Body size interacts with the structure of the central nervous system: A multi-center in vivo neuroimaging study.

Clinical research emphasizes the implementation of rigorous and reproducible study designs that rely on between-group matching or controlling for sources of biological variation such as subject's sex and age. However, corrections for body size (i.e. height and weight) are mostly lacking in clinical neuroimaging designs. This study investigates the importance of body size parameters in their relationship with spinal cord (SC) and brain magnetic resonance imaging (MRI) metrics. Data were derived from a cosmopolitan population of 267 healthy human adults (age 30.1±6.6 years old, 125 females). We show that body height correlated strongly or moderately with brain gray matter (GM) volume, cortical GM volume, total cerebellar volume, brainstem volume, and cross-sectional area (CSA) of cervical SC white matter (CSA-WM; 0.44≤r≤0.62). In comparison, age correlated weakly with cortical GM volume, precentral GM volume, and cortical thickness (-0.21≥r≥-0.27). Body weight correlated weakly with magnetization transfer ratio in the SC WM, dorsal columns, and lateral corticospinal tracts (-0.20≥r≥-0.23). Body weight further correlated weakly with the mean diffusivity derived from diffusion tensor imaging (DTI) in SC WM (r=-0.20) and dorsal columns (-0.21), but only in males. CSA-WM correlated strongly or moderately with brain volumes (0.39≤r≤0.64), and weakly with precentral gyrus thickness and DTI-based fractional anisotropy in SC dorsal columns and SC lateral corticospinal tracts (-0.22≥r≥-0.25). Linear mixture of sex and age explained 26±10% of data variance in brain volumetry and SC CSA. The amount of explained variance increased at 33±11% when body height was added into the mixture model. Age itself explained only 2±2% of such variance. In conclusion, body size is a significant biological variable. Along with sex and age, body size should therefore be included as a mandatory variable in the design of clinical neuroimaging studies examining SC and brain structure.

Spinal Cord fMRI: A New Window into the Central Nervous System.

With the brain, the spinal cord forms the central nervous system. Initially considered a passive relay between the brain and the periphery, the spinal cord is now recognized as being active and plastic. Yet, it remains largely overlooked by the human neuroscience community, in stark contrast with the wealth of research investigating the brain. In this review, we argue that fMRI, traditionally used to image cerebral function, can be extended beyond the brain to help unravel spinal mechanisms involved in human behaviors. To this end, we first outline strategies that have been proposed to tackle the challenges inherent to spinal cord fMRI. Then, we discuss how they have been utilized to provide insights into the functional organization of spinal sensorimotor circuits, highlighting their potential to address fundamental and clinical questions. By summarizing guidelines and applications of spinal cord fMRI, we hope to stimulate and support further research into this promising yet underexplored field.

Post-stroke reorganization of transient brain activity characterizes deficits and recovery of cognitive functions.

Functional magnetic resonance imaging (fMRI) has been widely employed to study stroke pathophysiology. In particular, analyses of fMRI signals at rest were directed at quantifying the impact of stroke on spatial features of brain networks. However, brain networks have intrinsic time features that were, so far, disregarded in these analyses. In consequence, standard fMRI analysis failed to capture temporal imbalance resulting from stroke lesions, hence restricting their ability to reveal the interdependent pathological changes in structural and temporal network features following stroke. Here, we longitudinally analyzed hemodynamic-informed transient activity in a large cohort of stroke patients (n = 103) to assess spatial and temporal changes of brain networks after stroke. Metrics extracted from the hemodynamic-informed transient activity were replicable within- and between-individuals in healthy participants, hence supporting their robustness and their clinical applicability. While large-scale spatial patterns of brain networks were preserved after stroke, their durations were altered, with stroke subjects exhibiting a varied pattern of longer and shorter network activations compared to healthy individuals. Specifically, patients showed a longer duration in the lateral precentral gyrus and anterior cingulum, and a shorter duration in the occipital lobe and in the cerebellum. These temporal alterations were associated with white matter damage in projection and association pathways. Furthermore, they were tied to deficits in specific behavioral domains as restoration of healthy brain dynamics paralleled recovery of cognitive functions (attention, language and spatial memory), but was not significantly correlated to motor recovery. These findings underscore the critical importance of network temporal properties in dissecting the pathophysiology of brain changes after stroke, thus shedding new light on the clinical potential of time-resolved methods for fMRI analysis.

Activity-dependent spinal cord neuromodulation rapidly restores trunk and leg motor functions after complete paralysis.

Epidural electrical stimulation (EES) targeting the dorsal roots of lumbosacral segments restores walking in people with spinal cord injury (SCI). However, EES is delivered with multielectrode paddle leads that were originally designed to target the dorsal column of the spinal cord. Here, we hypothesized that an arrangement of electrodes targeting the ensemble of dorsal roots involved in leg and trunk movements would result in superior efficacy, restoring more diverse motor activities after the most severe SCI. To test this hypothesis, we established a computational framework that informed the optimal arrangement of electrodes on a new paddle lead and guided its neurosurgical positioning. We also developed software supporting the rapid configuration of activity-specific stimulation programs that reproduced the natural activation of motor neurons underlying each activity. We tested these neurotechnologies in three individuals with complete sensorimotor paralysis as part of an ongoing clinical trial ( www.clinicaltrials.gov identifier NCT02936453). Within a single day, activity-specific stimulation programs enabled these three individuals to stand, walk, cycle, swim and control trunk movements. Neurorehabilitation mediated sufficient improvement to restore these activities in community settings, opening a realistic path to support everyday mobility with EES in people with SCI.

Towards reliable spinal cord fMRI: Assessment of common imaging protocols.

Functional magnetic resonance imaging (fMRI) has revolutionized the investigation of brain function. Similar approaches can be translated to probe spinal mechanisms. However, imaging the spinal cord remains challenging, notably due to its size and location. Technological advances are gradually tackling these issues, though there is yet no consensus on optimal acquisition protocols. In this study, we assessed the performance of three sequences during a simple motor task and at rest, in 15 healthy humans. Building upon recent literature, we selected three imaging protocols: a sequence integrating outer volume suppression (OVS) and two sequences implementing inner field-of-view imaging (ZOOMit) with different spatial and temporal resolutions. Images acquired using the OVS sequence appeared more prone to breathing-induced signal fluctuations, though they exhibited a higher temporal signal-to-noise ratio than ZOOMit sequences. Conversely, the spatial signal-to-noise ratio was higher for the two ZOOMit schemes. In spite of these differences in signal properties, all sequences yielded comparable performance in detecting group-level task-related activity, observed in the expected spinal levels. Nevertheless, our results suggest a superior sensitivity and robustness of patterns imaged using the OVS acquisition scheme. To analyze the data acquired at rest, we deployed a dynamic functional connectivity framework, SpiCiCAP, and we evaluated the ability of the three acquisition schemes to disentangle intrinsic spinal signals. We demonstrated that meaningful subdivisions of the spinal cord's functional architecture could be uncovered for all three sequences, with similar spatio-temporal properties across acquisition parameters. Cleaner and more stable components were, however, obtained using ZOOMit sequences. This study emphasizes the potential of fMRI as a robust tool to image spinal activity in vivo and it highlights specificities and similarities of three acquisition methods. This represents a key step towards the establishment of standardized spinal cord fMRI protocols.

Open-access quantitative MRI data of the spinal cord and reproducibility across participants, sites and manufacturers.

In a companion paper by Cohen-Adad et al. we introduce the spine generic quantitative MRI protocol that provides valuable metrics for assessing spinal cord macrostructural and microstructural integrity. This protocol was used to acquire a single subject dataset across 19 centers and a multi-subject dataset across 42 centers (for a total of 260 participants), spanning the three main MRI manufacturers: GE, Philips and Siemens. Both datasets are publicly available via git-annex. Data were analysed using the Spinal Cord Toolbox to produce normative values as well as inter/intra-site and inter/intra-manufacturer statistics. Reproducibility for the spine generic protocol was high across sites and manufacturers, with an average inter-site coefficient of variation of less than 5% for all the metrics. Full documentation and results can be found at https://spine-generic.rtfd.io/ . The datasets and analysis pipeline will help pave the way towards accessible and reproducible quantitative MRI in the spinal cord.

Generic acquisition protocol for quantitative MRI of the spinal cord.

Quantitative spinal cord (SC) magnetic resonance imaging (MRI) presents many challenges, including a lack of standardized imaging protocols. Here we present a prospectively harmonized quantitative MRI protocol, which we refer to as the spine generic protocol, for users of 3T MRI systems from the three main manufacturers: GE, Philips and Siemens. The protocol provides guidance for assessing SC macrostructural and microstructural integrity: T1-weighted and T2-weighted imaging for SC cross-sectional area computation, multi-echo gradient echo for gray matter cross-sectional area, and magnetization transfer and diffusion weighted imaging for assessing white matter microstructure. In a companion paper from the same authors, the spine generic protocol was used to acquire data across 42 centers in 260 healthy subjects. The key details of the spine generic protocol are also available in an open-access document that can be found at https://github.com/spine-generic/protocols . The protocol will serve as a starting point for researchers and clinicians implementing new SC imaging initiatives so that, in the future, inclusion of the SC in neuroimaging protocols will be more common. The protocol could be implemented by any trained MR technician or by a researcher/clinician familiar with MRI acquisition.

Dynamic Functional Connectivity of Resting-State Spinal Cord fMRI Reveals Fine-Grained Intrinsic Architecture.

The neuroimaging community has shown tremendous interest in exploring the brain's spontaneous activity using functional magnetic resonance imaging (fMRI). On the contrary, the spinal cord has been largely overlooked despite its pivotal role in processing sensorimotor signals. Only a handful of studies have probed the organization of spinal resting-state fluctuations, always using static measures of connectivity. Many innovative approaches have emerged for analyzing dynamics of brain fMRI, but they have not yet been applied to the spinal cord, although they could help disentangle its functional architecture. Here, we leverage a dynamic connectivity method based on the clustering of hemodynamic-informed transients to unravel the rich dynamic organization of spinal resting-state signals. We test this approach in 19 healthy subjects, uncovering fine-grained spinal components and highlighting their neuroanatomical and physiological nature. We provide a versatile tool, the spinal innovation-driven co-activation patterns (SpiCiCAP) framework, to characterize spinal circuits during rest and task, as well as their disruption in neurological disorders.

A multimodal approach to capture post-stroke temporal dynamics of recovery.

OBJECTIVE: Several training programs have been developed in the past to restore motor functions after stroke. Their efficacy strongly relies on the possibility to assess individual levels of impairment and recovery rate. However, commonly used clinical scales rely mainly on subjective functional assessments and are not able to provide a complete description of patients' neuro-biomechanical status. Therefore, current clinical tests should be integrated with specific physiological measurements, i.e. kinematic, muscular, and brain activities, to obtain a deep understanding of patients' condition and of its evolution through time and rehabilitative intervention. APPROACH: We proposed a multivariate approach for motor control assessment that simultaneously measures kinematic, muscle and brain activity and combines the main physiological variables extracted from these signals using principal component analysis (PCA). We tested it in a group of six sub-acute stroke subjects evaluated extensively before and after a four-week training, using an upper-limb exoskeleton while performing a reaching task, along with brain and muscle measurements. MAIN RESULTS: After training, all subjects exhibited clinical improvements correlating with changes in kinematics, muscle synergies, and spinal maps. Movements were smoother and faster, while muscle synergies increased in numbers and became more similar to those of the healthy controls. These findings were coupled with changes in cortical oscillations depicted by EEG-topographies. When combining these physiological variables using PCA, we found that (i) patients' kinematic and spinal maps parameters improved continuously during the four assessments; (ii) muscle coordination augmented mainly during treatment, and (iii) brain oscillations recovered mostly pre-treatment as a consequence of short-term subacute changes. SIGNIFICANCE: Although these are preliminary results, the proposed approach has the potential of identifying significant biomarkers for patient stratification as well as for the design of more effective rehabilitation protocols.

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

BACKGROUND: In the past years, robotic systems have become increasingly popular in upper limb rehabilitation. Nevertheless, clinical studies have so far not been able to confirm superior efficacy of robotic therapy over conventional methods. The personalization of robot-aided therapy according to the patients' individual motor deficits has been suggested as a pivotal step to improve the clinical outcome of such approaches. METHODS: Here, we present a model-based approach to personalize robot-aided rehabilitation therapy within training sessions. The proposed method combines the information from different motor performance measures recorded from the robot to continuously estimate patients' motor improvement for a series of point-to-point reaching movements in different directions. Additionally, it comprises a personalization routine to automatically adapt the rehabilitation training. We engineered our approach using an upper-limb exoskeleton. The implementation was tested with 17 healthy subjects, who underwent a motor-adaptation paradigm, and two subacute stroke patients, exhibiting different degrees of motor impairment, who participated in a pilot test undergoing rehabilitative motor training. RESULTS: The results of the exploratory study with healthy subjects showed that the participants divided into fast and slow adapters. The model was able to correctly estimate distinct motor improvement progressions between the two groups of participants while proposing individual training protocols. For the two pilot patients, an analysis of the selected motor performance measures showed that both patients were able to retain the improvements gained during training when reaching movements were reintroduced at a later stage. These results suggest that the automated training adaptation was appropriately timed and specifically tailored to the abilities of each individual. CONCLUSIONS: The results of our exploratory study demonstrated the feasibility of the proposed model-based approach for the personalization of robot-aided rehabilitation therapy. The pilot test with two subacute stroke patients further supported our approach, while providing encouraging results for the applicability in clinical settings. Trial registration This study is registered in ClinicalTrials.gov (NCT02770300, registered 30 March 2016, https://clinicaltrials.gov/ct2/show/NCT02770300).

Functional imaging of rostrocaudal spinal activity during upper limb motor tasks.

The spinal cord is the main interface between the brain and the periphery. It notably plays a central role in motor control, as spinal motoneurons activate skeletal muscles involved in voluntary movements. Yet, the spinal mechanisms underlying human movement generation have not been completely elucidated. In this regard, functional magnetic resonance imaging (fMRI) represents a potential tool to probe spinal cord function non-invasively and with high spatial resolution. Nonetheless, a thorough characterization of this approach is still lacking, currently limiting its impact. Here, we aimed at systematically quantifying to which extent fMRI can reveal spinal cord activity along the rostrocaudal direction. We investigated changes in the blood oxygenation level dependent signal of the human cervical spinal cord during bimanual upper limb movements (wrist extension, wrist adduction and finger abduction) in nineteen healthy volunteers. Prior to scanning, we recorded the muscle activity associated with these movements in order to reconstruct the theoretical motor-pool output pattern using an anatomy-based mapping of the electromyographic (EMG) waveforms. EMG-derived spinal maps were characterized by distinct rostrocaudal patterns of activation, thus confirming the task-specific features of the different movements. Analogous activation patterns were captured using spinal cord fMRI. Finally, an additional fMRI dataset was acquired from a subset of the participants (n = 6) to deploy a multivoxel pattern analysis, which allowed successful decoding of movements. These combined results suggest that spinal cord fMRI can be used to image rostrocaudal activation patterns reflecting the underlying activity of the motoneuron pools innervating the task-related muscles. Spinal cord fMRI offers the prospect of a novel tool to study motor processes and potentially their modification following neurological motor disorders.

Balancing the playing field: collaborative gaming for physical training.

BACKGROUND: Multiplayer video games promoting exercise-based rehabilitation may facilitate motor learning, by increasing motivation through social interaction. However, a major design challenge is to enable meaningful inter-subject interaction, whilst allowing for significant skill differences between players. We present a novel motor-training paradigm that allows real-time collaboration and performance enhancement, across a wide range of inter-subject skill mismatches, including disabled vs. able-bodied partnerships. METHODS: A virtual task consisting of a dynamic ball on a beam, is controlled at each end using independent digital force-sensing handgrips. Interaction is mediated through simulated physical coupling and locally-redundant control. Game performance was measured in 16 healthy-healthy and 16 patient-expert dyads, where patients were hemiparetic stroke survivors using their impaired arm. Dual-player was compared to single-player performance, in terms of score, target tracking, stability, effort and smoothness; and questionnaires probing user-experience and engagement. RESULTS: Performance of less-able subjects (as ranked from single-player ability) was enhanced by dual-player mode, by an amount proportionate to the partnership's mismatch. The more abled partners' performances decreased by a similar amount. Such zero-sum interactions were observed for both healthy-healthy and patient-expert interactions. Dual-player was preferred by the majority of players independent of baseline ability and subject group; healthy subjects also felt more challenged, and patients more skilled. CONCLUSION: This is the first demonstration of implicit skill balancing in a truly collaborative virtual training task leading to heightened engagement, across both healthy subjects and stroke patients.