Neighbourhood environments and cognitive health in the longitudinal Personality and Total Health (PATH) through life study: A 12-year follow-up of older Australians.

BACKGROUND: Urban neighbourhood environments may impact older adults' cognitive health. However, longitudinal studies examining key environmental correlates of cognitive health are lacking. We estimated cross-sectional and longitudinal associations of neighbourhood built and natural environments and ambient air pollution with multiple cognitive health outcomes in Australian urban dwellers aged 60+ years. METHODS: The study included 1160 participants of the PATH Through Life study (60+ cohort) who were followed up for 12 years (four assessments; 2001/02 to 2013/15) and with data on socio-demographics, health, cognitive functions and diagnoses, and full residential address. Neighbourhood environmental features encompassed population and street-intersection densities, non-commercial land use mix, transit points, presence of blue space, percentages of commercial land, parkland and tree cover, and annual average PM2.5 and NO2 concentrations. All exposures except for tree cover were assessed at two time points. Generalised additive mixed models estimated associations of person-level average, and within-person changes in, exposures with cognitive functions. Multi-state hidden Markov models estimated the associations of neighbourhood attributes with transitions to/from mild cognitive impairment (MCI). RESULTS: Dense, destination-rich neighbourhoods were associated with a lower likelihood of transition to MCI and reversal to no MCI. Positive cross-sectional and longitudinal associations of non-commercial land use mix, street intersection density and percentage of commercial land were observed especially with global cognition and processing speed. While access to parkland and blue spaces were associated with a lower risk of transition to MCI, the findings related to cognitive functions were mixed and supportive of an effect of parkland on verbal memory only. Higher levels of PM2.5 and NO2 were consistently associated with steeper declines and/or decreases in cognitive functions and worse cognitive states across time. CONCLUSION: To support cognitive health in ageing populations, neighbourhoods need to provide an optimal mix of environmental complexity, destinations and access to the natural environment and, at the same time, minimise ambient air pollution.

Prognostic enrichment for early-stage Huntington's disease: An explainable machine learning approach for clinical trial.

BACKGROUND: In Huntington's disease clinical trials, recruitment and stratification approaches primarily rely on genetic load, cognitive and motor assessment scores. They focus less on in vivo brain imaging markers, which reflect neuropathology well before clinical diagnosis. Machine learning methods offer a degree of sophistication which could significantly improve prognosis and stratification by leveraging multimodal biomarkers from large datasets. Such models specifically tailored to HD gene expansion carriers could further enhance the efficacy of the stratification process. OBJECTIVES: To improve stratification of Huntington's disease individuals for clinical trials. METHODS: We used data from 451 gene positive individuals with Huntington's disease (both premanifest and diagnosed) from previously published cohorts (PREDICT, TRACK, TrackON, and IMAGE). We applied whole-brain parcellation to longitudinal brain scans and measured the rate of lateral ventricular enlargement, over 3 years, which was used as the target variable for our prognostic random forest regression models. The models were trained on various combinations of features at baseline, including genetic load, cognitive and motor assessment score biomarkers, as well as brain imaging-derived features. Furthermore, a simplified stratification model was developed to classify individuals into two homogenous groups (low risk and high risk) based on their anticipated rate of ventricular enlargement. RESULTS: The predictive accuracy of the prognostic models substantially improved by integrating brain imaging features alongside genetic load, cognitive and motor biomarkers: a 24 % reduction in the cross-validated mean absolute error, yielding an error of 530 mm3/year. The stratification model had a cross-validated accuracy of 81 % in differentiating between moderate and fast progressors (precision = 83 %, recall = 80 %). CONCLUSIONS: This study validated the effectiveness of machine learning in differentiating between low- and high-risk individuals based on the rate of ventricular enlargement. The models were exclusively trained using features from HD individuals, which offers a more disease-specific, simplified, and accurate approach for prognostic enrichment compared to relying on features extracted from healthy control groups, as done in previous studies. The proposed method has the potential to enhance clinical utility by: i) enabling more targeted recruitment of individuals for clinical trials, ii) improving post-hoc evaluation of individuals, and iii) ultimately leading to better outcomes for individuals through personalized treatment selection.

Real-time fMRI-based neurofeedback to restore brain function in substance use disorders: A systematic review of the literature.

INTRODUCTION: Real-time functional magnetic resonance based-neurofeedback (fMRI-neurofeedback) is a neuromodulation tool where individuals self-modulate brain function based on real-time feedback of their brain activity. fMRI-neurofeedback has been used to target brain dysfunction in substance use disorders (SUDs) and to reduce craving, but a systematic synthesis of up-to-date literature is lacking. METHOD: Following PRISMA guidelines, we conducted a systematic review of all the literature that examined the effects of fMRI-neurofeedback on individuals with regular psychoactive substance use (PROSPERO pre-registration = CRD42023401137). RESULTS: The literature included 16 studies comprising 446 participants with SUDs involving alcohol, tobacco, and cocaine. There is consistent between-condition (e.g., fMRI-neurofeedback versus control), less consistent pre-to-post fMRI-neurofeedback, and little intervention-by-time effects on brain function in prefrontal-striatal regions and craving. CONCLUSION: The evidence for changes in brain function/craving was early and inconsistent. More rigorous experiments including repeated measure designs with placebo control conditions, are required to confirm the efficacy of fMRI-neurofeedback in reducing brain alterations and craving in SUDs.

Conscious but not thinking-Mind-blanks during visuomotor tracking: An fMRI study of endogenous attention lapses.

Attention lapses (ALs) are complete lapses of responsiveness in which performance is briefly but completely disrupted and during which, as opposed to microsleeps, the eyes remain open. Although the phenomenon of ALs has been investigated by behavioural and physiological means, the underlying cause of an AL has largely remained elusive. This study aimed to investigate the underlying physiological substrates of behaviourally identified endogenous ALs during a continuous visuomotor task, primarily to answer the question: Were the ALs during this task due to extreme mind-wandering or mind-blanks? The data from two studies were combined, resulting in data from 40 healthy non-sleep-deprived subjects (20M/20F; mean age 27.1 years, 20-45). Only 17 of the 40 subjects were used in the analysis due to a need for a minimum of two ALs per subject. Subjects performed a random 2-D continuous visuomotor tracking task for 50 and 20 min in Studies 1 and 2, respectively. Tracking performance, eye-video, and functional magnetic resonance imaging (fMRI) were recorded simultaneously. A human expert visually inspected the tracking performance and eye-video recordings to identify and categorise lapses of responsiveness as microsleeps or ALs. Changes in neural activity during 85 ALs (17 subjects) relative to responsive tracking were estimated by whole-brain voxel-wise fMRI and by haemodynamic response (HR) analysis in regions of interest (ROIs) from seven key networks to reveal the neural signature of ALs. Changes in functional connectivity (FC) within and between the key ROIs were also estimated. Networks explored were the default mode network, dorsal attention network, frontoparietal network, sensorimotor network, salience network, visual network, and working memory network. Voxel-wise analysis revealed a significant increase in blood-oxygen-level-dependent activity in the overlapping dorsal anterior cingulate cortex and supplementary motor area region but no significant decreases in activity; the increased activity is considered to represent a recovery-of-responsiveness process following an AL. This increased activity was also seen in the HR of the corresponding ROI. Importantly, HR analysis revealed no trend of increased activity in the posterior cingulate of the default mode network, which has been repeatedly demonstrated to be a strong biomarker of mind-wandering. FC analysis showed decoupling of external attention, which supports the involuntary nature of ALs, in addition to the neural recovery processes. Other findings were a decrease in HR in the frontoparietal network before the onset of ALs, and a decrease in FC between default mode network and working memory network. These findings converge to our conclusion that the ALs observed during our task were involuntary mind-blanks. This is further supported behaviourally by the short duration of the ALs (mean 1.7 s), which is considered too brief to be instances of extreme mind-wandering. This is the first study to demonstrate that at least the majority of complete losses of responsiveness on a continuous visuomotor task are, if not due to microsleeps, due to involuntary mind-blanks.

Associations between Sleep Quality and Serum Levels of Neurofilament Light in Individuals with Premanifest Huntington Disease.

Objectives To evaluate the associations between sleep quality and serum levels of neurofilament light (NfL) protein in individuals with premanifest Huntington disease (HD). Materials and Methods We recruited 28 individuals with premanifest HD from a pre-existing database (of the Huntington's Environmental Research Optimisation Scheme, HEROs). The participants filled out the Pittsburgh Sleep Quality Index (PSQI), a subjective measure of sleep quality, and blood was collected via routine venepuncture to measure peripheral NfL levels. Results The PSQI scores (median: 5.0; interquartile range: 4.0-7.5) indicated poor sleep quality. General linear modelling revealed no significant ( p = 0.242) association between PSQI scores and NfL levels. No significant differences were found between individuals with good and poor sleep quality for any demographic variable collected. Discussion Contrary to studies on other neurological conditions, there was no association between sleep quality and NfL levels in individuals with premanifest HD. This was unexpected, given the influence of environmental factors (such as social network size) on neurodegeneration in individuals with premanifest HD.

Blood brain barrier disruption and glutamatergic excitotoxicity in post-acute sequelae of SARS COV-2 infection cognitive impairment: potential biomarkers and a window into pathogenesis.

Objective: To investigate the association between blood-brain barrier permeability, brain metabolites, microstructural integrity of the white matter, and cognitive impairment (CI) in post-acute sequelae of SARS-COV-2 infection (PASC). Methods: In this multimodal longitudinal MRI study 14 PASC participants with CI and 10 healthy controls were enrolled. All completed investigations at 3 months following acute infection (3 months ± 2 weeks SD), and 10 PASC participants completed at 12 months ± 2.22 SD weeks. The assessments included a standard neurological assessment, a cognitive screen using the brief CogState battery and multi-modal MRI derived metrics from Dynamic contrast enhanced (DCE) perfusion Imaging, Diffusion Tensor Imaging (DTI), and single voxel proton Magnetic Resonance Spectroscopy. These measures were compared between patients and controls and correlated with cognitive scores. Results: At baseline, and relative to controls, PASC participants had higher K-Trans and Myo-inositol, and lower levels of Glutamate/Glutamine in the frontal white matter (FWM) (p < 0.01) as well as in brain stem (p < 0.05), and higher FA and lower MD in the FWM (p < 0.05). In PASC participants, FA and MD decreased in the FWM at 12 months compared to baseline (p < 0.05). K-Trans and metabolite concentrations did not change significantly over time. Neurocognitive scores did not correlation with the increased permeability (K trans). Interpretation: PASC with CI is associated with BBB impairment, loss of WM integrity, and inflammation at 3 months which significantly but not uniformly improved at 12 months. The loss of WM integrity is possibly mediated by BBB impairment and associated glutamatergic excitotoxicity.

Network Representation of fMRI Data Using Visibility Graphs: The Impact of Motion and Test-Retest Reliability.

Visibility graphs provide a novel approach for analysing time-series data. Graph theoretical analysis of visibility graphs can provide new features for data mining applications in fMRI. However, visibility graphs features have not been used widely in the field of neuroscience. This is likely due to a lack of understanding of their robustness in the presence of noise (e.g., motion) and their test-retest reliability. In this study, we investigated visibility graph properties of fMRI data in the human connectome project (N = 1010) and tested their sensitivity to motion and test-retest reliability. We also characterised the strength of connectivity obtained using degree synchrony of visibility graphs. We found that strong correlation (r > 0.5) between visibility graph properties, such as the number of communities and average degrees, and motion in the fMRI data. The test-retest reliability (Intraclass correlation coefficient (ICC)) of graph theoretical features was high for the average degrees (0.74, 95% CI = [0.73, 0.75]), and moderate for clustering coefficient (0.43, 95% CI = [0.41, 0.44]) and average path length (0.41, 95% CI = [0.38, 0.44]). Functional connectivity between brain regions was measured by correlating the visibility graph degrees. However, the strength of correlation was found to be moderate to low (r < 0.35). These findings suggest that even small movement in fMRI data can strongly influence robustness and reliability of visibility graph features, thus, requiring robust motion correction strategies prior to data analysis. Further studies are necessary for better understanding of the potential application of visibility graph features in fMRI.

Prediction of cognitive outcome after mild traumatic brain injury from acute measures of communication within brain networks.

A considerable but ill-defined proportion of patients with mild traumatic brain injury (mTBI) experience persistent cognitive sequelae; the ability to identify such individuals early can help their neurorehabilitation. Here we tested the hypothesis that acute measures of efficient communication within brain networks are associated with patients' risk for unfavorable cognitive outcome six months after mTBI. Diffusion and T1-weighted magnetic resonance imaging, alongside cognitive measures, were obtained to map connectomes both one week and six months post injury in 113 adult patients with mTBI (71 males). For task-related brain networks, communication measures (characteristic path length, global efficiency, navigation efficiency) were moderately correlated with changes in cognition. Taking into account the covariance of age and sex, more unfavorable communication within networks were associated with worse outcomes within cognitive domains frequently impacted by mTBI (episodic and working memory, verbal fluency, inductive reasoning, and processing speed). Individuals with more unfavorable outcomes had significantly longer and less efficient pathways within networks supporting verbal fluency (all t > 2.786, p < .006), highlighting the vulnerability of language to mTBI. Participants in whom a task-related network was relatively inefficient one week post injury were up to eight times more likely to have unfavorable cognitive outcome pertaining to that task. Our findings suggest that communication measures within task-related networks identify mTBI patients who are unlikely to develop persistent cognitive deficits after mTBI. Our approach and findings can help to stratify mTBI patients according to their expected need for follow-up and/or neurorehabilitation.

The shape of things to come. Mapping spatiotemporal progression of striatal morphology in Huntington disease: The IMAGE-HD study.

Mapping the spatiotemporal progression of neuroanatomical change in Huntington's Disease (HD) is fundamental to the development of bio-measures for prognostication. Statistical shape analysis to measure the striatum has been performed in HD, however there have been a limited number of longitudinal studies. To address these limitations, we utilised the Spherical Harmonic Point Distribution Method (SPHARM-PDM) to generate point distribution models of the striatum in individuals, and used linear mixed models to test for localised shape change over time in pre-manifest HD (pre-HD), symp-HD (symp-HD) and control individuals. Longitudinal MRI scans from the IMAGE-HD study were used (baseline, 18 and 30 months). We found significant differences in the shape of the striatum between groups. Significant group-by-time interaction was observed for the putamen bilaterally, but not for caudate. A differential rate of shape change between groups over time was observed, with more significant deflation in the symp-HD group in comparison with the pre-HD and control groups. CAG repeats were correlated with bilateral striatal shape in pre-HD and symp-HD. Robust statistical analysis of the correlates of striatal shape change in HD has confirmed the suitability of striatal morphology as a potential biomarker correlated with CAG-repeat length, and potentially, an endophenotype.

Hippocampal morphology in Huntington's disease, implications for plasticity and pathogenesis: The IMAGE-HD study.

While striatal changes in Huntington's Disease (HD) are well established, few studies have investigated changes in the hippocampus, a key neuronal hub. Using MRI scans obtained from the IMAGE-HD study, hippocampi were manually traced and then analysed with the Spherical Harmonic Point Distribution Method (SPHARM-PDM) in 36 individuals with presymptomatic-HD, 37 with early symptomatic-HD, and 36 healthy matched controls. There were no significant differences in overall hippocampal volume between groups. Interestingly we found decreased bilateral hippocampal volume in people with symptomatic-HD who took selective serotonin reuptake inhibitors compared to those who did not, despite no significant differences in anxiety, depressive symptoms, or motor incapacity between the two groups. In symptomatic-HD, there was also significant shape deflation in the right hippocampal head, showing the utility of using manual tracing and SPHARM-PDM to characterise subtle shape changes which may be missed by other methods. This study confirms previous findings of the lack of hippocampal volumetric differentiation in presymptomatic-HD and symptomatic-HD compared to controls. We also find novel shape and volume findings in those with symptomatic-HD, especially in relation to decreased hippocampal volume in those treated with SSRIs.

Characteristics of urban neighbourhood environments and cognitive age in mid-age and older adults.

In this cross-sectional study, we examined the extent to which features of the neighbourhood natural, built, and socio-economic environments were related to cognitive age in adults (N = 3418, Mage = 61 years) in Australia. Machine learning estimated an individual's cognitive age from assessments of processing speed, verbal memory, premorbid intelligence. A 'cognitive age gap' was calculated by subtracting chronological age from predicted cognitive age and was used as a marker of cognitive age. Greater parkland availability and higher neighbourhood socio-economic status were associated with a lower cognitive age gap score in confounder- and mediator-adjusted regression models. Cross-sectional design is a limitation. Living in affluent neighbourhoods with access to parks maybe beneficial for cognitive health, although selection mechanisms may contribute to the findings.

Exploring personalized structural connectomics for moderate to severe traumatic brain injury.

Graph theoretical analysis of the structural connectome has been employed successfully to characterize brain network alterations in patients with traumatic brain injury (TBI). However, heterogeneity in neuropathology is a well-known issue in the TBI population, such that group comparisons of patients against controls are confounded by within-group variability. Recently, novel single-subject profiling approaches have been developed to capture inter-patient heterogeneity. We present a personalized connectomics approach that examines structural brain alterations in five chronic patients with moderate to severe TBI who underwent anatomical and diffusion magnetic resonance imaging. We generated individualized profiles of lesion characteristics and network measures (including personalized graph metric GraphMe plots, and nodal and edge-based brain network alterations) and compared them against healthy reference cases (N = 12) to assess brain damage qualitatively and quantitatively at the individual level. Our findings revealed alterations of brain networks with high variability between patients. With validation and comparison to stratified, normative healthy control comparison cohorts, this approach could be used by clinicians to formulate a neuroscience-guided integrative rehabilitation program for TBI patients, and for designing personalized rehabilitation protocols based on their unique lesion load and connectome.

Selective perforant-pathway atrophy in Huntington disease: MRI analysis of hippocampal subfields.

INTRODUCTION: While individuals with Huntington disease (HD) show memory impairment that indicates hippocampal dysfunction, the available literature does not consistently identify structural evidence for involvement of the whole hippocampus but rather suggests that hippocampal atrophy may be confined to certain hippocampal subregions. METHODS: We processed T1-weighted MRI from IMAGE-HD study using FreeSurfer 7.0 and compared the volumes of the hippocampal subfields among 36 early motor symptomatic (symp-HD), 40 pre-symptomatic (pre-HD), and 36 healthy control individuals across three timepoints over 36 months. RESULTS: Mixed-model analyses revealed significantly lower subfield volumes in symp-HD, compared with pre-HD and control groups, in the subicular regions of the perforant-pathway: presubiculum, subiculum, dentate gyrus, tail, and right molecular layer. These adjoining subfields aggregated into a single principal component, which demonstrated an accelerated rate of atrophy in the symp-HD. Volumes between pre-HD and controls did not show any significant difference. In the combined HD groups, CAG repeat length and disease burden score were associated with presubiculum, molecular layer, tail, and perforant-pathway subfield volumes. Hippocampal left tail and perforant-pathway subfields were associated with motor onset in the pre-HD group. CONCLUSIONS: Hippocampal subfields atrophy in early symptomatic HD affects key regions of the perforant-pathway, which may implicate the distinctive memory impairment at this stage of illness. Their volumetric associations with genetic and clinical markers suggest the selective susceptibility of these subfields to mutant Huntingtin and disease progression.

Increased cerebral activity during microsleeps reflects an unconscious drive to re-establish consciousness.

BACKGROUND: Microsleeps are brief instances of sleep, causing complete lapses in responsiveness and partial or total extended closure of both eyes. Microsleeps can have devastating consequences, particularly in the transportation sector. STUDY OBJECTIVES: Questions remain regarding the neural signature and underlying mechanisms of microsleeps. This study aimed to gain a better understanding of the physiological substrates of microsleeps, which might lead to a better understanding of the phenomenon. METHODS: Data from an earlier study, involving 20 healthy non-sleep-deprived subjects, were analysed. Each session lasted 50 min and required subjects to perform a 2-D continuous visuomotor tracking task. Simultaneous data collection included tracking performance, eye-video, EEG, and fMRI. A human expert visually inspected each participant's tracking performance and eye-video recordings to identify microsleeps. Our interest was in microsleeps of ≥4-s duration, leaving us with a total of 226 events from 10 subjects. The microsleep events were divided into four 2-s segments (pre, start, end, and post) (with a gap in the middle, between start and end segments, for microsleeps >4 s), then each segment was analysed relative to its prior segment by examining changes in source-reconstructed EEG power in the delta, theta, alpha, beta, and gamma bands. RESULTS: EEG power increased in the theta and alpha bands between the pre and start of microsleeps. There was also increased power in the delta, beta, and gamma bands between the start and end of microsleeps. Conversely, there was a reduction in power between the end and post of microsleeps in the delta and alpha bands. These findings support previous findings in the delta, theta, and alpha bands. However, increased power in the beta and gamma bands has not been previously reported. CONCLUSIONS: We contend that increased high-frequency activity during microsleeps reflects unconscious 'cognitive' activity aimed at re-establishing consciousness following falling asleep during an active task.

Structural-functional connectivity bandwidth predicts processing speed in mild traumatic brain Injury: A multiplex network analysis.

An emerging body of work has revealed alterations in structural (SC) and functional (FC) brain connectivity following mild TBI (mTBI), with mixed findings. However, these studies seldom integrate complimentary neuroimaging modalities within a unified framework. Multilayer network analysis is an emerging technique to uncover how white matter organization enables functional communication. Using our novel graph metric (SC-FC Bandwidth), we quantified the information capacity of synchronous brain regions in 53 mild TBI patients (46 females; age mean = 40.2 years (y), σ = 16.7 (y), range: 18-79 (y). Diffusion MRI and resting state fMRI were administered at the acute and chronic post-injury intervals. Moreover, participants completed a cognitive task to measure processing speed (30 Seconds and Counting Task; 30-SACT). Processing speed was significantly increased at the chronic, relative to the acute post-injury intervals (p = <0.001). Nonlinear principal components of direct (t = -1.84, p = 0.06) and indirect SC-FC Bandwidth (t = 3.86, p = <0.001) predicted processing speed with a moderate effect size (R2 = 0.43, p < 0.001), while controlling for age. A subnetwork of interhemispheric edges with increased SC-FC Bandwidth was identified at the chronic, relative to the acute mTBI post-injury interval (pFDR = 0.05). Increased interhemispheric SC-FC Bandwidth of this network corresponded with improved processing speed at the chronic post-injury interval (partial r = 0.32, p = 0.02). Our findings revealed that mild TBI results in complex reorganization of brain connectivity optimized for maximum information flow, supporting improved cognitive performance as a compensatory mechanism. Moving forward, this measurement may complement clinical assessment as an objective marker of mTBI recovery.

Molecular characterization stratifies VQ myeloma cells into two clusters with distinct risk signatures and drug responses.

Multiple myeloma (MM) is a cancer of malignant plasma cells in the bone marrow and extramedullary sites. We previously characterized a VQ model for human high-risk MM. The various VQ lines display different disease phenotypes and survival rates, suggesting significant intra-model variation. Here, we use whole-exome sequencing and copy number variation (CNV) analysis coupled with RNA-Seq to stratify the VQ lines into corresponding clusters: Group A cells had monosomy chromosome (chr) 5 and overexpressed genes and pathways associated with sensitivity to bortezomib (Btz) treatment in human MM patients. By contrast, Group B VQ cells carried recurrent amplification (Amp) of chr3 and displayed high-risk MM features, including downregulation of Fam46c, upregulation of cancer growth pathways associated with functional high-risk MM, and expression of Amp1q and high-risk UAMS-70 and EMC-92 gene signatures. Consistently, in sharp contrast to Group A VQ cells that showed short-term response to Btz, Group B VQ cells were de novo resistant to Btz in vivo. Our study highlights Group B VQ lines as highly representative of the human MM subset with ultrahigh risk.

Individualised profiling of white matter organisation in moderate-to-severe traumatic brain injury patients.

BACKGROUND AND PURPOSE: Approximately 65% of moderate-to-severe traumatic brain injury (m-sTBI) patients present with poor long-term behavioural outcomes, which can significantly impair activities of daily living. Numerous diffusion-weighted MRI studies have linked these poor outcomes to decreased white matter integrity of several commissural tracts, association fibres and projection fibres in the brain. However, most studies have focused on group-based analyses, which are unable to deal with the substantial between-patient heterogeneity in m-sTBI. As a result, there is increasing interest and need in conducting individualised neuroimaging analyses. MATERIALS AND METHODS: Here, we generated a detailed subject-specific characterisation of microstructural organisation of white matter tracts in 5 chronic patients with m-sTBI (29 - 49y, 2 females), presented as a proof-of-concept. We developed an imaging analysis framework using fixel-based analysis and TractLearn to determine whether the values of fibre density of white matter tracts at the individual patient level deviate from the healthy control group (n = 12, 8F, Mage = 35.7y, age range 25 - 64y). RESULTS: Our individualised analysis revealed unique white matter profiles, confirming the heterogenous nature of m-sTBI and the need of individualised profiles to properly characterise the extent of injury. Future studies incorporating clinical data, as well as utilising larger reference samples and examining the test-retest reliability of the fixel-wise metrics are warranted. CONCLUSIONS: Individualised profiles may assist clinicians in tracking recovery and planning personalised training programs for chronic m-sTBI patients, which is necessary to achieve optimal behavioural outcomes and improved quality of life.

Do neighbourhood traffic-related air pollution and socio-economic status moderate the associations of the neighbourhood physical environment with cognitive function? Findings from the AusDiab study.

Characteristics of the neighbourhood environment, including the built and natural environment, area-level socio-economic status (SES) and air pollution, have been linked to cognitive health. However, most studies have focused on single neighbourhood characteristics and have not considered the extent to which the effects of environmental factors may interact. We examined the associations of measures of the neighbourhood built and natural environment, area-level SES and traffic-related air pollution (TRAP) with two cognitive function domains (memory and processing speed), and the extent to which area-level SES and TRAP moderated the associations. We used cross-sectional data from the AusDiab3 study, an Australian cohort study of adults (mean age: 61 years) in 2011-12 (N = 4141) for which geocoded residential addresses were available. Spatial data were used to create composite indices of built environment complexity (population density, intersection density, non-commercial land use mix, commercial land use) and natural environment (parkland and blue spaces). Area-level SES was obtained from national census indices and TRAP was based on estimates of annual average levels of nitrogen dioxide (NO2). Confounder-adjusted generalised additive mixed models were used to estimate the independent associations of the environmental measures with cognitive function and the moderating effects of area-level SES and TRAP. The positive associations between built environment complexity and memory were stronger in those living in areas with higher SES and lower NO2 concentrations. A positive association between the natural environment and memory was found only in those living in areas with lower NO2 concentrations and average or below-average SES. Built environment complexity and the natural environment were positively related to processing speed. Complex urban environments and access to nature may benefit cognitive health in ageing populations. For higher-order cognitive abilities, such as memory, these positive effects may be stronger in areas with lower levels of TRAP.

Brain reward function in people who use cannabis: a systematic review.

Rationale: Cannabis is one of the most widely used psychoactive substances globally. Cannabis use can be associated with alterations of reward processing, including affective flattening, apathy, anhedonia, and lower sensitivity to natural rewards in conjunction with higher sensitivity to cannabis-related rewards. Such alterations have been posited to be driven by changes in underlying brain reward pathways, as per prominent neuroscientific theories of addiction. Functional neuroimaging (fMRI) studies have examined brain reward function in cannabis users via the monetary incentive delay (MID) fMRI task; however, this evidence is yet to be systematically synthesised. Objectives: We aimed to systematically integrate the evidence on brain reward function in cannabis users examined by the MID fMRI task; and in relation to metrics of cannabis exposure (e.g., dosage, frequency) and other behavioural variables. Method: We pre-registered the review in PROSPERO and reported it using PRISMA guidelines. Literature searches were conducted in PsycINFO, PubMed, Medline, CINAHL, and Scopus. Results: Nine studies were included, comprising 534 people with mean ages 16-to-28 years, of which 255 were people who use cannabis daily or almost daily, and 279 were controls. The fMRI literature to date led to largely non-significant group differences. A few studies reported group differences in the ventral striatum while participants anticipated rewards and losses; and in the caudate while participants received neutral outcomes. A few studies examined correlations between brain function and withdrawal, dosage, and age of onset; and reported inconsistent findings. Conclusions: There is emerging but inconsistent evidence of altered brain reward function in cannabis users examined with the MID fMRI task. Future fMRI studies are required to confirm if the brain reward system is altered in vulnerable cannabis users who experience a Cannabis Use Disorder, as postulated by prominent neuroscientific theories of addiction.

Structural-functional connectivity bandwidth of the human brain.

BACKGROUND: 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). METHOD: 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. FINDINGS: 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. CONCLUSION: 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.