Mild Traumatic Brain Injury Disrupts Functional Dynamic Attractors of Healthy Mental States

AbstractThe human brain has the ability of changing its wiring configuration by increasing or decreasing functional connectivity strength between specific areas. Variable but recurring configuration patterns in dynamic functional connectivity have been observed during resting fMRI experiments, patterns which are defined as dynamic brain states. The question arises whether in a regular healthy brain these states evolve in a random fashion or in a specific sequential order. The current work reveals both the specific state sequence in healthy brains, as well as the set of disruptions in this sequence produced by traumatic brain injury. The healthy sequence consists of oscillatory dynamic connectivity patterns that orbit an attractor state in a high dimensional space. Using discovery (96 subjects) and replication (74 subjects) cohorts, this study demonstrated that mild traumatic brain injury results in immediate orbital disruptions that recover over time. Brain dynamics enter a status of disrupted orbits right after injury, with partial recovery at 4 weeks, and full recovery at 3 months post-injury. In summary, our results describe an aspect of neuronal dysfunction in mild traumatic brain injury that is fully based on brain state dynamics, and different from traditional brain connectivity strength measures.

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Severity of Ongoing Post-Concussive Symptoms as a Predictor of Cognitive Performance Following a Pediatric Mild Traumatic Brain Injury

Journal of the International Neuropsychological Society ◽

10.1017/s1355617720001228 ◽

2020 ◽

pp. 1-11

Author(s):

Veronik Sicard ◽

Danielle C. Hergert ◽

Sharvani Pabbathi Reddy ◽

Cidney R. Robertson-Benta ◽

Andrew B. Dodd ◽

...

Keyword(s):

Traumatic Brain Injury ◽

Brain Injury ◽

Cognitive Performance ◽

Mild Traumatic Brain Injury ◽

Parental Education ◽

Visual Learning ◽

Learning Task ◽

Risk Scores ◽

Group Differences ◽

Post Injury

Abstract Objective: This study aimed to examine the predictors of cognitive performance in patients with pediatric mild traumatic brain injury (pmTBI) and to determine whether group differences in cognitive performance on a computerized test battery could be observed between pmTBI patients and healthy controls (HC) in the sub-acute (SA) and the early chronic (EC) phases of injury. Method: 203 pmTBI patients recruited from emergency settings and 159 age- and sex-matched HC aged 8–18 rated their ongoing post-concussive symptoms (PCS) on the Post-Concussion Symptom Inventory and completed the Cogstate brief battery in the SA (1–11 days) phase of injury. A subset (156 pmTBI patients; 144 HC) completed testing in the EC (∼4 months) phase. Results: Within the SA phase, a group difference was only observed for the visual learning task (One-Card Learning), with pmTBI patients being less accurate relative to HC. Follow-up analyses indicated higher ongoing PCS and higher 5P clinical risk scores were significant predictors of lower One-Card Learning accuracy within SA phase, while premorbid variables (estimates of intellectual functioning, parental education, and presence of learning disabilities or attention-deficit/hyperactivity disorder) were not. Conclusions: The absence of group differences at EC phase is supportive of cognitive recovery by 4 months post-injury. While the severity of ongoing PCS and the 5P score were better overall predictors of cognitive performance on the Cogstate at SA relative to premorbid variables, the full regression model explained only 4.1% of the variance, highlighting the need for future work on predictors of cognitive outcomes.

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Language function in a child following mild traumatic brain injury: Evidence from pre- and post-injury language testing

Developmental Neurorehabilitation ◽

10.3109/17518423.2011.620576 ◽

2011 ◽

Vol 14 (6) ◽

pp. 348-354 ◽

Cited By ~ 3

Author(s):

Fiona M. Lewis ◽

Bruce E. Murdoch

Keyword(s):

Traumatic Brain Injury ◽

Brain Injury ◽

Mild Traumatic Brain Injury ◽

Language Testing ◽

Language Function ◽

Post Injury

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1171 SHORT-WAVELENGTH LIGHT THERAPY AS A WAY OF IMPROVING SLEEP, COGNITION, AND FUNCTIONAL CONNECTIVITY FOLLOWING A MILD TRAUMATIC BRAIN INJURY

SLEEP ◽

10.1093/sleepj/zsx050.1170 ◽

2017 ◽

Vol 40 (suppl_1) ◽

pp. A437-A437

Author(s):

JR Vanuk ◽

BR Shane ◽

S Bajaj ◽

M Millan ◽

M Grandner ◽

...

Keyword(s):

Traumatic Brain Injury ◽

Brain Injury ◽

Functional Connectivity ◽

Mild Traumatic Brain Injury ◽

Short Wavelength ◽

Light Therapy ◽

Short Wavelength Light ◽

Wavelength Light

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Exosomal MicroRNA Differential Expression in Plasma of Young Adults with Chronic Mild Traumatic Brain Injury and Healthy Control

Biomedicines ◽

10.3390/biomedicines10010036 ◽

2021 ◽

Vol 10 (1) ◽

pp. 36

Author(s):

Rany Vorn ◽

Maiko Suarez ◽

Jacob C. White ◽

Carina A. Martin ◽

Hyung-Suk Kim ◽

...

Keyword(s):

Traumatic Brain Injury ◽

Young Adults ◽

Brain Injury ◽

Mild Traumatic Brain Injury ◽

Pathophysiological Mechanism ◽

Post Injury ◽

Persistent Symptoms ◽

Healthy Control ◽

Underlying Mechanisms

Chronic mild traumatic brain injury (mTBI) has long-term consequences, such as neurological disability, but its pathophysiological mechanism is unknown. Exosomal microRNAs (exomiRNAs) may be important mediators of molecular and cellular changes involved in persistent symptoms after mTBI. We profiled exosomal microRNAs (exomiRNAs) in plasma from young adults with or without a chronic mTBI to decipher the underlying mechanisms of its long-lasting symptoms after mTBI. We identified 25 significantly dysregulated exomiRNAs in the chronic mTBI group (n = 29, with 4.48 mean years since the last injury) compared to controls (n = 11). These miRNAs are associated with pathways of neurological disease, organismal injury and abnormalities, and psychological disease. Dysregulation of these plasma exomiRNAs in chronic mTBI may indicate that neuronal inflammation can last long after the injury and result in enduring and persistent post-injury symptoms. These findings are useful for diagnosing and treating chronic mTBIs.

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Structural brain connectivity predicts acute pain after mild traumatic brain injury

10.1101/2021.11.12.468345 ◽

2021 ◽

Author(s):

Paulo Branco ◽

Noam Bosak ◽

Jannis Bielefeld ◽

Olivia Cong ◽

Yelena Granovsky ◽

...

Keyword(s):

Traumatic Brain Injury ◽

Brain Injury ◽

White Matter ◽

Mild Traumatic Brain Injury ◽

Acute Pain ◽

Pain Perception ◽

Strong Predictor ◽

Pain Modulation ◽

Acute Injury ◽

Post Injury

Mild traumatic brain injury, mTBI, is a leading cause of disability worldwide, with acute pain manifesting as one of its most debilitating symptoms. Understanding acute post-injury pain is important since it is a strong predictor of long-term outcomes. In this study, we imaged the brains of 172 patients with mTBI, following a motorized vehicle collision and used a machine learning approach to extract white matter structural and resting state fMRI functional connectivity measures to predict acute pain. Stronger white matter tracts within the sensorimotor, thalamic-cortical, and default-mode systems predicted 20% of the variance in pain severity within 72 hours of the injury. This result generalized in two independent groups: 39 mTBI patients and 13 mTBI patients without whiplash symptoms. White matter measures collected at 6-months after the collision still predicted mTBI pain at that timepoint (n = 36). These white-matter connections were associated with two nociceptive psychophysical outcomes tested at a remote body site – namely conditioned pain modulation and magnitude of suprathreshold pain–, and with pain sensitivity questionnaire scores. Our validated findings demonstrate a stable white-matter network, the properties of which determine a significant amount of pain experienced after acute injury, pinpointing a circuitry engaged in the transformation and amplification of nociceptive inputs to pain perception.

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Self-Reported Complaints as Prognostic Markers for Outcome After Mild Traumatic Brain Injury in Elderly: A Machine Learning Approach

Frontiers in Neurology ◽

10.3389/fneur.2021.751539 ◽

2021 ◽

Vol 12 ◽

Author(s):

Mayra Bittencourt ◽

Sebastián A. Balart-Sánchez ◽

Natasha M. Maurits ◽

Joukje van der Naalt

Keyword(s):

Machine Learning ◽

Traumatic Brain Injury ◽

Brain Injury ◽

Elderly Patients ◽

Neck Pain ◽

Functional Outcome ◽

Mild Traumatic Brain Injury ◽

Prognostic Markers ◽

The Elderly ◽

Post Injury

Self-reported complaints are common after mild traumatic brain injury (mTBI). Particularly in the elderly with mTBI, the pre-injury status might play a relevant role in the recovery process. In most mTBI studies, however, pre-injury complaints are neither analyzed nor are the elderly included. Here, we aimed to identify which individual pre- and post-injury complaints are potential prognostic markers for incomplete recovery (IR) in elderly patients who sustained an mTBI. Since patients report many complaints across several domains that are strongly related, we used an interpretable machine learning (ML) approach to robustly deal with correlated predictors and boost classification performance. Pre- and post-injury levels of 20 individual complaints, as self-reported in the acute phase, were analyzed. We used data from two independent studies separately: UPFRONT study was used for training and validation and ReCONNECT study for independent testing. Functional outcome was assessed with the Glasgow Outcome Scale Extended (GOSE). We dichotomized functional outcome into complete recovery (CR; GOSE = 8) and IR (GOSE ≤ 7). In total 148 elderly with mTBI (median age: 67 years, interquartile range [IQR]: 9 years; UPFRONT: N = 115; ReCONNECT: N = 33) were included in this study. IR was observed in 74 (50%) patients. The classification model (IR vs. CR) achieved a good performance (the area under the receiver operating characteristic curve [ROC-AUC] = 0.80; 95% CI: 0.74–0.86) based on a subset of only 8 out of 40 pre- and post-injury complaints. We identified increased neck pain (p = 0.001) from pre- to post-injury as the strongest predictor of IR, followed by increased irritability (p = 0.011) and increased forgetfulness (p = 0.035) from pre- to post-injury. Our findings indicate that a subset of pre- and post-injury physical, emotional, and cognitive complaints has predictive value for determining long-term functional outcomes in elderly patients with mTBI. Particularly, post-injury neck pain, irritability, and forgetfulness scores were associated with IR and should be assessed early. The application of an ML approach holds promise for application in self-reported questionnaires to predict outcomes after mTBI.

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Traumatic Brain Injury as a Disorder of Brain Connectivity

Journal of the International Neuropsychological Society ◽

10.1017/s1355617715000740 ◽

2016 ◽

Vol 22 (2) ◽

pp. 120-137 ◽

Cited By ~ 83

Author(s):

Jasmeet P. Hayes ◽

Erin D. Bigler ◽

Mieke Verfaellie

Keyword(s):

Traumatic Brain Injury ◽

Brain Injury ◽

White Matter ◽

Functional Connectivity ◽

Negative Impact ◽

Axonal Injury ◽

Resting State Functional Connectivity ◽

Post Injury ◽

Recent Advances

AbstractObjectives:Recent advances in neuroimaging methodologies sensitive to axonal injury have made it possible to assess in vivo the extent of traumatic brain injury (TBI) -related disruption in neural structures and their connections. The objective of this paper is to review studies examining connectivity in TBI with an emphasis on structural and functional MRI methods that have proven to be valuable in uncovering neural abnormalities associated with this condition.Methods:We review studies that have examined white matter integrity in TBI of varying etiology and levels of severity, and consider how findings at different times post-injury may inform underlying mechanisms of post-injury progression and recovery. Moreover, in light of recent advances in neuroimaging methods to study the functional connectivity among brain regions that form integrated networks, we review TBI studies that use resting-state functional connectivity MRI methodology to examine neural networks disrupted by putative axonal injury.Results:The findings suggest that TBI is associated with altered structural and functional connectivity, characterized by decreased integrity of white matter pathways and imbalance and inefficiency of functional networks. These structural and functional alterations are often associated with neurocognitive dysfunction and poor functional outcomes.Conclusions:TBI has a negative impact on distributed brain networks that lead to behavioral disturbance. (JINS, 2016,22, 120–137)

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Longitudinal Resting State Functional Connectivity Predicts Clinical Outcome in Mild Traumatic Brain Injury

Journal of Neurotrauma ◽

10.1089/neu.2018.5739 ◽

2019 ◽

Vol 36 (5) ◽

pp. 650-660 ◽

Cited By ~ 11

Author(s):

Radhika Madhavan ◽

Suresh E. Joel ◽

Rakesh Mullick ◽

Taylor Cogsil ◽

Sumit N. Niogi ◽

...

Keyword(s):

Traumatic Brain Injury ◽

Brain Injury ◽

Functional Connectivity ◽

Clinical Outcome ◽

Mild Traumatic Brain Injury ◽

Resting State ◽

Resting State Functional Connectivity

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Highly Sensitive Single Molecular Array Immunoassay Measurement of t-Tau, NF-L, GFAP, and UCH-L1 Biomarkers in Acute Concussion/Mild Traumatic Brain Injury (mTBI) Patient Serum and Saliva Samples

Neurology ◽

10.1212/01.wnl.0000581020.28808.bd ◽

2019 ◽

Vol 93 (14 Supplement 1) ◽

pp. S19.3-S20

Author(s):

Ahmed Chenna ◽

Christos Petropoulos ◽

John Winslow

Keyword(s):

Traumatic Brain Injury ◽

Brain Injury ◽

Mild Traumatic Brain Injury ◽

Limited Information ◽

Post Injury ◽

Time Points ◽

Highly Sensitive ◽

Biomarker Analysis ◽

T Tau ◽

Control Samples

ObjectiveTo determine if t-Tau, NF-L, GFAP and UCH-L1 protein biomarkers are elevated in early time points of acute concussion/mild traumatic brain injury patient serum and saliva, relative to control samples.Backgroundt-Tau, NF-L, GFAP and UCH-L1 levels have been reported to increase in cerebral spinal fluid (CSF) and blood following head trauma within 24 hours or longer, and are candidate diagnostic and prognostic biomarkers of concussion and mild to moderate TBI. However, limited information exists on the relationship between these biomarkers at short time points post-injury, and detectability in saliva of mTBI patients.Design/MethodsBiomarker analysis of serum from a total of 120 participants, derived from two independent sample groups consisting of 60 concussion/mTBI patients each, with blood collected within 1-4 hr and 8-16 hr post-injury, respectively, was compared with 30 healthy control sera. Saliva samples were collected after 8-16 hr post-injury from a n = 30 subset of the same patients. Quanterix Simoa 4-plex immunoassay was used for highly sensitive measurements of these biomarkers.ResultsMedian levels of NF-L, GFAP and UCH-L1 were significantly higher in independent sets of patient serum samples (n = 60 each), both at early (1–4 hr) and later (8–16 hr) time points post-mTBI/concussion, relative to control samples (n = 30) (p < 0.0001, = 0.0001, <0.0001, respectively). Low levels of t-Tau are detected, but are significantly elevated post-concussion relative to controls (p = 0.0001). Significant correlations were observed between levels of t-Tau and UCH-L1, NF-L and GFAP, and t-Tau and GFAP in both post-injury time-point groups, and between NF-L and UCH-L1 levels in the 8-16 hr group. The four biomarkers were detected in saliva from concussion/mTBI patients (n = 30).ConclusionsThis study supports the utility of ultra-sensitive multiplex immunoassays to detect increases in CNS proteins at high sensitivity in serum and saliva within 1-4 and 8-16 hr of concussion/mTBI.

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