Decreased long-range temporal correlations in the resting-state functional magnetic resonance imaging blood-oxygen-level-dependent signal reflect motor sequence learning up to 2 weeks following training.

Decreased long-range temporal correlations (LRTC) in brain signals can be used to measure cognitive effort during task execution. Here, we examined how learning a motor sequence affects long-range temporal memory within resting-state functional magnetic resonance imaging signal. Using the Hurst exponent (HE), we estimated voxel-wise LRTC and assessed changes over 5 consecutive days of training, followed by a retention scan 12 days later. The experimental group learned a complex visuomotor sequence while a complementary control group performed tightly matched movements. An interaction analysis revealed that HE decreases were specific to the complex sequence and occurred in well-known motor sequence learning associated regions including left supplementary motor area, left premotor cortex, left M1, left pars opercularis, bilateral thalamus, and right striatum. Five regions exhibited moderate to strong negative correlations with overall behavioral performance improvements. Following learning, HE values returned to pretraining levels in some regions, whereas in others, they remained decreased even 2 weeks after training. Our study presents new evidence of HE's possible relevance for functional plasticity during the resting-state and suggests that a cortical subset of sequence-specific regions may continue to represent a functional signature of learning reflected in decreased long-range temporal dependence after a period of inactivity.

Visuo-motor transformations in the intraparietal sulcus mediate the acquisition of endovascular medical skill.

Performing endovascular medical interventions safely and efficiently requires a diverse set of skills that need to be practised in dedicated training sessions. Here, we used multimodal magnetic resonance (MR) imaging to determine the structural and functional plasticity and core skills associated with skill acquisition. A training group learned to perform a simulator-based endovascular procedure, while a control group performed a simplified version of the task; multimodal MR images were acquired before and after training. Using a well-controlled interaction design, we found strong multimodal evidence for the role of the intraparietal sulcus (IPS) in endovascular skill acquisition that is in line with previous work implicating the structure in visuospatial transformations including simple visuo-motor and mental rotation tasks. Our results provide a unique window into the multimodal nature of rapid structural and functional plasticity of the human brain while learning a multifaceted and complex clinical skill. Further, our results provide a detailed description of the plasticity process associated with endovascular skill acquisition and highlight specific facets of skills that could enhance current medical pedagogy and be useful to explicitly target during clinical resident training.

Using cortico-cerebellar structural patterns to classify early- and late-trained musicians.

A body of current evidence suggests that there is a sensitive period for musical training: people who begin training before the age of seven show better performance on tests of musical skill, and also show differences in brain structure-especially in motor cortical and cerebellar regions-compared with those who start later. We used support vector machine models-a subtype of supervised machine learning-to investigate distributed patterns of structural differences between early-trained (ET) and late-trained (LT) musicians and to better understand the age boundaries of the sensitive period for early musicianship. After selecting regions of interest from the cerebellum and cortical sensorimotor regions, we applied recursive feature elimination with cross-validation to produce a model which optimally and accurately classified ET and LT musicians. This model identified a combination of 17 regions, including 9 cerebellar and 8 sensorimotor regions, and maintained a high accuracy and sensitivity (true positives, i.e., ET musicians) without sacrificing specificity (true negatives, i.e., LT musicians). Critically, this model-which defined ET musicians as those who began their training before the age of 7-outperformed all other models in which age of start was earlier or later (between ages 5-10). Our model's ability to accurately classify ET and LT musicians provides additional evidence that musical training before age 7 affects cortico-cerebellar structure in adulthood, and is consistent with the hypothesis that connected brain regions interact during development to reciprocally influence brain and behavioral maturation.

Modeling venous bias in resting state functional MRI metrics.

Resting-state (rs) functional magnetic resonance imaging (fMRI) is used to detect low-frequency fluctuations in the blood oxygen-level dependent (BOLD) signal across brain regions. Correlations between temporal BOLD signal fluctuations are commonly used to infer functional connectivity. However, because BOLD is based on the dilution of deoxyhemoglobin, it is sensitive to veins of all sizes, and its amplitude is biased by draining veins. These biases affect local BOLD signal location and amplitude, and may also influence BOLD-derived connectivity measures, but the magnitude of this venous bias and its relation to vein size and proximity is unknown. Here, veins were identified using high-resolution quantitative susceptibility maps and utilized in a biophysical model to investigate systematic venous biases on common local rsfMRI-derived measures. Specifically, we studied the impact of vein diameter and distance to veins on the amplitude of low-frequency fluctuations (ALFF), fractional ALFF (fALFF), Hurst exponent (HE), regional homogeneity (ReHo), and eigenvector centrality values in the grey matter. Values were higher across all distances in smaller veins, and decreased with increasing vein diameter. Additionally, rsfMRI values associated with larger veins decrease with increasing distance from the veins. ALFF and ReHo were the most biased by veins, while HE and fALFF exhibited the smallest bias. Across all metrics, the amplitude of the bias was limited in voxel-wise data, confirming that venous structure is not the dominant source of contrast in these rsfMRI metrics. Finally, the models presented can be used to correct this venous bias in rsfMRI metrics.

The impact of lesion side on bilateral upper limb coordination after stroke.

BACKGROUND: A stroke frequently results in impaired performance of activities of daily life. Many of these are highly dependent on effective coordination between the two arms. In the context of bimanual movements, cyclic rhythmical bilateral arm coordination patterns can be classified into two fundamental modes: in-phase (bilateral homologous muscles contract simultaneously) and anti-phase (bilateral muscles contract alternately) movements. We aimed to investigate how patients with left (LHS) and right (RHS) hemispheric stroke are differentially affected in both individual-limb control and inter-limb coordination during bilateral movements. METHODS: We used kinematic measurements to assess bilateral coordination abilities of 18 chronic hemiparetic stroke patients (9 LHS; 9 RHS) and 18 age- and sex-matched controls. Using KINARM upper-limb exoskeleton system, we examined individual-limb control by quantifying trajectory variability in each hand and inter-limb coordination by computing the phase synchronization between hands during anti- and in-phase movements. RESULTS: RHS patients exhibited greater impairment in individual- and inter-limb control during anti-phase movements, whilst LHS patients showed greater impairment in individual-limb control during in-phase movements alone. However, LHS patients further showed a swap in hand dominance during in-phase movements. CONCLUSIONS: The current study used individual-limb and inter-limb kinematic profiles and showed that bilateral movements are differently impaired in patients with left vs. right hemispheric strokes. Our results demonstrate that both fundamental bilateral coordination modes are differently controlled in both hemispheres using a lesion model approach. From a clinical perspective, we suggest that lesion side should be taken into account for more individually targeted bilateral coordination training strategies. TRIAL REGISTRATION: the current experiment is not a health care intervention study.

Mapping pontocerebellar connectivity with diffusion MRI.

The cerebellum's involvement in cognitive, affective and motor functions is mediated by connections to different regions of the cerebral cortex. A distinctive feature of cortico-cerebellar loops that has been demonstrated in the animal work is a topographic organization that is preserved across its corticopontine, pontocerebellar, and cerebello-thalmo-cortical segments. Here we used tractography derived from diffusion imaging data to characterize the connections between the pons and the individual lobules of the cerebellum and generate a parcellation of the pons and middle cerebellar peduncle based on the pattern of connectivity. We identified a rostral to caudal gradient in the pons, similar to that observed in the animal work, such that rostral regions were preferentially connected to cerebellar lobules involved in non-motor, and caudal regions with motor regions. These findings advance our fundamental understanding of the cerebellum, and the parcellations we generated provide context for future research into the pontocerebellar tract's involvement in health and disease.

Investigating microstructural variation in the human hippocampus using non-negative matrix factorization.

In this work we use non-negative matrix factorization to identify patterns of microstructural variance in the human hippocampus. We utilize high-resolution structural and diffusion magnetic resonance imaging data from the Human Connectome Project to query hippocampus microstructure on a multivariate, voxelwise basis. Application of non-negative matrix factorization identifies spatial components (clusters of voxels sharing similar covariance patterns), as well as subject weightings (individual variance across hippocampus microstructure). By assessing the stability of spatial components as well as the accuracy of factorization, we identified 4 distinct microstructural components. Furthermore, we quantified the benefit of using multiple microstructural metrics by demonstrating that using three microstructural metrics (T1-weighted/T2-weighted signal, mean diffusivity and fractional anisotropy) produced more stable spatial components than when assessing metrics individually. Finally, we related individual subject weightings to demographic and behavioural measures using a partial least squares analysis. Through this approach we identified interpretable relationships between hippocampus microstructure and demographic and behavioural measures. Taken together, our work suggests non-negative matrix factorization as a spatially specific analytical approach for neuroimaging studies and advocates for the use of multiple metrics for data-driven component analyses.

Improving Safety of MRI in Patients with Deep Brain Stimulation Devices.

MRI is a valuable clinical and research tool for patients undergoing deep brain stimulation (DBS). However, risks associated with imaging DBS devices have led to stringent regulations, limiting the clinical and research utility of MRI in these patients. The main risks in patients with DBS devices undergoing MRI are heating at the electrode tips, induced currents, implantable pulse generator dysfunction, and mechanical forces. Phantom model studies indicate that electrode tip heating remains the most serious risk for modern DBS devices. The absence of adverse events in patients imaged under DBS vendor guidelines for MRI demonstrates the general safety of MRI for patients with DBS devices. Moreover, recent work indicates that-given adequate safety data-patients may be imaged outside these guidelines. At present, investigators are primarily focused on improving DBS device and MRI safety through the development of tools, including safety simulation models. Existing guidelines provide a standardized framework for performing safe MRI in patients with DBS devices. It also highlights the possibility of expanding MRI as a tool for research and clinical care in these patients going forward.

Immune activation by DNA damage predicts response to chemotherapy and survival in oesophageal adenocarcinoma.

OBJECTIVE: Current strategies to guide selection of neoadjuvant therapy in oesophageal adenocarcinoma (OAC) are inadequate. We assessed the ability of a DNA damage immune response (DDIR) assay to predict response following neoadjuvant chemotherapy in OAC. DESIGN: Transcriptional profiling of 273 formalin-fixed paraffin-embedded prechemotherapy endoscopic OAC biopsies was performed. All patients were treated with platinum-based neoadjuvant chemotherapy and resection between 2003 and 2014 at four centres in the Oesophageal Cancer Clinical and Molecular Stratification consortium. CD8 and programmed death ligand 1 (PD-L1) immunohistochemical staining was assessed in matched resection specimens from 126 cases. Kaplan-Meier and Cox proportional hazards regression analysis were applied according to DDIR status for recurrence-free survival (RFS) and overall survival (OS). RESULTS: A total of 66 OAC samples (24%) were DDIR positive with the remaining 207 samples (76%) being DDIR negative. DDIR assay positivity was associated with improved RFS (HR: 0.61; 95% CI 0.38 to 0.98; p=0.042) and OS (HR: 0.52; 95% CI 0.31 to 0.88; p=0.015) following multivariate analysis. DDIR-positive patients had a higher pathological response rate (p=0.033), lower nodal burden (p=0.026) and reduced circumferential margin involvement (p=0.007). No difference in OS was observed according to DDIR status in an independent surgery-alone dataset.DDIR-positive OAC tumours were also associated with the presence of CD8+ lymphocytes (intratumoural: p<0.001; stromal: p=0.026) as well as PD-L1 expression (intratumoural: p=0.047; stromal: p=0.025). CONCLUSION: The DDIR assay is strongly predictive of benefit from DNA-damaging neoadjuvant chemotherapy followed by surgical resection and is associated with a proinflammatory microenvironment in OAC.

Neuroimaging Technological Advancements for Targeting in Functional Neurosurgery.

PURPOSE OF REVIEW: Ablations and particularly deep brain stimulation (DBS) of a variety of CNS targets are established therapeutic tools for movement disorders. Accurate targeting of the intended structure is crucial for optimal clinical outcomes. However, most targets used in functional neurosurgery are sub-optimally visualized on routine MRI. This article reviews recent neuroimaging advancements for targeting in movement disorders. RECENT FINDINGS: Dedicated MRI sequences can often visualize to some degree anatomical structures commonly targeted during DBS surgery, including at 1.5-T field strengths. Due to recent technological advancements, MR images using ultra-high magnetic field strengths and new acquisition parameters allow for markedly improved visualization of common movement disorder targets. In addition, novel neuroimaging techniques have enabled group-level analysis of DBS patients and delineation of areas associated with clinical benefits. These areas might diverge from the conventionally targeted nuclei and may instead correspond to white matter tracts or hubs of functional networks. Neuroimaging advancements have enabled improved direct visualization-based targeting as well as optimization and adjustment of conventionally targeted structures.

Gray-matter structural variability in the human cerebellum: Lobule-specific differences across sex and hemisphere.

Though commonly thought of as a "motor structure", we now know that the cerebellum's reciprocal connections to the cerebral cortex underlie contributions to both motor and non-motor behavior. Further, recent research has shown that cerebellar dysfunction may contribute to a wide range of neuropsychiatric disorders. However, there has been little characterization of normative variability at the level of cerebellar structure that can facilitate and further our understanding of disease biomarkers. In this manuscript we examine normative variation of the cerebellum using data from the Human Connectome Project (HCP). The Multiple Automatically Generated Templates (MAGeT) segmentation tool was used to identify the cerebella and 33 anatomically-defined lobules from 327 individuals from the HCP. To characterize normative variation, we estimated population mean volume and variability, assessed differences in hemisphere and sex, and related lobular volume to motor and non-motor behavior. We found that the effects of hemisphere and sex were not homogeneous across all lobules of the cerebellum. Greater volume in the right hemisphere was primarily driven by lobules Crus I, II, and H VIIB, with H VIIIA exhibiting the greatest left>right asymmetry. Relative to total cerebellar gray-matter volume, females had larger Crus II (known to be connected with non-motor regions of the cerebral cortex) while males had larger motor-connected lobules including H V, and VIIIA/B. When relating lobular volume to memory, motor performance, and emotional behavior, we found some evidence for relationships that have previously been identified in the literature. Our observations of normative cerebellar structure and variability in young adults provide evidence for lobule-specific differences in volume and the relationship with sex and behavior - indicating that the cerebellum cannot be considered a single structure with uniform function, but as a set of regions with functions that are likely as diverse as their connectivity with the cerebral cortex.

BIDS apps: Improving ease of use, accessibility, and reproducibility of neuroimaging data analysis methods.

The rate of progress in human neurosciences is limited by the inability to easily apply a wide range of analysis methods to the plethora of different datasets acquired in labs around the world. In this work, we introduce a framework for creating, testing, versioning and archiving portable applications for analyzing neuroimaging data organized and described in compliance with the Brain Imaging Data Structure (BIDS). The portability of these applications (BIDS Apps) is achieved by using container technologies that encapsulate all binary and other dependencies in one convenient package. BIDS Apps run on all three major operating systems with no need for complex setup and configuration and thanks to the comprehensiveness of the BIDS standard they require little manual user input. Previous containerized data processing solutions were limited to single user environments and not compatible with most multi-tenant High Performance Computing systems. BIDS Apps overcome this limitation by taking advantage of the Singularity container technology. As a proof of concept, this work is accompanied by 22 ready to use BIDS Apps, packaging a diverse set of commonly used neuroimaging algorithms.

Dexamethasone alone and in combination with desipramine, phenytoin, valproic acid or levetiracetam interferes with 5-ALA-mediated PpIX production and cellular retention in glioblastoma cells.

Extent of resection of glioblastoma (GBM) correlates with overall survival. Fluorescence-guided resection (FGR) using 5-aminolevulinic acid (5-ALA) can improve the extent of resection. Unfortunately not all patients given 5-ALA accumulate sufficient quantities of protoporphyrin IX (PpIX) for successful FGR. In this study, we investigated the effects of dexamethasone, desipramine, phenytoin, valproic acid, and levetiracetam on the production and accumulation of PpIX in U87MG cells. All of these drugs, except levetiracetam, reduce the total amount of PpIX produced by GBM cells (p < 0.05). When dexamethasone is mixed with another drug (desipramine, phenytoin, valproic acid or levetiracetam) the amount of PpIX produced is further decreased (p < 0.01). However, when cells are analyzed for PpIX cellular retention, dexamethasone accumulated significantly more PpIX than the vehicle control (p < 0.05). Cellular retention of PpIX was not different from controls in cells treated with dexamethasone plus desipramine, valproic acid or levetiracetam, but was significantly less for dexamethasone plus phenytoin (p < 0.01). These data suggest that medications given before and during surgery may interfere with PpIX accumulation in malignant cells. At this time, levetiracetam appears to be the best medication in its class (anticonvulsants) for patients undergoing 5-ALA-mediated FGR.

Improving motor performance without training: the effect of combining mirror visual feedback with transcranial direct current stimulation.

Mirror visual feedback (MVF) during motor training has been shown to improve motor performance of the untrained hand. Here we thought to determine if MVF-induced performance improvements of the left hand can be augmented by upregulating plasticity in right primary motor cortex (M1) by means of anodal transcranial direct current stimulation (a-tDCS) while subjects trained with the right hand. Participants performed a ball-rotation task with either their left (untrained) or right (trained) hand on two consecutive days (days 1 and 2). During training with the right hand, MVF was provided concurrent with two tDCS conditions: group 1 received a-tDCS over right M1 (n = 10), whereas group 2 received sham tDCS (s-tDCS, n = 10). On day 2, performance was reevaluated under the same experimental conditions compared with day 1 but without tDCS. While baseline performance of the left hand (day 1) was not different between groups, a-tDCS exhibited stronger MVF-induced performance improvements compared with s-tDCS. Similar results were observed for day 2 (without tDCS application). A control experiment (n = 8) with a-tDCS over right M1 as outlined above but without MVF revealed that left hand improvement was significantly less pronounced than that induced by combined a-tDCS and MVF. Based on these results, we provide novel evidence that upregulating activity in the untrained M1 by means of a-tDCS is capable of augmenting MVF-induced performance improvements in young normal volunteers. Our findings suggest that concurrent MVF and tDCS might have synergistic and additive effects on motor performance of the untrained hand, a result of relevance for clinical approaches in neurorehabilitation and/or exercise science.

Augmenting mirror visual feedback-induced performance improvements in older adults.

Previous studies have indicated that age-related behavioral alterations are not irreversible but are subject to amelioration through specific training interventions. Both training paradigms and non-invasive brain stimulation (NIBS) can be used to modulate age-related brain alterations and thereby influence behavior. It has been shown that mirror visual feedback (MVF) during motor skill training improves performance of the trained and untrained hands in young adults. The question remains of whether MVF also improves motor performance in older adults and how performance improvements can be optimised via NIBS. Here, we sought to determine whether anodal transcranial direct current stimulation (a-tDCS) can be used to augment MVF-induced performance improvements in manual dexterity. We found that older adults receiving a-tDCS over the right primary motor cortex (M1) during MVF showed superior performance improvements of the (left) untrained hand relative to sham stimulation. An additional control experiment in participants receiving a-tDCS over the right M1 only (without MVF/motor training of the right hand) revealed no significant behavioral gains in the left (untrained) hand. On the basis of these findings, we propose that combining a-tDCS with MVF might be relevant for future clinical studies that aim to optimise the outcome of neurorehabilitation.

Early musical training and white-matter plasticity in the corpus callosum: evidence for a sensitive period.

Training during a sensitive period in development may have greater effects on brain structure and behavior than training later in life. Musicians are an excellent model for investigating sensitive periods because training starts early and can be quantified. Previous studies suggested that early training might be related to greater amounts of white matter in the corpus callosum, but did not control for length of training or identify behavioral correlates of structural change. The current study compared white-matter organization using diffusion tensor imaging in early- and late-trained musicians matched for years of training and experience. We found that early-trained musicians had greater connectivity in the posterior midbody/isthmus of the corpus callosum and that fractional anisotropy in this region was related to age of onset of training and sensorimotor synchronization performance. We propose that training before the age of 7 years results in changes in white-matter connectivity that may serve as a scaffold upon which ongoing experience can build.

MVComp toolbox: MultiVariate Comparisons of brain MRI features accounting for common information across metrics.

Multivariate approaches have recently gained in popularity to address the physiological unspecificity of neuroimaging metrics and to better characterize the complexity of biological processes underlying behavior. However, commonly used approaches are biased by the intrinsic associations between variables, or they are computationally expensive and may be more complicated to implement than standard univariate approaches. Here, we propose using the Mahalanobis distance (D2), an individual-level measure of deviation relative to a reference distribution that accounts for covariance between metrics. To facilitate its use, we introduce an open-source python-based tool for computing D2 relative to a reference group or within a single individual: the MultiVariate Comparison (MVComp) toolbox. The toolbox allows different levels of analysis (i.e., group- or subject-level), resolutions (e.g., voxel-wise, ROI-wise) and dimensions considered (e.g., combining MRI metrics or WM tracts). Several example cases are presented to showcase the wide range of possible applications of MVComp and to demonstrate the functionality of the toolbox. The D2 framework was applied to the assessment of white matter (WM) microstructure at 1) the group-level, where D2 can be computed between a subject and a reference group to yield an individualized measure of deviation. We observed that clustering applied to D2 in the corpus callosum yields parcellations that highly resemble known topography based on neuroanatomy, suggesting that D2 provides an integrative index that meaningfully reflects the underlying microstructure. 2) At the subject level, D2 was computed between voxels to obtain a measure of (dis)similarity. The loadings of each MRI metric (i.e., its relative contribution to D2) were then extracted in voxels of interest to showcase a useful option of the MVComp toolbox. These relative contributions can provide important insights into the physiological underpinnings of differences observed. Integrative multivariate models are crucial to expand our understanding of the complex brain-behavior relationships and the multiple factors underlying disease development and progression. Our toolbox facilitates the implementation of a useful multivariate method, making it more widely accessible.

Early musical training shapes cortico-cerebellar structural covariation.

Adult abilities in complex cognitive domains such as music appear to depend critically on the age at which training or experience begins, and relevant experience has greater long-term effects during periods of peak maturational change. Previous work has shown that early trained musicians (ET; < age 7) out-perform later-trained musicians (LT; > age 7) on tests of musical skill, and also have larger volumes of the ventral premotor cortex (vPMC) and smaller volumes of the cerebellum. These cortico-cerebellar networks mature and function in relation to one another, suggesting that early training may promote coordinated developmental plasticity. To test this hypothesis, we examined structural covariation between cerebellar volume and cortical thickness (CT) in sensorimotor regions in ET and LT musicians and non-musicians (NMs). Results show that ETs have smaller volumes in cerebellar lobules connected to sensorimotor cortices, while both musician groups had greater cortical thickness in right pre-supplementary motor area (SMA) and right PMC compared to NMs. Importantly, early musical training had a specific effect on structural covariance between the cerebellum and cortex: NMs showed negative correlations between left lobule VI and right pre-SMA and PMC, but this relationship was reduced in ET musicians. ETs instead showed a significant negative correlation between vermal IV and right pre-SMA and dPMC. Together, these results suggest that early musical training has differential impacts on the maturation of cortico-cerebellar networks important for optimizing sensorimotor performance. This conclusion is consistent with the hypothesis that connected brain regions interact during development to reciprocally influence brain and behavioral maturation.

Predicting future cognitive decline from non-brain and multimodal brain imaging data in healthy and pathological aging.

Previous literature has focused on predicting a diagnostic label from structural brain imaging. Since subtle changes in the brain precede a cognitive decline in healthy and pathological aging, our study predicts future decline as a continuous trajectory instead. Here, we tested whether baseline multimodal neuroimaging data improve the prediction of future cognitive decline in healthy and pathological aging. Nonbrain data (demographics, clinical, and neuropsychological scores), structural MRI, and functional connectivity data from OASIS-3 (N = 662; age = 46-96 years) were entered into cross-validated multitarget random forest models to predict future cognitive decline (measured by CDR and MMSE), on average 5.8 years into the future. The analysis was preregistered, and all analysis code is publicly available. Combining non-brain with structural data improved the continuous prediction of future cognitive decline (best test-set performance: R2 = 0.42). Cognitive performance, daily functioning, and subcortical volume drove the performance of our model. Including functional connectivity did not improve predictive accuracy. In the future, the prognosis of age-related cognitive decline may enable earlier and more effective individualized cognitive, pharmacological, and behavioral interventions.

Motor sequences; separating the sequence from the motor. A longitudinal rsfMRI study.

In motor learning, sequence specificity, i.e. the learning of specific sequential associations, has predominantly been studied using task-based fMRI paradigms. However, offline changes in resting state functional connectivity after sequence-specific motor learning are less well understood. Previous research has established that plastic changes following motor learning can be divided into stages including fast learning, slow learning and retention. A description of how resting state functional connectivity after sequence-specific motor sequence learning (MSL) develops across these stages is missing. This study aimed to identify plastic alterations in whole-brain functional connectivity after learning a complex motor sequence by contrasting an active group who learned a complex sequence with a control group who performed a control task matched for motor execution. Resting state fMRI and behavioural performance were collected in both groups over the course of 5 consecutive training days and at follow-up after 12 days to encompass fast learning, slow learning, overall learning and retention. Between-group interaction analyses showed sequence-specific decreases in functional connectivity during overall learning in the right supplementary motor area (SMA). We found that connectivity changes in a key region of the motor network, the superior parietal cortex (SPC) were not a result of sequence-specific learning but were instead linked to motor execution. Our study confirms the sequence-specific role of SMA that has previously been identified in online task-based learning studies, and extends it to resting state network changes after sequence-specific MSL.