"financialInterests":"","formattedTitle":"Neural Mechanisms underlying Bimanual Coordination in Healthy and Stroke Individuals and Application of Non-Invasive Brain Stimulation: A Scoping Review","fulltext":[{"header":"Background","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eAccording to the 2021 Global Burden of Disease study, stroke is not only a leading cause of the loss of disability-adjusted life years, but also one of the most widespread adult-onset neurological disabilities worldwide [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Among stroke survivors, dysfunction in the upper extremities is the most common complication, which leads to difficulty in completing occupational activities [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePerforming most activities of daily living (ADLs), including playing musical instruments, working with tools, and performing some household chores, considerably depends on the cooperation and coordination of bilateral upper extremities. Patients with coordination deficits in bilateral upper extremities have increased difficulty in performing certain ADLs [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Most relevant studies focused on the affected limbs, with the aim of promoting independence in ADLs through the improvement of motor function in the hemiplegic limb [\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. However, functional bilateral abilities are not as simple but involve a combination of one-handed motor skills. Exploring unilateral dysfunction alone cannot aid in determining the extent of bilateral upper-limb deficits. Similarly, resolving upper-limb impairment does not engender improvements in bilateral cooperative movement [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Therefore, exploring changes in neural activities underlying the bilateral upper-limb coordination in patients with stroke is warranted.\u003c/p\u003e \u003cp\u003eUpper-limb bimanual coordination involves an interrelationship between the spatial and temporal domains for accomplishing a clear goal (i.e., common goal and independent goal). On the basis of the spatiotemporal feature, theoretically based classes of bilateral coordination can be obtained; for example, bilateral upper-limb movements can be either symmetric and asymmetric driven by either a common goal or an independent goal [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. The main characteristics of symmetric movements are temporal and spatial coupling and the simultaneous engagement of homologous muscles. In contrast, asymmetric movements are mainly characterized by different relative phases of movement and spatial uncoupling. According to the theory of egocentric and allocentric constraints, asymmetrical movements are less accurate and stable than symmetrical movements [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. In a psychophysical experiment in healthy adults, as the anti-phase movement frequency increases the tendency towards symmetrical movements becomes stronger, leading to the eventual transition of movements from being anti-phase to being in-phase [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. The way in which a person perceives the goal of a specific task (i.e., independent or common) can also affect bimanual coordination, particularly in terms of determining bimanual movements of the upper limbs [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. According to task characteristics, bimanual movements can be divided into two categories: bilateral movements with an independent goal (BMIG) and bilateral movements with a common goal (BMCG). Each category can be further divided into two classes, and they are the symmetric independent goal (e.g., reaching forward to grab two different objects) and asymmetric independent goal (e.g. using one hand to draw a circle and the other to draw a line); symmetric common goal (e.g. reaching forward to grasp the same object) and asymmetric common goal (e.g. opening a bottle cap; folding a towel or clothes) [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Importantly, ADLs completed using bilateral upper limbs typically involve either a symmetric or an asymmetric common goal.\u003c/p\u003e \u003cp\u003eMany studies explored the relevant kinematic and neural mechanisms underlying deficits in bimanual coordination in patients with stroke, with the aim of improving independence in ADL. Some studies investigated the distinction in neural mechanisms during unilateral movement versus bilateral movement, and the findings revealed that bimanual activities exhibited heightened interhemispheric interactions compared to unilateral movement [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Kim et al. reviewed 17 studies, including a total of 103 patients with stroke and 90 healthy individuals [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The authors concluded that the patients performing both symmetric and asymmetric BMCG appeared to have major coordination deficits in the kinematic and kinetic domains. However, during symmetrical BMIG, no considerable impairment in coordination was observed in the patients compared with healthy individuals. Moreover, patients with stroke demonstrated a longer pickup time while reaching for a box using both hands than healthy individuals. During an asymmetric task, where one hand is used to open the drawer and the other presses the button, patients demonstrated a longer delay than control individuals [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Another review suggested that an extended cortical network, including the sensorimotor cortex, supplementary motor area (SMA), cingulate cortex, dorsal premotor cortex (PMd), and posterior parietal cortex, is involved in normal bilateral movements [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. De Oliveira et al. proposed a classical bilateral movement model of three theories: generalized motor program, intermanual crosstalk model, and dynamic systems approach to explain and attempt to predict the neural basis of in-phase and anti-phase bimanual behavior [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Subsequent clinical trials have confirmed the presence of changes in neural activities [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. A functional magnetic resonance imaging (fMRI)-based study reported higher activation of the right dorsal lateral prefrontal cortex (DLPFC) during temporal uncoupling movements than during symmetrical movements [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Van Dun et al. used activation likelihood estimation to quantify and synthetically analysed the differences between all in-phase, anti-phase, and out-of-phase bilateral movements; they found that the anterior cerebellar vermis played a vital role during anti-phase and out-of-phase movements, whereas the posterior cerebellar vermis played a vital role during out-of-phase movements [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. The extent and areas of activation during BMCG were partly determined based on the differences in the motor and task characteristics. However, no studies reviewed the neural mechanism of BMCG in healthy individuals and stroke patients.\u003c/p\u003e \u003cp\u003eNon-invasive brain stimulation (NIBS) is a modern technique for stroke rehabilitation in which abnormal brain activity is increased or reduced for physical function improvement. In general, NIBS comprises transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS) [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Regarding unilateral motor impairment, decreased excitability of the impaired hemisphere and imbalanced interhemispheric inhibition (IHI) after stroke are the main reasons underlying poor motor function recovery [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. The disturbed neural network involving PMC and cerebellum and disturbed interhemispheric interaction between SMA and M1 were the primary reasons for poor recovery in bimanual coordination compared to unilateral movement [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. When applied to the ipsilesional primary motor cortex (M1), high-frequency repetitive TMS (rTMS) could effectively enhance the motor function recovery of the paretic upper limbs. Still, whether it leads to any improvement in bimanual coordination through acting in motor-related areas is unclear [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. The development of novel brain modulation techniques aimed at improving bimanual coordination and filling the gap between impaired neurological assessment and advanced training of coordinated bilateral movements is ongoing.\u003c/p\u003e \u003cp\u003eRecent neuroimaging experiments have clarified neural activity changes underlying BMCG in healthy individuals and patients with stroke. Moreover, many studies used advanced NIBS to enhance bimanual coordination (i.e., BMIG and BMCG). However, most of these studies are limited by a small sample size; furthermore, high variability has been noted across different studies. Therefore, a scoping review with a qualitative synthesis of the literature on BMCG\u0026ndash;related neural activity in healthy and stroke patients and the effects of NIBS on BMCG improvement is warranted. In the current scoping review, we thus carry three main objectives. First, we identify the brain areas consistently activated during BMCG in healthy individuals, compared to BMIG and rest. Second, we investigate differences in brain activity between patients with stroke and healthy individuals during BMCG. Third, we provide a comprehensive summary of advanced NIBS applied in both neurologically intact individuals and patients with stroke for the improvement of their BMCG.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThis review was carried out by conforming to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e] and was already registered on Inplasy.com (INPLASY202350080).\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eDatabase Search\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eWe searched PubMed, Embase, Medline via EBSCO, and Web of Science databases for relevant articles published from inception until 1 February 2023. We used the following search terms: stroke, CVA, hemiplegia, cerebrovascular accidents, cerebrovascular disorder, paresis, healthy individuals, healthy participants, healthy subjects, normal volunteer, bilateral coordination, bimanual coordination, cooperative, bimanual cooperative, coordination, symmetric, asymmetric, out-of-phase, upper limb, upper extremities, upper limbs, upper extremity, hand, hands; functional imaging, fMRI, functional magnetic resonance imaging, brain imaging, MRI, EEG, electromyography, near-infrared spectrometry, NIRS, TMS, and transcranial magnetic stimulation. Our search strategy is detailed in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eStudy Selection Criteria\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eAccording to the PICOS principle, we included studies on neural changes that met the following criteria: studies that recruited adult participants diagnosed as having a stroke, healthy individuals, or both [population (P)]; studies that compared BMCG with other types of movement [intervention (I)]; and studies that described at least one outcome assessing upper-limb neural functions, such as TMS-EMG, electroencephalography (EEG), and fMRI [outcomes (O)]. We excluded studies that (1) recruited patients with primary neurological diseases other than stroke; (2) were published in dissertations or books or as conference abstracts without access to their full papers; (3) included only symmetric and asymmetric BMIG; (4) focused on infants, children, or adolescents; and (5) were not published in the English language.\u003c/p\u003e \u003cp\u003eAmong all articles on neural mechanisms of bimanual coordination, we selected studies on NIBS aimed at enhancing BMCG according to the PICOS principle. Specifically, we included studies on NIBS that met the following inclusion criteria: studies that recruited adult participants diagnosed as having stroke, healthy subjects, or both (P) and those that employed NIBS or experimental paradigms such as rTMS, theta burst stimulation (TBS), tDCS, and transcranial alternating current stimulation (tACS) to improve BMCG (I). However, we excluded studies that (1) did not employ NIBS to promote BMCG; (2) recruited patients without a diagnosis of stroke or included infants, children, and adolescents; (4) were published as research protocols, conference proceedings, or conference abstracts; and (5) were not published in the English language.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eData Extraction\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eAfter identifying relevant studies, two authors (JYW and JQL) independently extracted the following information from each article: (1) the first author and publication year; (2) patient characteristics (i.e., age, time since stroke onset, and initial impairment level) and the characteristics of healthy individuals (i.e., age and handedness); (3) the NIBS used for both the groups, including the intervention type and duration and measurement details; (4) the modalities used for functional neuroimaging, EEG, or both; and (5) the outcome data, including brain activation and functional connectivity. Any disagreements between the two authors were resolved through discussion with the third author (WHK).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eOutcome Measurement Assessment\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eBMCG and BMIG induced differential activation patterns in each brain region as measured by fMRI in separate brain regions of interest or the whole brain. Functional connectivity is evaluated using the task-based fMRI. This method tests how different brain regions interact during a specific task. EEG is another technique to measure the change of inter/intra-cortical connectivity through electrodes covering interested brain areas.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eActivation Pattern Identification\u003c/h2\u003e \u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eAll statistical analyses were performed using SPSS 26.0 (SPSS Inc., Chicago, USA). We used hierarchical clustering analysis with Ward\u0026rsquo;s model to classify BMCG into different groups according to the specific activated brain regions in each study. To discover the specific brain activation patterns during BMCG, we used K-means clustering\u0026mdash;an unsupervised machine learning algorithm\u0026mdash;with the number of groups as the K value (i.e., the number of clusters). The algorithm first assigned data points to random groups and then estimated the group centres. The studies were iteratively grouped according to the distance between each data point and the group centres; this was repeated until no change occurred in the grouped studies from the previous iteration. Finally, one-way analysis of variance (ANOVA) was used to compare differences in activation patterns among the clusters.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eStudy Characteristics\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eIn the initial search, we retrieved 2735 articles. We then removed duplicates and screened the remaining 1875 articles. Out of these articles, we excluded 1782 articles because they were irrelevant (n\u0026thinsp;=\u0026thinsp;1765), reviews or meta-analyses (n\u0026thinsp;=\u0026thinsp;10), or conference abstracts (n\u0026thinsp;=\u0026thinsp;7). Next, we screened the full text of the remaining 93 articles. Out of these, 78 articles were excluded for the following reasons: they did not employ fMRI in healthy individuals or fMRI or electroencephalography (EEG) for comparing outcomes between patients with stroke and healthy individuals (n\u0026thinsp;=\u0026thinsp;17), they used unclear experimental designs in terms of whether BMCG (n\u0026thinsp;=\u0026thinsp;56) were involved, they reported improved bimanual coordination without the use of NIBS (n\u0026thinsp;=\u0026thinsp;5). Finally, this scoping review included 15 studies. Out of these, nine studies aimed at the neurological mechanism of BMCG involving 144 healthy individuals and 24 patients with stroke and seven studies aimed at the effect of NIBS involving 184 and 31 healthy and stroke population. One study either reported neurological mechanism of BMCG and the effect of NIBS on BMCG. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e illustrates our study selection flowchart.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eBrain Activation Patterns in Healthy Individuals\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eAfter they were subjected to hierarchical cluster analysis using Ward\u0026rsquo;s method, five studies (six units) were found to report brain activities associated with BMCG [\u003cspan additionalcitationids=\"CR33 CR34 CR35\" citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. On the basis of the different activated brain regions, the brain activation patterns underlying BMCG could be divided into three clusters. The resulting dendrogram presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e provides the clusters that reflect the three brain activation patterns. The results of the K-means cluster analysis of these studies corroborated those of the hierarchical cluster analysis (Table I). The \u0026lsquo;familiar\u0026rsquo; and \u0026lsquo;unfamiliar\u0026rsquo; BMCG-related neural activities were reported in healthy adults using an imitation task paradigm of familiar and unfamiliar actions.\u003c/p\u003e \u003cp\u003eThe specific brain activation patterns of the three clusters are presented in Figure. 3. Cluster I [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e] pertained to the brain activation pattern underlying BMCG in healthy individuals, which comprised the bilateral interior parietal cortex (IPC), M1, inferior temporal cortex (ITC), superior frontal cortex (SFC), cerebellum, medial occipital cortex (MOC), the primary somatosensory cortex (S1), medial frontal cortex (MFC), superior parietal cortex (SPC), right inferior frontal cortex (IFC), intraparietal sulcus (IPS), precuneus, ventral premotor cortex (PMv), superior temporal cortex (STC), anterior cingulate cortex (ACC), DLPFC, medial temporal cortex (MTC), orbitofrontal cortex (OFC), and angular gyrus, left PMd and basal ganglia (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003ea). Cluster II [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e] pertained to the brain activation patterns for the imitation of familiar movements involving the bilateral wrists and hands, which included the medial prefrontal cortex (PFC) and cerebellum in the right hemisphere and the SFC, middle cingulate cortex (MCC), angular gyrus, and precuneus in the left hemisphere, bilateral STC, S1, and cuneus (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eb). Cluster III [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] mainly reflected the brain activation pattern for BMCG with wrist joint, which comprised the bilateral cerebellum, M1, S1, SMA, premotor cortex (PMC), thalamus, the secondary somatosensory cortex (S2), ACC, posterior cingulate cortex (PCC), basal ganglia, cuneus, parietal and frontal opercular cortex (FPO), supramarginal gyrus, lateral PFC (PFl), ventral PMC (PMv) and dorsal PMC (PMd), the right MTC, and left insular cortex (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003ec). Differences among the activation patterns were found to be significant (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eK-means cluster analysis distribution\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCluster\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDistance\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKoeneke 2004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHanawa 2016a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHanawa 2016b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.449\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDietz 2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.803\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuque 2010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.449\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePuttemans 2005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.803\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003ea: Familiar BMCG for healthy subjects; b: Unfamiliar BMCG for healthy subjects. Familiarity refers to the subjects seeing the action many times, whereas non-familiarity refers to the action that looks difficult to perform for the subjects.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eMajor Differences of Brain Activation Between BMCG and BMIG in Healthy Individuals\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eFour studies have investigated differences in brain activation between BMCG and BMIG in healthy individuals [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Specifically, Duque et al. and Ullen et al. used fMRI to investigate the differences in brain activation between bilateral hand movements with a given speed ratio and bilateral hand movements without a given speed ratio [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. The findings of the former demonstrated that BMCG involves a greater activation in the right SMA, M1, and STC than BMIG. In contrast, the latter indicated that BMCG has a greater activation in bilateral STC, right IPS, and middle preSMA. Another two studies comparing bilateral wrist movement with simulating open-and-close bottles and bilateral wrist pro-and supination movement indicate that bilateral S2 are sensitive to BMCG [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. In addition, one of the two studies, bilateral S1, left insular cortex, cerebellum, and right posterior thalamus may also be responsible for BMCG, as activity in these areas significantly increases during BMCG than BMIG [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eMajor Differences of Brain Activation of BMCG Between Patients with Stroke and Healthy Individuals\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eTwo studies reported differences in activated brain areas and functional connectivity (FC) between healthy individuals and patients with stroke [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Schrafl-Altermatt et al. [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e] found that when the affected arm was stimulated during BMCG, the somatosensory evoked potential amplitude ratio was higher (indicating more contralateral hemisphere involvement) in patients with stroke (1.23\u0026thinsp;\u0026plusmn;\u0026thinsp;028) than in healthy individuals (0.99\u0026thinsp;\u0026plusmn;\u0026thinsp;0.44). Grefkes et al. [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e] demonstrated that healthy individuals had significantly increased inhibitory of FC among the bilateral M1, PMC, and SMA and positive interaction within the hemisphere. In contrast, stroke patients showed reduced positive neural coupling between the ipsilateral SMA and ipsilateral M1 and decreased inhibitory FC between bilateral SMA and between contralateral SMA and ipsilateral M1 than healthy individuals. Finally, impairments in BMCG in patients with stroke were associated with low coupling strength from the ipsilateral SMA to the ipsilateral M1 (Pearson\u0026rsquo;s r\u0026thinsp;=\u0026thinsp;0.62, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Tables S2 present the characteristics of all included studies on neural changes.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eNon-Invasive Brain Stimulation in Healthy Individuals Targeting the BMCG\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eFive studies reported the effects of NIBS on BMCG in healthy individuals. In particular, anodal tDCS (1.5 mA, for 15-min stimulation) on the cerebellum when performing two-hand coordinated movements improved skill acquisition (i.e., error time reduction); by contrast, the consolidation of adapting learning of tasks (off-line learning) was enhanced when tDCS (1.5 mA, for 15-min stimulation) was administered before the performance of two-hand coordinated movements [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. A study by Duque et al. found significantly increased hand error in BMCG in healthy individuals after virtual lesion over the right STC inducing by 18 min of 10-Hz rTMS trains compared with no train [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. In addition, 10-Hz TMS applied over the left PMd (110% rest motor threshold, 5 pulses) enhanced bilateral hand motor speed and accuracy during BMCG [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. However, in-phase or out-of-phase beta-tACS (2 mA, for 20-min stimulation) or sham tACS over the bilateral M1 led to no learning-related changes [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Similarly, 10-Hz and 20-Hz tACS (1 mA, for 20-min stimulation) and sham tACS over the left IPC did not result in differences in bimanual coordination improvement [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. Table S3 present the characteristics of all included studies on NIBS.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eNon-Invasive Brain Stimulation in Patients with Stroke targeting the BMCG\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eTwo studies reported the effects of NIBS on BMCG in stroke patients. Compared with sham stimulation, anodal tDCS (1 mA, for 30-min conditioning) over the cM1 did not lead to enhancement in bimanual motor skill learning and generalization (i.e. applying learned motor skills to other tasks) in chronic stroke patients with mild and moderate impairment [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. In addition, 5-Hz rTMS (70% of active motor threshold, 1200 pulses) over the cPMd or iM1 led to enhanced two-arm temporal coordination: stimulation over the iM1 increased bimanual coordination in patients with mild impairment and strong IHI from the contralateral to the ipsilateral M1, and stimulation over the cPMd increased bimanual coordination in those with severe impairment and weak IHI [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe review concluded that a general bimanual network was activated when healthy subjects underwent different types of BMCG, which consisted of the bilateral M1, SMA, cerebellum, and S1. Secondly, previous studies showed that increased unimpaired hemisphere involvement and decreased positive neural coupling between the ipsilateral SMA and the ipsilateral M1 were the major differences in neural patterns between patients with stroke and healthy individuals who performed BMCG. Thirdly, excitatory NIBS applied over the left PMd and the bilateral cerebellum led to a positive influence on BMCG in healthy individuals, whereas applied over the bilateral M1 and the left IPC, they did not induce a positive effect on BMCG in healthy subjects. Finally, stroke patients with mild impairment benefited from excitatory stimulation of the ipsilateral M1, and those with severe impairment benefited from stimulation of the contralateral PMd in terms of improvement in BMIG. In contrast, chronic stroke patients with mild to moderate impairment did not benefit from excitatory stimulation of the contralateral M1 in terms of improvement in BMCG.\u003c/p\u003e \u003cp\u003eRegarding the findings of the general bimanual network, a study examining the effects of NIBS on healthy individuals to improve BMCG showed that excitatory stimulation over the cerebellum resulted in positive changes in bimanual coordination [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. This aligns with our findings that all patterns activate the cerebellum during BMCG (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), suggesting that the anterior and posterior cerebellar vermis are involved in spatial and temporal control during complex bimanual tasks. Additionally, Dietz et al. identified a neural network related to BMCG, primarily involving bilateral M1, SMA, and cerebellum [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. However, our results indicate significant extra-activation on the bilateral S1 compared to Dietz et al.\u0026rsquo;s findings [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. More precisely, sensory information, such as proprioceptive and cutaneous sensory input, predominantly contributes to motor learning and control. Moreover, functional goal-oriented tasks (i.e., reaching out and grasping a ball) elicit higher activation in S1 than non-functional movements [\u003cspan additionalcitationids=\"CR48\" citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. This implies that bilateral S1 plays a pivotal role in BMCG, especially in activities demanding purposeful movements and the integration of sensory input to enhance coordinated actions involving both upper limbs or hands.\u003c/p\u003e \u003cp\u003eOur hierarchical cluster analysis revealed three distinct activation patterns within the brain regions when various BMCG tasks were performed. Notably, Cluster I was only associated with the execution of an object manipulation task performed while participants observed a computer screen. Object manipulation necessitates intricate fine motor control and the concurrent operation of two sensory systems\u0026mdash;namely, proprioception and somatic sensation. Signals originating from tactile and proprioceptive fibers, which innervate the skin and muscles of the hand, are conveyed to the S1 through the ventro-postero-lateral nucleus of the thalamus and the cuneate nucleus in the brainstem. [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. This observation is consistent with our results that the IPC in the bilateral hemispheres was more significantly activated in Cluster I than in Cluster II. In addition, visual information regarding the cursor\u0026rsquo;s location helped foster a proper motion plan. Specialised circuits in the primary visual cortex located in the occipital lobe can aid in achieving this visuomotor transformation through the posterior parietal cortex, PMd, and PMv. Therefore, our results indicated that the BMCG in Cluster I led to the significant activation of the bilateral MOC, right PMv, and left PMd compared to Cluster II and III [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe complexity of BMCG varied between Clusters II and III, specifically in terms of relative phase, temporal aspects (relative interlimb frequency), and spatial elements (direction and amplitude). In contrast to the tasks in Cluster II, those in Cluster III exhibited increased complexity across all these domains. Two studies investigating age-related changes in the brain highlighted that complex bimanual motor tasks led to heightened activities in the PFC and primary M1 in both hemispheres [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. Debaere et al. proposed a positive association between spatiotemporal complexity of bilateral movements and activation in the SPC, SMA, and thalamus in both hemispheres. Additionally, they suggested that the movement frequency of bimanual tasks were positively associated mainly with activities in the bilateral CMC, PMC, and thalamus [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. This partly aligns with our findings that complex bilateral movements activate the bilateral M1, PMC, thalamus, CMC, and PFC (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.). However, in contrast to the findings of Debaere et al., our results demonstrated that the bimanual movements of different complexities led to significant activation of the bilateral SMA. Notably, augmented activities in the SPC in the bilateral hemispheres were observed during relatively simple bilateral tasks but not during relatively complex bilateral tasks; this outcome may be related to the neural mechanism of imitation [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe primary distinction between Cluster II and Clusters I and III lies in the level of familiarity that healthy subjects have with BMCG. Specifically, when healthy participants were learning a new bilateral task, bilateral M1 and SMA exhibited the most pronounced activation and the most extensive network of functional connectivity [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. In addition, some studies indicated that the cerebellum plays a crucial role in the motor learning network by facilitating SMA to M1 communication, which means that the communication between the cerebellum and motor cortical areas is vital for motor learning [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. These findings support our discovery of a cortical-striato-cerebellar network involved in motor learning, specifically bilateral M1, SMA, and the left cerebellum, which undergoes modulation changes when healthy individuals attempt an innovative bilateral task. However, we also observed increased activation in the right MTC when healthy individuals performed a novel BMCG task, which may be associated with the neural mechanisms underlying explicit and implicit motor learning processes. Previous research has shown that improved activation in the MTC is associated with increased cognitive demand during the learning and execution of new tasks [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe key contrast observed between BMCG and BMIG in healthy individuals during a hand activity with a specific speed ratio was the enhanced activation in the right STC. Specifically, when engaging in a hand activity with a given fixed rhythm, there were generally greater demands in spatial and temporal aspects compared to activities without rhythm. Previous studies have highlighted the dominant role of the right hemisphere for spatial representation and attention, particularly in the STC [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. Heightened activation of the right STC may contribute to the proficient execution of BMCG by enabling constant monitoring of the spatial positions of both hands in healthy individuals. Our observation aligns with a study on the impact of NIBS, supporting the notion that stimulating the right STC actively enhances bimanual coordination performance, thereby promoting awareness of the spatial locations of both hands [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. When examining task-oriented activities, it became evident that the disparity between BMCG and BMIG in healthy individuals resulted in excessive activation of bilateral S2. This can be attributed to the fact that S2 is responsible for merging sensory input from both hands, an essential requirement for coordinating movements between the two sides during cooperative actions rather than non-cooperative ones [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. Interestingly, our findings are in agreement with the research conducted by Michels et al., which also revealed similar outcomes, indicating that younger individuals exhibit heightened activation in bilateral S2 when performing task-specific BMCG as opposed to BMIG [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e]. These findings support our assertion that bilateral S2 is critical in task-based BMCG in healthy individuals.\u003c/p\u003e \u003cp\u003eThe primary neural distinctions observed between stroke patients and healthy individuals performing BMCG included heightened engagement of the unaffected hemisphere and reduced positive neural connectivity between the ipsilateral SMA and the ipsilateral M1. Neural coupling during BMCG is achieved through the exchange of information from each hand to both the hemispheres through the corpus callosum while producing effective FC between specific sensorimotor areas, resulting in the appropriate control of bimanual coordination [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Compared with healthy individuals, stroke patients who received nerve stimulation of the affected hand when performing BMCG demonstrated increased engagement of the unaffected hemisphere, which may involve S2 activation. The S2 acts as an integration area for sensory input from the right hand, left hand, or both hands, and it is significantly activated after stimulation [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e]. In addition, the bilateral S2 is more activated in BMCG (i.e., bottle opening and closing) than in non-cooperative movements [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e]. In other words, increased bilateral S2 activation aids in performing BMCG in patients with stroke compared with that in healthy individuals. Another finding of this review is that an imbalance in inter-hemispheric inhibition arises from diminished neural coupling between the ipsilateral M1 and the contralateral SMA and between bilateral SMA, disrupting the neural functions and leading to their overactivation. Balanced interhemispheric coupling is crucial for the coordination of bilateral patterns [\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e]. This imbalance in inter-hemispheric inhibition results in impaired coordination. In addition, underactivation in ipsilateral M1 induced by decreased positive neural coupling between ipsilateral M1 and ipsilateral SMA that negatively affected BMCG in stroke patients closely aligned with our results of excitatory NIBS applied over the ipsilateral M1 improved BMCG in stroke patients with mild impairment.\u003c/p\u003e \u003cp\u003eWe observed differences among the effects of NIBS on healthy individuals for improving BMCG. This difference was due to the distinction in the stimulation sites, outcome measures, and ceiling effect among the included studies. First, excitatory stimulation over the cerebellum induced positive change in bimanual coordination because the anterior and posterior cerebellar vermis perform spatial and temporal control during complex bimanual tasks [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]; this is consistent with our result that all types of activation patterns activate the cerebellum during BMCG. Moreover, virtual lesions over the right STC disrupted bimanual coordination performance because the right STC is mainly responsible for spatial awareness and exploration associated with both object- and spatial-related information, which aid in fostering the spatial location of the two hands [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. Second, compared with sham stimulation, excitatory stimulation over the bilateral M1 did not trigger a positive effect in terms of bilateral task performance (i.e., error rate and movement time). This may have been due to the stimulation frequency used; specifically, beta may not be the optimal stimulation frequency for motor learning compared with the other frequencies (e.g., gamma and alpha) [\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e]. This may be due to beta-tACS increasing beta in the M1 by entrain endogenous beta rhythms and causing cortical reorganisation associated with motor learning. Third, healthy individuals aged 18\u0026ndash;30 years have great bimanual coordination, which may have led to a ceiling effect (where the effects of 10- and 20-Hz tACS were indistinguishable), leaving only little room for significant enhancement after tACS. Similar findings were found in some other studies on healthy individuals [\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe effects of NIBS applied in the M1 for improving BMCG are highly dependent on the impairment levels of patients with stroke. This is consistent with the bimodal recovery model - mild impairment needs a re-establishment of IHI, while severe impairment needs contralesional compensation [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. Specifically, stimulation over the M1 on the impaired hemisphere than on the unimpaired hemisphere led to significant improvement in bimanual coordination in stroke patients with mild impairment. This is because, compared with other impairment levels, stimulation over the ipsilateral M1 leads to a great response, which is positively associated with motor recovery [\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e], which is also consistent with our findings that reduced positive neural coupling between ipsilateral M1 and ipsilateral SMA was observed when performed BMCG in stroke patients compared with healthy individuals (Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e). However, stroke patients with severe impairment did not benefit from simulation over the ipsilateral M1 because strong transcallosal inhibition from the unaffected hemisphere to the affected hemisphere reduced patient response to NIBS [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. They may benefit from stimulation over the contralateral PMd. This is because the contralateral PMd compensatorily supports the general motor functions in severe stroke patients and can trigger more facilitatory and less inhibitory effects on the ipsilateral M1 than in those with other impairment levels [\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e, \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e]. Thus, we guess the improvement of BMCG in stroke is because of the improvement of general motor impairment rather than a specific effect on BMCG. The difference in effect between individuals with healthy and stroke also supports this statement that excitatory stimulation over the M1 is ineffective, whereas, over the PMC and cerebellum, it is effective in healthy individuals.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThis review has some limitations. The quantitative outcomes and changes in neural activities during BMCG in healthy individuals and patients with stroke still need to be clarified due to the limited number and the heterogeneity of the included studies on outcome measurement. Thus, a meta-analysis of neuroimaging data has not been performed, and the result cannot be generalized to the whole population. Potential factors, such as differences in measurement methods, targeted areas, and definitions of bimanual coordination tasks, among the included studies rendered the detection of the brain areas involved in bimanual coordination in patients with stroke difficult. Studies identifying differences in brain activation between patients with stroke and healthy individuals during BMCG targeting the whole brain, and not only areas of interest (e.g., bilateral M1), are warranted. Furthermore, both internal and external factors influence bimanual coordination performance. However, our review primarily focuses on external factors, precisely task complexity, while internal factors, including age, gender, and inherent motor skills, remain to be thoroughly investigated [\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eFuture research\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThis study is intended to serve as a foundation for future research, pinpointing potential areas for the application of NIBS for improving the BMCG in stroke patients. It is proposed that future research can concentrate on cerebellum, STC, premotor, and ITC.\u003c/p\u003e \u003cp\u003eAlthough NIBS has shown potential in enhancing BMCG in stroke patients through its influence on neural plasticity and brain regions, the existing findings are still insufficient. Further investigation is needed to understand how neural activation patterns during BMCG evolve over time in post-stroke recovery. This could be achieved through a series of longitudinal studies, offering valuable insights into the dynamic changes in brain function and bimanual coordination at different stages of rehabilitation.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eDuring BMCG, three activation patterns mainly occur in the brain of a healthy individual. In healthy individuals, there are noticeable differences in brain activation patterns between BMCG and BMIG, with specific brain areas (i.e., the right STC and bilateral S2) showing increased activation. The differences noted between healthy individuals and those with stroke are associated with increased unaffected cortical areas engagement and poor positive neural coupling between the ipsilateral SMA and the ipsilateral M1. Excitatory NIBS may effectively enhance BMCG when applied to the M1 in the affected hemisphere in stroke patients with mild impairment and the PMd in the unaffected hemisphere in stroke patients with severe impairment, whereas stimulation over the contralateral M1 does not induce a positive effect in terms of BMCG in chronic stroke patients with mild to moderate impairment. This review allows researchers and clinicians to understand better the neural bases behind BMCG in daily lives among individuals with health and stroke, whereas how to effectively apply patient-specific NIBS for improving BMCG after stroke needs to be further studied.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eADL \u0026nbsp;Activities of daily living\u003c/p\u003e\n\u003cp\u003eBMIG \u0026nbsp;Bilateral movements with an independent goal\u003c/p\u003e\n\u003cp\u003eBMCG \u0026nbsp;Bilateral movements with a common goal\u003c/p\u003e\n\u003cp\u003eSMA \u0026nbsp;Supplementary motor area\u003c/p\u003e\n\u003cp\u003ePMd \u0026nbsp;Dorsal premotor cortex\u003c/p\u003e\n\u003cp\u003efMRI \u0026nbsp;Functional magnetic resonance imaging\u003c/p\u003e\n\u003cp\u003eDLPFC \u0026nbsp;Dorsal lateral prefrontal cortex\u003c/p\u003e\n\u003cp\u003eNIBS \u0026nbsp;Non-invasive brain stimulation\u003c/p\u003e\n\u003cp\u003eTMS \u0026nbsp;Transcranial magnetic stimulation\u003c/p\u003e\n\u003cp\u003etDCS \u0026nbsp;Transcranial direct current stimulation\u003c/p\u003e\n\u003cp\u003eIHI \u0026nbsp;Imbalanced interhemispheric inhibition\u003c/p\u003e\n\u003cp\u003eM1 \u0026nbsp;Primary motor cortex\u003c/p\u003e\n\u003cp\u003eEEG \u0026nbsp;Electroencephalography\u003c/p\u003e\n\u003cp\u003eTBS \u0026nbsp;Theta burst stimulation\u003c/p\u003e\n\u003cp\u003etACS \u0026nbsp;Transcranial alternating current stimulation\u003c/p\u003e\n\u003cp\u003eIPC \u0026nbsp;Interior parietal cortex\u003c/p\u003e\n\u003cp\u003eITC \u0026nbsp;Inferior temporal cortex\u003c/p\u003e\n\u003cp\u003eSFC \u0026nbsp;Superior frontal cortex\u003c/p\u003e\n\u003cp\u003eMOC \u0026nbsp;Medial occipital cortex\u003c/p\u003e\n\u003cp\u003eS1 \u0026nbsp;Primary somatosensory cortex\u003c/p\u003e\n\u003cp\u003eMFC \u0026nbsp;Medial frontal cortex\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSPC \u0026nbsp;Superior parietal cortex\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIFC \u0026nbsp;Inferior frontal cortex\u003c/p\u003e\n\u003cp\u003eIPS \u0026nbsp;Intraparietal sulcus\u003c/p\u003e\n\u003cp\u003ePMv \u0026nbsp;Ventral premotor cortex\u003c/p\u003e\n\u003cp\u003eSTC \u0026nbsp;Superior temporal cortex\u003c/p\u003e\n\u003cp\u003eACC \u0026nbsp;Anterior cingulate cortex\u003c/p\u003e\n\u003cp\u003eMTC \u0026nbsp;Medial temporal cortex\u003c/p\u003e\n\u003cp\u003eOFC \u0026nbsp;Orbitofrontal cortex\u003c/p\u003e\n\u003cp\u003ePFC \u0026nbsp;Prefrontal cortex\u003c/p\u003e\n\u003cp\u003eMCC \u0026nbsp;Middle cingulate cortex\u003c/p\u003e\n\u003cp\u003ePMC \u0026nbsp;Premotor cortex\u003c/p\u003e\n\u003cp\u003ePCC \u0026nbsp;Posterior cingulate cortex\u003c/p\u003e\n\u003cp\u003eFPO \u0026nbsp;Parietal and frontal opercular cortex\u003c/p\u003e\n\u003cp\u003ePFl \u0026nbsp;Lateral\u0026nbsp;prefrontal cortex,\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePMv \u0026nbsp;Ventral\u0026nbsp;premotor cortex\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePMd \u0026nbsp;Dorsal premotor cortex\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot Applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot Applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study utilized publicly available datasets, and the findings of the study are detailed in the article and/or supplementary materials.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no competing interests to declare that are relevant to the content of this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Hong Kong Polytechnic University (grant No. P0042680).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization: [KWH, AS, and JYW]; Methodology: [JYW and JQL]; Formal analysis and investigation: [JYW and KWH]; Writing - original draft preparation: [JYW, AS, JJQZ, and KWH]; Writing - review and editing: [KWH and AS]; Funding acquisition: [KWH]; Supervision: [KWH and AS].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMboi N, Murty Surbakti I, Trihandini I, Elyazar I, Houston Smith K, Bahjuri Ali P et al. 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Brain mapping: an encyclopedic reference. 2015;2:475\u0026thinsp;\u0026ndash;\u0026thinsp;82. 10.1016%2Fb978-0-12-397025-1.00030-0.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Hand, Motor Skills Disorders, Neurovascular Coupling, Physical Functional Performance, Stroke, Non-invasive brain stimulation","lastPublishedDoi":"10.21203/rs.3.rs-3975753/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3975753/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003ePost-stroke dysfunction in bimanual coordination causes decreased independence in activities of daily living. Past studies and reviews have reported the neural mechanisms underlying bilateral movements with an independent goal (BMIG) in healthy adults; however, those underlying bilateral movements with a common goal (BMCG) remain unclear. The purpose of this study is twofold: to review the neural mechanisms underlying upper-limb BMCG in healthy and stroke individuals, compared with BMIG and rest, and to determine the effects of non-invasive brain stimulation (NIBS) on improving BMCG in healthy and stroke individuals.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe conducted a literature search in the PubMed, Embase, Medline vis EBSCO, and Web of Science databases. Two authors independently screened the studies, extracted data, and qualitatively synthesized the studies.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eFifteen studies were included. Of these studies, nine focused on brain activation underlying BMCG, and seven focused on the effects of NIBS on BMCG. In healthy individuals, three brain activation patterns underlying different BMCGs were identified. When healthy individuals performed BMCG and BMIG, the main differences observed were increased activation in the right superior temporal cortex and bilateral secondary somatosensory cortex. Compared with healthy controls, stroke patients demonstrated increased involvement of the unaffected cortical areas and decreased positive neural coupling between the primary motor cortex (M1) and supplementary motor area in the affected hemisphere during BMCG. Excitatory stimulation applied over the ipsilateral M1 and the contralateral dorsal premotor cortex may improve the performance of BMCG in stroke patients with mild and severe impairments, respectively.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eStroke patients may be compensatorily recruited with more brain areas to execute the BMCG tasks compared to healthy individuals. The improvement of BMCG in stroke is because of the improvement of general motor impairment rather than a specific effect on BMCG.\u003c/p\u003e\u003ch2\u003eSystematic Review Registration\u003c/h2\u003e \u003cp\u003eThis review was registered on Inplasy.com (INPLASY202350080)\u003c/p\u003e","manuscriptTitle":"Neural Mechanisms underlying Bimanual Coordination in Healthy and Stroke Individuals and Application of Non-Invasive Brain Stimulation: A Scoping Review","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-05-02 20:40:25","doi":"10.21203/rs.3.rs-3975753/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a2342d47-d716-40b4-978b-fc984de27ec2","owner":[],"postedDate":"May 2nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-09-26T18:53:28+00:00","versionOfRecord":[],"versionCreatedAt":"2024-05-02 20:40:25","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3975753","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3975753","identity":"rs-3975753","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}