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Article: Differential Intrinsic Coupling Modes in Psychological and Physical Trauma.

Dunkley, Benjamin T

2015 Volume 6, Page(s) 140

Language	English
Publishing date	2015-10-06
Publishing country	Switzerland
Document type	Journal Article ; Review
ZDB-ID	2564218-2
ISSN	1664-0640
ISSN	1664-0640
DOI	10.3389/fpsyt.2015.00140
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Cortical gyrification morphology in PTSD: A neurobiological risk factor for severity?

Gharehgazlou, Avideh / Richardson, J Don / Jetly, Rakesh / Dunkley, Benjamin T

Neurobiology of stress

2021 Volume 14, Page(s) 100299

Abstract: Post-traumatic stress disorder (PTSD) is a prevalent psychiatric disorder, particularly among military personnel and veterans. Cortical gyrification, as a specific metric derived from structural MRI, is an index of the convoluted folding and patterning ... ...

Abstract	Post-traumatic stress disorder (PTSD) is a prevalent psychiatric disorder, particularly among military personnel and veterans. Cortical gyrification, as a specific metric derived from structural MRI, is an index of the convoluted folding and patterning of the gyri and sulci, and is thought to facilitate the efficiency of local neuronal wiring. It has the potential to act as a neurobiological risk factor for emergent psychiatric disorders - to date, it has been understudied in PTSD. Here, using a local measure of the degree of gyrification (local Gyrification Index,
Language	English
Publishing date	2021-01-23
Publishing country	United States
Document type	Journal Article
ZDB-ID	2816500-7
ISSN	2352-2895
ISSN	2352-2895
DOI	10.1016/j.ynstr.2021.100299
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Article ; Online: Brain network properties of clinical versus subclinical seizures among critically ill children.

Koster, Laura K / Zamyadi, Rouzbeh / Yan, Luowei / Payne, Eric T / McBain, Kristin L / Dunkley, Benjamin T / Hahn, Cecil D

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology

2023 Volume 149, Page(s) 33–41

Abstract: Objective: Electrographic seizures are common among critically ill children, and have been associated with worse outcomes. Despite their often-widespread cortical representation, most of these seizures remain subclinical, a phenomenon which remains ... ...

Abstract	Objective: Electrographic seizures are common among critically ill children, and have been associated with worse outcomes. Despite their often-widespread cortical representation, most of these seizures remain subclinical, a phenomenon which remains poorly understood. We compared the brain network properties of clinical versus subclinical seizures to gain insight into their relative potential deleterious effects. Methods: Functional connectivity (phase lag index) and graph measures (global efficiency and clustering coefficients) were computed for 2178 electrographic seizures recorded during 48-hours of 19-channel continuous EEG monitoring obtained in 20 comatose children. Frequency-specific group differences in clinical versus subclinical seizures were analyzed using a non-parametric ANCOVA, adjusting for age, sex, medication exposure, treatment intensity and seizures per subject. Results: Clinical seizures demonstrated greater functional connectivity than subclinical seizures at alpha frequencies, but less connectivity than subclinical seizures at delta frequencies. Clinical seizures also demonstrated significantly higher median global efficiency than subclinical seizures (p < 0.01), and significantly higher median clustering coefficients across all electrodes at alpha frequencies. Conclusions: Clinical expression of seizures correlates with greater alpha synchronization of distributed brain networks. Significance: The stronger global and local alpha-mediated functional connectivity observed during clinical seizures may indicate greater pathological network recruitment. These observations motivate further studies to investigate whether the clinical expression of seizures may influence their potential to cause secondary brain injury.
MeSH term(s)	Child ; Humans ; Critical Illness ; Electroencephalography/adverse effects ; Epilepsies, Partial ; Brain ; Seizures/etiology
Language	English
Publishing date	2023-02-15
Publishing country	Netherlands
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	1463630-x
ISSN	1872-8952 ; 0921-884X ; 1388-2457
ISSN (online)	1872-8952
ISSN	0921-884X ; 1388-2457
DOI	10.1016/j.clinph.2023.02.160
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Article ; Online: Classifying post-traumatic stress disorder using the magnetoencephalographic connectome and machine learning.

Zhang, Jing / Richardson, J Don / Dunkley, Benjamin T

Scientific reports

2020 Volume 10, Issue 1, Page(s) 5937

Abstract: Given the subjective nature of conventional diagnostic methods for post-traumatic stress disorder (PTSD), an objectively measurable biomarker is highly desirable; especially to clinicians and researchers. Macroscopic neural circuits measured using ... ...

Abstract	Given the subjective nature of conventional diagnostic methods for post-traumatic stress disorder (PTSD), an objectively measurable biomarker is highly desirable; especially to clinicians and researchers. Macroscopic neural circuits measured using magnetoencephalography (MEG) has previously been shown to be indicative of the PTSD phenotype and severity. In the present study, we employed a machine learning-based classification framework using MEG neural synchrony to distinguish combat-related PTSD from trauma-exposed controls. Support vector machine (SVM) was used as the core classification algorithm. A recursive random forest feature selection step was directly incorporated in the nested SVM cross validation process (CV-SVM-rRF-FS) for identifying the most important features for PTSD classification. For the five frequency bands tested, the CV-SVM-rRF-FS analysis selected the minimum numbers of edges per frequency that could serve as a PTSD signature and be used as the basis for SVM modelling. Many of the selected edges have been reported previously to be core in PTSD pathophysiology, with frequency-specific patterns also observed. Furthermore, the independent partial least squares discriminant analysis suggested low bias in the machine learning process. The final SVM models built with selected features showed excellent PTSD classification performance (area-under-curve value up to 0.9). Testament to its robustness when distinguishing individuals from a heavily traumatised control group, these developments for a classification model for PTSD also provide a comprehensive machine learning-based computational framework for classifying other mental health challenges using MEG connectome profiles.
MeSH term(s)	Adult ; Algorithms ; Brain/diagnostic imaging ; Brain/physiology ; Canada ; Computational Biology ; Connectome ; Humans ; Machine Learning ; Magnetoencephalography/methods ; Male ; Middle Aged ; Stress Disorders, Post-Traumatic/diagnosis ; Support Vector Machine ; Young Adult
Language	English
Publishing date	2020-04-03
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-020-62713-5
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Article ; Online: Occipital cortex is modulated by transsaccadic changes in spatial frequency: an fMRI study.

Baltaretu, Bianca R / Dunkley, Benjamin T / Stevens, W Dale / Crawford, J Douglas

Scientific reports

2021 Volume 11, Issue 1, Page(s) 8611

Abstract: Previous neuroimaging studies have shown that inferior parietal and ventral occipital cortex are involved in the transsaccadic processing of visual object orientation. Here, we investigated whether the same areas are also involved in transsaccadic ... ...

Abstract	Previous neuroimaging studies have shown that inferior parietal and ventral occipital cortex are involved in the transsaccadic processing of visual object orientation. Here, we investigated whether the same areas are also involved in transsaccadic processing of a different feature, namely, spatial frequency. We employed a functional magnetic resonance imaging paradigm where participants briefly viewed a grating stimulus with a specific spatial frequency that later reappeared with the same or different frequency, after a saccade or continuous fixation. First, using a whole-brain Saccade > Fixation contrast, we localized two frontal (left precentral sulcus and right medial superior frontal gyrus), four parietal (bilateral superior parietal lobule and precuneus), and four occipital (bilateral cuneus and lingual gyri) regions. Whereas the frontoparietal sites showed task specificity, the occipital sites were also modulated in a saccade control task. Only occipital cortex showed transsaccadic feature modulations, with significant repetition enhancement in right cuneus. These observations (parietal task specificity, occipital enhancement, right lateralization) are consistent with previous transsaccadic studies. However, the specific regions differed (ventrolateral for orientation, dorsomedial for spatial frequency). Overall, this study supports a general role for occipital and parietal cortex in transsaccadic vision, with a specific role for cuneus in spatial frequency processing.
MeSH term(s)	Adult ; Brain Mapping/methods ; Female ; Humans ; Magnetic Resonance Imaging/methods ; Male ; Occipital Lobe/physiology ; Parietal Lobe/physiology ; Saccades/physiology ; Young Adult
Language	English
Publishing date	2021-04-21
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-021-87506-2
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Article: A Systematic Scoping Review of New Attention Problems Following Traumatic Brain Injury in Children.

Stojanovski, Sonja / Scratch, Shannon E / Dunkley, Benjamin T / Schachar, Russell / Wheeler, Anne L

Frontiers in neurology

2021 Volume 12, Page(s) 751736

Abstract: Objective: ...

Abstract	Objective:
Language	English
Publishing date	2021-11-10
Publishing country	Switzerland
Document type	Systematic Review
ZDB-ID	2564214-5
ISSN	1664-2295
ISSN	1664-2295
DOI	10.3389/fneur.2021.751736
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Article ; Online: Cortical Gyrification Morphology in Adult Males with Mild Traumatic Brain Injury.

Gharehgazlou, Avideh / Jetly, Rakesh / Rhind, Shawn G / Reichelt, Amy C / Da Costa, Leodante / Dunkley, Benjamin T

Neurotrauma reports

2022 Volume 3, Issue 1, Page(s) 299–307

Abstract: Cortical gyrification, as a specific measure derived from magnetic resonance imaging, remains understudied in mild traumatic brain injury (mTBI). Local gyrification index ( ...

Abstract	Cortical gyrification, as a specific measure derived from magnetic resonance imaging, remains understudied in mild traumatic brain injury (mTBI). Local gyrification index (
Language	English
Publishing date	2022-08-09
Publishing country	United States
Document type	Journal Article
ISSN	2689-288X
ISSN (online)	2689-288X
DOI	10.1089/neur.2021.0032
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Article ; Online: Classifying post-traumatic stress disorder using the magnetoencephalographic connectome and machine learning

Jing Zhang / J. Don Richardson / Benjamin T. Dunkley

Scientific Reports, Vol 10, Iss 1, Pp 1-

2020 Volume 10

Abstract: Abstract Given the subjective nature of conventional diagnostic methods for post-traumatic stress disorder (PTSD), an objectively measurable biomarker is highly desirable; especially to clinicians and researchers. Macroscopic neural circuits measured ... ...

Abstract	Abstract Given the subjective nature of conventional diagnostic methods for post-traumatic stress disorder (PTSD), an objectively measurable biomarker is highly desirable; especially to clinicians and researchers. Macroscopic neural circuits measured using magnetoencephalography (MEG) has previously been shown to be indicative of the PTSD phenotype and severity. In the present study, we employed a machine learning-based classification framework using MEG neural synchrony to distinguish combat-related PTSD from trauma-exposed controls. Support vector machine (SVM) was used as the core classification algorithm. A recursive random forest feature selection step was directly incorporated in the nested SVM cross validation process (CV-SVM-rRF-FS) for identifying the most important features for PTSD classification. For the five frequency bands tested, the CV-SVM-rRF-FS analysis selected the minimum numbers of edges per frequency that could serve as a PTSD signature and be used as the basis for SVM modelling. Many of the selected edges have been reported previously to be core in PTSD pathophysiology, with frequency-specific patterns also observed. Furthermore, the independent partial least squares discriminant analysis suggested low bias in the machine learning process. The final SVM models built with selected features showed excellent PTSD classification performance (area-under-curve value up to 0.9). Testament to its robustness when distinguishing individuals from a heavily traumatised control group, these developments for a classification model for PTSD also provide a comprehensive machine learning-based computational framework for classifying other mental health challenges using MEG connectome profiles.
Keywords	Medicine ; R ; Science ; Q
Subject code	150
Language	English
Publishing date	2020-04-01T00:00:00Z
Publisher	Nature Portfolio
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Alpha connectivity and inhibitory control in adults with autism spectrum disorder.

Yuk, Veronica / Dunkley, Benjamin T / Anagnostou, Evdokia / Taylor, Margot J

Molecular autism

2020 Volume 11, Issue 1, Page(s) 95

Abstract: Background: Individuals with autism spectrum disorder (ASD) often report difficulties with inhibition in everyday life. During inhibition tasks, adults with ASD show reduced activation of and connectivity between brain areas implicated in inhibition, ... ...

Abstract	Background: Individuals with autism spectrum disorder (ASD) often report difficulties with inhibition in everyday life. During inhibition tasks, adults with ASD show reduced activation of and connectivity between brain areas implicated in inhibition, suggesting impairments in inhibitory control at the neural level. Our study further investigated these differences by using magnetoencephalography (MEG) to examine the frequency band(s) in which functional connectivity underlying response inhibition occurs, as brain functions are frequency specific, and whether connectivity in certain frequency bands differs between adults with and without ASD. Methods: We analysed MEG data from 40 adults with ASD (27 males; 26.94 ± 6.08 years old) and 39 control adults (27 males; 27.29 ± 5.94 years old) who performed a Go/No-go task. The task involved two blocks with different proportions of No-go trials: Inhibition (25% No-go) and Vigilance (75% No-go). We compared whole-brain connectivity in the two groups during correct No-go trials in the Inhibition vs. Vigilance blocks between 0 and 400 ms. Results: Despite comparable performance on the Go/No-go task, adults with ASD showed reduced connectivity compared to controls in the alpha band (8-14 Hz) in a network with a main hub in the right inferior frontal gyrus. Decreased connectivity in this network predicted more self-reported difficulties on a measure of inhibition in everyday life. Limitations: Measures of everyday inhibitory control were not available for all participants, so this relationship between reduced network connectivity and inhibitory control abilities may not be necessarily representative of all adults with ASD or the larger ASD population. Further research with independent samples of adults with ASD, including those with a wider range of cognitive abilities, would be valuable. Conclusions: Our findings demonstrate reduced functional brain connectivity during response inhibition in adults with ASD. As alpha-band synchrony has been linked to top-down control mechanisms, we propose that the lack of alpha synchrony observed in our ASD group may reflect difficulties in suppressing task-irrelevant information, interfering with inhibition in real-life situations.
MeSH term(s)	Adolescent ; Adult ; Alpha Rhythm/physiology ; Autism Spectrum Disorder/physiopathology ; Brain/physiopathology ; Case-Control Studies ; Female ; Humans ; Male ; Nerve Net/physiopathology ; Neural Inhibition/physiology ; Surveys and Questionnaires ; Task Performance and Analysis ; Young Adult
Language	English
Publishing date	2020-12-07
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2540930-X
ISSN	2040-2392 ; 2040-2392
ISSN (online)	2040-2392
ISSN	2040-2392
DOI	10.1186/s13229-020-00400-y
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Mild traumatic brain injury is associated with dysregulated neural network functioning in children and adolescents.

Safar, Kristina / Zhang, Jing / Emami, Zahra / Gharehgazlou, Avideh / Ibrahim, George / Dunkley, Benjamin T

Brain communications

2021 Volume 3, Issue 2, Page(s) fcab044

Abstract: Mild traumatic brain injury is highly prevalent in paediatric populations, and can result in chronic physical, cognitive and emotional impairment, known as persistent post-concussive symptoms. Magnetoencephalography has been used to investigate ... ...

Abstract	Mild traumatic brain injury is highly prevalent in paediatric populations, and can result in chronic physical, cognitive and emotional impairment, known as persistent post-concussive symptoms. Magnetoencephalography has been used to investigate neurophysiological dysregulation in mild traumatic brain injury in adults; however, whether neural dysrhythmia persists in chronic mild traumatic brain injury in children and adolescents is largely unknown. We predicted that children and adolescents would show similar dysfunction as adults, including pathological slow-wave oscillations and maladaptive, frequency-specific, alterations to neural connectivity. Using magnetoencephalography, we investigated regional oscillatory power and distributed brain-wide networks in a cross-sectional sample of children and adolescents in the chronic stages of mild traumatic brain injury. Additionally, we used a machine learning pipeline to identify the most relevant magnetoencephalography features for classifying mild traumatic brain injury and to test the relative classification performance of regional power versus functional coupling. Results revealed that the majority of participants with chronic mild traumatic brain injury reported persistent post-concussive symptoms. For neurophysiological imaging, we found increased regional power in the delta band in chronic mild traumatic brain injury, predominantly in bilateral occipital cortices and in the right inferior temporal gyrus. Those with chronic mild traumatic brain injury also showed dysregulated neuronal coupling, including decreased connectivity in the delta range, as well as hyper-connectivity in the theta, low gamma and high gamma bands, primarily involving frontal, temporal and occipital brain areas. Furthermore, our multivariate classification approach combined with functional connectivity data outperformed regional power in terms of between-group classification accuracy. For the first time, we establish that local and large-scale neural activity are altered in youth in the chronic phase of mild traumatic brain injury, with the majority presenting persistent post-concussive symptoms, and that dysregulated interregional neural communication is a reliable marker of lingering paediatric 'mild' traumatic brain injury.
Language	English
Publishing date	2021-03-17
Publishing country	England
Document type	Journal Article
ISSN	2632-1297
ISSN (online)	2632-1297
DOI	10.1093/braincomms/fcab044
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