Effect of a physiotherapy-directed rehabilitation programme on patients with multidirectional instability of the glenohumeral joint: a multimodal interventional MRI study protocol.

INTRODUCTION: Altered neuromuscular control of the scapula and humeral head is a typical feature of multidirectional instability (MDI) of the glenohumeral joint, suggesting a central component to this condition. A previous randomised controlled trial showed MDI patients participating in the Watson Instability Program 1 (WIP1) had significantly improved clinical outcomes compared with a general shoulder strength programme. The aim of this paper is to outline a multimodal MRI protocol to identify potential ameliorative effects of the WIP1 on the brain. METHODS AND ANALYSIS: Thirty female participants aged 18-35 years with right-sided atraumatic MDI and 30 matched controls will be recruited. MDI patients will participate in 24 weeks of the WIP1, involving prescription and progression of a home exercise programme. Multimodal MRI scans will be collected from both groups at baseline and in MDI patients at follow-up. Potential brain changes (primary outcome 1) in MDI patients will be probed using region-of-interest (ROI) and whole-brain approaches. ROIs will depict areas of functional alteration in MDI patients during executed and imagined shoulder movements (MDI vs controls at baseline), then examining the effects of the 24-week WIP1 intervention (baseline vs follow-up in MDI patients only). Whole-brain analyses will examine baseline versus follow-up voxel-wise measures in MDI patients only. Outcome measures used to assess WIP1 efficacy will include the Western Ontario Shoulder Index and the Melbourne Instability Shoulder Score (primary outcomes 2 and 3). Secondary outcomes will include the Tampa Scale for Kinesiophobia, Short Form Orebro, Global Rating of Change Score, muscle strength, scapular upward rotation, programme compliance and adverse events. DISCUSSION: This trial will establish if the WIP1 is associated with brain changes in MDI. ETHICS AND DISSEMINATION: Participant confidentiality will be maintained with publication of results. Swinburne Human Research Ethics Committee (Ref: 20202806-5692). TRIAL REGISTRATION NUMBER: Australian New Zealand Clinical Trial Registry (ACTRN12621001207808).

Neurodesk: an accessible, flexible and portable data analysis environment for reproducible neuroimaging.

Neuroimaging research requires purpose-built analysis software, which is challenging to install and may produce different results across computing environments. The community-oriented, open-source Neurodesk platform ( https://www.neurodesk.org/ ) harnesses a comprehensive and growing suite of neuroimaging software containers. Neurodesk includes a browser-accessible virtual desktop, command-line interface and computational notebook compatibility, allowing for accessible, flexible, portable and fully reproducible neuroimaging analysis on personal workstations, high-performance computers and the cloud.

MFCSC: Novel method to calculate mismatch between functional and structural brain connectomes, and its application for detecting hemispheric functional specialisations.

We introduce a novel connectomics method, MFCSC, that integrates information on structural connectivity (SC) from diffusion MRI tractography and functional connectivity (FC) from functional MRI, at individual subject level. The MFCSC method is based on the fact that SC only broadly predicts FC, and for each connection in the brain, the method calculates a value that quantifies the mismatch that often still exists between the two modalities. To capture underlying physiological properties, MFCSC minimises biases in SC and addresses challenges with the multimodal analysis, including by using a data-driven normalisation approach. We ran MFCSC on data from the Human Connectome Project and used the output to detect pairs of left and right unilateral connections that have distinct relationship between structure and function in each hemisphere; we suggest that this reflects cases of hemispheric functional specialisation. In conclusion, the MFCSC method provides new information on brain organisation that may not be inferred from an analysis that considers SC and FC separately.

The association of dietary and nutrient patterns on neurocognitive decline: A systematic review of MRI and PET studies.

BACKGROUND: As the global population ages, there has been a growing incidence of neurodegenerative diseases such as Alzheimer's. More recently, studies exploring the relationship between dietary patterns and neuroimaging outcomes have received particular attention. This systematic literature review provides a structured overview of the association between dietary and nutrient patterns on neuroimaging outcomes and cognitive markers in middle-aged to older adults. A comprehensive literature search was conducted to find relevant articles published from 1999 to date using the following databases Ovid MEDLINE, Embase, PubMed, Scopus and Web of Science. The inclusion criteria for the articles comprised studies reporting on the association between dietary patterns and neuroimaging outcomes, which includes both specific pathological hallmarks of neurodegenerative diseases such as Aß and tau and nonspecific markers such as structural MRI and glucose metabolism. The risk of bias was evaluated using the Quality Assessment tool from the National Heart, Lung, and Blood Institute of the National Institutes of Health. The results were then organized into a summary of results table, collated based on synthesis without meta-analysis. After conducting the search, 6050 records were extracted and screened for eligibility, with 107 eligible for full-text screening and 42 articles ultimately being included in this review. The results of the systematic review indicate that there is some evidence suggesting that healthy dietary and nutrient patterns were associated with neuroimaging measures, indicative of a protective influence on neurodegeneration and brain ageing. Conversely, unhealthy dietary and nutrient patterns showed evidence pointing to decreased brain volumes, poorer cognition and increased Aß deposition. Future research should focus on sensitive neuroimaging acquisition and analysis methods, to study early neurodegenerative changes and identify critical periods for interventions and prevention. SYSTEMATIC REVIEW REGISTRATION: PROSPERO registration no, CRD42020194444).

Neurodesk: An accessible, flexible, and portable data analysis environment for reproducible neuroimaging.

Neuroimaging data analysis often requires purpose-built software, which can be challenging to install and may produce different results across computing environments. Beyond being a roadblock to neuroscientists, these issues of accessibility and portability can hamper the reproducibility of neuroimaging data analysis pipelines. Here, we introduce the Neurodesk platform, which harnesses software containers to support a comprehensive and growing suite of neuroimaging software (https://www.neurodesk.org/). Neurodesk includes a browser-accessible virtual desktop environment and a command line interface, mediating access to containerized neuroimaging software libraries on various computing platforms, including personal and high-performance computers, cloud computing and Jupyter Notebooks. This community-oriented, open-source platform enables a paradigm shift for neuroimaging data analysis, allowing for accessible, flexible, fully reproducible, and portable data analysis pipelines.

Investigating white matter structure in social anxiety disorder using fixel-based analysis.

Social anxiety disorder (SAD) is one of the most common mental health disorders in youth, defined by a persistent and intense fear of negative evaluation by others. Recent research has examined its neurological underpinnings, including structural connectivity changes in the brain. This has been examined through measurement of the white matter (WM) structure of fibre pathways. Previous studies have shown inconsistent results. This study attempts to resolve these inconsistencies by utilising a recently proposed, advanced method for diffusion MRI analysis, known as fixel based analysis (FBA). This technique enables examination of WM macro- and micro-structure with measures of fibre density (FD), fibre bundle cross-section (FC) and fibre density-cross-section (FDC). This study evidenced increased FDC in a region of the right superior longitudinal fasciculus (SLF) from a whole brain FBA, along with increased FC and FDC from an analysis restricted to a-priori tracts of interest, in regions of the right inferior longitudinal fasciculus (R-ILF). The average FDC of the left uncinate fasciculus (L-UF) was also increased. To examine the relationship between WM structure and severity of symptoms, these FBA metrics were correlated with Leibowitz Social Anxiety Scale (LSAS) scores. From the tract-restricted analysis an inverse correlation between FC and LSAS scores was found in the R-ILF. The average FC of the R-ILF was also inversely correlated with symptom severity. By utilising a more sensitive and fibre-specific method of analysis than previous studies, these findings highlight innovative outcomes relating to white matter in numerous fibre tracts.

Fixel-based Analysis of Diffusion MRI: Methods, Applications, Challenges and Opportunities.

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.

Is removal of weak connections necessary for graph-theoretical analysis of dense weighted structural connectomes from diffusion MRI?

Recent advances in diffusion MRI tractography permit the generation of dense weighted structural connectomes that offer greater insight into brain organization. However, these efforts are hampered by the lack of consensus on how to extract topological measures from the resulting graphs. Here we evaluate the common practice of removing the graphs' weak connections, which is primarily intended to eliminate spurious connections and emphasize strong connections. Because this processing step requires arbitrary or heuristic-based choices (e.g., setting a threshold level below which connections are removed), and such choices might complicate statistical analysis and inter-study comparisons, in this work we test whether removing weak connections is indeed necessary. To this end, we systematically evaluated the effect of removing weak connections on a range of popular graph-theoretical metrics. Specifically, we investigated if (and at what extent) removal of weak connections introduces a statistically significant difference between two otherwise equal groups of healthy subjects when only applied to one of the groups. Using data from the Human Connectome Project, we found that removal of weak connections had no statistical effect even when removing the weakest ∼70-90% connections. Removing yet a larger extent of weak connections, thus reducing connectivity density even further, did produce a predictably significant effect. However, metric values became sensitive to the exact connectivity density, which has ramifications regarding the stability of the statistical analysis. This pattern persisted whether connections were removed by connection strength threshold or connectivity density, and for connectomes generated using parcellations at different resolutions. Finally, we showed that the same pattern also applies for data from a clinical-grade MRI scanner. In conclusion, our analysis revealed that removing weak connections is not necessary for graph-theoretical analysis of dense weighted connectomes. Because removal of weak connections provides no practical utility to offset the undesirable requirement for arbitrary or heuristic-based choices, we recommend that this step is avoided in future studies.

White matter pathways in persistent developmental stuttering: Lessons from tractography.

PURPOSE: Fluent speech production relies on the coordinated processing of multiple brain regions. This highlights the role of neural pathways that connect distinct brain regions in producing fluent speech. Here, we aim to investigate the role of the white matter pathways in persistent developmental stuttering (PDS), where speech fluency is disrupted. METHODS: We use diffusion weighted imaging and tractography to compare the white matter properties between adults who do and do not stutter. We compare the diffusion properties along 18 major cerebral white matter pathways. We complement the analysis with an overview of the methodology and a roadmap of the pathways implicated in PDS according to the existing literature. RESULTS: We report differences in the microstructural properties of the anterior callosum, the right inferior longitudinal fasciculus and the right cingulum in people who stutter compared with fluent controls. CONCLUSIONS: Persistent developmental stuttering is consistently associated with differences in bilateral distributed networks. We review evidence showing that PDS involves differences in bilateral dorsal fronto-temporal and fronto-parietal pathways, in callosal pathways, in several motor pathways and in basal ganglia connections. This entails an important role for long range white matter pathways in this disorder. Using a wide-lens analysis, we demonstrate differences in additional, right hemispheric pathways, which go beyond the replicable findings in the literature. This suggests that the affected circuits may extend beyond the known language and motor pathways.

A systematic literature review of neuroimaging research on developmental stuttering between 1995 and 2016.

PURPOSE: Stuttering is a disorder that affects millions of people all over the world. Over the past two decades, there has been a great deal of interest in investigating the neural basis of the disorder. This systematic literature review is intended to provide a comprehensive summary of the neuroimaging literature on developmental stuttering. It is a resource for researchers to quickly and easily identify relevant studies for their areas of interest and enable them to determine the most appropriate methodology to utilize in their work. The review also highlights gaps in the literature in terms of methodology and areas of research. METHODS: We conducted a systematic literature review on neuroimaging studies on developmental stuttering according to the PRISMA guidelines. We searched for articles in the pubmed database containing "stuttering" OR "stammering" AND either "MRI", "PET", "EEG", "MEG", "TMS"or "brain" that were published between 1995/​01/​01 and 2016/​01/​01. RESULTS: The search returned a total of 359 items with an additional 26 identified from a manual search. Of these, there were a total of 111 full text articles that met criteria for inclusion in the systematic literature review. We also discuss neuroimaging studies on developmental stuttering published throughout 2016. The discussion of the results is organized first by methodology and second by population (i.e., adults or children) and includes tables that contain all items returned by the search. CONCLUSIONS: There are widespread abnormalities in the structural architecture and functional organization of the brains of adults and children who stutter. These are evident not only in speech tasks, but also non-speech tasks. Future research should make greater use of functional neuroimaging and noninvasive brain stimulation, and employ structural methodologies that have greater sensitivity. Newly planned studies should also investigate sex differences, focus on augmenting treatment, examine moments of dysfluency and longitudinally or cross-sectionally investigate developmental trajectories in stuttering.

Beyond production: Brain responses during speech perception in adults who stutter.

Developmental stuttering is a speech disorder that disrupts the ability to produce speech fluently. While stuttering is typically diagnosed based on one's behavior during speech production, some models suggest that it involves more central representations of language, and thus may affect language perception as well. Here we tested the hypothesis that developmental stuttering implicates neural systems involved in language perception, in a task that manipulates comprehensibility without an overt speech production component. We used functional magnetic resonance imaging to measure blood oxygenation level dependent (BOLD) signals in adults who do and do not stutter, while they were engaged in an incidental speech perception task. We found that speech perception evokes stronger activation in adults who stutter (AWS) compared to controls, specifically in the right inferior frontal gyrus (RIFG) and in left Heschl's gyrus (LHG). Significant differences were additionally found in the lateralization of response in the inferior frontal cortex: AWS showed bilateral inferior frontal activity, while controls showed a left lateralized pattern of activation. These findings suggest that developmental stuttering is associated with an imbalanced neural network for speech processing, which is not limited to speech production, but also affects cortical responses during speech perception.

Dorsal and ventral language pathways in persistent developmental stuttering.

Persistent developmental stuttering is a speech disorder that affects an individual's ability to fluently produce speech. While the disorder mainly manifests in situations that require language production, it is still unclear whether persistent developmental stuttering is indeed a language impairment, and if so, which language stream is implicated in people who stutter. In this study, we take a neuroanatomical approach to this question by examining the structural properties of the dorsal and ventral language pathways in adults who stutter (AWS) and fluent controls. We use diffusion magnetic resonance imaging and individualized tract identification to extract white matter volumes and diffusion properties of these tracts in samples of adults who do and do not stutter. We further quantify diffusion properties at multiple points along the tract and examine group differences within these diffusivity profiles. Our results show differences in the dorsal, but not in the ventral, language-related tracts. Specifically, AWS show reduced volume of the left dorsal stream, as well as lower anisotropy in the right dorsal stream. These data provide neuroanatomical support for the view that stuttering involves an impairment in the bidirectional mapping between auditory and articulatory cortices supported by the dorsal pathways, not in lexical access and semantic aspects of language processing which are thought to rely more heavily on the left ventral pathways.

The frontal aslant tract underlies speech fluency in persistent developmental stuttering.

The frontal aslant tract (FAT) is a pathway that connects the inferior frontal gyrus with the supplementary motor area (SMA) and pre-SMA. The FAT was recently identified and introduced as part of a "motor stream" that plays an important role in speech production. In this study, we use diffusion imaging to examine the hypothesis that the FAT underlies speech fluency, by studying its properties in individuals with persistent developmental stuttering, a speech disorder that disrupts the production of fluent speech. We use tractography to quantify the volume and diffusion properties of the FAT in a group of adults who stutter (AWS) and fluent controls. Additionally, we use tractography to extract these measures from the corticospinal tract (CST), a well-known component of the motor system. We compute diffusion measures in multiple points along the tracts, and examine the correlation between these diffusion measures and behavioral measures of speech fluency. Our data show increased mean diffusivity in bilateral FAT of AWS compared with controls. In addition, the results show regions within the left FAT and the left CST where diffusivity values are increased in AWS compared with controls. Last, we report that in AWS, diffusivity values measured within sub-regions of the left FAT negatively correlate with speech fluency. Our findings are the first to relate the FAT with fluent speech production in stuttering, thus adding to the current knowledge of the functional role that this tract plays in speech production and to the literature of the etiology of persistent developmental stuttering.

Reduced fractional anisotropy in the anterior corpus callosum is associated with reduced speech fluency in persistent developmental stuttering.

Developmental stuttering is a speech disorder that severely limits one's ability to communicate. White matter anomalies were reported in stuttering, but their functional significance is unclear. We analyzed the relation between white matter properties and speech fluency in adults who stutter (AWS). We used diffusion tensor imaging with tract-based spatial statistics, and examined group differences as well as correlations with behavioral fluency measures. We detected a region in the anterior corpus callosum with significantly lower fractional anisotropy in AWS relative to controls. Within the AWS group, reduced anisotropy in that region is associated with reduced fluency. A statistically significant interaction was found between group and age in two additional regions: the left Rolandic operculum and the left posterior corpus callosum. Our findings suggest that anterior callosal anomaly in stuttering may represent a maladaptive reduction in interhemispheric inhibition, possibly leading to a disadvantageous recruitment of right frontal cortex in speech production.

Computational modeling of stuttering caused by impairments in a basal ganglia thalamo-cortical circuit involved in syllable selection and initiation.

Atypical white-matter integrity and elevated dopamine levels have been reported for individuals who stutter. We investigated how such abnormalities may lead to speech dysfluencies due to their effects on a syllable-sequencing circuit that consists of basal ganglia (BG), thalamus, and left ventral premotor cortex (vPMC). "Neurally impaired" versions of the neurocomputational speech production model GODIVA were utilized to test two hypotheses: (1) that white-matter abnormalities disturb the circuit via corticostriatal projections carrying copies of executed motor commands and (2) that dopaminergic abnormalities disturb the circuit via the striatum. Simulation results support both hypotheses: in both scenarios, the neural abnormalities delay readout of the next syllable's motor program, leading to dysfluency. The results also account for brain imaging findings during dysfluent speech. It is concluded that each of the two abnormality types can cause stuttering moments, probably by affecting the same BG-thalamus-vPMC circuit.

Overreliance on auditory feedback may lead to sound/syllable repetitions: simulations of stuttering and fluency-inducing conditions with a neural model of speech production.

UNLABELLED: This paper investigates the hypothesis that stuttering may result in part from impaired readout of feedforward control of speech, which forces persons who stutter (PWS) to produce speech with a motor strategy that is weighted too much toward auditory feedback control. Over-reliance on feedback control leads to production errors which if they grow large enough, can cause the motor system to "reset" and repeat the current syllable. This hypothesis is investigated using computer simulations of a "neurally impaired" version of the DIVA model, a neural network model of speech acquisition and production. The model's outputs are compared to published acoustic data from PWS' fluent speech, and to combined acoustic and articulatory movement data collected from the dysfluent speech of one PWS. The simulations mimic the errors observed in the PWS subject's speech, as well as the repairs of these errors. Additional simulations were able to account for enhancements of fluency gained by slowed/prolonged speech and masking noise. Together these results support the hypothesis that many dysfluencies in stuttering are due to a bias away from feedforward control and toward feedback control. EDUCATIONAL OBJECTIVES: The reader will be able to (a) describe the contribution of auditory feedback control and feedforward control to normal and stuttered speech production, (b) summarize the neural modeling approach to speech production and its application to stuttering, and (c) explain how the DIVA model accounts for enhancements of fluency gained by slowed/prolonged speech and masking noise.