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•The fixel-based analysis framework was proposed for fibre-specific statistical analysis of diffusion MRI data.•A “fixel” represents an individual fibre population in a voxel, allowing for increased specificity over voxel-wise measures.•A state-of-the-art fixel-based analysis pipeline consists of several bespoke steps, but is conceptually similar to a voxel-based analysis.•Fixel-based analysis has seen increased adoption recently, with 75 published studies to date.•The framework has unique benefits and future opportunities, but specific challenges and limitations exist as well. Diffusion MRI has provided the neuroimaging community with a powerful tool to acquire in-vivo data sensitive to microstructural features of white matter, up to 3 orders of magnitude smaller than typical voxel sizes. The key to extracting such valuable information lies in complex modelling techniques, which form the link between the rich diffusion MRI data and various metrics related to the microstructural organization. Over time, increasingly advanced techniques have been developed, up to the point where some diffusion MRI models can now provide access to properties specific to individual fibre populations in each voxel in the presence of multiple “crossing” fibre pathways. While highly valuable, such fibre-specific information poses unique challenges for typical image processing pipelines and statistical analysis. In this work, we review the “Fixel-Based Analysis” (FBA) framework, which implements bespoke solutions to this end. It has recently seen a stark increase in adoption for studies of both typical (healthy) populations as well as a wide range of clinical populations. We describe the main concepts related to Fixel-Based Analyses, as well as the methods and specific steps involved in a state-of-the-art FBA pipeline, with a focus on providing researchers with practical advice on how to interpret results. We also include an overview of the scope of all current FBA studies, categorized across a broad range of neuro-scientific domains, listing key design choices and summarizing their main results and conclusions. Finally, we critically discuss several aspects and challenges involved with the FBA framework, and outline some directions and future opportunities. [Display omitted]

Background Virtual-reality based rehabilitation (VR) shows potential as an engaging and effective way to improve upper-limb function and cognitive abilities following a stroke. However, an updated synthesis of the literature is needed to capture growth in recent research and address gaps in our understanding of factors that may optimize training parameters and treatment effects. Methods Published randomized controlled trials comparing VR to conventional therapy were retrieved from seven electronic databases. Treatment effects (Hedge’s g ) were estimated using a random effects model, with motor and functional outcomes between different protocols compared at the Body Structure/Function , Activity , and Participation levels of the International Classification of Functioning. Results Thirty-three studies were identified, including 971 participants (492 VR participants). VR produced small to medium overall effects ( g  = 0.46; 95% CI: 0.33–0.59, p  < 0.01), above and beyond conventional therapies. Small to medium effects were observed on Body Structure/Function ( g  = 0.41; 95% CI: 0.28–0.55; p  < 0.01) and Activity outcomes ( g  = 0.47; 95% CI: 0.34–0.60, p  < 0.01), while Participation outcomes failed to reach significance ( g  = 0.38; 95% CI: -0.29-1.04, p  = 0.27). Superior benefits for Body Structure/Function ( g  = 0.56) and Activity outcomes ( g  = 0.62) were observed when examining outcomes only from purpose-designed VR systems. Preliminary results ( k  = 4) suggested small to medium effects for cognitive outcomes ( g  = 0.41; 95% CI: 0.28–0.55; p  < 0.01). Moderator analysis found no advantage for higher doses of VR, massed practice training schedules, or greater time since injury. Conclusion VR can effect significant gains on Body Structure/Function and Activity level outcomes, including improvements in cognitive function, for individuals who have sustained a stroke. The evidence supports the use of VR as an adjunct for stroke rehabilitation, with effectiveness evident for a variety of platforms, training parameters, and stages of recovery.

Repetitive transcranial magnetic stimulation (rTMS) is an established treatment for major depressive disorder (MDD), but its clinical efficacy remains rather modest. One reason for this could be that the propagation of rTMS effects via structural connections from the stimulated area to deeper brain structures (such as the cingulate cortices) is suboptimal. We investigated whether structural connectivity — derived from diffusion MRI data — could serve as a biomarker to predict treatment response. We hypothesized that stronger structural connections between the patient-specific stimulation position in the left dorsolateral prefrontal cortex (dlPFC) and the cingulate cortices would predict better clinical outcomes. We applied accelerated intermittent theta burst stimulation (aiTBS) to the left dlPFC in 40 patients with MDD. We correlated baseline structural connectivity, quantified using various metrics (fractional anisotropy, mean diffusivity, tract density, tract volume and number of tracts), with changes in depression severity scores after aiTBS. Exploratory results (p < 0.05) showed that structural connectivity between the patient-specific stimulation site and the caudal and posterior parts of the cingulate cortex had predictive potential for clinical response to aiTBS. We used the diffusion tensor to perform tractography. A main limitation was that multiple fibre directions within voxels could not be resolved, which might have led to missing connections in some patients. Stronger structural frontocingular connections may be of essence to optimally benefit from left dlPFC rTMS treatment in MDD. Even though the results are promising, further investigation with larger numbers of patients, more advanced tractography algorithms and classic daily rTMS treatment paradigms is warranted. http://clinicaltrials.gov/show/NCT01832805

•We introduce a novel multimodal MRI graph metric termed “SC-FC Bandwidth”.•Most FC nodes are mediated by indirect SC.•Nodes with higher SC-FC Bandwidth tend to be closer, and highly synchronous.•High bandwidth SC-FC triangles predominate the somatomotor network.•High-bandwidth SC-FC quads predominate the default mode network. The human brain is a complex network that seamlessly manifests behaviour and cognition. This network comprises neurons that directly, or indirectly mediate communication between brain regions. Here, we show how multilayer/multiplex network analysis provides a suitable framework to uncover the throughput of structural connectivity (SC) to mediate information transfer—giving rise to functional connectivity (FC). We implemented a novel method to reconcile SC and FC using diffusion and resting-state functional MRI connectivity data from 484 subjects (272 females, 212 males; age = 29.15 ± 3.47) from the Human Connectome Project. First, we counted the number of direct and indirect structural paths that mediate FC. FC nodes with indirect SC paths were then weighted according to their least restrictive SC path. We refer to this as SC-FC Bandwidth. We then mapped paths with the highest SC-FC Bandwidth across 7 canonical resting-state networks. We found that most pairs of FC nodes were connected by SC paths of length two and three (SC paths of length >5 were virtually non-existent). Direct SC-FC connections accounted for only 10% of all SC-FC connections. The majority of FC nodes without a direct SC path were mediated by a proportion of two (44%) or three SC path lengths (39%). Only a small proportion of FC nodes were mediated by SC path lengths of four (5%). We found high-bandwidth direct SC-FC connections show dense intra- and sparse inter-network connectivity, with a bilateral, anteroposterior distribution. High bandwidth SC-FC triangles have a right superomedial distribution within the somatomotor network. High-bandwidth SC-FC quads have a superoposterior distribution within the default mode network. Our method allows the measurement of indirect SC-FC using undirected, weighted graphs derived from multimodal MRI data in order to map the location and throughput of SC to mediate FC. An extension of this work may be to explore how SC-FC Bandwidth changes over time, relates to cognition/behavior, and if this measure reflects a marker of neurological injury or psychiatric disorders.

Processing speed on cognitive tasks relies upon efficient communication between widespread regions of the brain. Recently, novel methods of quantifying network communication like ‘navigation efficiency’ have emerged, which aim to be more biologically plausible compared to traditional shortest path length-based measures. However, it is still unclear whether there is a direct link between these communication measures and processing speed. We tested this relationship in forty-five healthy adults (27 females), where processing speed was defined as decision-making time and measured using drift rate from the hierarchical drift diffusion model. Communication measures were calculated from a graph theoretical analysis of the whole-brain structural connectome and of a task-relevant fronto-parietal structural subnetwork, using the large-scale Desikan–Killiany atlas. We found that faster processing speed on trials that require greater cognitive control are correlated with higher navigation efficiency (of both the whole-brain and the task-relevant subnetwork). In contrast, faster processing speed on trials that require more automatic processing are correlated with shorter path length within the task-relevant subnetwork. Our findings reveal that differences in the way communication is modelled between shortest path length and navigation may be sensitive to processing of automatic and controlled responses, respectively. Further, our findings suggest that there is a relationship between the speed of cognitive processing and the structural constraints of the human brain network.

IntroductionCancer-related cognitive impairment is common among people diagnosed with and treated for cancer. This can be a distressing and disabling side effect for impacted individuals. Interventions to mitigate cognitive dysfunction are available, but, to date, most have been trialled in samples that are largely or exclusively composed of people with solid tumours. Intervention strategies to support cognitive functioning are needed, but there is a paucity of research in this area. The main aim of this study is to test the feasibility and acceptability of methods and procedures intended for use in a definitive trial of a web-based cognitive rehabilitation programme, Responding to Cognitive Concerns (eReCog), in people who have received chemotherapy for aggressive lymphoma.Methods and analysisThe proposed study is a single-site, parallel-group, pilot randomised controlled trial, with one baseline and one follow-up (or postintervention) assessment. 38 people from the target population with low perceived cognitive function based on the Cognitive Change Screen will be recruited from a specialist cancer centre between July 2023 and June 2024. After baseline assessment, participants will be randomised one-to-one to receive usual care only (a factsheet about changes in memory and thinking for people with cancer) or eReCog plus usual care. The 4-week eReCog intervention consists of four online modules offering psychoeducation on cognitive impairment associated with cancer and its treatment, skills training for improving memory, and attention and relaxation training. Study outcomes will include the feasibility of recruitment and retention at follow-up assessment (primary outcomes), as well as adherence to, usability of and intrinsic motivation to engage with eReCog, and compliance with study measures. The potential efficacy of eReCog will also be evaluated.Ethics and disseminationEthical approval was granted by the Peter MacCallum Cancer Centre Human Research Ethics Committee in Victoria, Australia (HREC/97384/PMCC). Study findings will be disseminated via peer-reviewed publications and conference presentations.Trial registration numberAustralian New Zealand Clinical Trials Registry, ACTRN12623000705684.

Postural control is a complex sensorimotor task that requires an intact network of white matter connections. The ability to weight proprioceptive signals is crucial for postural control. However, research into central processing of proprioceptive signals for postural control is lacking. This is specifically of interest in individuals with non-specific low back pain (NSLBP), because impairments in postural control have been observed as possible underlying mechanisms of NSLBP. Therefore, the objective was to investigate potential differences in sensorimotor white matter microstructure between individuals with NSLBP and healthy controls, and to determine whether the alterations in individuals with NSLBP are associated with the capacity to weight proprioceptive signals for postural control. The contribution of proprioceptive signals from the ankle and back muscles to postural control was evaluated by local muscle vibration in 18 individuals with NSLBP and 18 healthy controls. Center of pressure displacement in response to muscle vibration was determined during upright standing on a stable and unstable support surface. Diffusion magnetic resonance imaging was applied to examine whether this proprioceptive contribution was associated with sensorimotor white matter microstructure. Individuals with NSLBP showed a trend towards a reduced fractional anisotropy along the left superior cerebellar peduncle compared to healthy controls (p = 0.039). The impaired microstructural integrity of the superior cerebellar peduncle in individuals with NSLBP was significantly correlated with the response to ankle muscle vibration (p<0.003). In individuals with NSLBP, a decreased integrity of the superior cerebellar peduncle was associated with an increased reliance on ankle muscle proprioception, even on unstable support surface, which implies an impaired proprioceptive weighting capacity. Our findings emphasize the importance of the superior cerebellar peduncle in proprioceptive weighting for postural control in individuals with NSLBP.

Cannabis use disorder (CUD) is associated with adverse mental health effects, as well as social and cognitive impairment. Given prevalence rates of CUD are increasing, there is considerable efforts, and need, to identify prognostic markers which may aid in minimising any harm associated with this condition. Previous neuroimaging studies have revealed changes in white matter (WM) organization in people with CUD, though, the findings are mixed. In this study, we applied MRI-based analysis techniques that offer complimentary mechanistic insights, i.e., a connectome approach and fixel-based analysis (FBA) to investigate properties of individual WM fibre populations and their microstructure across the entire brain, providing a highly sensitive approach to detect subtle changes and overcome limitations of previous diffusion models. We compared 56 individuals with CUD (median age 25 years) to a sample of 38 healthy individuals (median age 31.5 years). Compared to controls, those with CUD had significantly increased structural connectivity strength (FDR corrected) across 9 edges between the right parietal cortex and several cortical and subcortical regions, including left orbitofrontal, left temporal pole, and left hippocampus and putamen. Utilizing FBA, WM density was significantly higher in those with CUD (FWE-corrected) across the splenium of the corpus callosum, and lower in the bilateral cingulum and right cerebellum. We observed significant correlation between cannabis use over the past month and connectivity strength of the frontoparietal edge, and between age of regular use and WM density of the bilateral cingulum and right cerebellum. Our findings enhance the understanding of WM architecture alterations associated with CUD.

Traumatic brain injury (TBI) can lead to deficits in gait and posture, which are often asymmetric. A possible factor mediating these deficits may be asymmetry in strength of the leg muscles. However, muscle strength in the lower extremities has rarely been investigated in (young) TBI patients. Here, we investigated associations between lower-extremity muscle weakness, strength asymmetry, and impairments in gait and posture in young TBI patients. A group of young patients with moderate-to-severe TBI (n=19; age, 14 years 11 months ±2 years) and a group of typically developing subjects (n=31; age, 14 years 1 month±3 years) participated in this study. A force platform was used to measure postural sway to quantify balance control during normal standing and during conditions of compromised visual and/or somatosensory feedback. Spatiotemporal gait parameters were assessed during comfortable and fast-speed walking, using an electronic walkway. Muscle strength in four lower-extremity muscle groups was measured bilaterally using a handheld dynamometer. Findings revealed that TBI patients had poorer postural balance scores across all sensory conditions, as compared to typically developing subjects. During comfortable and fast gait, TBI patients demonstrated a lower gait velocity, longer double-support phase, and increased step-length asymmetry. Further, TBI patients had a reduced strength of leg muscles and an increased strength asymmetry. Correlation analyses revealed that asymmetry in muscle strength was predictive of a poorer balance control and a more variable and asymmetric gait. To the best of our knowledge, this is the first study to measure strength asymmetry in leg muscles of a sample of TBI patients and illustrate the importance of muscular asymmetry as a potential marker and possible risk factor of impairments in control of posture and gait.

In bimanual coordination, older and younger adults activate a common cerebral network but the elderly also have additional activation in a secondary network of brain areas to master task performance. It remains unclear whether the functional connectivity within these primary and secondary motor networks differs between the old and the young and whether task difficulty modulates connectivity. We applied graph-theoretical network analysis (GTNA) to task-driven fMRI data in 16 elderly and 16 young participants using a bimanual coordination task including in-phase and anti-phase flexion/extension wrist movements. Network nodes for the GTNA comprised task-relevant brain areas as defined by fMRI activation foci. The elderly matched the motor performance of the young but showed an increased functional connectivity in both networks across a wide range of connectivity metrics, i.e., higher mean connectivity degree, connection strength, network density and efficiency, together with shorter mean communication path length between the network nodes and also a lower betweenness centrality. More difficult movements showed an increased connectivity in both groups. The network connectivity of both groups had \"small world\" character. The present findings indicate (a) that bimanual coordination in the aging brain is associated with a higher functional connectivity even between areas also activated in young adults, independently from task difficulty, and (b) that adequate motor coordination in the context of task-driven bimanual control in older adults may not be solely due to additional neural recruitment but also to aging-related changes of functional relationships between brain regions.