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Vestibular Agnosia - where peripheral vestibular activation triggers the usual reflex nystagmus response but with attenuated or no self-motion perception - is found in brain disease with disrupted cortical network functioning, e.g. traumatic brain injury (TBI) or neurodegeneration (Parkinson's Disease). Patients with acute focal hemispheric lesions (e.g. stroke) do not manifest vestibular agnosia. Thus, brain network mapping techniques, e.g. resting state functional MRI (rsfMRI), are needed to interrogate functional brain networks mediating vestibular agnosia. Hence, we prospectively recruited 39 acute TBI patients with preserved peripheral vestibular function and obtained self-motion perceptual thresholds during passive yaw rotations in the dark and additionally acquired whole-brain rsfMRI in the acute phase. Following quality-control checks, 26 patient scans were analyzed. Using self-motion perceptual thresholds from a matched healthy control group, 11 acute TBI patients were classified as having vestibular agnosia versus 15 with normal self-motion perception thresholds. Using independent component analysis on the rsfMRI data, we found altered functional connectivity in bilateral lingual gyrus and temporo-occipital fusiform cortex in the vestibular agnosia patients. Moreover, regions of interest analyses showed both inter-hemispheric and intra-hemispheric network disruption in vestibular agnosia. In conclusion, our results show that vestibular agnosia is mediated by bilateral anterior and posterior network dysfunction and reveal the distributed brain mechanisms mediating vestibular self-motion perception., Competing Interests: Declaration of Competing Interest The authors declare that they have no conflict of interest., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

Long-term outcomes are difficult to predict after paediatric traumatic brain injury. The presence or absence of focal brain injuries often do not explain cognitive, emotional and behavioural disabilities that are common and disabling. In adults, traumatic brain injury produces progressive brain atrophy that can be accurately measured and is associated with cognitive decline. However, the effect of paediatric traumatic brain injury on brain volumes is more challenging to measure because of its interaction with normal brain development. Here we report a robust approach to the individualized estimation of brain volume following paediatric traumatic brain injury and investigate its relationship to clinical outcomes. We first used a large healthy control dataset (n > 1200, age 8-22) to describe the healthy development of white and grey matter regions through adolescence. Individual estimates of grey and white matter regional volume were then generated for a group of moderate/severe traumatic brain injury patients injured in childhood (n = 39, mean age 13.53 ± 1.76, median time since injury = 14 months, range 4-168 months) by comparing brain volumes in patients to age-matched controls. Patients were individually classified as having low or normal brain volume. Neuropsychological and neuropsychiatric outcomes were assessed using standardized testing and parent/carer assessments. Relative to head size, grey matter regions decreased in volume during normal adolescence development whereas white matter tracts increased in volume. Traumatic brain injury disrupted healthy brain development, producing reductions in both grey and white matter brain volumes after correcting for age. Of the 39 patients investigated, 11 (28%) had at least one white matter tract with reduced volume and seven (18%) at least one area of grey matter with reduced volume. Those classified as having low brain volume had slower processing speed compared to healthy controls, emotional impairments, higher levels of apathy, increased anger and learning difficulties. In contrast, the presence of focal brain injury and microbleeds were not associated with an increased risk of these clinical impairments. In summary, we show how brain volume abnormalities after paediatric traumatic brain injury can be robustly calculated from individual T1 MRI using a large normative dataset that allows the effects of healthy brain development to be controlled for. Using this approach, we show that volumetric abnormalities are common after moderate/severe traumatic brain injury in both grey and white matter regions, and are associated with higher levels of cognitive, emotional and behavioural abnormalities that are common after paediatric traumatic brain injury., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Guarantors of Brain.)

Following hyperacute management after traumatic brain injury (TBI), most patients receive treatment which is inadequate or inappropriate, and delayed. This results in suboptimal rehabilitation outcome and avoidable detrimental chronic effects on patients' recovery. This worsens long-term disability, and magnifies costs to the individual and society. We believe that accurate diagnosis (at the level of pathology, impairment and function) of the causes of disability is a prerequisite for appropriate care and for accessing effective rehabilitation. An expert-led, integrated care pathway is needed to deliver accurate and timely diagnosis and optimal treatment at all stages during a TBI patient's care.We propose the introduction of a specialist interdisciplinary traumatic brain injury team, led by a neurosciences-trained brain injury consultant. This team would engage acutely and for a longer term after TBI to provide accurate diagnoses, which guides subsequent management and rehabilitation. This approach would also encourage more efficient collaboration between research and the clinic. We propose that the current major trauma network is leveraged to introduce and evaluate this proposal. Improvements to patient outcomes through this approach would lead to reduced personal, societal and economic impact of TBI., (© Royal College of Physicians 2021. All rights reserved.)

Objective: To image β-amyloid (Aβ) plaque burden in long-term survivors of traumatic brain injury (TBI), test whether traumatic axonal injury and Aβ are correlated, and compare the spatial distribution of Aβ to Alzheimer disease (AD)., Methods: Patients 11 months to 17 years after moderate-severe TBI underwent (11)C-Pittsburgh compound B ((11)C-PiB)-PET, structural and diffusion MRI, and neuropsychological examination. Healthy aged controls and patients with AD underwent PET and structural MRI. Binding potential (BPND) images of (11)C-PiB, which index Aβ plaque density, were computed using an automatic reference region extraction procedure. Voxelwise and regional differences in BPND were assessed. In TBI, a measure of white matter integrity, fractional anisotropy, was estimated and correlated with (11)C-PiB BPND., Results: Twenty-eight participants (9 with TBI, 9 controls, 10 with AD) were assessed. Increased (11)C-PiB BPND was found in TBI vs controls in the posterior cingulate cortex and cerebellum. Binding in the posterior cingulate cortex increased with decreasing fractional anisotropy of associated white matter tracts and increased with time since injury. Compared to AD, binding after TBI was lower in neocortical regions but increased in the cerebellum., Conclusions: Increased Aβ burden was observed in TBI. The distribution overlaps with, but is distinct from, that of AD. This suggests a mechanistic link between TBI and the development of neuropathologic features of dementia, which may relate to axonal damage produced by the injury., (© 2016 American Academy of Neurology.)

Background: Traumatic brain injury can trigger chronic neuroinflammation, which may predispose to neurodegeneration. Animal models and human pathological studies demonstrate persistent inflammation in the thalamus associated with axonal injury, but this relationship has never been shown in vivo., Findings: Using [(11)C]-PK11195 positron emission tomography, a marker of microglial activation, we previously demonstrated thalamic inflammation up to 17 years after traumatic brain injury. Here, we use diffusion MRI to estimate axonal injury and show that thalamic inflammation is correlated with thalamo-cortical tract damage., Conclusions: These findings support a link between axonal damage and persistent inflammation after brain injury.

Current theory proposes that healthy neural dynamics operate in a metastable regime, where brain regions interact to simultaneously maximize integration and segregation. Metastability may confer important behavioral properties, such as cognitive flexibility. It is increasingly recognized that neural dynamics are constrained by the underlying structural connections between brain regions. An important challenge is, therefore, to relate structural connectivity, neural dynamics, and behavior. Traumatic brain injury (TBI) is a pre-eminent structural disconnection disorder whereby traumatic axonal injury damages large-scale connectivity, producing characteristic cognitive impairments, including slowed information processing speed and reduced cognitive flexibility, that may be a result of disrupted metastable dynamics. Therefore, TBI provides an experimental and theoretical model to examine how metastable dynamics relate to structural connectivity and cognition. Here, we use complementary empirical and computational approaches to investigate how metastability arises from the healthy structural connectome and relates to cognitive performance. We found reduced metastability in large-scale neural dynamics after TBI, measured with resting-state functional MRI. This reduction in metastability was associated with damage to the connectome, measured using diffusion MRI. Furthermore, decreased metastability was associated with reduced cognitive flexibility and information processing. A computational model, defined by empirically derived connectivity data, demonstrates how behaviorally relevant changes in neural dynamics result from structural disconnection. Our findings suggest how metastable dynamics are important for normal brain function and contingent on the structure of the human connectome., (Copyright © 2015 the authors 0270-6474/15/359050-14$15.00/0.)

Traumatic brain injury affects brain connectivity by producing traumatic axonal injury. This disrupts the function of large-scale networks that support cognition. The best way to describe this relationship is unclear, but one elegant approach is to view networks as graphs. Brain regions become nodes in the graph, and white matter tracts the connections. The overall effect of an injury can then be estimated by calculating graph metrics of network structure and function. Here we test which graph metrics best predict the presence of traumatic axonal injury, as well as which are most highly associated with cognitive impairment. A comprehensive range of graph metrics was calculated from structural connectivity measures for 52 patients with traumatic brain injury, 21 of whom had microbleed evidence of traumatic axonal injury, and 25 age-matched controls. White matter connections between 165 grey matter brain regions were defined using tractography, and structural connectivity matrices calculated from skeletonized diffusion tensor imaging data. This technique estimates injury at the centre of tract, but is insensitive to damage at tract edges. Graph metrics were calculated from the resulting connectivity matrices and machine-learning techniques used to select the metrics that best predicted the presence of traumatic brain injury. In addition, we used regularization and variable selection via the elastic net to predict patient behaviour on tests of information processing speed, executive function and associative memory. Support vector machines trained with graph metrics of white matter connectivity matrices from the microbleed group were able to identify patients with a history of traumatic brain injury with 93.4% accuracy, a result robust to different ways of sampling the data. Graph metrics were significantly associated with cognitive performance: information processing speed (R(2) = 0.64), executive function (R(2) = 0.56) and associative memory (R(2) = 0.25). These results were then replicated in a separate group of patients without microbleeds. The most influential graph metrics were betweenness centrality and eigenvector centrality, which provide measures of the extent to which a given brain region connects other regions in the network. Reductions in betweenness centrality and eigenvector centrality were particularly evident within hub regions including the cingulate cortex and caudate. Our results demonstrate that betweenness centrality and eigenvector centrality are reduced within network hubs, due to the impact of traumatic axonal injury on network connections. The dominance of betweenness centrality and eigenvector centrality suggests that cognitive impairment after traumatic brain injury results from the disconnection of network hubs by traumatic axonal injury., (© The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain.)

Objective: The long-term effects of traumatic brain injury (TBI) can resemble observed in normal ageing, suggesting that TBI may accelerate the ageing process. We investigate this using a neuroimaging model that predicts brain age in healthy individuals and then apply it to TBI patients. We define individuals' differences in chronological and predicted structural "brain age," and test whether TBI produces progressive atrophy and how this relates to cognitive function., Methods: A predictive model of normal ageing was defined using machine learning in 1,537 healthy individuals, based on magnetic resonance imaging-derived estimates of gray matter (GM) and white matter (WM). This ageing model was then applied to test 99 TBI patients and 113 healthy controls to estimate brain age., Results: The initial model accurately predicted age in healthy individuals (r = 0.92). TBI brains were estimated to be "older," with a mean predicted age difference (PAD) between chronological and estimated brain age of 4.66 years (±10.8) for GM and 5.97 years (±11.22) for WM. This PAD predicted cognitive impairment and correlated strongly with the time since TBI, indicating that brain tissue loss increases throughout the chronic postinjury phase., Interpretation: TBI patients' brains were estimated to be older than their chronological age. This discrepancy increases with time since injury, suggesting that TBI accelerates the rate of brain atrophy. This may be an important factor in the increased susceptibility in TBI patients for dementia and other age-associated conditions, motivating further research into the age-like effects of brain injury and other neurological diseases., (© 2015 The Authors Annals of Neurology published by Wiley Periodicals, Inc. on behalf of American Neurological Association.)

Interactions between the Salience Network (SN) and the Default Mode Network (DMN) are thought to be important for cognitive control. However, evidence for a causal relationship between the networks is limited. Previously, we have reported that traumatic damage to white matter tracts within the SN predicts abnormal DMN function. Here we investigate the effect of this damage on network interactions that accompany changing motor control. We initially used fMRI of the Stop Signal Task to study response inhibition in humans. In healthy subjects, functional connectivity (FC) between the right anterior insula (rAI), a key node of the SN, and the DMN transiently increased during stopping. This change in FC was not seen in a group of traumatic brain injury (TBI) patients with impaired cognitive control. Furthermore, the amount of SN tract damage negatively correlated with FC between the networks. We confirmed these findings in a second group of TBI patients. Here, switching rather than inhibiting a motor response: (1) was accompanied by a similar increase in network FC in healthy controls; (2) was not seen in TBI patients; and (3) tract damage after TBI again correlated with FC breakdown. This shows that coupling between the rAI and DMN increases with cognitive control and that damage within the SN impairs this dynamic network interaction. This work provides compelling evidence for a model of cognitive control where the SN is involved in the attentional capture of salient external stimuli and signals the DMN to reduce its activity when attention is externally focused., (Copyright © 2014 Jilka et al.)

Diffuse axonal injury after traumatic brain injury (TBI) produces neurological impairment by disconnecting brain networks. This structural damage can be mapped using diffusion MRI, and its functional effects can be investigated in large-scale intrinsic connectivity networks (ICNs). Here, we review evidence that TBI substantially disrupts ICN function, and that this disruption predicts cognitive impairment. We focus on two ICNs--the salience network and the default mode network. The activity of these ICNs is normally tightly coupled, which is important for attentional control. Damage to the structural connectivity of these networks produces predictable abnormalities of network function and cognitive control. For example, the brain normally shows a 'small-world architecture' that is optimized for information processing, but TBI shifts network function away from this organization. The effects of TBI on network function are likely to be complex, and we discuss how advanced approaches to modelling brain dynamics can provide insights into the network dysfunction. We highlight how structural network damage caused by axonal injury might interact with neuroinflammation and neurodegeneration in the pathogenesis of Alzheimer disease and chronic traumatic encephalopathy, which are late complications of TBI. Finally, we discuss how network-level diagnostics could inform diagnosis, prognosis and treatment development following TBI.

Self-awareness is commonly impaired after traumatic brain injury. This is an important clinical issue as awareness affects long-term outcome and limits attempts at rehabilitation. It can be investigated by studying how patients respond to their errors and monitor their performance on tasks. As awareness is thought to be an emergent property of network activity, we tested the hypothesis that impaired self-awareness is associated with abnormal brain network function. We investigated a group of subjects with traumatic brain injury (n = 63) split into low and high performance-monitoring groups based on their ability to recognize and correct their own errors. Brain network function was assessed using resting-state and event-related functional magnetic resonance imaging. This allowed us to investigate baseline network function, as well as the evoked response of networks to specific events including errors. The low performance-monitoring group underestimated their disability and showed broad attentional deficits. Neural activity within what has been termed the fronto-parietal control network was abnormal in patients with impaired self-awareness. The dorsal anterior cingulate cortex is a key part of this network that is involved in performance-monitoring. This region showed reduced functional connectivity to the rest of the fronto-parietal control network at 'rest'. In addition, the anterior insulae, which are normally tightly linked to the dorsal anterior cingulate cortex, showed increased activity following errors in the impaired group. Interestingly, the traumatic brain injury patient group with normal performance-monitoring showed abnormally high activation of the right middle frontal gyrus, putamen and caudate in response to errors. The impairment of self-awareness was not explained either by the location of focal brain injury, or the amount of traumatic axonal injury as demonstrated by diffusion tensor imaging. The results suggest that impairments of self-awareness after traumatic brain injury result from breakdown of functional interactions between nodes within the fronto-parietal control network.

Objective: Pituitary dysfunction is a recognized consequence of traumatic brain injury (TBI) that causes cognitive, psychological, and metabolic impairment. Hormone replacement offers a therapeutic opportunity. Blast TBI (bTBI) from improvised explosive devices is commonly seen in soldiers returning from recent conflicts. We investigated: (1) the prevalence and consequences of pituitary dysfunction following moderate to severe bTBI and (2) whether it is associated with particular patterns of brain injury., Methods: Nineteen male soldiers with moderate to severe bTBI (median age = 28.3 years) and 39 male controls with moderate to severe nonblast TBI (nbTBI; median age = 32.3 years) underwent full dynamic endocrine assessment between 2 and 48 months after injury. In addition, soldiers had structural brain magnetic resonance imaging, including diffusion tensor imaging (DTI), and cognitive assessment., Results: Six of 19 (32.0%) soldiers with bTBI, but only 1 of 39 (2.6%) nbTBI controls, had anterior pituitary dysfunction (p = 0.004). Two soldiers had hyperprolactinemia, 2 had growth hormone (GH) deficiency, 1 had adrenocorticotropic hormone (ACTH) deficiency, and 1 had combined GH/ACTH/gonadotrophin deficiency. DTI measures of white matter structure showed greater traumatic axonal injury in the cerebellum and corpus callosum in those soldiers with pituitary dysfunction than in those without. Soldiers with pituitary dysfunction after bTBI also had a higher prevalence of skull/facial fractures and worse cognitive function. Four soldiers (21.1%) commenced hormone replacement(s) for hypopituitarism., Interpretation: We reveal a high prevalence of anterior pituitary dysfunction in soldiers suffering moderate to severe bTBI, which was more frequent than in a matched group of civilian moderate to severe nbTBI subjects. We recommend that all patients with moderate to severe bTBI should routinely have comprehensive assessment of endocrine function., (© 2013 The Authors. Annals of Neurology published by Wiley Periodicals, Inc. on behalf of the American Neurological Association.)

Objective: We test the hypothesis that brain networks associated with cognitive function shift away from a "small-world" organization following traumatic brain injury (TBI)., Methods: We investigated 20 TBI patients and 21 age-matched controls. Resting-state functional MRI was used to study functional connectivity. Graph theoretical analysis was then applied to partial correlation matrices derived from these data. The presence of white matter damage was quantified using diffusion tensor imaging., Results: Patients showed characteristic cognitive impairments as well as evidence of damage to white matter tracts. Compared to controls, the graph analysis showed reduced overall connectivity, longer average path lengths, and reduced network efficiency. A particular impact of TBI is seen on a major network hub, the posterior cingulate cortex. Taken together, these results confirm that a network critical to cognitive function shows a shift away from small-world characteristics., Conclusions: We provide evidence that key brain networks involved in supporting cognitive function become less small-world in their organization after TBI. This is likely to be the result of diffuse white matter damage, and may be an important factor in producing cognitive impairment after TBI.

Objective: Traumatic brain injury (TBI) often results in traumatic axonal injury (TAI). This can be difficult to identify using conventional imaging. Diffusion tensor imaging (DTI) offers a method of assessing axonal damage in vivo, but has previously mainly been used to investigate groups of patients. Machine learning techniques are increasingly used to improve diagnosis based on complex imaging measures. We investigated whether machine learning applied to DTI data can be used to diagnose white matter damage after TBI and to predict neuropsychological outcome in individual patients., Methods: We trained pattern classifiers to predict the presence of white matter damage in 25 TBI patients with microbleed evidence of TAI compared to neurologically healthy age-matched controls. We then applied these classifiers to 35 additional patients with no conventional imaging evidence of TAI. Finally, we used regression analyses to predict indices of neuropsychological outcome for information processing speed, executive function, and associative memory in a group of 70 heterogeneous patients., Results: The classifiers discriminated between patients with microbleeds and age-matched controls with a high degree of accuracy, and outperformed other methods. When the trained classifiers were applied to patients without microbleeds, patients having likely TAI showed evidence of greater cognitive impairment in information processing speed and executive function. The classifiers were also able to predict the extent of impairments in information processing speed and executive function., Interpretation: The work provides a proof of principle that multivariate techniques can be used with DTI to provide diagnostic information about clinically significant TAI., (Copyright © 2012 American Neurological Association.)

Purpose of Review: Traumatic brain injury (TBI) often results in long-term cognitive impairments. This is often due to the disruption of brain networks that support cognition. Major advances have recently been made in our understanding of these networks. Here we review work that investigates the effect of TBI on brain networks, and discuss the potential importance of these findings for rehabilitation., Recent Findings: Large-scale brain networks, which we refer to as intrinsic connectivity networks (ICNs), have been identified. Traumatic axonal injury disrupts their white-matter connections, and altered brain activity within the networks is frequently observed after TBI. These changes relate to the pattern of cognitive impairment, and are useful for predicting clinical outcome. The effect of drugs such as methylphenidate, which can be used to augment rehabilitation, are beginning to be studied in the context of their effect on network function after TBI., Summary: The assessment of brain network function after TBI provides insights into the pathophysiology of cognitive dysfunction and the mechanisms involved in recovery. These advances should provide the basis for a more detailed understanding of rehabilitation, and ultimately guide the development of targeted individualized therapy after TBI.

Damage to the structural connections of the thalamus is a frequent feature of traumatic brain injury (TBI) and can be a key factor in determining clinical outcome. Until recently it has been difficult to quantify the extent of this damage in vivo. Diffusion tensor imaging (DTI) provides a validated method to investigate traumatic axonal injury, and can be applied to quantify damage to thalamic connections. DTI can also be used to assess white matter tract structure using tractography, and this technique has been used to study thalamo-cortical connections in the healthy brain. However, the presence of white matter injury can cause failure of tractography algorithms. Here, we report a method for investigating thalamo-cortical connectivity that bypasses the need for individual tractography. We first created a template for a number of thalamo-cortical connections using probabilistic tractography performed in ten healthy subjects. This template for investigating white matter structure was validated by comparison with individual tractography in the same group, as well as in an independent control group (N=11). We also evaluated two methods of masking tract location using the tract skeleton generated by tract based spatial statistics, and a cerebrospinal fluid mask. Voxel-wise estimates of fractional anisotropy derived from the template were more strongly correlated with individual tractography when both types of masking were used. The tract templates were then used to sample DTI measures from a group of TBI patients (N=22), with direct comparison performed against probabilistic tractography in individual patients. Probabilistic tractography often failed to produce anatomically plausible tracts in TBI patients. Importantly, we show that this problem increases as tracts become more damaged, and leads to underestimation of the amount of traumatic axonal injury. In contrast, the tract template can be used in these cases, allowing a more accurate assessment of white matter damage. In summary, we propose a method suitable for assessing specific thalamo-cortical white matter connections after TBI that is robust to the presence of varying amounts of traumatic axonal injury, as well as highlighting the potential problems of applying tractography algorithms in patient populations., (Copyright © 2012 Elsevier Inc. All rights reserved.)

Efficient behavior involves the coordinated activity of large-scale brain networks, but the way in which these networks interact is uncertain. One theory is that the salience network (SN)--which includes the anterior cingulate cortex, presupplementary motor area, and anterior insulae--regulates dynamic changes in other networks. If this is the case, then damage to the structural connectivity of the SN should disrupt the regulation of associated networks. To investigate this hypothesis, we studied a group of 57 patients with cognitive impairments following traumatic brain injury (TBI) and 25 control subjects using the stop-signal task. The pattern of brain activity associated with stop-signal task performance was studied by using functional MRI, and the structural integrity of network connections was quantified by using diffusion tensor imaging. Efficient inhibitory control was associated with rapid deactivation within parts of the default mode network (DMN), including the precuneus and posterior cingulate cortex. TBI patients showed a failure of DMN deactivation, which was associated with an impairment of inhibitory control. TBI frequently results in traumatic axonal injury, which can disconnect brain networks by damaging white matter tracts. The abnormality of DMN function was specifically predicted by the amount of white matter damage in the SN tract connecting the right anterior insulae to the presupplementary motor area and dorsal anterior cingulate cortex. The results provide evidence that structural integrity of the SN is necessary for the efficient regulation of activity in the DMN, and that a failure of this regulation leads to inefficient cognitive control.

Purpose of Review: Traumatic brain injury (TBI) often results in traumatic axonal injury (TAI). This is difficult to identify using conventional neuroimaging methods. We review recent work that uses advanced imaging methods to identify TAI following mild (m)TBI., Recent Findings: Susceptibility-weighted imaging (SWI) is a highly sensitive way of identifying microbleeds, which are a marker of TAI. Diffusion tensor imaging (DTI) provides a more flexible way of investigating white matter injury. Recent studies largely confirm that DTI is sensitive to white matter damage after mTBI. Distinct DTI abnormalities are observed in the acute and subacute/chronic stages. DTI measurements change dynamically after an injury, reflecting the evolving pathological processes. DTI abnormalities correlate with cognitive and neuropsychiatric impairments. Importantly, DTI can contribute to the prediction of clinical outcome and has begun to be applied to the study of sports and blast injury., Summary: DTI and SWI are important advances in MRI that allow more detailed investigation of white matter injury. SWI is a highly sensitive way of identifying microbleeds. DTI is a flexible way of quantifying white matter integrity, and provides a method of diagnosing clinically significant white matter injury when conventional imaging is normal.

Traumatic brain injury (TBI) frequently produces impairments of attention in humans. These can result in a failure to maintain consistent goal-directed behavior. A predominantly right-lateralized frontoparietal network is often engaged during attentionally demanding tasks. However, lapses of attention have also been associated with increases in activation within the default mode network (DMN). Here, we study TBI patients with sustained attention impairment, defined on the basis of the consistency of their behavioral performance over time. We show that sustained attention impairments in patients are associated with an increase in DMN activation, particularly within the precuneus and posterior cingulate cortex. Furthermore, the interaction of the precuneus with the rest of the DMN at the start of the task, i.e., its functional connectivity, predicts which patients go on to show impairments of attention. Importantly, this predictive information is present before any behavioral evidence of sustained attention impairment, and the relationship is also found in a subgroup of patients without focal brain damage. TBI often results in diffuse axonal injury, which produces cognitive impairment by disconnecting nodes in distributed brain networks. Using diffusion tensor imaging, we demonstrate that structural disconnection within the DMN also correlates with the level of sustained attention. These results show that abnormalities in DMN function are a sensitive marker of impairments of attention and suggest that changes in connectivity within the DMN are central to the development of attentional impairment after TBI.

Objective: Patient outcome after traumatic brain injury (TBI) is highly variable. The underlying pathophysiology of this is poorly understood, but inflammation is potentially an important factor. Microglia orchestrate many aspects of this response. Their activation can be studied in vivo using the positron emission tomography (PET) ligand [11C](R)PK11195 (PK). In this study, we investigate whether an inflammatory response to TBI persists, and whether this response relates to structural brain abnormalities and cognitive function., Methods: Ten patients, studied at least 11 months after moderate to severe TBI, underwent PK PET and structural magnetic resonance imaging (including diffusion tensor imaging). PK binding potentials were calculated in and around the site of focal brain damage, and in selected distant and subcortical brain regions. Standardized neuropsychological tests were administered., Results: PK binding was significantly raised in the thalami, putamen, occipital cortices, and posterior limb of the internal capsules after TBI. There was no increase in PK binding at the original site of focal brain injury. High PK binding in the thalamus was associated with more severe cognitive impairment, although binding was not correlated with either the time since the injury or the extent of structural brain damage., Interpretation: We demonstrate that increased microglial activation can be present up to 17 years after TBI. This suggests that TBI triggers a chronic inflammatory response particularly in subcortical regions. This highlights the importance of considering the response to TBI as evolving over time and suggests interventions may be beneficial for longer intervals after trauma than previously assumed., (Copyright © 2011 American Neurological Association.)

Traumatic brain injury often results in cognitive impairments that limit recovery. The underlying pathophysiology of these impairments is uncertain, which restricts clinical assessment and management. Here, we use magnetic resonance imaging to test the hypotheses that: (i) traumatic brain injury results in abnormalities of functional connectivity within key cognitive networks; (ii) these changes are correlated with cognitive performance; and (iii) functional connectivity within these networks is influenced by underlying changes in structural connectivity produced by diffuse axonal injury. We studied 20 patients in the chronic phase after traumatic brain injury compared with age-matched controls. Network function was investigated in detail using functional magnetic resonance imaging to analyse both regional brain activation, and the interaction of brain regions within a network (functional connectivity). We studied patients during performance of a simple choice-reaction task and at 'rest'. Since functional connectivity reflects underlying structural connectivity, diffusion tensor imaging was used to quantify axonal injury, and test whether structural damage correlated with functional change. The patient group showed typical impairments in information processing and attention, when compared with age-matched controls. Patients were able to perform the task accurately, but showed slow and variable responses. Brain regions activated by the task were similar between the groups, but patients showed greater deactivation within the default mode network, in keeping with an increased cognitive load. A multivariate analysis of 'resting' state functional magnetic resonance imaging was then used to investigate whether changes in network function were present in the absence of explicit task performance. Overall, default mode network functional connectivity was increased in the patient group. Patients with the highest functional connectivity had the least cognitive impairment. In addition, functional connectivity at rest also predicted patterns of brain activation during later performance of the task. As expected, patients showed widespread white matter damage compared with controls. Lower default mode network functional connectivity was seen in those patients with more evidence of diffuse axonal injury within the adjacent corpus callosum. Taken together, our results demonstrate altered patterns of functional connectivity in cognitive networks following injury. The results support a direct relationship between white matter organization within the brain's structural core, functional connectivity within the default mode network and cognitive function following brain injury. They can be explained by two related changes: a compensatory increase in functional connectivity within the default mode network; and a variable degree of structural disconnection that modulates this change in network function.

White matter disruption is an important determinant of cognitive impairment after brain injury, but conventional neuroimaging underestimates its extent. In contrast, diffusion tensor imaging provides a validated and sensitive way of identifying the impact of axonal injury. The relationship between cognitive impairment after traumatic brain injury and white matter damage is likely to be complex. We applied a flexible technique-tract-based spatial statistics-to explore whether damage to specific white matter tracts is associated with particular patterns of cognitive impairment. The commonly affected domains of memory, executive function and information processing speed were investigated in 28 patients in the post-acute/chronic phase following traumatic brain injury and in 26 age-matched controls. Analysis of fractional anisotropy and diffusivity maps revealed widespread differences in white matter integrity between the groups. Patients showed large areas of reduced fractional anisotropy, as well as increased mean and axial diffusivities, compared with controls, despite the small amounts of cortical and white matter damage visible on standard imaging. A stratified analysis based on the presence or absence of microbleeds (a marker of diffuse axonal injury) revealed diffusion tensor imaging to be more sensitive than gradient-echo imaging to white matter damage. The location of white matter abnormality predicted cognitive function to some extent. The structure of the fornices was correlated with associative learning and memory across both patient and control groups, whilst the structure of frontal lobe connections showed relationships with executive function that differed in the two groups. These results highlight the complexity of the relationships between white matter structure and cognition. Although widespread and, sometimes, chronic abnormalities of white matter are identifiable following traumatic brain injury, the impact of these changes on cognitive function is likely to depend on damage to key pathways that link nodes in the distributed brain networks supporting high-level cognitive functions.

Traumatic brain injury (TBI) has the highest incidence of all common neurological disorders, and poses a substantial public health burden. TBI is increasingly documented not only as an acute condition but also as a chronic disease with long-term consequences, including an increased risk of late-onset neurodegeneration. The first Lancet Neurology Commission on TBI, published in 2017, called for a concerted effort to tackle the global health problem posed by TBI. Since then, funding agencies have supported research both in high-income countries (HICs) and in low-income and middle-income countries (LMICs). In November 2020, the World Health Assembly, the decision-making body of WHO, passed resolution WHA73.10 for global actions on epilepsy and other neurological disorders, and WHO launched the Decade for Action on Road Safety plan in 2021. New knowledge has been generated by large observational studies, including those conducted under the umbrella of the International Traumatic Brain Injury Research (InTBIR) initiative, established as a collaboration of funding agencies in 2011. InTBIR has also provided a huge stimulus to collaborative research in TBI and has facilitated participation of global partners. The return on investment has been high, but many needs of patients with TBI remain unaddressed. This update to the 2017 Commission presents advances and discusses persisting and new challenges in prevention, clinical care, and research. In LMICs, the occurrence of TBI is driven by road traffic incidents, often involving vulnerable road users such as motorcyclists and pedestrians. In HICs, most TBI is caused by falls, particularly in older people (aged ≥65 years), who often have comorbidities. Risk factors such as frailty and alcohol misuse provide opportunities for targeted prevention actions. Little evidence exists to inform treatment of older patients, who have been commonly excluded from past clinical trials—consequently, appropriate evidence is urgently required. Although increasing age is associated with worse outcomes from TBI, age should not dictate limitations in therapy. However, patients injured by low-energy falls (who are mostly older people) are about 50% less likely to receive critical care or emergency interventions, compared with those injured by high-energy mechanisms, such as road traffic incidents. Mild TBI, defined as a Glasgow Coma sum score of 13–15, comprises most of the TBI cases (over 90%) presenting to hospital. Around 50% of adult patients with mild TBI presenting to hospital do not recover to pre-TBI levels of health by 6 months after their injury. Fewer than 10% of patients discharged after presenting to an emergency department for TBI in Europe currently receive follow-up. Structured follow-up after mild TBI should be considered good practice, and urgent research is needed to identify which patients with mild TBI are at risk for incomplete recovery. The selection of patients for CT is an important triage decision in mild TBI since it allows early identification of lesions that can trigger hospital admission or life-saving surgery. Current decision making for deciding on CT is inefficient, with 90–95% of scanned patients showing no intracranial injury but being subjected to radiation risks. InTBIR studies have shown that measurement of blood-based biomarkers adds value to previously proposed clinical decision rules, holding the potential to improve efficiency while reducing radiation exposure. Increased concentrations of biomarkers in the blood of patients with a normal presentation CT scan suggest structural brain damage, which is seen on MR scanning in up to 30% of patients with mild TBI. Advanced MRI, including diffusion tensor imaging and volumetric analyses, can identify additional injuries not detectable by visual inspection of standard clinical MR images. Thus, the absence of CT abnormalities does not exclude structural damage—an observation relevant to litigation procedures, to management of mild TBI, and when CT scans are insufficient to explain the severity of the clinical condition. Although blood-based protein biomarkers have been shown to have important roles in the evaluation of TBI, most available assays are for research use only. To date, there is only one vendor of such assays with regulatory clearance in Europe and the USA with an indication to rule out the need for CT imaging for patients with suspected TBI. Regulatory clearance is provided for a combination of biomarkers, although evidence is accumulating that a single biomarker can perform as well as a combination. Additional biomarkers and more clinical-use platforms are on the horizon, but cross-platform harmonisation of results is needed. Health-care efficiency would benefit from diversity in providers. In the intensive care setting, automated analysis of blood pressure and intracranial pressure with calculation of derived parameters can help individualise management of TBI. Interest in the identification of subgroups of patients who might benefit more from some specific therapeutic approaches than others represents a welcome shift towards precision medicine. Comparative-effectiveness research to identify best practice has delivered on expectations for providing evidence in support of best practices, both in adult and paediatric patients with TBI. Progress has also been made in improving outcome assessment after TBI. Key instruments have been translated into up to 20 languages and linguistically validated, and are now internationally available for clinical and research use. TBI affects multiple domains of functioning, and outcomes are affected by personal characteristics and life-course events, consistent with a multifactorial bio-psycho-socio-ecological model of TBI, as presented in the US National Academies of Sciences, Engineering, and Medicine (NASEM) 2022 report. Multidimensional assessment is desirable and might be best based on measurement of global functional impairment. More work is required to develop and implement recommendations for multidimensional assessment. Prediction of outcome is relevant to patients and their families, and can facilitate the benchmarking of quality of care. InTBIR studies have identified new building blocks (eg, blood biomarkers and quantitative CT analysis) to refine existing prognostic models. Further improvement in prognostication could come from MRI, genetics, and the integration of dynamic changes in patient status after presentation. Neurotrauma researchers traditionally seek translation of their research findings through publications, clinical guidelines, and industry collaborations. However, to effectively impact clinical care and outcome, interactions are also needed with research funders, regulators, and policy makers, and partnership with patient organisations. Such interactions are increasingly taking place, with exemplars including interactions with the All Party Parliamentary Group on Acquired Brain Injury in the UK, the production of the NASEM report in the USA, and interactions with the US Food and Drug Administration. More interactions should be encouraged, and future discussions with regulators should include debates around consent from patients with acute mental incapacity and data sharing. Data sharing is strongly advocated by funding agencies. From January 2023, the US National Institutes of Health will require upload of research data into public repositories, but the EU requires data controllers to safeguard data security and privacy regulation. The tension between open data-sharing and adherence to privacy regulation could be resolved by cross-dataset analyses on federated platforms, with the data remaining at their original safe location. Tools already exist for conventional statistical analyses on federated platforms, however federated machine learning requires further development. Support for further development of federated platforms, and neuroinformatics more generally, should be a priority. This update to the 2017 Commission presents new insights and challenges across a range of topics around TBI: epidemiology and prevention (section 1); system of care (section 2); clinical management (section 3); characterisation of TBI (section 4); outcome assessment (section 5); prognosis (Section 6); and new directions for acquiring and implementing evidence (section 7). Table 1 summarises key messages from this Commission and proposes recommendations for the way forward to advance research and clinical management of TBI.

The global burden of mortality and morbidity caused by traumatic brain injury (TBI) is significant, and the heterogeneity of TBI patients and the relatively small sample sizes of most current neuroimaging studies is a major challenge for scientific advances and clinical translation. The ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) Adult moderate/severe TBI (AMS-TBI) working group aims to be a driving force for new discoveries in AMS-TBI by providing researchers world-wide with an effective framework and platform for large-scale cross-border collaboration and data sharing. Based on the principles of transparency, rigor, reproducibility and collaboration, we will facilitate the development and dissemination of multiscale and big data analysis pipelines for harmonized analyses in AMS-TBI using structural and functional neuroimaging in combination with non-imaging biomarkers, genetics, as well as clinical and behavioral measures. Ultimately, we will offer investigators an unprecedented opportunity to test important hypotheses about recovery and morbidity in AMS-TBI by taking advantage of our robust methods for large-scale neuroimaging data analysis. In this consensus statement we outline the working group's short-term, intermediate, and long-term goals.

Background: Home monitoring systems utilising artificial intelligence hold promise for digitally enhanced healthcare in older adults. Their real-world use will depend on acceptability to the end user i.e. older adults and caregivers. We explored the experiences of adults over the age of 60 and their social and care networks with a home monitoring system installed on hospital discharge after sustaining a moderate/severe Traumatic Brain Injury (TBI), a growing public health concern. Methods: A qualitative descriptive approach was taken to explore experiential data from older adults and their caregivers as part of a feasibility study. Semi-structured interviews were conducted with 6 patients and 6 caregivers (N = 12) at 6-month study exit. Data were analysed using Framework analysis. Potential factors affecting acceptability and barriers and facilitators to the use of home monitoring in clinical care and research were examined. Results: Home monitoring was acceptable to older adults with TBI and their caregivers. Facilitators to the use of home monitoring were perceived need for greater support after hospital discharge, the absence of sound and video recording, and the peace of mind provided to care providers. Potential barriers to adoption were reliability, lack of confidence in technology and uncertainty at how data would be acted upon to improve safety at home. Conclusions: Remote monitoring approaches are likely to be acceptable, especially if patients and caregivers see direct benefit to their care. We identified key barriers and facilitators to the use of home monitoring in older adults who had sustained TBI, which can inform the development of home monitoring for research and clinical use. For sustained use in this demographic the technology should be developed in conjunction with older adults and their social and care networks. [ABSTRACT FROM AUTHOR]

Introduction: Traumatic brain injury (TBI) is associated with health problems across multiple domains and TBI patients are reported to have high rates of medication use. However, prior evidence is thin due to methodological limitations. Our aim was thus to examine the use of a wide spectrum of medications prescribed to address pain and somatic conditions in a populationbased cohort of TBI patients, and to compare this to a sex- and age-matched cohort. We also examined how patient factors such as sex, age, and TBI severity were associated with medication use. Methods: We assessed Swedish nationwide registers to include all individuals treated for TBI in hospitals or specialist outpatient care between 2006 and 2012. We examined dispensed prescriptions for eight different non-psychotropic medication classes for the 12 months before, and 12 months after, the TBI. We applied a fixed-effects model to compare TBI patients with the matched population cohort. We also stratified TBI patients by sex, age, TBI severity and carried out comparisons using a generalized linear model. Results: We identified 239,425 individuals with an incident TBI and 239,425 matched individuals. TBI patients were more likely to use any medication [Odds ratio (OR) = 2.03, 95% Confidence Interval (CI) = 2.00-2.05], to present with polypharmacy (OR = 1.96, 95% CI = 1.90-2.02), and to use each of the eight medication classes before their TBI, as compared to the matched population cohort. Following the TBI, TBI patients were more likely to use any medication (OR = 1.83, 95% CI = 1.80-1.86), to present with polypharmacy (OR = 1.74, 95% CI = 1.67-1.80), and to use all medication classes, although differences were attenuated. However, differences increased for antibiotics/antivirals (OR = 2.02, 95% CI = 1.99-2.05) and NSAIDs/antirheumatics (OR = 1.62, 95% CI = 1.59-1.65) post-TBI. We also found that females and older patients were more likely to use medications after their TBI than males and younger patients, respectively. Patients with more severe TBIs demonstrated increased use of antibiotics/antivirals and NSAIDs/antirheumatics than those with less severe TBIs. Discussion: Taken together, our results point to poor overall health in TBI patients, suggesting that medical follow-up should be routine, particularly in females with TBI, and include a review of medication use to address potential polypharmacy. [ABSTRACT FROM AUTHOR]

Internet of things (IOT) based in‐home monitoring systems can passively collect high temporal resolution data in the community, offering valuable insight into the impact of health conditions on patients' day‐to‐day lives. We used this technology to monitor activity and sleep patterns in older adults recently discharged after traumatic brain injury (TBI). The demographics of TBI are changing, and it is now a leading cause of hospitalisation in older adults. However, research in this population is minimal. We present three cases, showcasing the potential of in‐home monitoring systems in understanding and managing early recovery in older adults following TBI. [ABSTRACT FROM AUTHOR]

Diffusion weighted imaging (DWI) is key in clinical neuroimaging studies. In recent years, DWI has undergone rapid evolution and increasing applications. Diffusion magnetic resonance imaging (dMRI) is widely used to analyse group-level differences in white matter (WM), but suffers from limitations that can be particularly impactful in clinical groups where 1) structural abnormalities may increase erroneous inter-subject registration and 2) subtle differences in WM microstructure between individuals can be missed. It also lacks standardization protocols for analyses at the subject level. Region of Interest (ROI) analyses in native diffusion space can help overcome these challenges, with manual segmentation still used as the gold standard. However, robust automated approaches for the analysis of ROI-extracted native diffusion characteristics are limited. Subject-Specific Diffusion Segmentation (SSDS) is an automated pipeline that uses pre-existing imaging analysis methods to carry out WM investigations in native diffusion space, while overcoming the need to interpolate diffusion images and using an intermediate T1 image to limit registration errors and guide segmentation. SSDS is validated in a cohort of healthy subjects scanned three times to derive test-retest reliability measures and compared to other methods, namely manual segmentation and tract-based spatial statistics as an example of group-level method. The performance of the pipeline is further tested in a clinical population of patients with traumatic brain injury and structural abnormalities. Mean FA values obtained from SSDS showed high test-retest and were similar to FA values estimated from the manual segmentation of the same ROIs (p-value > 0.1). The average dice similarity coefficients (DSCs) comparing results from SSDS and manual segmentations was 0.8 ± 0.1. Case studies of TBI patients showed robustness to the presence of significant structural abnormalities, indicating its potential clinical application in the identification and diagnosis of WM abnormalities. Further recommendation is given regarding the tracts used with SSDS. [ABSTRACT FROM AUTHOR]

Associative binding is key to normal memory function and is transiently disrupted during periods of post-traumatic amnesia (PTA) following traumatic brain injury (TBI). Electrophysiological abnormalities, including low-frequency activity, are common following TBI. Here, we investigate associative memory binding during PTA and test the hypothesis that misbinding is caused by pathological slowing of brain activity disrupting cortical communication. Thirty acute moderate to severe TBI patients (25 males; 5 females) and 26 healthy controls (20 males; 6 females) were tested with a precision working memory paradigm requiring the association of object and location information. Electrophysiological effects of TBI were assessed using resting-state EEG in a subsample of 17 patients and 21 controls. PTA patients showed abnormalities in working memory function and made significantly more misbinding errors than patients who were not in PTA and controls. The distribution of localization responses was abnormally biased by the locations of non-target items for patients in PTA, suggesting a specific impairment of object and location binding. Slow-wave activity was increased following TBI. Increases in the δ-α ratio indicative of an increase in low-frequency power specifically correlated with binding impairment in working memory. Connectivity changes in TBI did not correlate with binding impairment. Working memory and electrophysiological abnormalities normalized at 6 month follow-up. These results show that patients in PTA show high rates of misbinding that are associated with a pathological shift toward lower-frequency oscillations. [ABSTRACT FROM AUTHOR]

Long-term outcomes are difficult to predict after paediatric traumatic brain injury. The presence or absence of focal brain injuries often do not explain cognitive, emotional and behavioural disabilities that are common and disabling. In adults, traumatic brain injury produces progressive brain atrophy that can be accurately measured and is associated with cognitive decline. However, the effect of paediatric traumatic brain injury on brain volumes is more challenging to measure because of its interaction with normal brain development. Here we report a robust approach to the individualized estimation of brain volume following paediatric traumatic brain injury and investigate its relationship to clinical outcomes. We first used a large healthy control dataset (n > 1200, age 8-22) to describe the healthy development of white and grey matter regions through adolescence. Individual estimates of grey and white matter regional volume were then generated for a group of moderate/severe traumatic brain injury patients injured in childhood (n = 39, mean age 13.53 ± 1.76, median time since injury = 14 months, range 4-168 months) by comparing brain volumes in patients to age-matched controls. Patients were individually classified as having low or normal brain volume. Neuropsychological and neuropsychiatric outcomes were assessed using standardized testing and parent/carer assessments. Relative to head size, grey matter regions decreased in volume during normal adolescence development whereas white matter tracts increased in volume. Traumatic brain injury disrupted healthy brain development, producing reductions in both grey and white matter brain volumes after correcting for age. Of the 39 patients investigated, 11 (28%) had at least one white matter tract with reduced volume and seven (18%) at least one area of grey matter with reduced volume. Those classified as having low brain volume had slower processing speed compared to healthy controls, emotional impairments, higher levels of apathy, increased anger and learning difficulties. In contrast, the presence of focal brain injury and microbleeds were not associated with an increased risk of these clinical impairments. In summary, we show how brain volume abnormalities after paediatric traumatic brain injury can be robustly calculated from individual T1 MRI using a large normative dataset that allows the effects of healthy brain development to be controlled for. Using this approach, we show that volumetric abnormalities are common after moderate/severe traumatic brain injury in both grey and white matter regions, and are associated with higher levels of cognitive, emotional and behavioural abnormalities that are common after paediatric traumatic brain injury. [ABSTRACT FROM AUTHOR]

Neurovascular injury is often observed in traumatic brain injury (TBI). However, the relationship between mechanical forces and vascular injury is still unclear. A key question is whether the complex anatomy of vasculature plays a role in increasing forces in cerebral vessels and producing damage. We developed a high-fidelity multiscale finite element model of the rat brain featuring a detailed definition of the angioarchitecture. Controlled cortical impacts were performed experimentally and in-silico. The model was able to predict the pattern of blood–brain barrier damage. We found strong correlation between the area of fibrinogen extravasation and the brain area where axial strain in vessels exceeds 0.14. Our results showed that adjacent vessels can sustain profoundly different axial stresses depending on their alignment with the principal direction of stress in parenchyma, with a better alignment leading to larger stresses in vessels. We also found a strong correlation between axial stress in vessels and the shearing component of the stress wave in parenchyma. Our multiscale computational approach explains the unrecognised role of the vascular anatomy and shear stresses in producing distinct distribution of large forces in vasculature. This new understanding can contribute to improving TBI diagnosis and prevention. [ABSTRACT FROM AUTHOR]

The Cerebrospinal Fluid (CSF) can undergo shear deformations under head motions. Finite Element (FE) models, which are commonly used to simulate biomechanics of the brain, including traumatic brain injury, employ solid elements to represent the CSF. However, the limited number of elements paired with shear deformations in CSF can decrease the accuracy of their predictions. Large deformation problems can be accurately modelled using the mesh‐free Smoothed Particle Hydrodynamics (SPH) method, but there is limited previous work on using this method for modelling the CSF. Here we explored the stability and accuracy of key modelling parameters of an SPH model of the CSF when predicting relative brain/skull displacements in a simulation of an in vivo mild head impact in human. The Moving Least Squares (MLS) SPH formulation and Ogden rubber material model were found to be the most accurate and stable. The strain and strain rate in the brain differed across the SPH and FE models of CSF. The FE mesh anchored the gyri, preventing them from experiencing the level of strains seen in the in vivo brain experiments and predicted by the SPH model. Additionally, SPH showed higher levels of strains in the sulci compared to the FE model. However, tensile instability was found to be a key challenge of the SPH method, which needs to be addressed in future. Our study provides a detailed investigation of the use of SPH and shows its potential for improving the accuracy of computational models of brain biomechanics. [ABSTRACT FROM AUTHOR]

The TRACK-TBI LONG study has shown that outcomes are highly variable in the 7 years after traumatic brain injury (TBI). Although many patients remain stable, almost one-third experience declines in cognitive, psychiatric and functional state. These findings suggest that TBI is a chronic disease and that its management should change accordingly. [ABSTRACT FROM AUTHOR]

Memory impairment is a common, disabling effect of traumatic brain injury. In healthy individuals, successful memory encoding is associated with activation of the dorsal attention network as well as suppression of the default mode network. Here, in traumatic brain injury patients we examined whether: (i) impairments in memory encoding are associated with abnormal brain activation in these networks; (ii) whether changes in this brain activity predict subsequent memory retrieval; and (iii) whether abnormal white matter integrity underpinning functional networks is associated with impaired subsequent memory. Thirty-five patients with moderate-severe traumatic brain injury aged 23-65 years (74% males) in the post-acute/chronic phase after injury and 16 healthy control subjects underwent functional MRI during performance of an abstract image memory encoding task. Diffusion tensor imaging was used to assess structural abnormalities across patient groups compared to 28 age-matched healthy controls. Successful memory encoding across all participants was associated with activation of the dorsal attention network, the ventral visual stream and medial temporal lobes. Decreased activation was seen in the default mode network. Patients with preserved episodic memory demonstrated increased activation in areas of the dorsal attention network. Patients with impaired memory showed increased left anterior prefrontal activity. White matter microstructure underpinning connectivity between core nodes of the encoding networks was significantly reduced in patients with memory impairment. Our results show for the first time that patients with impaired episodic memory show abnormal activation of key nodes within the dorsal attention network and regions regulating default mode network activity during encoding. Successful encoding was associated with an opposite direction of signal change between patients with and without memory impairment, suggesting that memory encoding mechanisms could be fundamentally altered in this population. We demonstrate a clear relationship between functional networks activated during encoding and underlying abnormalities within the structural connectome in patients with memory impairment. We suggest that encoding failures in this group are likely due to failed control of goal-directed attentional resources. [ABSTRACT FROM AUTHOR]

Vestibular dysfunction, causing dizziness and imbalance, is a common yet poorly understood feature in patients with TBI. Damage to the inner ear, nerve, brainstem, cerebellum and cerebral hemispheres may all affect vestibular functioning, hence, a multi-level assessment-from reflex to perception-is required. In a previous report, postural instability was the commonest neurological feature in ambulating acute patients with TBI. During ward assessment, we also frequently observe a loss of vertigo sensation in patients with acute TBI, common inner ear conditions and a related vigorous vestibular-ocular reflex nystagmus, suggesting a 'vestibular agnosia'. Patients with vestibular agnosia were also more unbalanced; however, the link between vestibular agnosia and imbalance was confounded by the presence of inner ear conditions. We investigated the brain mechanisms of imbalance in acute TBI, its link with vestibular agnosia, and potential clinical impact, by prospective laboratory assessment of vestibular function, from reflex to perception, in patients with preserved peripheral vestibular function. Assessment included: vestibular reflex function, vestibular perception by participants' report of their passive yaw rotations in the dark, objective balance via posturography, subjective symptoms via questionnaires, and structural neuroimaging. We prospectively screened 918 acute admissions, assessed 146 and recruited 37. Compared to 37 matched controls, patients showed elevated vestibular-perceptual thresholds (patients 12.92°/s versus 3.87°/s) but normal vestibular-ocular reflex thresholds (patients 2.52°/s versus 1.78°/s). Patients with elevated vestibular-perceptual thresholds [3 standard deviations (SD) above controls' average], were designated as having vestibular agnosia, and displayed worse posturography than non-vestibular-agnosia patients, despite no difference in vestibular symptom scores. Only in patients with impaired postural control (3 SD above controls' mean), whole brain diffusion tensor voxel-wise analysis showed elevated mean diffusivity (and trend lower fractional anisotropy) in the inferior longitudinal fasciculus in the right temporal lobe that correlated with vestibular agnosia severity. Thus, impaired balance and vestibular agnosia are co-localized to the inferior longitudinal fasciculus in the right temporal lobe. Finally, a clinical audit showed a sevenfold reduction in clinician recognition of a common peripheral vestibular condition (benign paroxysmal positional vertigo) in acute patients with clinically apparent vestibular agnosia. That vestibular agnosia patients show worse balance, but without increased dizziness symptoms, explains why clinicians may miss treatable vestibular diagnoses in these patients. In conclusion, vestibular agnosia mediates imbalance in traumatic brain injury both directly via white matter tract damage in the right temporal lobe, and indirectly via reduced clinical recognition of common, treatable vestibular diagnoses. [ABSTRACT FROM AUTHOR]

Poor outcomes after traumatic brain injury (TBI) are common yet remain difficult to predict. Diffuse axonal injury is important for outcomes, but its assessment remains limited in the clinical setting. Currently, axonal injury is diagnosed based on clinical presentation, visible damage to the white matter or via surrogate markers of axonal injury such as microbleeds. These do not accurately quantify axonal injury leading to misdiagnosis in a proportion of patients. Diffusion tensor imaging provides a quantitative measure of axonal injury in vivo, with fractional anisotropy often used as a proxy for white matter damage. Diffusion imaging has been widely used in TBI but is not routinely applied clinically. This is in part because robust analysis methods to diagnose axonal injury at the individual level have not yet been developed. Here, we present a pipeline for diffusion imaging analysis designed to accurately assess the presence of axonal injury in large white matter tracts in individuals. Average fractional anisotropy is calculated from tracts selected on the basis of high test-retest reliability, good anatomical coverage and their association to cognitive and clinical impairments after TBI. We test our pipeline for common methodological issues such as the impact of varying control sample sizes, focal lesions and age-related changes to demonstrate high specificity, sensitivity and test-retest reliability. We assess 92 patients with moderate-severe TBI in the chronic phase (≥6 months post-injury), 25 patients in the subacute phase (10 days to 6 weeks post-injury) with 6-month follow-up and a large control cohort (n = 103). Evidence of axonal injury is identified in 52% of chronic and 28% of subacute patients. Those classified with axonal injury had significantly poorer cognitive and functional outcomes than those without, a difference not seen for focal lesions or microbleeds. Almost a third of patients with unremarkable standard MRIs had evidence of axonal injury, whilst 40% of patients with visible microbleeds had no diffusion evidence of axonal injury. More diffusion abnormality was seen with greater time since injury, across individuals at various chronic injury times and within individuals between subacute and 6-month scans. We provide evidence that this pipeline can be used to diagnose axonal injury in individual patients at subacute and chronic time points, and that diffusion MRI provides a sensitive and complementary measure when compared to susceptibility weighted imaging, which measures diffuse vascular injury. Guidelines for the implementation of this pipeline in a clinical setting are discussed. [ABSTRACT FROM AUTHOR]

The relationship between biomechanical forces and neuropathology is key to understanding traumatic brain injury. White matter tracts are damaged by high shear forces during impact, resulting in axonal injury, a key determinant of long-term clinical outcomes. However, the relationship between biomechanical forces and patterns of white matter injuries, associated with persistent diffusion MRI abnormalities, is poorly understood. This limits the ability to predict the severity of head injuries and the design of appropriate protection. Our previously developed human finite element model of head injury predicted the location of post-traumatic neurodegeneration. A similar rat model now allows us to experimentally test whether strain patterns calculated by the model predicts in vivo MRI and histology changes. Using a controlled cortical impact, mild and moderate injuries (1 and 2 mm) were performed. Focal and axonal injuries were quantified with volumetric and diffusion 9.4 T MRI at 2 weeks post injury. Detailed analysis of the corpus callosum was conducted using multi-shell diffusion MRI and histopathology. Microglia and astrocyte density, including process parameters, along with white matter structural integrity and neurofilament expression were determined by quantitative immunohistochemistry. Linear mixed effects regression analyses for strain and strain rate with the employed outcome measures were used to ascertain how well immediate biomechanics could explain MRI and histology changes. The spatial pattern of mechanical strain and strain rate in the injured cortex shows good agreement with the probability maps of focal lesions derived from volumetric MRI. Diffusion metrics showed abnormalities in the corpus callosum, indicating white matter changes in the segments subjected to high strain, as predicted by the model. The same segments also exhibited a severity-dependent increase in glia cell density, white matter thinning and reduced neurofilament expression. Linear mixed effects regression analyses showed that mechanical strain and strain rate were significant predictors of in vivo MRI and histology changes. Specifically, strain and strain rate respectively explained 33% and 28% of the reduction in fractional anisotropy, 51% and 29% of the change in neurofilament expression and 51% and 30% of microglia density changes. The work provides evidence that strain and strain rate in the first milliseconds after injury are important factors in determining patterns of glial and axonal injury and serve as experimental validators of our computational model of traumatic brain injury. Our results provide support for the use of this model in understanding the relationship of biomechanics and neuropathology and can guide the development of head protection systems, such as airbags and helmets. [ABSTRACT FROM AUTHOR]

Traumatic brain injury is associated with elevated rates of neurodegenerative diseases such as Alzheimer's disease and chronic traumatic encephalopathy. In experimental models, diffuse axonal injury triggers post-traumatic neurodegeneration, with axonal damage leading to Wallerian degeneration and toxic proteinopathies of amyloid and hyperphosphorylated tau. However, in humans the link between diffuse axonal injury and subsequent neurodegeneration has yet to be established. Here we test the hypothesis that the severity and location of diffuse axonal injury predicts the degree of progressive post-traumatic neurodegeneration. We investigated longitudinal changes in 55 patients in the chronic phase after moderate-severe traumatic brain injury and 19 healthy control subjects. Fractional anisotropy was calculated from diffusion tensor imaging as a measure of diffuse axonal injury. Jacobian determinant atrophy rates were calculated from serial volumetric T1 scans as a measure of measure post-traumatic neurodegeneration. We explored a range of potential predictors of longitudinal post-traumatic neurodegeneration and compared the variance in brain atrophy that they explained. Patients showed widespread evidence of diffuse axonal injury, with reductions of fractional anisotropy at baseline and follow-up in large parts of the white matter. No significant changes in fractional anisotropy over time were observed. In contrast, abnormally high rates of brain atrophy were seen in both the grey and white matter. The location and extent of diffuse axonal injury predicted the degree of brain atrophy: fractional anisotropy predicted progressive atrophy in both whole-brain and voxelwise analyses. The strongest relationships were seen in central white matter tracts, including the body of the corpus callosum, which are most commonly affected by diffuse axonal injury. Diffuse axonal injury predicted substantially more variability in white matter atrophy than other putative clinical or imaging measures, including baseline brain volume, age, clinical measures of injury severity and microbleeds (>50% for fractional anisotropy versus <5% for other measures). Grey matter atrophy was not predicted by diffuse axonal injury at baseline. In summary, diffusion MRI measures of diffuse axonal injury are a strong predictor of post-traumatic neurodegeneration. This supports a causal link between axonal injury and the progressive neurodegeneration that is commonly seen after moderate/severe traumatic brain injury but has been of uncertain aetiology. The assessment of diffuse axonal injury with diffusion MRI is likely to improve prognostic accuracy and help identify those at greatest neurodegenerative risk for inclusion in clinical treatment trials. [ABSTRACT FROM AUTHOR]

Traumatic brain injury (TBI) leads to increased rates of dementia, including Alzheimer's disease. The mechanisms by which trauma can trigger neurodegeneration are increasingly understood. For example, diffuse axonal injury is implicated in disrupting microtubule function, providing the potential context for pathologies of tau and amyloid to develop. The neuropathology of post-traumatic dementias is increasingly well characterised, with recent work focusing on chronic traumatic encephalopathy (CTE). However, clinical diagnosis of post-traumatic dementia is problematic. It is often difficult to disentangle the direct effects of TBI from those produced by progressive neurodegeneration or other post-traumatic sequelae such as psychiatric impairment. CTE can only be confidently identified at postmortem and patients are often confused and anxious about the most likely cause of their post-traumatic problems. A new approach to the assessment of the long-term effects of TBI is needed. Accurate methods are available for the investigation of other neurodegenerative conditions. These should be systematically employed in TBI. MRI and positron emission tomography neuroimaging provide biomarkers of neurodegeneration which may be of particular use in the postinjury setting. Brain atrophy is a key measure of disease progression and can be used to accurately quantify neuronal loss. Fluid biomarkers such as neurofilament light can complement neuroimaging, representing sensitive potential methods to track neurodegenerative processes that develop after TBI. These biomarkers could characterise endophenotypes associated with distinct types of post-traumatic neurodegeneration. In addition, they might profitably be used in clinical trials of neuroprotective and disease-modifying treatments, improving trial design by providing precise and sensitive measures of neuronal loss. [ABSTRACT FROM AUTHOR]

Non-invasive brain stimulation has been widely investigated as a potential treatment for a range of neurological and psychiatric conditions, including brain injury. However, the behavioural effects of brain stimulation are variable, for reasons that are poorly understood. This is a particular challenge for traumatic brain injury, where patterns of damage and their clinical effects are heterogeneous. Here we test the hypothesis that the response to transcranial direct current stimulation following traumatic brain injury is dependent on white matter damage within the stimulated network. We used a novel simultaneous stimulation-MRI protocol applying anodal, cathodal and sham stimulation to 24 healthy control subjects and 35 patients with moderate/severe traumatic brain injury. Stimulation was applied to the right inferior frontal gyrus/anterior insula node of the salience network, which was targeted because our previous work had shown its importance to executive function. Stimulation was applied during performance of the Stop Signal Task, which assesses response inhibition, a key component of executive function. Structural MRI was used to assess the extent of brain injury, including diffusion MRI assessment of post-traumatic axonal injury. Functional MRI, which was simultaneously acquired to delivery of stimulation, assessed the effects of stimulation on cognitive network function. Anodal stimulation improved response inhibition in control participants, an effect that was not observed in the patient group. The extent of traumatic axonal injury within the salience network strongly influenced the behavioural response to stimulation. Increasing damage to the tract connecting the stimulated right inferior frontal gyrus/anterior insula to the rest of the salience network was associated with reduced beneficial effects of stimulation. In addition, anodal stimulation normalized default mode network activation in patients with poor response inhibition, suggesting that stimulation modulates communication between the networks involved in supporting cognitive control. These results demonstrate an important principle: that white matter structure of the connections within a stimulated brain network influences the behavioural response to stimulation. This suggests that a personalized approach to non-invasive brain stimulation is likely to be necessary, with structural integrity of the targeted brain networks an important criterion for patient selection and an individualized approach to the selection of stimulation parameters. [ABSTRACT FROM AUTHOR]

Imaging long-lasting deposition: Positron emission tomography (PET) using the radioligand for tau protein flortaucipir is a recently developed noninvasive method for measuring tau protein deposition. Although traumatic brain injury (TBI) has been associated with increased tau in postmortem samples, the long-term effects of a single TBI on tau deposition and its relationship with brain damage is unclear. Now, Gorgoraptis et al. reported increased flortaucipir signal (index of increased tau deposition) in long-term TBI survivors compared to healthy controls. Cerebrospinal fluid biomarkers of neurodegeneration and white matter damage correlated with flortaucipir signal, suggesting that flortaucipir PET imaging might be useful for diagnosis and prognostication of neuronal damage after TBI. Traumatic brain injury (TBI) can trigger progressive neurodegeneration, with tau pathology seen years after a single moderate-severe TBI. Identifying this type of posttraumatic pathology in vivo might help to understand the role of tau pathology in TBI pathophysiology. We used flortaucipir positron emission tomography (PET) to investigate whether tau pathology is present many years after a single TBI in humans. We examined PET data in relation to markers of neurodegeneration in the cerebrospinal fluid (CSF), structural magnetic resonance imaging measures, and cognitive performance. Cerebral flortaucipir binding was variable, with many participants with TBI showing increases in cortical and white matter regions. At the group level, flortaucipir binding was increased in the right occipital cortex in TBI when compared to healthy controls. Flortaucipir binding was associated with increased total tau, phosphorylated tau, and ubiquitin carboxyl-terminal hydrolase L1 CSF concentrations, as well as with reduced fractional anisotropy and white matter tissue density in TBI. Apolipoprotein E (APOE) ε4 genotype affected the relationship between flortaucipir binding and time since injury, CSF β amyloid 1–42 (Aβ42) concentration, white matter tissue density, and longitudinal Mini-Mental State Examination scores in TBI. The results demonstrate that tau PET is a promising approach to investigating progressive neurodegeneration associated with tauopathy after TBI. [ABSTRACT FROM AUTHOR]

Cognitive impairment is common following traumatic brain injury. Dopaminergic drugs can enhance cognition after traumatic brain injury, but individual responses are highly variable. This may be due to variability in dopaminergic damage between patients. We investigate whether measuring dopamine transporter levels using 123I-ioflupane single-photon emission computed tomography (SPECT) predicts response to methylphenidate, a stimulant with dopaminergic effects. Forty patients with moderate-severe traumatic brain injury and cognitive impairments completed a randomized, double-blind, placebo-controlled, crossover study. 123I-ioflupane SPECT, MRI and neuropsychological testing were performed. Patients received 0.3 mg/kg of methylphenidate or placebo twice a day in 2-week blocks. Subjects received neuropsychological assessment after each block and completed daily home cognitive testing during the trial. The primary outcome measure was change in choice reaction time produced by methylphenidate and its relationship to stratification of patients into groups with normal and low dopamine transporter binding in the caudate. Overall, traumatic brain injury patients showed slow information processing speed. Patients with low caudate dopamine transporter binding showed improvement in response times with methylphenidate compared to placebo [median change = -16 ms; 95% confidence interval (CI): -28 to -3 ms; P = 0.02]. This represents a 27% improvement in the slowing produced by traumatic brain injury. Patients with normal dopamine transporter binding did not improve. Daily home-based choice reaction time results supported this: the low dopamine transporter group improved (median change -19 ms; 95% CI: -23 to -7 ms; P = 0.002) with no change in the normal dopamine transporter group (P = 0.50). The low dopamine transporter group also improved on self-reported and caregiver apathy assessments (P = 0.03 and P = 0.02, respectively). Both groups reported improvements in fatigue (P = 0.03 and P = 0.007). The cognitive effects of methylphenidate after traumatic brain injury were only seen in patients with low caudate dopamine transporter levels. This shows that identifying patients with a hypodopaminergic state after traumatic brain injury can help stratify the choice of cognitive enhancing therapy. [ABSTRACT FROM AUTHOR]

Background The optimum method of defining cognitive impairment in virally suppressed people living with HIV is unknown. We evaluated the relationships between cognitive impairment, including using a novel multivariate method (NMM), patient– reported outcome measures (PROMs), and neuroimaging markers of brain structure across 3 cohorts. Methods Differences in the prevalence of cognitive impairment, PROMs, and neuroimaging data from the COBRA, CHARTER, and POPPY cohorts (total n = 908) were determined between HIV-positive participants with and without cognitive impairment defined using the HIV-associated neurocognitive disorders (HAND), global deficit score (GDS), and NMM criteria. Results The prevalence of cognitive impairment varied by up to 27% between methods used to define impairment (eg, 48% for HAND vs 21% for NMM in the CHARTER study). Associations between objective cognitive impairment and subjective cognitive complaints generally were weak. Physical and mental health summary scores (SF-36) were lowest for NMM-defined impairment (P <.05). There were no differences in brain volumes or cortical thickness between participants with and without cognitive impairment defined using the HAND and GDS measures. In contrast, those identified with cognitive impairment by the NMM had reduced mean cortical thickness in both hemispheres (P <.05), as well as smaller brain volumes (P <.01). The associations with measures of white matter microstructure and brain-predicted age generally were weaker. Conclusion Different methods of defining cognitive impairment identify different people with varying symptomatology and measures of brain injury. Overall, NMM-defined impairment was associated with most neuroimaging abnormalities and poorer self-reported health status. This may be due to the statistical advantage of using a multivariate approach. [ABSTRACT FROM AUTHOR]

BACKGROUND: Cognitive impairment is a common and disabling consequence of traumatic brain injury (TBI) but its impact on health-related quality of life is not well understood. OBJECTIVE: To investigate the relationship between cognitive impairment and health-related quality of life (HRQoL) after TBI. METHODS: Retrospective, cross-sectional study of a specialist TBI outpatient clinic patient sample. Outcome measures: Addenbrooke's Cognitive Examination Tool - Revised (ACE-R), and SF-36 quality of life, Beck Depression Inventory II (BDI-II), Pittsburgh Sleep Quality Index (PSQI) and Epworth Sleepiness Scale (ESS) questionnaires. RESULTS: 240 adults were assessed: n = 172 (71.7%) moderate-severe, 41 (23.8%) mild, 27 (11.3%) symptomatic TBI, 174 (72.5%) male, median age (range): 44 (22–91) years. TBI patients reported poorer scores on all domains of SF-36 compared to age-matched UK normative data. Cognitively impaired patients reported poorer HRQoL on the physical, social role and emotional role functioning, and mental health domains. Cognitive impairment predicted poorer HRQoL on the social and emotional role functioning domains, independently of depressive symptoms, sleep disturbance, daytime sleepiness and TBI severity. Mediation analysis revealed that the effect of depressive symptoms on the emotional role functioning domain of HRQoL was partially mediated by cognitive dysfunction. CONCLUSION: Cognitive impairment is associated with worse health-related quality of life after TBI and partially mediates the effect of depressive symptoms on emotional role functioning. [ABSTRACT FROM AUTHOR]

Traumatic brain injury leads to significant loss of brain volume, which continues into the chronic stage. This can be sensitively measured using volumetric analysis of MRI. Here we: (i) investigated longitudinal patterns of brain atrophy; (ii) tested whether atrophy is greatest in sulcal cortical regions; and (iii) showed how atrophy could be used to power intervention trials aimed at slowing neurodegeneration. In 61 patients with moderate-severe traumatic brain injury (mean age = 41.55 years ± 12.77) and 32 healthy controls (mean age = 34.22 years ± 10.29), cross-sectional and longitudinal (1-year follow-up) brain structure was assessed using voxel-based morphometry on T1-weighted scans. Longitudinal brain volume changes were characterized using a novel neuroimaging analysis pipeline that generates a Jacobian determinant metric, reflecting spatial warping between baseline and follow-up scans. Jacobian determinant values were summarized regionally and compared with clinical and neuropsychological measures. Patients with traumatic brain injury showed lower grey and white matter volume in multiple brain regions compared to controls at baseline. Atrophy over 1 year was pronounced following traumatic brain injury. Patients with traumatic brain injury lost a mean (± standard deviation) of 1.55% ± 2.19 of grey matter volume per year, 1.49% ± 2.20 of white matter volume or 1.51% ± 1.60 of whole brain volume. Healthy controls lost 0.55% ± 1.13 of grey matter volume and gained 0.26% ± 1.11 of white matter volume; equating to a 0.22% ± 0.83 reduction in whole brain volume. Atrophy was greatest in white matter, where the majority (84%) of regions were affected. This effect was independent of and substantially greater than that of ageing. Increased atrophy was also seen in cortical sulci compared to gyri. There was no relationship between atrophy and time since injury or age at baseline. Atrophy rates were related to memory performance at the end of the follow-up period, as well as to changes in memory performance, prior to multiple comparison correction. In conclusion, traumatic brain injury results in progressive loss of brain tissue volume, which continues for many years post-injury. Atrophy is most prominent in the white matter, but is also more pronounced in cortical sulci compared to gyri. These findings suggest the Jacobian determinant provides a method of quantifying brain atrophy following a traumatic brain injury and is informative in determining the long-term neurodegenerative effects after injury. Power calculations indicate that Jacobian determinant images are an efficient surrogate marker in clinical trials of neuroprotective therapeutics. [ABSTRACT FROM AUTHOR]

Traumatic brain injury can reduce striatal dopamine levels. The cause of this is uncertain, but is likely to be related to damage to the nigrostriatal system. We investigated the pattern of striatal dopamine abnormalities using 123I-Ioflupane single-photon emission computed tomography (SPECT) scans and their relationship to nigrostriatal damage and clinical features. We studied 42 moderate-severe traumatic brain injury patients with cognitive impairments but no motor parkinsonism signs and 20 healthy controls. 123I-Ioflupane scanning was used to assess dopamine transporter levels. Clinical scan reports were compared to quantitative dopamine transporter results. Advanced MRI methods were used to assess the nigrostriatal system, including the area through which the nigrostriatal projections pass as defined from high-resolution Human Connectome data. Detailed clinical and neuropsychological assessments were performed. Around 20% of our moderate-severe patients had clear evidence of reduced specific binding ratios for the dopamine transporter in the striatum measured using 123I-Ioflupane SPECT. The caudate was affected more consistently than other striatal regions. Dopamine transporter abnormalities were associated with reduced substantia nigra volume. In addition, diffusion MRI provided evidence of damage to the regions through which the nigrostriatal tract passes, particularly the area traversed by dopaminergic projections to the caudate. Only a small percentage of patients had evidence of macroscopic lesions in the striatum and there was no relationship between presence of lesions and dopamine transporter specific binding ratio abnormalities. There was also no relationship between reduced volume in the striatal subregions and reduced dopamine transporter specific binding ratios. Patients with low caudate dopamine transporter specific binding ratios show impaired processing speed and executive dysfunction compared to patients with normal levels. Taken together, our results suggest that the dopaminergic system is affected by a moderate-severe traumatic brain injury in a significant proportion of patients, even in the absence of clinical motor parkinsonism. Reduced dopamine transporter levels are most commonly seen in the caudate and this is likely to reflect the pattern of nigrostriatal tract damage produced by axonal injury and associated midbrain damage. [ABSTRACT FROM AUTHOR]

Survivors of a traumatic brain injury can deteriorate years later, developing brain atrophy and dementia. Traumatic brain injury triggers chronic microglial activation, but it is unclear whether this is harmful or beneficial. A successful chronic-phase treatment for traumatic brain injury might be to target microglia. In experimental models, the antibiotic minocycline inhibits microglial activation. We investigated the effect of minocycline on microglial activation and neurodegeneration using PET, MRI, and measurement of the axonal protein neurofilament light in plasma. Microglial activation was assessed using 11C-PBR28 PET. The relationships of microglial activation to measures of brain injury, and the effects of minocycline on disease progression, were assessed using structural and diffusion MRI, plasma neurofilament light, and cognitive assessment. Fifteen patients at least 6 months after a moderate-to-severe traumatic brain injury received either minocycline 100 mg orally twice daily or no drug, for 12 weeks. At baseline, 11C-PBR28 binding in patients was increased compared to controls in cerebral white matter and thalamus, and plasma neurofilament light levels were elevated. MRI measures of white matter damage were highest in areas of greater 11C-PBR28 binding. Minocycline reduced 11C-PBR28 binding (mean Δwhite matter binding = -23.30%, 95% confidence interval -40.9 to -5.64%, P = 0.018), but increased plasma neurofilament light levels. Faster rates of brain atrophy were found in patients with higher baseline neurofilament light levels. In this experimental medicine study, minocycline after traumatic brain injury reduced chronic microglial activation while increasing a marker of neurodegeneration. These findings suggest that microglial activation has a reparative effect in the chronic phase of traumatic brain injury. [ABSTRACT FROM AUTHOR]

Traumatic brain injury often produces executive dysfunction. This characteristic cognitive impairment often causes long-term problems with behaviour and personality. Frontal lobe injuries are associated with executive dysfunction, but it is unclear how these injuries relate to corticostriatal interactions that are known to play an important role in behavioural control. We hypothesized that executive dysfunction after traumatic brain injury would be associated with abnormal corticostriatal interactions, a question that has not previously been investigated. We used structural and functional MRI measures of connectivity to investigate this. Corticostriatal functional connectivity in healthy individuals was initially defined using a data-driven approach. A constrained independent component analysis approach was applied in 100 healthy adult dataset from the Human Connectome Project. Diffusion tractography was also performed to generate white matter tracts. The output of this analysis was used to compare corticostriatal functional connectivity and structural integrity between groups of 42 patients with traumatic brain injury and 21 age-matched controls. Subdivisions of the caudate and putamen had distinct patterns of functional connectivity. Traumatic brain injury patients showed disruption to functional connectivity between the caudate and a distributed set of cortical regions, including the anterior cingulate cortex. Cognitive impairments in the patients were mainly seen in processing speed and executive function, as well as increased levels of apathy and fatigue. Abnormalities of caudate functional connectivity correlated with these cognitive impairments, with reductions in right caudate connectivity associated with increased executive dysfunction, information processing speed and memory impairment. Structural connectivity, measured using diffusion tensor imaging between the caudate and anterior cingulate cortex was impaired and this also correlated with measures of executive dysfunction. We show for the first time that altered subcortical connectivity is associated with large-scale network disruption in traumatic brain injury and that this disruption is related to the cognitive impairments seen in these patients. [ABSTRACT FROM AUTHOR]