scholarly journals Effect of Zolpidem in the Aftermath of Traumatic Brain Injury: An MEG Study

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Praveen Sripad ◽  
Jessica Rosenberg ◽  
Frank Boers ◽  
Christian P. Filss ◽  
Norbert Galldiks ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Functional Connectivity ◽  
Brain Activity ◽  
Brain Regions ◽  
Phase Lag ◽  
Before And After ◽  
Source Level ◽  
Weighted Phase Lag Index

In the past two decades, many studies have shown the paradoxical efficacy of zolpidem, a hypnotic used to induce sleep, in transiently alleviating various disorders of consciousness such as traumatic brain injury (TBI), dystonia, and Parkinson’s disease. The mechanism of action of this effect of zolpidem is of great research interest. In this case study, we use magnetoencephalography (MEG) to investigate a fully conscious, ex-coma patient who suffered from neurological difficulties for a few years due to traumatic brain injury. For a few years after injury, the patient was under medication with zolpidem that drastically improved his symptoms. MEG recordings taken before and after zolpidem showed a reduction in power in the theta-alpha (4–12 Hz) and lower beta (15–20 Hz) frequency bands. An increase in power after zolpidem intake was found in the higher beta/lower gamma (20–43 Hz) frequency band. Source level functional connectivity measured using weighted-phase lag index showed changes after zolpidem intake. Stronger connectivity between left frontal and temporal brain regions was observed. We report that zolpidem induces a change in MEG resting power and functional connectivity in the patient. MEG is an informative and sensitive tool to detect changes in brain activity for TBI.

scholarly journals Seizures are a druggable mechanistic link between TBI and subsequent tauopathy

2020 ◽  
Author(s):  
Hadeel Alyenbaawi ◽  
Richard Kanyo ◽  
Laszlo F. Locskai ◽  
Razieh Kamali-Jamil ◽  
Michèle G. DuVal ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Cell Death ◽  
Brain Injury ◽  
Chronic Traumatic Encephalopathy ◽  
Brain Activity ◽  
Brain Regions ◽  
List Type ◽  
Larval Zebrafish ◽  
Post Traumatic

SummaryTraumatic brain injury (TBI) is a prominent risk factor for neurodegenerative diseases and dementias including chronic traumatic encephalopathy (CTE). TBI and CTE, like all tauopathies, are characterized by accumulation of Tau into aggregates that progressively spread to other brain regions in a prion-like manner. The mechanisms that promote spreading and cellular uptake of tau seeds after TBI are not fully understood, in part due to lack of tractable animal models. Here, we test the putative roles for excess neuronal activity and dynamin-dependent endocytosis in promoting the in vivo spread of tauopathy. We introduce ‘tauopathy reporter’ zebrafish expressing a genetically-encoded fluorescent Tau biosensor that reliably reports accumulation of human tau species when seeded via intra-ventricular brain injections. Subjecting zebrafish larvae to a novel TBI paradigm produced various TBI symptoms including cell death, hemorrhage, blood flow abnormalities, post–traumatic seizures, and Tau inclusions. Bath application of anticonvulsant drugs rescued TBI-induced tauopathy and cell death; these benefits were attributable to inhibition of post-traumatic seizures because co-application of convulsants reversed these beneficial effects. However, one convulsant drug, 4-Aminopyridine, unexpectedly abrogated TBI-induced tauopathy - this was due to its inhibitory action on endocytosis as confirmed via additional dynamin inhibitors. These data suggest a role for seizure activity and dynamin-dependent endocytosis in the prion-like seeding and spreading of tauopathy following TBI. Further work is warranted regarding anti-convulsants that dampen post-traumatic seizures as a route to moderating subsequent tauopathy. Moreover, the data highlight the utility of deploying in vivo Tau biosensor and TBI methods in larval zebrafish, especially regarding drug screening and intervention.Graphical AbstractHighlightsIntroduces first Traumatic Brain Injury (TBI) model in larval zebrafish, and its easyTBI induces clinically relevant cell death, haemorrhage & post-traumatic seizuresCa2+ imaging during TBI reveals spike in brain activity concomitant with seizuresTau-GFP Biosensor allows repeated in vivo measures of prion-like tau aggregationpost-TBI, anticonvulsants stop tauopathies akin to Chronic Traumatic Encephalopathy

scholarly journals Alterations in Dynamic Spontaneous Network Microstates in Mild Traumatic Brain Injury: A MEG Beamformed Dynamic Connectivity Analysis

2019 ◽  
Author(s):  
Marios Antonakakis ◽  
Stavros I. Dimitriadis ◽  
Michalis Zervakis ◽  
Andrew C. Papanicolaou ◽  
George Zouridakis
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Mild Traumatic Brain Injury ◽  
Brain Connectivity ◽  
Brain Regions ◽  
Phase Lag ◽  
Brain Rhythms ◽  
Complexity Index ◽  
Discrimination Rate ◽  
Significant Difference

AbstractDynamic functional connectivity (DFC) analysis has attracted interest in the last years for the characterization of brain electrophysiological activity at rest. In this work, we investigated changes in mild Traumatic Brain Injury (mTBI) patients using magnetoencephalographic (MEG) resting-state recordings and a DFC approach. The activity of several well-known brain rhythms was first beamformed using linearly constrained minimum norm variance of the MEG data to determine ninety anatomical brain regions of interest. A DFC graph was formulated using the imaginary part of phase lag value which were obtained from 30 mTBI patients and 50 normal controls. Filtering each quasi-static graph statistically and topologically, we estimated a normalized Laplacian transformation of every single quasistatic graph based on the degree of each node. Then, the related eigenvalues of the synchronization of each node were computed by incorporating the complete topology. Using the neural-gas algorithm, we modelled the evolution of the eigenvalues for each group, resulting in distinct FC microstates (FCμstates). Using the so-called chronnectomics (transition rate, occupancy time of FCμstate, and Dwell time) and complexity index over the evolution of the FCμstates, we evaluated the level of discrimination and derived statistical differences between the two groups. In both groups, we detected equal number of FCμstates with statistically significant transitions in the δ, α, β, and γlow frequency bands. The discrimination rate between the two groups was very high in the θ and γlow bands, followed by a statistically significant difference between the two groups in all the chronnectomics and the complexity index. Statistically significant differences in the degree of several anatomical subnetworks (BAN – brain anatomical networks: default mode network; frontoparietal; occipital; cingulo-opercular; and sensorimotor) were revealed in most FCμstates for the θ, α, β, and γlow brain rhythms, indicating a higher level of communication within and between the BAN in the mTBI group. In our previous studies, we focused on intra- and inter-frequency couplings of static FC. Our current study summarizes a complete set of frequency-dependent connectomic markers of mTBI-caused alterations in brain connectivity that potentially could also serve as markers to assess the return of an injured subject back to normality.

scholarly journals Depressive symptoms following traumatic brain injury are associated with resting-state functional connectivity

2021 ◽  
pp. 1-8
Author(s):  
Lizhu Luo ◽  
Christelle Langley ◽  
Laura Moreno-Lopez ◽  
Keith Kendrick ◽  
David K. Menon ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Depressive Symptoms ◽  
Brain Injury ◽  
Functional Connectivity ◽  
Resting State ◽  
Emotional Regulation ◽  
Positive Association ◽  
Structural Mri ◽  
Brain Regions ◽  
Resting State Functional Connectivity

Abstract Background To determine whether depressive symptoms in traumatic brain injury (TBI) patients were associated with altered resting-state functional connectivity (rs-fc) or voxel-based morphology in brain regions involved in emotional regulation and associated with depression. Methods In the present study, we examined 79 patients (57 males; age range = 17–70 years, M ± s.d. = 38 ± 16.13; BDI-II, M ± s.d. = 9.84 ± 8.67) with TBI. We used structural MRI and resting-state fMRI to examine whether there was a relationship between depression, as measured with the Beck Depression Inventory (BDI-II), and the voxel-based morphology or functional connectivity in regions previously identified as involved in emotional regulation in patients following TBI. Patients were at least 4 months post-TBI (M ± s.d. = 15.13 ± 11.67 months) and the severity of the injury included mild to severe cases [Glasgow Coma Scale (GCS), M ± s.d. = 6.87 ± 3.31]. Results Our results showed that BDI-II scores were unrelated to voxel-based morphology in the examined regions. We found a positive association between depression scores and rs-fc between limbic regions and cognitive control regions. Conversely, there was a negative association between depression scores and rs-fc between limbic and frontal regions involved in emotion regulation. Conclusion These findings lead to a better understanding of the exact mechanisms that contribute to depression following TBI and better inform treatment decisions.

scholarly journals On the time-course of functional connectivity: theory of a dynamic progression of concussion effects

2020 ◽  
Vol 2 (2) ◽  
Author(s):  
Rober Boshra ◽  
Kyle I Ruiter ◽  
Kiret Dhindsa ◽  
Ranil Sonnadara ◽  
James P Reilly ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Functional Connectivity ◽  
Human Brain ◽  
Mild Traumatic Brain Injury ◽  
Time Course ◽  
Linear Time ◽  
Acute Stage ◽  
Phase Lag ◽  
Time Dependent Effect

Abstract The current literature presents a discordant view of mild traumatic brain injury and its effects on the human brain. This dissonance has often been attributed to heterogeneities in study populations, aetiology, acuteness, experimental paradigms and/or testing modalities. To investigate the progression of mild traumatic brain injury in the human brain, the present study employed data from 93 subjects (48 healthy controls) representing both acute and chronic stages of mild traumatic brain injury. The effects of concussion across different stages of injury were measured using two metrics of functional connectivity in segments of electroencephalography time-locked to an active oddball task. Coherence and weighted phase-lag index were calculated separately for individual frequency bands (delta, theta, alpha and beta) to measure the functional connectivity between six electrode clusters distributed from frontal to parietal regions across both hemispheres. Results show an increase in functional connectivity in the acute stage after mild traumatic brain injury, contrasted with significantly reduced functional connectivity in chronic stages of injury. This finding indicates a non-linear time-dependent effect of injury. To understand this pattern of changing functional connectivity in relation to prior evidence, we propose a new model of the time-course of the effects of mild traumatic brain injury on the brain that brings together research from multiple neuroimaging modalities and unifies the various lines of evidence that at first appear to be in conflict.

scholarly journals Magnetoencephalography-based identification of functional connectivity network disruption following mild traumatic brain injury

2016 ◽  
Vol 116 (4) ◽  
pp. 1840-1847 ◽  
Author(s):  
Ahmad Alhourani ◽  
Thomas A. Wozny ◽  
Deepa Krishnaswamy ◽  
Sudhir Pathak ◽  
Shawn A. Walls ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Functional Connectivity ◽  
Mild Traumatic Brain Injury ◽  
Phase Locking ◽  
Brain Regions ◽  
Memory And Attention ◽  
Control Subjects ◽  
Cortical Regions ◽  
Phase Locking Value

Mild traumatic brain injury (mTBI) leads to long-term cognitive sequelae in a significant portion of patients. Disruption of normal neural communication across functional brain networks may explain the deficits in memory and attention observed after mTBI. In this study, we used magnetoencephalography (MEG) to examine functional connectivity during a resting state in a group of mTBI subjects ( n = 9) compared with age-matched control subjects ( n = 15). We adopted a data-driven, exploratory analysis in source space using phase locking value across different frequency bands. We observed a significant reduction in functional connectivity in band-specific networks in mTBI compared with control subjects. These networks spanned multiple cortical regions involved in the default mode network (DMN). The DMN is thought to subserve memory and attention during periods when an individual is not engaged in a specific task, and its disruption may lead to cognitive deficits after mTBI. We further applied graph theoretical analysis on the functional connectivity matrices. Our data suggest reduced local efficiency in different brain regions in mTBI patients. In conclusion, MEG can be a potential tool to investigate and detect network alterations in patients with mTBI. The value of MEG to reveal potential neurophysiological biomarkers for mTBI patients warrants further exploration.

scholarly journals Emotional Information in News Reporting on Audience Cognitive Processing in the Age of Posttruth: An Electroencephalogram and Functional Connectivity Approach

2021 ◽  
Vol 12 ◽  
Author(s):  
Ya Yang ◽  
Lichao Xiu ◽  
Guoming Yu
Keyword(s):  
Functional Connectivity ◽  
Cognitive Processing ◽  
Emotional Expression ◽  
Brain Activity ◽  
Cognitive Resources ◽  
Phase Lag ◽  
Emotional Information ◽  
News Reporting ◽  
Brain Functional Connectivity ◽  
Weighted Phase Lag Index

The purpose of the present study is to explore how the emotionalized expression of news content in the posttruth era affects the cognitive processing of the audiences. One news that was text-written with two different expression types (emotional expression vs. neutral expression) was adopted as an experiment material in the study, and changes in cortical activity during news reporting reading tasks were examined with electroencephalograms, sampled from nine sites and four channels and analyzed with weighted phase lag index (wPLI) based on brain functional connectivity (FC) method. The results show that emotional discourses caused a stronger cortical brain activity and more robust brain FC (beta oscillations); besides, reading emotionalized expression consumed more attention resources but fewer cognitive resources, which may impede further rational thinking of the audiences.

Artifact removal from neurophysiological signals: impact on intracranial and arterial pressure monitoring in traumatic brain injury

2020 ◽  
Vol 132 (6) ◽  
pp. 1952-1960 ◽  
Author(s):  
Seung-Bo Lee ◽  
Hakseung Kim ◽  
Young-Tak Kim ◽  
Frederick A. Zeiler ◽  
Peter Smielewski ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Neurological Status ◽  
Cerebrovascular Reactivity ◽  
Cerebral Hypoperfusion ◽  
Clinical Parameters ◽  
Artifact Removal ◽  
Clinical Events ◽  
Arterial Blood ◽  
Before And After

OBJECTIVEMonitoring intracranial and arterial blood pressure (ICP and ABP, respectively) provides crucial information regarding the neurological status of patients with traumatic brain injury (TBI). However, these signals are often heavily affected by artifacts, which may significantly reduce the reliability of the clinical determinations derived from the signals. The goal of this work was to eliminate signal artifacts from continuous ICP and ABP monitoring via deep learning techniques and to assess the changes in the prognostic capacities of clinical parameters after artifact elimination.METHODSThe first 24 hours of monitoring ICP and ABP in a total of 309 patients with TBI was retrospectively analyzed. An artifact elimination model for ICP and ABP was constructed via a stacked convolutional autoencoder (SCAE) and convolutional neural network (CNN) with 10-fold cross-validation tests. The prevalence and prognostic capacity of ICP- and ABP-related clinical events were compared before and after artifact elimination.RESULTSThe proposed SCAE-CNN model exhibited reliable accuracy in eliminating ABP and ICP artifacts (net prediction rates of 97% and 94%, respectively). The prevalence of ICP- and ABP-related clinical events (i.e., systemic hypotension, intracranial hypertension, cerebral hypoperfusion, and poor cerebrovascular reactivity) all decreased significantly after artifact removal.CONCLUSIONSThe SCAE-CNN model can be reliably used to eliminate artifacts, which significantly improves the reliability and efficacy of ICP- and ABP-derived clinical parameters for prognostic determinations after TBI.

Sign in / Sign up

Export Citation Format

Share Document