Mining cross-frequency coupling microstates from resting state MEG: An application to mild traumatic brain injury

2016 ◽  
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 ◽  
Resting State ◽  
Frequency Coupling ◽  
Cross Frequency Coupling

scholarly journals Altered cross-frequency coupling in resting-state MEG after mild traumatic brain injury

2016 ◽  
Vol 102 ◽  
pp. 1-11 ◽  
Author(s):  
Marios Antonakakis ◽  
Stavros I. Dimitriadis ◽  
Michalis Zervakis ◽  
Sifis Micheloyannis ◽  
Roozbeh Rezaie ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Mild Traumatic Brain Injury ◽  
Resting State ◽  
Frequency Coupling ◽  
Cross Frequency Coupling

scholarly journals Reconfiguration of Dominant Coupling Modes in Mild Traumatic Brain Injury Mediated by δ-band Activity: a Resting State MEG Study

2017 ◽  
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 ◽  
Resting State ◽  
Large Scale ◽  
Compensatory Mechanism ◽  
Type I ◽  
Type Ii ◽  
Rich Club ◽  
Frequency Coupling

AbstractDuring the last few years, rich-club (RC) organization has been studied as a possible brain-connectivity organization model for large-scale brain networks. At the same time, empirical and simulated data of neurophysiological models have demonstrated the significant role of intra-frequency and inter-frequency coupling among distinct brain areas. The current study investigates further the importance of these couplings using recordings of resting-state magnetoencephalographic activity obtained from 30 mild traumatic brain injury (mTBI) subjects and 50 healthy controls. Intra-frequency and inter-frequency coupling modes are incorporated in a single graph to detect group differences within individual rich-club subnetworks (type I networks) and networks connecting RC nodes with the rest of the nodes (type II networks). Our results show a higher probability of inter-frequency coupling for (δ−γ1), (δ−γ2), (θ−β), (θ−γ2), (α−γ2), (γ1−γ2) and intra-frequency coupling for (γ1−γ1) and (δ−δ) for both type I and type II networks in the mTBI group. Additionally, mTBI and control subjects can be correctly classified with high accuracy (98.6%), whereas a general linear regression model can effectively predict the subject group using the ratio of type I and type II coupling in the (δ, θ), (δ, β), (δ, γ1), and (δ, γ2) frequency pairs. These findings support the presence of an RC organization simultaneously with dominant frequency interactions within a single functional graph. Our results demonstrate a hyperactivation of intrinsic RC networks in mTBI subjects compared to controls, which can be seen as a plausible compensatory mechanism for alternative frequency-dependent routes of information flow in mTBI subjects.

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

2019 ◽  
Vol 36 (5) ◽  
pp. 650-660 ◽  
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

Resting-state functional connectivity as a biomarker of aggression in mild traumatic brain injury

Neuroreport ◽  
2018 ◽  
Vol 29 (16) ◽  
pp. 1413-1417 ◽  
Author(s):  
Natalie S. Dailey ◽  
Ryan Smith ◽  
John R. Vanuk ◽  
Adam C. Raikes ◽  
William D.S. Killgore
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Functional Connectivity ◽  
Mild Traumatic Brain Injury ◽  
Resting State ◽  
Resting State Functional Connectivity

scholarly journals Resting State Functional Connectivity is Directly Related to Clinical Presentation of Mild Traumatic Brain Injury

Neurology ◽  
2019 ◽  
Vol 93 (14 Supplement 1) ◽  
pp. S26.2-S27
Author(s):  
Teena Shetty ◽  
Joseph Nguyen ◽  
Esther Kim ◽  
George Skulikidis ◽  
Matthew Garvey ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
White Matter ◽  
Functional Connectivity ◽  
Mild Traumatic Brain Injury ◽  
Resting State ◽  
Symptom Severity ◽  
Grey Matter ◽  
Clinical Presentation ◽  
Severity Scores

ObjectiveTo determine the utility of fractional amplitude of low frequency fluctuations (fALFF) during resting state fMRI (rs-fMRI) as an advanced neuroimaging biomarker for Mild Traumatic Brain Injury (mTBI).BackgroundmTBI is defined by a constellation of functional rather than structural deficits. As a measure of functional connectivity, fALFF has been implicated in long-term outcomes post-mTBI. It is unclear however, how longitudinal changes in fALFF may relate to the clinical presentation of mTBI.Design/Methods111 patients and 32 controls (15–50 years old) were enrolled acutely after mTBI and followed with up to 4 standardized serial assessments. Patients were enrolled at either Encounter 1 (E1), within 72 hours, or Encounter 2 (E2), 5–10 days post-injury, and returned for Encounter 3 (E3) at 15–29 days and Encounter 4 (E4) at 83–97 days. Each encounter included a clinical exam, neuropsychological assessment, as well as rs-fMRI imaging. fALFF was analyzed independently in 14 functional networks and, in grey and white matter as a function of symptom severity. Symptom severity scores (SSS) ranged from 0–132 as defined by the SCAT2 symptom evaluation.ResultsIn mTBI patients, fALFF scores across 5 functional brain networks (language, sensorimotor, visuospatial, higher-order visual, and posterior salience) differed between mTBI patients with low versus high SSS (SSS <5 and >30, respectively). Overall, greater SSS were indexed by reduced connectivity (p < 0.03, Bonferroni corrected). Further analysis also identified corresponding network pairs which were most predictive of increased SSS. White matter fALFF was not correlated with symptom severity, however, decreased grey matter fALFF was significantly correlated with greater SSS (r = −0.25, p = 0.002).ConclusionsGrey matter fALFF was correlated with mTBI symptom burden suggesting that patterns of neural connectivity relate directly to the clinical presentation of mTBI. Furthermore, differences in functional network connectivity as a function of SSS may reflect which networks are implicated in recovery of mTBI.

Exploring Variations in Functional Connectivity of the Resting State Default Mode Network in Mild Traumatic Brain Injury

2015 ◽  
Vol 5 (2) ◽  
pp. 102-114 ◽  
Author(s):  
Dominic E. Nathan ◽  
Terrence R. Oakes ◽  
Ping Hong Yeh ◽  
Louis M. French ◽  
Jamie F. Harper ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Functional Connectivity ◽  
Mild Traumatic Brain Injury ◽  
Default Mode Network ◽  
Resting State ◽  
Default Mode

scholarly journals Altered Rich-Club and Frequency-Dependent Subnetwork Organization in Mild Traumatic Brain Injury: A MEG Resting-State Study

2017 ◽  
Vol 11 ◽  
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 ◽  
Resting State ◽  
Frequency Dependent ◽  
Rich Club ◽  
State Study

scholarly journals Severities in persistent mild traumatic brain injury related headache is associated with changes in supraspinal pain modulatory functions

2021 ◽  
Vol 17 ◽  
pp. 174480692110378
Author(s):  
Matthew Flowers ◽  
Albert Leung ◽  
Dawn M Schiehser ◽  
Valerie Metzger-Smith ◽  
Lisa Delano-Wood ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Mild Traumatic Brain Injury ◽  
Parietal Cortex ◽  
Resting State ◽  
Premotor Cortex ◽  
Sensory Response ◽  
Control Group ◽  
The Right ◽  
Mild Headache

Emerging evidence suggests mild traumatic brain injury related headache (MTBI-HA) is a form of neuropathic pain state. Previous supraspinal mechanistic studies indicate patients with MTBI-HA demonstrate a dissociative state with diminished levels of supraspinal prefrontal pain modulatory functions and enhanced supraspinal sensory response to pain in comparison to healthy controls. However, the relationship between supraspinal pain modulatory functional deficit and severity of MTBI-HA is largely unknown. Understanding this relationship may provide enhanced levels of insight about MTBI-HA and facilitate the development of treatments. This study assessed pain related supraspinal resting states among MTBI-HA patients with various headache intensity phenotypes with comparisons to controls via functional magnetic resonance imaging (fMRI). Resting state fMRI data was analyzed with self-organizing-group-independent-component-analysis in three MTBI-HA intensity groups (mild, moderate, and severe) and one control group (n = 16 per group) within a pre-defined supraspinal pain network based on prior studies. In the mild-headache group, significant increases in supraspinal function were observed in the right premotor cortex (T = 3.53, p < 0.001) and the left premotor cortex (T = 3.99, p < 0.0001) when compared to the control group. In the moderate-headache group, a significant (T = −3.05, p < 0.01) decrease in resting state activity was observed in the left superior parietal cortex when compared to the mild-headache group. In the severe-headache group, significant decreases in resting state supraspinal activities in the right insula (T = −3.46, p < 0.001), right premotor cortex (T = −3.30, p < 0.01), left premotor cortex (T = −3.84, p < 0.001), and left parietal cortex (T = −3.94, p < 0.0001), and an increase in activity in the right secondary somatosensory cortex (T = 4.05, p < 0.0001) were observed when compared to the moderate-headache group. The results of the study suggest that the increase in MTBI-HA severity may be associated with an imbalance in the supraspinal pain network with decline in supraspinal pain modulatory function and enhancement of sensory/pain decoding.

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