(1) Background: Traumatic brain injury (TBI) often results in cognitive impairments, including in visuospatial planning and executive function. Methylphenidate (MPh) demonstrates potential improvements in several cognitive domains in patients with TBI. The Tower of London (TOL) is a visuospatial planning task used to assess executive function. (2) Methods: Volunteers with a history of TBI (n = 16) participated in a randomised, double-blinded, placebo-controlled, fMRI study to investigate the neurobiological correlates of visuospatial planning and executive function, on and off MPh. (3) Results: Healthy controls (HCs) (n = 18) and patients on placebo (TBI-placebo) differed significantly in reaction time (p < 0.0005) and accuracy (p < 0.0001) when considering all task loads, but especially for high cognitive loads for reaction time (p < 0.001) and accuracy (p < 0.005). Across all task loads, TBI-MPh were more accurate than TBI-placebo (p < 0.05) but remained less accurate than HCs (p < 0.005). TBI-placebo substantially improved in accuracy with MPh administration (TBI-MPh) to a level statistically comparable to HCs at low (p = 0.443) and high (p = 0.175) cognitive loads. Further, individual patients that performed slower on placebo at low cognitive loads were faster with MPh (p < 0.05), while individual patients that performed less accurately on placebo were more accurate with MPh at both high and low cognitive loads (p < 0.005). TBI-placebo showed reduced activity in the bilateral inferior frontal gyri (IFG) and insulae versus HCs. MPh normalised these regional differences. MPh enhanced within-network connectivity (between parietal, striatal, insula, and cerebellar regions) and enhanced beyond-network connectivity (between parietal, thalamic, and cerebellar regions). Finally, individual changes in cerebellar-thalamic (p < 0.005) and cerebellar-parietal (p < 0.05) connectivity with MPh related to individual changes in accuracy with MPh. (4) Conclusions: This work highlights behavioural and neurofunctional differences between HCs and patients with chronic TBI, and that adverse differences may benefit from MPh treatment.

Functional interactions between brain regions can be viewed as a network, enabling neuroscientists to investigate brain function through network science. Here, we systematically evaluate 768 data-processing pipelines for network reconstruction from resting-state functional MRI, evaluating the effect of brain parcellation, connectivity definition, and global signal regression. Our criteria seek pipelines that minimise motion confounds and spurious test-retest discrepancies of network topology, while being sensitive to both inter-subject differences and experimental effects of interest. We reveal vast and systematic variability across pipelines' suitability for functional connectomics. Inappropriate choice of data-processing pipeline can produce results that are not only misleading, but systematically so, with the majority of pipelines failing at least one criterion. However, a set of optimal pipelines consistently satisfy all criteria across different datasets, spanning minutes, weeks, and months. We provide a full breakdown of each pipeline's performance across criteria and datasets, to inform future best practices in functional connectomics.

Post-mortem studies have shown that patients dying from severe acute respiratory syndrome coronavirus (SARS-CoV-2) infection frequently have pathological changes in their CNS, particularly in the brainstem. Many of these changes are proposed to result from para-infectious and/or post-infection immune responses. Clinical symptoms such as fatigue, breathlessness, and chest pain are frequently reported in post-hospitalized coronavirus disease 2019 (COVID-19) patients. We propose that these symptoms are in part due to damage to key neuromodulatory brainstem nuclei. While brainstem involvement has been demonstrated in the acute phase of the illness, the evidence of long-term brainstem change on MRI is inconclusive. We therefore used ultra-high field (7 T) quantitative susceptibility mapping (QSM) to test the hypothesis that brainstem abnormalities persist in post-COVID patients and that these are associated with persistence of key symptoms. We used 7 T QSM data from 30 patients, scanned 93-548 days after hospital admission for COVID-19 and compared them to 51 age-matched controls without prior history of COVID-19 infection. We correlated the patients' QSM signals with disease severity (duration of hospital admission and COVID-19 severity scale), inflammatory response during the acute illness (C-reactive protein, D-dimer and platelet levels), functional recovery (modified Rankin scale), depression (Patient Health Questionnaire-9) and anxiety (Generalized Anxiety Disorder-7). In COVID-19 survivors, the MR susceptibility increased in the medulla, pons and midbrain regions of the brainstem. Specifically, there was increased susceptibility in the inferior medullary reticular formation and the raphe pallidus and obscurus. In these regions, patients with higher tissue susceptibility had worse acute disease severity, higher acute inflammatory markers, and significantly worse functional recovery. This study contributes to understanding the long-term effects of COVID-19 and recovery. Using non-invasive ultra-high field 7 T MRI, we show evidence of brainstem pathophysiological changes associated with inflammatory processes in post-hospitalized COVID-19 survivors.

ImportanceThe chronic neuronal burden of traumatic brain injury (TBI) is not fully characterized by routine imaging, limiting understanding of the role of neuronal substrates in adverse outcomes.ObjectiveTo determine whether tissues that appear healthy on routine imaging can be investigated for selective neuronal loss using [11C]flumazenil (FMZ) positron emission tomography (PET) and to examine whether this neuronal loss is associated with long-term outcomes.Design, Setting, and ParticipantsIn this cross-sectional study, data were collected prospectively from 2 centers (University of Cambridge in the UK and Weill Cornell Medicine in the US) between September 1, 2004, and May 31, 2021. Patients with TBI (>6 months postinjury) were compared with healthy control participants (all aged >18 years). Individuals with neurological disease, benzodiazepine use, or contraindication to magnetic resonance imaging were excluded. Data were retrospectively collated with nonconsecutive recruitment, owing to convenience and scanner or PET ligand availability. Data were analyzed between February 1 and September 30, 2023.ExposureFlumazenil voxelwise binding potential relative to nondisplaceable binding potential (BPND).Main Outcomes and MeasuresSelective neuronal loss identified with FMZ PET was compared between groups on voxelwise and regional scales, and its association with functional, cognitive, and psychological outcomes was examined using Glasgow Outcome Scale (GOS) scores, measures of sustained executive attention (animal and sustained fluency), and 36-Item Short Form Health Survey (SF-36) scores. Diffusion tensor imaging was used to assess structural connectivity of regions of cortical damage, and its association with thalamic selective neuronal loss.ResultsIn this study, 24 patients with chronic TBI (mean [SD] age, 39.2 [12.3] years; 18 men [75.0%]) and 33 healthy control participants (mean [SD] age, 47.6 [20.5] years; 23 men [69.7%]) underwent FMZ PET. Patients with TBI had a median time of 29 (range, 7-95) months from injury to scan. They displayed selective neuronal loss in thalamic nuclei, over and above gross volume loss in the left thalamus, and bilateral central, mediodorsal, ventral-lateral dorsal, anterior, and ventral anterior thalamic nuclei, across a wide range of injury severities. Neuronal loss was associated with worse functional outcome using GOS scores (left thalamus, left ventral anterior, and bilateral central, mediodorsal, and anterior nuclei), worse cognitive outcome on measures of sustained executive attention (left thalamus, bilateral central, and right mediodorsal nuclei), and worse emotional outcome using SF-36 scores (right central thalamic nucleus). Chronic thalamic neuronal loss partially mirrored the location of primary cortical contusions, which may indicate secondary injury mechanisms of transneuronal degeneration.Conclusions and RelevanceThe findings of this study suggest that selective thalamic vulnerability may have chronic neuronal consequences with relevance to long-term outcome, suggesting the evolving and potentially lifelong thalamic neuronal consequences of TBI. FMZ PET is a more sensitive marker of the burden of neuronal injury than routine imaging; therefore, it could inform outcome prognostication and may lead to the development of individualized precision medicine approaches.

A central question in neuroscience is how consciousness arises from the dynamic interplay of brain structure and function. Here we decompose functional MRI signals from pathological and pharmacologically-induced perturbations of consciousness into distributed patterns of structure-function dependence across scales: the harmonic modes of the human structural connectome. We show that structure-function coupling is a generalisable indicator of consciousness that is under bi-directional neuromodulatory control. We find increased structure-function coupling across scales during loss of consciousness, whether due to anaesthesia or brain injury, capable of discriminating between behaviourally indistinguishable sub-categories of brain-injured patients, tracking the presence of covert consciousness. The opposite harmonic signature characterises the altered state induced by LSD or ketamine, reflecting psychedelic-induced decoupling of brain function from structure and correlating with physiological and subjective scores. Overall, connectome harmonic decomposition reveals how neuromodulation and the network architecture of the human connectome jointly shape consciousness and distributed functional activation across scales.

Functional interactions between brain regions can be viewed as a network, empowering neuroscientists to leverage network science to investigate distributed brain function. However, obtaining a brain network from functional neuroimaging data involves multiple steps of data manipulation, which can drastically affect the organisation and validity of the estimated brain network and its properties. Here, we provide a systematic evaluation of 576 unique data-processing pipelines for functional connectomics from resting-state functional MRI, obtained from all possible recombinations of popular choices for brain atlas type and size, connectivity definition and selection, and global signal regression. We use the portrait divergence, an information-theoretic measure of differences in network topology across scales, to quantify the influence of analytic choices on the overall organisation of the derived functional connectome. We evaluate each pipeline across an entire battery of criteria, seeking pipelines that (i) minimise spurious test-retest discrepancies of network topology, while simultaneously (ii) mitigating motion confounds, and being sensitive to both (iii) inter-subject differences and (iv) experimental effects of interest, as demonstrated by propofol-induced general anaesthesia. Our findings reveal vast and systematic variability across pipelines’ suitability for functional connectomics. Choice of the wrong data-processing pipeline can lead to results that are not only misleading, but systematically so, distorting the functional connectome more drastically than the passage of several months. We also found that the majority of pipelines failed to meet at least one of our criteria. However, we identified 8 candidates satisfying all criteria across each of four independent datasets spanning minutes, weeks, and months, ensuring the generalisability of our recommendations. Our results also generalise to alternative acquisition parameters and preprocessing and denoising choices. By providing the community with a full breakdown of each pipeline’s performance across this multi-dataset, multi-criteria, multi-scale and multi-step approach, we establish a comprehensive set of benchmarks to inform future best practices in functional connectomics.

Post mortem studies have shown that patients dying from severe SARS-CoV-2 infection frequently have pathological changes in their central nervous system, particularly in the brainstem. Many of these changes are proposed to result from para-infectious and/or post-infection immune responses. Clinical symptoms such as fatigue, breathlessness, and chest pain are frequently reported in post-hospitalized COVID-19 patients. We propose that these symptoms are in part due to damage to key neuromodulatory brainstem nuclei. While brainstem involvement has been demonstrated in the acute phase of the illness, the evidence of long-term brainstem change on magnetic resonance imaging (MRI) is inconclusive. We therefore used ultra-high field (7T) quantitative susceptibility mapping (QSM) to test the hypothesis that brainstem abnormalities persist in post-COVID patients and that these are associated with persistence of key symptoms. We used 7T QSM data from 30 patients, scanned 93-548 days after hospital admission for COVID-19 and compared them to 51 age-matched controls without prior history of COVID-19 infection. We correlated the patients' QSM signals with disease severity (duration of hospital admission and COVID-19 severity scale), inflammatory response during the acute illness (C-reactive protein, D-Dimer and platelet levels), functional recovery (modified Rankin scale; mRS), depression (PHQ-9) and anxiety (GAD-7). In COVID-19 survivors the MR susceptibility increased in the medulla, pons and midbrain regions of the brainstem. Specifically, there was increased susceptibility in the inferior medullary reticular formation and the raphe pallidus and obscurus. In these regions, patients with higher tissue susceptibility had worse acute disease severity, higher acute inflammatory markers, and significantly worse functional recovery. Using non-invasive ultra-high field 7T MRI, we show evidence of brainstem pathophysiological changes associated with inflammatory processes in post-hospitalized COVID-19 survivors. This study contributes to understanding the mechanisms of long-term effects of COVID-19 and recovery. ### Competing Interest Statement Dr. Pattinson is named as co-inventor on a provisional U.K. patent application titled "Use of cerebral nitric oxide donors in the assessment of the extent of brain dysfunction following injury". Dr Pattinson is named as co-inventors on a provisional U.K. patent titled "Discordant sensory stimulus in VR based exercise" UK Patent office application: 2204698.1 filing date 31/3/2022. ### Funding Statement This work was supported by the NIHR Cambridge Biomedical Research Centre (BRC-1215-20014). The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care. JBR was supported by the Wellcome Trust (103838; 220258) and Medical Research Council (M C\_UU\_00030/14). VFJN was supported by an Academy of Medical Sciences / The Health Foundation Clinician Scientist Fellowship. ETB was supported by an NIHR Senior Investigator award. BR, MC, SN are supported by NIHR Oxford BRC and BHF Oxford CRE. WTC was supported by funding from Wellcome Trust [225924/Z/22/Z]. CTR was supported by funding from Wellcome Trust [098436/Z/12/B]. For the purpose of open access, the authors have applied a CC-BY public copyright licence to any Author Accepted Manuscript version arising from this submission. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The study was approved by the following ethics committees: Cambridgeshire Research Ethics Committee HBREC.2016.13.am3, East of England Research Ethics Committee 17/EE/0025 , Norfolk Research Ethics Committee EE/0395, and North West Preston Research Ethics Committee 20/NW/0235. All participants provided informed consent in accordance with the Declaration of Helsinki. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes We can provide average QSM χ extracted values from the brainstem and subregions upon reasonable request.

Background:The growth in multi-center neuroimaging studies generated a need for methods that mitigate the differences in hardware and acquisition protocols across sites i.e., scanner effects. ComBat harmonization methods have shown promise but have not yet been tested on all the data types commonly studied with magnetic resonance imaging (MRI). This study aimed to validate neuroCombat, longCombat and gamCombat on both structural and diffusion metrics in both cross-sectional and longitudinal data. Methods:We used a travelling subject design whereby 73 healthy volunteers contributed 161 scans across two sites and four machines using one T1 and five diffusion MRI protocols. Scanner was defined as a composite of site, machine and protocol. A common pipeline extracted two structural metrics (volumes and cortical thickness) and two diffusion tensor imaging metrics (mean diffusivity and fractional anisotropy) for seven regions of interest including gray and (except for cortical thickness) white matter regions. Results:Structural data exhibited no significant scanner effect and therefore did not benefit from harmonization in our particular cohort. Indeed, attempting harmonization obscured the true biological effect for some regions of interest. Diffusion data contained marked scanner effects and was successfully harmonized by all methods, resulting in smaller scanner effects and better detection of true biological effects. LongCombat less effectively reduced the scanner effect for cross-sectional white matter data but had a slightly lower probability of incorrectly finding group differences in simulations, compared to neuroCombat and gamCombat. False positive rates for all methods and all metrics did not significantly exceed 5%. Conclusions:Statistical harmonization of structural data is not always necessary and harmonization in the absence of a scanner effect may be harmful. Harmonization of diffusion MRI data is highly recommended with neuroCombat, longCombat and gamCombat performing well in cross-sectional and longitudinal settings.

Human coronavirus disease 2019 (COVID-19) due to severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has multiple neurological consequences, but its long-term effect on brain health is still uncertain. The cerebrovascular consequences of COVID-19 may also affect brain health. We studied the chronic effect of COVID-19 on cerebrovascular health, in relation to acute severity, adverse clinical outcomes and in contrast to control group data. Here we assess cerebrovascular health in 45 patients six months after hospitalisation for acute COVID-19 using the resting state fluctuation amplitudes (RSFA) from functional magnetic resonance imaging, in relation to disease severity and in contrast with 42 controls. Acute COVID-19 severity was indexed by COVID-19 WHO Progression Scale, inflammatory and coagulatory biomarkers. Chronic widespread changes in frontoparietal RSFA were related to the severity of the acute COVID-19 episode. This relationship was not explained by chronic cardiorespiratory dysfunction, age, or sex. The level of cerebrovascular dysfunction was associated with cognitive, mental, and physical health at follow-up. The principal findings were consistent across univariate and multivariate approaches. The results indicate chronic cerebrovascular impairment following severe acute COVID-19, with the potential for long-term consequences on cognitive function and mental wellbeing.

Newcombe et al. report that serum GFAP and neurofilament light levels remain elevated months to years after traumatic brain injury, and correlate with microstructural injury and atrophy. Biomarker levels may identify survivors at risk of late neurological damage after traumatic brain injury. There is substantial interest in the potential for traumatic brain injury to result in progressive neurological deterioration. While blood biomarkers such as glial fibrillary acid protein (GFAP) and neurofilament light have been widely explored in characterizing acute traumatic brain injury (TBI), their use in the chronic phase is limited. Given increasing evidence that these proteins may be markers of ongoing neurodegeneration in a range of diseases, we examined their relationship to imaging changes and functional outcome in the months to years following TBI. Two-hundred and three patients were recruited in two separate cohorts; 6 months post-injury (n = 165); and >5 years post-injury (n = 38; 12 of whom also provided data similar to 8 months post-TBI). Subjects underwent blood biomarker sampling (n = 199) and MRI (n = 172; including diffusion tensor imaging). Data from patient cohorts were compared to 59 healthy volunteers and 21 non-brain injury trauma controls. Mean diffusivity and fractional anisotropy were calculated in cortical grey matter, deep grey matter and whole brain white matter. Accelerated brain ageing was calculated at a whole brain level as the predicted age difference defined using T-1-weighted images, and at a voxel-based level as the annualized Jacobian determinants in white matter and grey matter, referenced to a population of 652 healthy control subjects. Serum neurofilament light concentrations were elevated in the early chronic phase. While GFAP values were within the normal range at similar to 8 months, many patients showed a secondary and temporally distinct elevations up to >5 years after injury. Biomarker elevation at 6 months was significantly related to metrics of microstructural injury on diffusion tensor imaging. Biomarker levels at similar to 8 months predicted white matter volume loss at >5 years, and annualized brain volume loss between similar to 8 months and 5 years. Patients who worsened functionally between similar to 8 months and >5 years showed higher than predicted brain age and elevated neurofilament light levels. GFAP and neurofilament light levels can remain elevated months to years after TBI, and show distinct temporal profiles. These elevations correlate closely with microstructural injury in both grey and white matter on contemporaneous quantitative diffusion tensor imaging. Neurofilament light elevations at similar to 8 months may predict ongoing white matter and brain volume loss over >5 years of follow-up. If confirmed, these findings suggest that blood biomarker levels at late time points could be used to identify TBI survivors who are at high risk of progressive neurological damage.

To understand how pharmacological interventions can exert their powerful effects on brain function, we need to understand how they engage the brain’s rich neurotransmitter landscape. Here, we bridge microscale molecular chemoarchitecture and pharmacologically-induced macroscale functional reorganisation, by relating the regional distribution of 19 neurotransmitter receptors and transporters obtained from Positron Emission Tomography, and the regional changes in functional MRI connectivity induced by 10 different mind-altering drugs: propofol, sevoflurane, ketamine, LSD, psilocybin, DMT, ayahuasca, MDMA, modafinil, and methylphenidate. Our results reveal that psychoactive drugs exert their effects on brain function by engaging multiple neurotransmitter systems. The effects of both anaesthetics and psychedelics on brain function are organised along hierarchical gradients of brain structure and function. Finally, we show that regional co-susceptibility to pharmacological interventions recapitulates co-susceptibility to disorder-induced structural alterations. Collectively, these results highlight rich statistical patterns relating molecular chemoarchitecture and drug-induced reorganisation of the brain’s functional architecture.

BackgroundPreliminary evidence has highlighted a possible association between severe COVID-19 and persistent cognitive deficits. Further research is required to confirm this association, determine whether cognitive deficits relate to clinical features from the acute phase or to mental health status at the point of assessment, and quantify rate of recovery.Methods46 individuals who received critical care for COVID-19 at Addenbrooke's hospital between 10th March 2020 and 31st July 2020 (16 mechanically ventilated) underwent detailed computerised cognitive assessment alongside scales measuring anxiety, depression and post-traumatic stress disorder under supervised conditions at a mean follow up of 6.0 (± 2.1) months following acute illness. Patient and matched control (N = 460) performances were transformed into standard deviation from expected scores, accounting for age and demographic factors using N = 66,008 normative datasets. Global accuracy and response time composites were calculated (G_SScore & G_RT). Linear modelling predicted composite score deficits from acute severity, mental-health status at assessment, and time from hospital admission. The pattern of deficits across tasks was qualitatively compared with normal age-related decline, and early-stage dementia.FindingsCOVID-19 survivors were less accurate (G_SScore=-0.53SDs) and slower (G_RT=+0.89SDs) in their responses than expected compared to their matched controls. Acute illness, but not chronic mental health, significantly predicted cognitive deviation from expected scores (G_SScore (p=​​0.0037) and G_RT (p = 0.0366)). The most prominent task associations with COVID-19 were for higher cognition and processing speed, which was qualitatively distinct from the profiles of normal ageing and dementia and similar in magnitude to the effects of ageing between 50 and 70 years of age. A trend towards reduced deficits with time from illness (r∼=0.15) did not reach statistical significance.InterpretationCognitive deficits after severe COVID-19 relate most strongly to acute illness severity, persist long into the chronic phase, and recover slowly if at all, with a characteristic profile highlighting higher cognitive functions and processing speed.FundingThis work was funded by the National Institute for Health Research (NIHR) Cambridge Biomedical Research Centre (BRC), NIHR Cambridge Clinical Research Facility (BRC-1215-20014), the Addenbrooke's Charities Trust and NIHR COVID-19 BioResource RG9402. AH is funded by the UK Dementia Research Institute Care Research and Technology Centre and Imperial College London Biomedical Research Centre. ETB and DKM are supported by NIHR Senior Investigator awards. JBR is supported by the Wellcome Trust (220258) and Medical Research Council (SUAG/051 G101400). VFJN is funded by an Academy of Medical Sciences/ The Health Foundation Clinician Scientist Fellowship. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care.

Aims, Objectives and BackgroundPatients who have sustained a traumatic brain injury (TBI) can have disturbances in coagulation that are distinct from other traumatic bleeding states.1 Coagulopathy is a risk factor for exacerbation of the primary injury, and these patients have less favourable outcomes and increased mortality compared to non-coagulopathic patients.1 Little is known about the longitudinal coagulation changes following TBI.The aim of this pilot study was to investigate the coagulation profiles of patients presenting with severe TBI over the first 7 days following injury.Method and DesignDesign: Prospective observational study25 patients presenting to an UK major trauma centre with TBI between August 2021-March 2022 were recruited <24 hours following injury. Professional and family consultee assent was gained and serial blood samples were collected up to three times per day up to day seven.Coagulation was assessed using thromboelastographs (TEGs) and conventional coagulation tests including Hb, Plt, PT, aPPT and fibrinogen. Pre-hospital, clinical, laboratory and imaging data were collected during the patient admission.Coagulopathy was defined as having an INR >1.2. The longitudinal changes in the coagulation parameters were plotted for the first seven 7 days and graphically represented. This is a pre-liminary analysis.Results and Conclusion25 patients with severe TBI (GCS <12) were recruited. Patients were stratified by their admission INR. 18 patients had an admission INR <1.2 (62% n= 18), and 7 had INR >1.2 (38% n=7). 7 patients who did not have INR >1.2 on their first admission blood test later developed coagulopathy (with an INR >1.2).Further exploration of the trends seen in conventional coagulation tests and TEG’s over time is required and to understand how these changes correlate to the clinical and imaging findings. The utility of viscoelastic studies such as TEG’s in the assessment of TBI associated coagulopathy remains unclear.

Significance Understanding the neural bases of consciousness is of basic scientific and clinical importance. Human neuroimaging has established that a network of interconnected brain regions known as the default mode network disintegrates in anesthesia and after brain damage that causes disorders of consciousness. However, the neurochemical underpinnings of this network change remain largely unknown. Motivated by preclinical animal work and clinical observations, we found that across pharmacological (sedation) and pathological (disorders of consciousness) consciousness perturbation, the dopaminergic source nucleus, the ventral tegmental area, disconnects from the main nodes of the default mode network. As the severity of this dopaminergic disconnection was associated with default mode network disintegration, we propose that dopaminergic modulation may be a central mechanism for consciousness maintenance.

The functional interactions between regions of the human brain can be viewed as a network, empowering neuroscientists to leverage tools such as graph theory to obtain insight about brain function. However, obtaining a brain network from functional neuroimaging data inevitably involves multiple steps of data manipulation, which can affect the organisation (topology) of the resulting network and its properties. Test-retest reliability is a gold standard for both basic research and clinical use: a suitable data-processing pipeline for brain networks should recover the same network topology across repeated scan sessions of the same individual. Analyzing resting-state functional Magnetic Resonance Imaging (rs-fMRI) recordings from two test-retest studies across short (45 minutes), medium (2-4 weeks) and long term delays (5-16 months), we investigated the reliability of network topologies constructed by applying 576 unique pipelines to the same fMRI data, obtained from considering combinations of atlas type and size, edge definition and thresholding, and use of global signal regression. We adopted the portrait divergence, an information-theoretic criterion to measure differences in network topology across all scales, enabling us to quantify the influence of different pipelines on the overall organisation of the resulting network. Remarkably, our findings reveal that the choice of pipeline plays a fundamental role in determining how reproducible an individual’s brain network topology will be across different scans: there is large and systematic variability across pipelines, such that an inappropriate choice of pipeline can distort the resulting network more than an interval of several months between scans. Across datasets and time-spans, we also identify specific combinations of data-processing steps that consistently yield networks with reproducible topology, enabling us to make recommendations about best practices to ensure high-quality brain networks.

AbstractDepression is a major albeit neglected complication in patients with traumatic brain injury (TBI). Elucidating its neural correlates remains an important milestone with respect to understanding the disorder and helping with the rehabilitation process. Towards this direction, neuropsychological theories have proposed abnormal brain dynamics as the neural basis of depressive symptomatology. This observational study addressed the question of whether depression in TBI patients is related to abnormal brain dynamics using a sample of 81 TBI patients with depressive symptomatology. To explore brain dynamics we employed the Hidden Markov model that utilises resting-state fMRI data to identify the states that the brain visits sequentially during scanning. Spatial (highest activated regions) and temporal (occupancy, switching rate) characteristics of these states were used to analyse the networks involved and probe differences between depressed and non-depressed TBI patients. We found a significant positive association between depression score and the fractional occupancy and switching rate of two specific states that distinguished between depressed and non-depressed TBI patients. These states spanned default mode, subcortical and cerebellar regions while also forming a temporally coherent “metastate” that the depressed brain would recurrently visit. Depression in TBI patients is characterised by abnormal recruitment and repetitive sequencing between certain neural networks. These results point to the existence of a reinforced, self-referential circuitry that could provide the basis for targeted therapies during the recovery process.

OBJECTIVE:To determine the effect of extracranial injury (ECI) on 6-month outcome in patients with mild traumatic brain injury (TBI) versus moderate-to-severe TBI.PARTICIPANTS/SETTING:Patients with TBI (n = 135) or isolated orthopedic injury (n = 25) admitted to a UK major trauma center and healthy volunteers (n = 99).DESIGN:Case-control observational study.MAIN MEASURES:Primary outcomes: (a) Glasgow Outcome Scale Extended (GOSE), (b) depression, (c) quality of life (QOL), and (d) cognitive impairment including verbal fluency, episodic memory, short-term recognition memory, working memory, sustained attention, and attentional flexibility.RESULTS:Outcome was influenced by both TBI severity and concomitant ECI. The influence of ECI was restricted to mild TBI; GOSE, QOL, and depression outcomes were significantly poorer following moderate-to-severe TBI than after isolated mild TBI (but not relative to mild TBI plus ECI). Cognitive impairment was driven solely by TBI severity. General health, bodily pain, semantic verbal fluency, spatial recognition memory, working memory span, and attentional flexibility were unaffected by TBI severity and additional ECI.CONCLUSION:The presence of concomitant ECI ought to be considered alongside brain injury severity when characterizing the functional and neurocognitive effects of TBI, with each presenting challenges to recovery.

Background An improved understanding of the trajectory of recovery after mild traumatic brain injury is important to be able to understand individual patient outcomes, for longitudinal patient care and to aid the design of clinical trials. Objective To explore changes in health, well-being and cognition over the 2 years following mTBI using latent growth curve (LGC) modelling. Methods Sixty-one adults with mTBI presenting to a UK Major Trauma Centre completed comprehensive longitudinal assessment at up to five time points after injury: 2 weeks, 3 months, 6 months, 1 year and 2 years. Results Persisting problems were seen with neurological symptoms, cognitive issues and poor quality of life measures including 28% reporting incomplete recovery on the Glasgow Outcome Score Extended at 2 years. Harmful drinking, depression, psychological distress, disability, episodic memory and working memory did not improve significantly over the 2 years following injury. For other measures, including the Rivermead Post-Concussion Symptoms and Quality of Life after Brain Injury (QOLIBRI), LGC analysis revealed significant improvement over time with recovery tending to plateau at 3–6 months. Interpretation Significant impairment may persist as late as 2 years after mTBI despite some recovery over time. Longitudinal analyses which make use of all available data indicate that recovery from mTBI occurs over a longer timescale than is commonly believed. These findings point to the need for long-term management of mTBI targeting individuals with persisting impairment.

The default mode network (DMN) is typically associated with off-task internal mentation, or with goal-oriented tasks that require self-referential processing such as autobiographical planning. However, recent reports suggest a broader involvement of the DMN in higher cognition. In line with this view, we report global connectivity changes that are centered on the main DMN hubs of precuneus and posterior cingulate cortex during a functional magnetic resonance imaging-based visuospatial version of the Tower of London planning task. Importantly, functional connectivity of these regions with the left caudate shows a significant relationship with faster reaction time to correct responses only during the high-demand planning condition, thus offering further evidence for the DMN's engagement during visuospatial planning. The results of this study not only provide robust evidence against the widely held notion of DMN disengagement during goal-oriented, attention-demanding, externally directed tasks but also support its involvement in a broader cognitive context with a memory-related role that extends beyond self-referential, internally directed mentation.