Objectives: Converging lines of evidence indicate that the long-term effects of moderate to severe traumatic brain injury (TBI) can mimic or accelerate the neural changes associated with pathological aging and dementia, including cortical atrophy and white matter loss. To date, however, it remains unclear how brain function is altered in response to the combined effects of the initial injury and subsequent neuropathological changes. The aim of this study is to investigate whether a history of TBI is associated with changes in functional connectivity over a 2-year period in participants with mild cognitive impairment.

Methods: A total of 79 participants with mild cognitive impairment (MCI) were drawn from the Ontario Neurodegenerative Research Initiative, including 24 with a previous history of traumatic brain injury MCI[TBI+] and 55 without MCI[TBI-]. BOLD-Resting state fMRI scans were acquired longitudinally over a 2-year period and both global and local connectivity were measured in the frontal and temporal lobes . Bayesian multilevel modelling was used to evaluate group differences in functional connectivity both cross-sectionally and longitudinally.

Results: MCI participants with prior TBI displayed greater longitudinal declines in local connectivity throughout both temporal and frontal lobes as well as frontal increases relative to MCI participants without prior TBI (Probability = 90-99%). At a global level, however, the MCI[TBI+] group demonstrated greater longitudinal increases in the prefrontal cortex and greater longitudinal decreases in global connectivity of the temporal gyri, relative to the MCI[TBI-] group.

Conclusions: Our study found evidence of greater longitudinal local and global connectivity declines in MCI participants with prior TBI, alongside a unique pattern of long-range prefrontal cortex connectivity in the MCI[TBI+] group. Overall, these findings shed light into longitudinal progression of MCI-related brain function and demonstrate that prefrontal global connectivity may be a unique feature associated with MCI[TBI+], providing further evidence that this group may be distinct, diagnostic category of interest.

Dementia is one remote sequelae of traumatic brain injury (TBI) and given the increased risk associated, TBI is considered a modifiable risk factor of dementia. With the evolving clinical use of plasma biomarkers in both dementia and TBI, there is need to better understand how TBI may influence associations of these biomarkers with dementia risk. This study leveraged data collected from community dwelling participants in the Atherosclerosis Risk in Communities (ARIC) Study. Participants were enrolled in 1987-1989 and were seen for subsequent in-person follow-up visits in 1990-1992 (Visit 2), 1993-1995 (Visit 3), 1996-1998 (Visit 4), 2011-2013 (Visit 5), 2016-2017 (Visit 6), and 2018-2019 (Visit 7). Incident TBI was defined using self-report and ICD-9/10 codes. Dementia was defined from neuropsychological assessments, annual/semi-annual telephone contact, and medical record/death certificate surveillance. Plasma biomarkers (amyloid β [Aβ] 40/42 ratio, phosphorylated tau 181 [p-Tau181], neurofilament light [NfL], glial fibrillary acidic protein [GFAP]) were measured on Quanterix Simoa platform in a subset of samples collected at Visit 3, Visit 5, and Visits 6/7. Covariate-adjusted Cox proportional hazards models were used to determine whether occurrence, severity, and number of TBIs modified associations of biomarkers with incident dementia. We assessed for interaction on the additive scale (i.e. sum of individual risks) using Relative Excess Risk due to Interaction (RERI) and on the multiplicative scale by including the product of each biomarker with TBI in the statistical model (i.e. synergism between TBI and biomarker levels resulted in integrated risk which is larger than the product of individual risks). We included 1,047 individuals without prevalent dementia at Visit 5 in the analyses. Mean (SD) age was 76.6 (5.3) years, 65.9% were female, 28.9% were self-reported Black race, and 13.4% had incident TBI. Hazard ratios for associations of each plasma biomarker with incident dementia by incident TBI status were examined. We found evidence of a non-multiplicative, positive additive interaction by incident TBI status in associations of late-life (Visit 5) log₂NfL with incident dementia (RERI p=0.02), but no evidence of interactions in midlife for any biomarker. We found both multiplicative and additive interactions by TBI frequency in associations of midlife Aβ42/Aβ40 ratio and late-life log₂p-Tau181 and log₂NfL with incident dementia. We also observed evidence for multiplicative and additive interactions by TBI severity in associations of midlife Aβ42/Aβ40 ratio and the change per decade between midlife and late-life in log₂GFAP with dementia risk. This study provides evidence that TBI events modify the associations of midlife and late-life plasma biomarkers with dementia risk. Importantly, we observed evidence for interaction by TBI status for associations of AD-related biomarkers as well as for biomarkers of neuronal injury and astrogliosis, suggesting that the pathologic processes underlying TBI-related dementia are heterogeneous and that these associations may be bi-directional.

Introduction: Disorders of consciousness (DoC) refer to a range of conditions where awareness is impaired due to brain injury, including unresponsive wakefulness syndrome (UWS), where patients are awake but lack signs of awareness, and the minimally conscious state (MCS), where awareness is inconsistent but detectable. The neurobehavioral condition of these patients is commonly assessed using clinical scales that primarily depend on motor responses to stimuli, which can lead to a high rate of misdiagnosis. To enhance diagnostic accuracy, neuroimaging techniques have been proposed, analyzing patients' brain responses to various stimuli and tasks, such as motor imagery, where patients imagine performing a movement. While neuroimaging techniques tend to be expensive and less accessible, electroencephalography (EEG) offers a more affordable, portable, and widely available option for examining brain activity in DoC patients, prompting its increased use in research. Functional near-infrared spectroscopy (fNIRS) shares the cost and portability advantages of EEG and can provide complementary information, though it has been less explored in DoC research. The aim of this study was to investigate using machine learning techniques the brain responses of patients with DoC, including EEG and fNIRS, to a motor imagery task.

Methods: A total of 27 healthy controls and 8 DoC patients (5 UWS and 3 MCS) participated in an ongoing study. Each participant engaged in a 12-minute task consisting of alternating 20-second blocks of motor imagery, during which they were instructed to imagine opening and closing both hands, followed by 20-second rest blocks. Neural activity was simultaneously recorded using a 32-channel LiveAmp EEG headset (BrainProducts, Gilching, Germany) and a 20-channel NirSport2 fNIRS system (NIRx, Berlin, Germany). Separate machine learning classifiers were trained for each data modality to assess the reliability of distinguishing between the imagined motor task and rest periods.

Results: The accuracy of the classification for both techniques was consistent with the level of consciousness. The EEG classifier achieved significant accuracies (>63%) for all healthy controls (85.04±9.93), and all healthy subjects but one showed significant results in the fNIRS classification (82.21±10.53). The average accuracy of the EEG classifiers for MCS patients (71.56±16.93) was higher than for UWS patients (56.67±12.96), and a similar pattern was observed with the fNIRS classifier, as MCS patients (60.18±12.96) outperformed UWS patients (50.50±12.96).

Conclusions: The EEG and fNIRS responses of healthy subjects and DoC patients during a motor imagery task were consistent with the level of consciousness. This results provide preliminary evidence of the potential of these techniques to improve diagnosis in DoC.

ACKNOWLEDGEMENTS: This work was supported by Conselleria d’Innovació, Universitats, Ciència i Societat Digital of Generalitat Valenciana (CIDEXG/2022/15), Ministerio de Ciencia e Innovación (PID2022-141498OA-I00), and Fundació la Marató de la TV3 (60/2023).

Detecting language function is a fundamentally important milestone in patients with severe brain injuries, as it represents the reintegration of cognitive processing and predicts ongoing recovery of functional independence. Yet, language processing can be difficult to accurately measure and can go unrecognized in many patients, particularly during the acute stage of recovery from severe brain injury in the intensive care unit (ICU). Moreover, there is a growing body of literature demonstrating that covert language function – detected using fMRI or EEG – may be diagnostically and prognostically useful in this patient population. To this end, we performed a series of multimodal, longitudinal investigations in 33 patients with acute severe TBI that integrated results from language resting-state functional MRI, stimulus-based fMRI that was examined hierarchically, diffusion tractography of language pathways, and behavioral assessments to 1) identify biomarkers of recovery; 2) parcellate lower- and higher-level language processing; and 3) assess longitudinal changes in language function that track with recovery. Regression modelling indicated that language network rs-fMRI and DTI outperformed stimulus-based fMRI for predicting recovery. These markers predicted functional recovery at 6 months with 87.5% accuracy and outperformed behavioural assessments, as well as clinical and demographic predictors in the ICU (p<0.001). Through a hierarchical ROI analysis, we parcellated lower-level language processing from high-level function in stimulus-based fMRI responses and found that all but one patient with covert awareness had neural activity in language ROIs implicated in higher-level language processing, suggesting that language stimuli-based paradigms may be sensitive for identifying higher-order language comprehension. At 6 months post injury, rs-fMRI and stimulus fMRI were indistinguishable from healthy controls, suggesting that functional neural markers of language processing were largely restored. Collectively, these results indicate that language biomarkers have prognostic potential in the ICU, index recovery of consciousness more so than other networks, and may provide more accurate tools for identifying covert cognitive processing and functional recovery after severe TBI.

Background: Headache is one of the most common and long-lasting post-concussion sequelae, with debilitating effects on patient quality of life. However, since it often presents concurrently with an array of other cognitive, somatic and emotional symptoms, it remains unclear whether headache is associated with distinct alterations in brain physiology, limiting our ability to improve on current interventions and management guidelines. To address this gap, the present study examined whether a predominantly-headache symptom presentation was associated with distinct patterns of functional connectivity in the brain.

Methods: A total of 102 concussed athletes were assessed in the first week of injury, along with 145 uninjured athletic controls, all recruited from a single university sport medicine clinic. All athletes were imaged on a 3T MRI system, and resting-state functional MRI was used to measure functional connectivity between brain regions using a standardized 246-region atlas. Symptoms were assessed concurrently with imaging via the Sport Concussion Assessment Tool (SCAT), and symptoms were ranked in severity per participant. Initial analyses examined the relative prevalence of headache-related symptoms (“headache”, “pressure in head”), followed by correlating relative symptom severity against pairwise functional connectivity.

Results: among the symptoms, both “headache” and “pressure in head” were consistently most highly ranked (p < 0.001, Friedman test). Subsequent analyses determined that increased relative severity of “headache” and “pressure in head” was associated with reduced connectivity of the insula and basal ganglia, respectively. Symptom frequencies and connectivity effects exceeded those seen in uninjured controls.

Conclusion: These findings provide new evidence that predominantly-headache symptom subtypes may have distinct functional abnormalities, with implications for patient management and the development of novel interventions.

Background: Concussions have considerable personal and economic consequences. Each year, approximately 40 million people globally, including approximately 450,000 Canadians, will experience a concussion, with up to 30% of them developing persistent post-concussion symptoms (PPCS). Many suffer debilitating symptoms like headaches, dizziness, and cognitive issues, with the most common symptom being post-traumatic headache (PTH). Up to 58% of patients with PPCS will have chronic PTH (cPTH) one year following their injury, experiencing reduced work productivity and quality of life. There is a limited understanding of the underlying pathophysiology of cPTH, and consequently, current treatments often lack efficacy.

Following concussion, a cascade of pathophysiological processes occurs, including alterations to the blood-brain barrier, increased central metabolites and increased inflammatory response. An inflammatory response is essential for appropriate healing, but if maladaptive can lead to protracted recovery, such as in cPTH. Recent studies have suggested a link between PPCS and fluid biomarkers indicative of inflammation and injury in the central nervous system, but the research remains inconclusive. Specifically, cytokines have been shown to be altered following various conditions, including acute concussion, tension headaches and migraine, although their relationship to cPTH remains unexplored. This research aims to address this critical gap in literature by exploring the relationship between cPTH and various cytokines in individuals with PPCS.

Methods: A total of 47 adults (18-65 years old) with PPCS (> 3 months to 5 years) provided blood samples. Patients scoring > 3 on the headache question on the Rivermead Post Concussion Symptoms Questionnaire were considered to have cPTH. Plasma cytokine levels were measured using a Bio-Plex 200 fluorescence magnetic-bead immunoassay. Linear regression examined the relationships between cPTH and cytokine levels while controlling for sex and age.

Results: When comparing patients with cPTH (> 3 on RPQ) to those without, several cytokine levels showed a significant positive correlation. Including Hu MCP-1 (MCAF) (β = 0.293, 95% Confidence Interval [CI; 0.043, 2.968], p = 0.043), FGF-basic (β = 0.332, CI [1.073, 14.283], p = 0.024), Hu IFN-g (β = 0.291, CI [0.0320, 5.080], p = 0.047), Hu IL-4 (β = 0.309, CI [0.009, 0.306], p = 0.038), Hu IL-7 (β = 0.328, CI [0.237, 3.851], p = 0.028), Hu IL-8 (β = 0.385, CI [0.165, 1.085], p = 0.009), Hu IL-9 (β = 0.321, CI [1.573, 26.288], p = 0.028), Hu IL-12 (p20) (β = 0.332, CI [0.039, 0.543], p = 0.024), Hu IL-16 (β = 0.317, CI [0.168, 1.716], p = 0.018, MIP-1β (β = 0.406, CI [1.065, 5.723], p = 0.005), PDGF-bb (β = 0.428, CI [24.503, 104.637], p = 0.002) and TNF-β (β = 0.318, CI [1.273, 23.564], p = 0.030). Notably, Hu IL-16 was negatively correlated with age (β = -0.332, CI [-0.140, -0.016], p = 0.014). Additionally, Hu TRAIL showed a significant positive correlation with males (β = 0.354, CI [0.917, 7.604], p = 0.031).


Significance: This study found a positive association between several inflammatory cytokines and cPTH in patients with PPCS. These findings suggest potential chronic inflammatory changes with cPTH and could lead to targeted interventions to improve patient outcomes.

Persistent symptoms after concussion (PSaC) affect approximately 25% of youths following mild traumatic brain injury (mTBI). Assessing demographic and medical factors may aid PSaC risk prediction. However, PSaC prognosis remains difficult, and this hampers early, personalized treatment. This study tested the hypothesis that assessing individual genomics could aid PSaC prediction in youths with mTBI. A prospective cohort study of 200 youths (ages 5-22 years) with mTBI was enrolled at initial presentation to emergency departments and outpatient clinics in the U.S. between January 2021 and February 2024 (35 ± 31 hrs post-mTBI). PSaC was defined as ≥ 2 symptoms above retrospective baseline on the Post-Concussion Symptom Inventory (PCSI) 30 days after mTBI. Saliva was collected at enrollment and four omics categories were assessed: microRNA levels (mir-148b-5p, miR-145-5p, miR-30e-5p, miR-320b, miR-532-5p, let-7e-5p), DNA polymorphisms (BDNF, ANKK1, APOE4, COMT, NGB), telomere length (Kilobases), and brain-related protein levels (NSE, S100-beta). Omic measures were compared between youths with and without PSaC using Wilcoxon Rank tests or likelihood ratio tests. Prognostic utility of an omics panel was compared against the current gold standard (5P tool) using hierarchical multivariate regression. Participants had a mean age of 14.7 (±3.3) years and were 59% male (117/200). Most (127/200; 63.5%) experienced sport-related concussion. Approximately one-quarter (59/200, 29%) had PSaC. Four salivary miRNAs differed in those with PSaC. Levels of Let-7e-5p (Effect = 0.29, p = 0.001), miR-30e-5p (Effect = 0.024, p = 0.008), miR-320b (Effect = 0.26, p = 0.004) and miR-532-5p (Effect = 0.18, p = 0.047) were higher in the PSaC group. There was no difference in the rates of DNA polymorphisms (BDNF, LR = 2.17, p = 0.33; ANKK1, LR = 0.35, p = 0.83; APOE4, LR = 0.73, p = 0.69; COMT, LR = 1.75, p = 0.41; NGB, LR = 0.91, p = 0.63), telomere length (Effect = 0.012, p = 0.89), or levels of brain-related proteins (NSE, Effect = 0.30, p = 0.25; S100-beta, Effect = 0.13, p = 0.62) among youths who developed PSaC. Participants’ 5P scores predicted PSaC with an area under the curve (AUC) of 0.613 (69% sensitive, 45% specific). A predictive model employing 3 miRNAs, while controlling for age and sex yielded an AUC of 0.725 (78% sensitive, 54% specific). Addition of 3 miRNAs to the 5P model yielded an AUC of 0.737 (73% sensitive, 60% specific), significantly boosting 5P performance (X2 = 15.7, p < 0.001). These results show that omics measures may add unique prognostic capacity for clinicians assessing PSaC risk, beyond standard medical and demographic factors. Specifically, measurement of microRNA levels may hold greater potential than assessment of polymorphisms, telomere length, or salivary proteins. Ongoing research seeks to validate these findings in a naïve test cohort.