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The long-term motor outcome of acute stroke patients may be correlated to the reorganization of brain motor network. Abundant neuroimaging studies contribute to understand the pathological changes and recovery of motor networks after stroke. In this review, we summarized how current neuroimaging studies have increased understanding of reorganization and plasticity in post stroke motor recovery. Firstly, we discussed the changes in the motor network over time during the motor-activation and resting states, as well as the overall functional integration trend of the motor network. These studies indicate that the motor network undergoes dynamic bilateral hemispheric functional reorganization, as well as a trend towards network randomization. In the second part, we summarized the current study progress in the application of neuroimaging technology to early predict the post-stroke motor outcome. In the third part, we discuss the neuroimaging techniques commonly used in the post-stroke recovery. These methods provide direct or indirect visualization patterns to understand the neural mechanisms of post-stroke motor recovery, opening up new avenues for studying spontaneous and treatment-induced recovery and plasticity after stroke.

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Research on brain functional connectivity often relies on intra-individual moment-to-moment correlations of functional brain activity, typically using techniques like functional MRI (fMRI). Inter-individual correlations are also employed on data from fMRI and positron emission tomography (PET). Many past studies have not specified tasks for participants, keeping them in an implicit "resting" condition. This lack of task specificity raises questions about how different tasks impact inter-individual correlation estimates. In our analysis of fMRI data from 100 unrelated participants, scanned during seven task conditions and in a resting state, we calculated Regional Homogeneity (ReHo) for each task as a regional measure of brain functions. We found that changes in ReHo due to different tasks were relatively small compared with the variations across brain regions. Cross-region variations of ReHo were highly correlated between different tasks. Similarly, whole-brain inter-individual correlation patterns were remarkably consistent across the tasks, showing correlations greater than 0.78. Changes in inter-individual correlations between tasks were primarily driven by connectivity in the visual, somatomotor, default mode network, and the interactions between them. The subtle yet statistically significant differences in functional connectivity may be linked to specific brain regions associated with the studied tasks. Future studies should consider task design when exploring inter-individual connectivity in specific brain systems.

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Background: Normative childhood motor network resting-state fMRI effective connectivity is undefined, yet necessary for translatable dynamic resting-state-network-informed evaluation in pediatric cerebral palsy. Methods: Cross-spectral dynamic causal modeling of resting-state-fMRI was investigated in 50 neurotypically developing 5- to 13-year-old children. Fully connected six-node network models per hemisphere included primary motor cortex, striatum, subthalamic nucleus, globus pallidus internus, thalamus, and contralateral cerebellum. Parametric Empirical Bayes with exhaustive Bayesian model reduction and Bayesian modeling averaging informed the model; Purdue Pegboard Test scores of hand motor behavior were the covariate at the group level to determine the effective-connectivity-functional behavior relationship. Results: Although both hemispheres exhibited similar effective connectivity of motor cortico-basal ganglia-cerebellar networks, magnitudes were slightly greater on the right, except for left-sided connections of the striatum which were more numerous and of opposite polarity. Inter-nodal motor network effective connectivity remained consistent and robust across subjects. Age had a greater impact on connections to the contralateral cerebellum, bilaterally. Motor behavior, however, affected different connections in each hemisphere, exerting a more prominent effect on the left modulatory connections to the subthalamic nucleus, contralateral cerebellum, primary motor cortex, and thalamus. Discussion: This study revealed a consistent pattern of directed resting-state effective connectivity in healthy children aged 5-13 years within the motor network, encompassing cortical, subcortical, and cerebellar regions, correlated with motor skill proficiency. Both hemispheres exhibited similar effective connectivity within motor cortico-basal ganglia-cerebellar networks reflecting inter-nodal signal direction predicted by other modalities, mainly differing from task-dependent studies due to network differences at rest. Notably, age-related changes were more pronounced in connections to the contralateral cerebellum. Conversely, motor behavior distinctly impacted connections in each hemisphere, emphasizing its role in modulating left sided connections to the subthalamic nucleus, contralateral cerebellum, primary motor cortex, and thalamus. Motor network effective connectivity was correlated with motor behavior, validating its physiological significance. This study is the first to evaluate a normative effective connectivity model for the pediatric motor network using resting-state functional MRI correlating with behavior and serves as a foundation for identifying abnormal findings and optimizing targeted interventions like deep brain stimulation, potentially influencing future therapeutic approaches for children with movement disorders.

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State-dependent non-invasive brain stimulation (NIBS) informed by electroencephalography (EEG) has contributed to the understanding of NIBS inter-subject and inter-session variability. While these approaches focus on local EEG characteristics, it is acknowledged that the brain exhibits an intrinsic long-range dynamic organization in networks. This proof-of-concept study explores whether EEG connectivity of the primary motor cortex (M1) in the pre-stimulation period aligns with the Motor Network (MN) and how the MN state affects responses to the transcranial magnetic stimulation (TMS) of M1. One thousand suprathreshold TMS pulses were delivered to the left M1 in eight subjects at rest, with simultaneous EEG. Motor-evoked potentials (MEPs) were measured from the right hand. The source space functional connectivity of the left M1 to the whole brain was assessed using the imaginary part of the phase locking value at the frequency of the sensorimotor µ-rhythm in a 1 s window before the pulse. Group-level connectivity revealed functional links between the left M1, left supplementary motor area, and right M1. Also, pulses delivered at high MN connectivity states result in a greater MEP amplitude compared to low connectivity states. At the single-subject level, this relation is more highly expressed in subjects that feature an overall high cortico-spinal excitability. In conclusion, this study paves the way for MN connectivity-based NIBS.

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Objective.The study aims to characterize movements with different sensory goals, by contrasting the neural activity involved in processing proprioceptive and visuo-motor information. To accomplish this, we have developed a new methodology that utilizes the irregularity of the instantaneous gamma frequency parameter for characterization.Approach.In this study, eight essential tremor patients undergoing an awake deep brain stimulation implantation surgery repetitively touched the clinician's finger (forward visually-guided/FV movement) and then one's own chin (backward proprioceptively-guided/BP movement). Neural electrocorticographic recordings from the motor (M1), somatosensory (S1), and posterior parietal cortex (PPC) were obtained and band-pass filtered in the gamma range (30-80 Hz). The irregularity of the inter-event intervals (IEI; inverse of instantaneous gamma frequency) were examined as: (1) auto-information of the IEI time series and (2) correlation between the amplitude and its proceeding IEI. We further explored the network connectivity after segmenting the FV and BP movements by periods of accelerating and decelerating forces, and applying the IEI parameter to transfer entropy methods.Main results.Conceptualizing that the irregularity in IEI reflects active new information processing, we found the highest irregularity in M1 during BP movement, highest in PPC during FV movement, and the lowest during rest at all sites. Also, connectivity was the strongest from S1 to M1 and from S1 to PPC during FV movement with accelerating force and weakest during rest.Significance. We introduce a novel methodology that utilize the instantaneous gamma frequency (i.e. IEI) parameter in characterizing goal-oriented movements with different sensory goals, and demonstrate its use to inform the directional connectivity within the motor cortical network. This method successfully characterizes different movement types, while providing interpretations to the sensory-motor integration processes.

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BACKGOUND: Although cognitive control is essential for efficient gait, the associations between cognitive and motor networks regarding gait in individuals with Parkinson's disease (PD) remain to be determined. Herein, we enrolled 28 PD and 28 controls to compare internetwork coupling among cognitive and motor networks and examine its relationship with single- and dual-task gait performance in PD. METHODS: The dorsal attention network (DAN), left and right frontoparietal control networks (FPNs), sensorimotor network, and lateral motor network were identified using resting-state functional magnetic resonance imaging data. The time taken to complete a 10-m walk test during cognitive or physical dual-tasks in PD was calculated representing gait performance. RESULTS: We observed that the internetwork couplings between the DAN and motor networks and between the motor networks decreased whereas those between the left FPN and DAN and motor networks increased in PD compared to controls using a permutation test. There was no significant correlation between the internetwork couplings and single- and dual-task gait performance in PD. Nevertheless, improved cognitive dual-task performance showed a positive correlation with the DAN and left FPN coupling and a negative correlation with the DAN and lateral motor network coupling in a good performance group. The opposite relationship was observed in the poor cognitive dual-task performance group. CONCLUSION: Our findings suggest a neural mechanism of cognitive control on gait to compensate for reduced goal-directed attention in PD who maintain cognitive dual-task performance.

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We tested previous post-hoc findings indicating a relationship between functional connectivity (FC) in the motor network and corticospinal excitability (CsE), in a real-time EEG-TMS experiment in healthy participants. We hypothesized that high FC between left and right motor cortex predicts high CsE. FC was quantified in real-time by single-trial phase-locking value (stPLV), and TMS single pulses were delivered based on the current FC. CsE was indexed by motor-evoked potential (MEP) amplitude in a hand muscle. Possible confounding factors (pre-stimulus µ-power and phase, interstimulus interval) were evaluated post hoc. MEPs were significantly larger during high FC compared to low FC. Post hoc analysis revealed that the FC condition showed a significant interaction with µ-power in the stimulated hemisphere. Further, inter-stimulus interval (ISI) interacted with high vs. low FC conditions. In summary, FC was confirmed to be predictive of CsE, but should not be considered in isolation from µ-power and ISI. Moreover, FC was complementary to µ-phase in predicting CsE. Motor network FC is another marker of real-time accessible CsE beyond previously established markers, in particular phase and power of the µ rhythm, and may help define a more robust composite biomarker of high/low excitability states of human motor cortex.

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The somatosensory-motor network (SMN) not only plays an important role in primary somatosensory and motor processing but is also central to many disorders. However, the SMN heterogeneity related to higher-order systems still remains unclear. Here, we investigated SMN heterogeneity from multiple perspectives. To characterize the SMN substructures in more detail, we used ultra-high-field functional MRI to delineate a finer-grained cortical parcellation containing 430 parcels that is more homogenous than the state-of-the-art parcellation. We personalized the new parcellation to account for individual differences and identified multiscale individual-specific brain structures. We found that the SMN subnetworks showed distinct resting-state functional connectivity (RSFC) patterns. The Hand subnetwork was central within the SMN and exhibited stronger RSFC with the attention systems than the other subnetworks, whereas the Tongue subnetwork exhibited stronger RSFC with the default systems. This two-fold differentiation was observed in the temporal ordering patterns within the SMN. Furthermore, we characterized how the distinct attention and default streams were carried forward into the functions of the SMN using dynamic causal modeling and identified two behavioral domains associated with this SMN fractionation using meta-analytic tools. Overall, our findings provided important insights into the heterogeneous SMN organization at the system level and suggested that the Hand subnetwork may be preferentially involved in exogenous processes, whereas the Tongue subnetwork may be more important in endogenous processes.

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The globus pallidus (GP) of primates is divided conventionally into distinct internal and external parts. The literature repeats since 1930 the opinion that the homolog of the primate internal pallidum in rodents is the hypothalamic entopeduncular nucleus (embedded within fiber tracts of the cerebral peduncle). To test this idea, we explored its historic fundaments, checked the development and genoarchitecture of mouse entopeduncular and pallidal neurons, and examined relevant comparative connectivity data. We found that the extratelencephalic mouse entopeduncular structure consists of four different components arrayed along a dorsoventral sequence in the alar hypothalamus. The ventral entopeduncular nucleus (EPV), with GABAergic neurons expressing Dlx5&6 and Nkx2-1, lies within the hypothalamic peduncular subparaventricular area. Three other formations-the dorsal entopeduncular nucleus (EPD), the prereticular entopeduncular nucleus (EPPRt ), and the preeminential entopeduncular nucleus (EPPEm )-lie within the overlying paraventricular area, under the subpallium. EPD contains glutamatergic neurons expressing Tbr1, Otp, and Pax6. The EPPRt has GABAergic cells expressing Isl1 and Meis2, whereas the EPPEm population expresses Foxg1 and may be glutamatergic. Genoarchitectonic observations on relevant areas of the mouse pallidal/diagonal subpallium suggest that the GP of rodents is constituted as in primates by two adjacent but molecularly and hodologically differentiable telencephalic portions (both expressing Foxg1). These and other reported data oppose the notion that the rodent extratelencephalic entopeduncular nucleus is homologous to the primate internal pallidum. We suggest instead that all mammals, including rodents, have dual subpallial GP components, whereas primates probably also have a comparable set of hypothalamic entopeduncular nuclei. Remarkably, there is close similarity in some gene expression properties of the telencephalic internal GP and the hypothalamic EPV. This apparently underlies their notable functional analogy, sharing GABAergic neurons and thalamopetal connectivity.

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The execution of voluntary movements is primarily governed by the cerebral hemisphere contralateral to the moving limb. Previous research indicates that the ipsilateral motor network, comprising the primary motor cortex (M1), supplementary motor area (SMA), and premotor cortex (PM), plays a crucial role in the planning and execution of limb movements. However, the precise functions of this network and its interplay in different task contexts have yet to be fully understood. Twenty healthy right-handed participants (10 females, mean age 26.1 ± 4.6 years) underwent functional MRI scans while performing biceps brachii representations such as bilateral, unilateral flexion, and bilateral flexion-extension. Ipsilateral motor evoked potentials (iMEPs) were obtained from the identical set of participants in a prior study using transcranial magnetic stimulation (TMS) targeting M1 while employing the same motor tasks. The voxel time series was extracted based on the region of interest (M1, SMA, ventral PM and dorsal PM). Directed functinal connectivity was derived from the extracted time series using time-resolved partial directed coherence. We found increased connectivity from left-PMv to both sides M1, as well as right-PMv to both sides SMA, in unilateral flexion compared to bilateral flexion. Connectivity from left M1 to left-PMv, and left-SMA to right-PMd, also increased in both unilateral flexion and bilateral flexion-extension compared to bilateral flexion. However, connectivity between PMv and right-M1 to left-PMd decreased during bilateral flexion-extension compared to unilateral flexion. Additionally, during bilateral flexion-extension, the connectivity from right-M1 to right-SMA had a negative relationship with the area ratio of iMEP in the dominant side. Our results provide corroborating evidence for prior research suggesting that the ipsilateral motor network is implicated in the voluntary movements and underscores its involvement in cognitive processes such as movement planning and coordination. Moreover, ipsilateral connectivity from M1 to SMA on the dominant side can modulate the degree of ipsilateral M1 activation during bilateral antagonistic contraction.

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BACKGROUND: In stroke patients, preserved cognitive function plays a role in motor recovery, but there is insufficient evidence on the involved mechanisms. These mechanisms require investigation in the human brain, which is composed of large-scale functionally specialized networks. OBJECTIVE: In this study, we investigated the role of cognition-related networks on upper extremity motor recovery using neuroimaging data of subacute stroke patients. METHODS: This study retrospectively analyzed cohort data of 108 subacute ischemic stroke patients. All patients underwent resting-state functional MRI and motor function assessments using the Fugl-Meyer assessment (FMA) at 2 weeks after stroke onset. The FMA upper extremity (FMA-UE) score was obtained again at three months after stroke onset to assess motor recovery. To construct a resting-state network, cortical surface parcellation was performed using the Gordon atlas, which included 333 regions of interest, and 12 resting-state networks were extracted. Linear regression was used to identify the relationships between the FMA-UE recovery score and resting-state networks. RESULTS: Cognition-related networks were correlated with the FMA-UE recovery score, as were motor-related networks. Interaction effects between motor- and cognition-related network states existed in motor recovery. Specifically, cognition-related networks were associated with motor recovery in patients with a lower strength of motor-related networks. CONCLUSIONS: These results suggested that the greater the damage to the motor network caused by stroke is, the more important the cognition-related networks are in motor recovery.

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Reward motivation is essential in shaping human behavior and cognition. Previous studies have shown altered reward motivation and reward brain circuitry in chronic pain conditions, including fibromyalgia. Fibromyalgia is a chronic disorder characterized by widespread musculoskeletal pain, fatigue, cognitive problems, and mood-related symptoms. In this study, we analyzed brain reward networks in patients with fibromyalgia by using a data-driven approach with task-based fMRI data. fMRI data from 24 patients with fibromyalgia and 24 healthy controls were acquired while subjects performed a monetary incentive delay (MID) reward task. Functional networks were derived using independent component analysis (ICA) focused on the gain anticipation phase of the reward task. Functional activity in the motor, value-driven attention, and basal ganglia networks was evaluated during gain anticipation in both patient and healthy control groups. Compared to controls, the motor network was more engaged during gain anticipation in patients with fibromyalgia. Our findings suggest that reward motivation may lead to hyperactivity in the motor network, possibly related to altered motor processing, such as restricted movement or dysregulated motor planning in fibromyalgia. As an exploratory analysis, we compared levels of motor network engagement during early and late timepoints of the gain anticipation phase. Both groups showed greater motor network engagement during the late timepoint (i.e., closer to response), which reflected motor preparation prior to target response. Importantly, compared to controls and consistent with the initial findings described above, patients exhibited greater engagement of the motor network during both early and late timepoints. In summary, by using a novel data-driven ICA approach to analyze task-based fMRI data, we identified elevated motor network engagement during gain anticipation in fibromyalgia.

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BACKGROUND: Deficits in executive functions (EF) and social cognition (SC) are often observed in bipolar disorder (BD), leading to a severe impairment in engaging a functional interaction with the others and the surrounding environment. Therefore, in recent years, resting-state functional magnetic resonance imaging (rs-fMRI) studies on BD tried to identify the neural underpinnings of these cognitive domains by exploring the association between the intrinsic functional connectivity (FC) and the scores in clinical scales evaluating these domains. METHODS: A bibliographic search on PubMed and Scopus of studies evaluating the correlations between rs-fMRI findings and EF and/or SC in BD was conducted until March 2022. Ten studies met the inclusion criteria. RESULTS: Overall, the results of the reviewed studies showed that BD patients had FC deficits compared to healthy controls (HC) in selective resting-state networks involved in EF and SC, which include the default mode network, especially the link between medial prefrontal cortex and posterior cingulate cortex, and the sensory-motor network. Finally, it also emerged the predominant role of alterations in prefrontal connections in explaining the cognitive deficits in BD patients. LIMITATIONS: The heterogeneity of the reviewed studies, in terms of the cognitive domains explored and the neuroimaging acquisitions employed, limited the comparability of the findings. CONCLUSIONS: rs-fMRI studies could help deepen the brain network alterations underlying EF and SC deficits in BD, pointing the attention on the neuronal underpinning of cognition, whose knowledge may lead to the development of new neurobiological-based approaches to improve the quality of life of these patients.

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When we interact with the environment around us, we are sometimes active participants, making directed physical motor movements and other times only mentally engaging with our environment, taking in sensory information and internally planning our next move without directed physical movement. Traditionally, cortical motor regions and key subcortical structures such as the cerebellum have been tightly linked to motor initiation, coordination, and directed motor behavior. However, recent neuroimaging studies have noted the activation of the cerebellum and wider cortical networks specifically during various forms of motor processing, including the observations of actions and mental rehearsal of movements through motor imagery. This phenomenon of cognitive engagement of traditional motor networks raises the question of how these brain regions are involved in the initiation of movement without physical motor output. Here, we will review evidence for distributed brain network activation during motor execution, observation, and imagery in human neuroimaging studies as well as the potential for cerebellar involvement specifically in motor-related cognition. Converging evidence suggests that a common global brain network is involved in both movement execution and motor observation or imagery, with specific task-dependent shifts in these global activation patterns. We will further discuss underlying cross-species anatomical support for these cognitive motor-related functions as well as the role of cerebrocerebellar communication during action observation and motor imagery.

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Significance: Motor function evaluation is essential for poststroke dyskinesia rehabilitation. Neuroimaging techniques combined with machine learning help decode a patient's functional status. However, more research is needed to investigate how individual brain function information predicts the dyskinesia degree of stroke patients. Aim: We investigated stroke patients' motor network reorganization and proposed a machine learning-based method to predict the patients' motor dysfunction. Approach: Near-infrared spectroscopy (NIRS) was used to measure hemodynamic signals of the motor cortex in the resting state (RS) from 11 healthy subjects and 31 stroke patients, 15 with mild dyskinesia (Mild), and 16 with moderate-to-severe dyskinesia (MtS). The graph theory was used to analyze the motor network characteristics. Results: The small-world properties of the motor network were significantly different between groups: (1) clustering coefficient, local efficiency, and transitivity: MtS > Mild > Healthy and (2) global efficiency: MtS < Mild < Healthy. These four properties linearly correlated with patients' Fugl-Meyer Assessment scores. Using the small-world properties as features, we constructed support vector machine (SVM) models that classified the three groups of subjects with an accuracy of 85.7%. Conclusions: Our results show that NIRS, RS functional connectivity, and SVM together constitute an effective method for assessing the poststroke dyskinesia degree at the individual level.

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The exact mechanisms behind the effects of transcranial direct current stimulation (tDCS) at a network level are still poorly understood, with most studies to date focusing on local (cortical) effects and changes in motor-evoked potentials or BOLD signal. Here, we explored stationary and dynamic effective connectivity across the motor network at rest in two experiments where we applied tDCS over the primary motor cortex (M1-tDCS) or the cerebellum (cb-tDCS) respectively. Two cohorts of healthy volunteers (n = 21 and n = 22) received anodal, cathodal, and sham tDCS sessions (counterbalanced) during 20 min of resting-state functional magnetic resonance imaging (fMRI). We used spectral Dynamic Causal Modelling (DCM) and hierarchical Parametrical Empirical Bayes (PEB) to analyze data after (compared to a pre-tDCS baseline) and during stimulation. We also implemented a novel dynamic (sliding windows) DCM/PEB approach to model the nature of network reorganisation across time. In both experiments we found widespread effects of tDCS that extended beyond the targeted area and modulated effective connectivity between cortex, thalamus, and cerebellum. These changes were characterised by unique nonlinear temporal fingerprints across connections and polarities. Our results support growing research challenging the classic notion of anodal and cathodal tDCS as excitatory and inhibitory respectively, as well as the idea of a cumulative effect of tDCS over time. Instead, they described a rich set of changes with specific spatial and temporal patterns. Our work provides a starting point for advancing our understanding of network-level tDCS effects and may guide future work to optimise its cognitive and clinical applications.

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Aberrant dynamic switches between internal brain states are believed to underlie motor dysfunction in Parkinson's disease. Deep brain stimulation of the subthalamic nucleus is a well-established treatment for the motor symptoms of Parkinson's disease, yet it remains poorly understood how subthalamic stimulation modulates the whole-brain intrinsic motor network state dynamics. To investigate this, we acquired resting-state functional magnetic resonance imaging time-series data from 27 medication-free patients with Parkinson's disease (mean age: 64.8 years, standard deviation: 7.6) who had deep brain stimulation electrodes implanted in the subthalamic nucleus, in both on and off stimulation states. Sixteen matched healthy individuals were included as a control group. We adopted a powerful data-driven modelling approach, known as a hidden Markov model, to disclose the emergence of recurring activation patterns of interacting motor regions (whole-brain intrinsic motor network states) via the blood oxygen level-dependent signal detected in the resting-state functional magnetic resonance imaging time-series data from all participants. The estimated hidden Markov model disclosed the dynamics of distinct whole-brain motor network states, including frequency of occurrence, state duration, fractional coverage and their transition probabilities. Notably, the data-driven decoding of whole-brain intrinsic motor network states revealed that subthalamic stimulation reshaped functional network expression and stabilized state transitions. Moreover, subthalamic stimulation improved motor symptoms by modulating key trajectories of state transition within whole-brain intrinsic motor network states. This modulation mechanism of subthalamic stimulation was manifested in three significant effects: recovery, relieving and remodelling effects. Significantly, recovery effects correlated with improvements in tremor and posture symptoms induced by subthalamic stimulation (P < 0.05). Furthermore, subthalamic stimulation was found to restore a relatively low level of fluctuation of functional connectivity in all motor regions to a level closer to that of healthy participants. Also, changes in the fluctuation of functional connectivity between motor regions were associated with improvements in tremor and gait symptoms (P < 0.05). These findings fill a gap in our knowledge of the role of subthalamic stimulation at the level of neural activity, revealing the regulatory effects of subthalamic stimulation on whole-brain inherent motor network states in Parkinson's disease. Our results provide mechanistic insight and explanation for how subthalamic stimulation modulates motor symptoms in Parkinson's disease.

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BACKGROUND: Idiopathic normal pressure hydrocephalus (iNPH) is a progressive and partially reversible form of dementia, characterized by impaired interactions between multiple brain regions. Because of the presence of comorbidities and a lack of accurate diagnostic and prognostic biomarkers, only a minority of patients receives disease-specific treatment. Recently, resting-state functional-magnetic resonance imaging (rs-fMRI) has demonstrated functional connectivity alterations in inter-hemispheric, frontal, occipital, default-mode (DMN) and motor network (MN) circuits. Herein, we report our experience in a cohort of iNPH patients that underwent cerebrospinal fluid (CSF) dynamics evaluation and rs-fMRI. The study aimed to identify functional circuits related to iNPH and explore the relationship between DMN and MN recordings and clinical modifications before and after infusion and tap test, trying to understand iNPH pathophysiology and to predict the best responders to ventriculoperitoneal shunt (VPS) implant. METHODS: We prospectively collected data regarding clinical assessment, neuroradiological findings, lumbar infusion and tap test of thirty-two iNPH patients who underwent VPS implant. Rs-fMRI was performed using MELODIC-ICA both before and after the tap test. Rs-fMRI data of thirty healthy subjects were also recorded. RESULTS: At the baseline, reduced z-DMN and z-MN scores were recorded in the iNPH cohort compared with controls. Higher z-scores were recorded in more impaired patients. Both z-scores significantly improved after the tap test except in subjects with a low resistance to outflow value and without a significant clinical improvement after the test. A statistically significant difference in mean MN connectivity scores for tap test responders and non-responders was demonstrated both before (p = 0.0236) and after the test (p = 0.00137). A statistically significant main effect of the tap test on DMN connectivity after CSF subtraction was recorded (p = 0.038). CONCLUSIONS: Our results suggest the presence of a partially reversible plasticity functional mechanism in DMN and MN. Low values compensate for the initial stages of the disease, while higher values of z-DMN were recorded in older patients with a longer duration of symptoms, suggesting an exhausted plasticity compensation. The standardization of this technique could play a role as a non-invasive biomarker in iNPH disease, suggesting the right time for surgery. Trial Registration Prot. IRB 090/2021.

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Multifocal transcranial direct current stimulation (tDCS) targeting several brain regions is promising for inducing cortical plasticity. It remains unknown whether multifocal tDCS aimed at the resting-state motor network (network-tDCS) can revert N2-P2 cortical responses otherwise attenuated during prolonged experimental pain. Thirty-eight healthy subjects participated in 2 sessions separated by 24 hours (Day1, Day2) of active (n = 19) or sham (n = 19) network-tDCS. Experimental pain induced by topical capsaicin was maintained for 24 hours and assessed using a numerical rating scale. Electrical detection and pain thresholds, and N2-P2 evoked potentials (electroencephalography) to noxious electrical stimulation were recorded before capsaicin-induced pain (Day1-baseline), after capsaicin application (Day1-post-cap), and after 2 sessions of network-tDCS (Day2). Capsaicin induced moderate pain at Day1-post-cap, which further increased at Day2 in both groups (P = .01). Electrical detection/pain thresholds did not change over time. N2-P2 responses were reduced on Day1-post-cap compared to Day1-baseline (P = .019). At Day2 compared with Day1-post-cap, N2-P2 responses were significantly higher in the Active network-tDCS group (P<.05), while the sham group remained inhibited. These results suggest that tDCS targeting regions associated with the motor network may modulate the late evoked brain responses to noxious peripheral stimulation otherwise initially inhibited by capsaicin-induced pain. PERSPECTIVE: This study extends the evidence of N2-P2 reduction due to capsaicin-induced pain from 30 minutes to 24 hrs. Moreover, 2 sessions of tDCS targeting the motor network in the early stage of nociceptive pain may revert the inhibition of N2-P2 associated with capsaicin-induced pain.

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Dual-site transcranial magnetic stimulation (ds-TMS) is well suited to investigate the causal effect of distant brain regions on the primary motor cortex, both at rest and during motor performance and learning. However, given the broad set of stimulation parameters, clarity about which parameters are most effective for identifying particular interactions is lacking. Here, evidence describing inter- and intra-hemispheric interactions during rest and in the context of motor tasks is reviewed. Our aims are threefold: (1) provide a detailed overview of ds-TMS literature regarding inter- and intra-hemispheric connectivity; (2) describe the applicability and contributions of these interactions to motor control, and; (3) discuss the practical implications and future directions. Of the 3659 studies screened, 109 were included and discussed. Overall, there is remarkable variability in the experimental context for assessing ds-TMS interactions, as well as in the use and reporting of stimulation parameters, hindering a quantitative comparison of results across studies. Further studies examining ds-TMS interactions in a systematic manner, and in which all critical parameters are carefully reported, are needed.

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