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Sarma AK, Popli G, Anzalone A, Contillo N, Cornell C, Nunn AM, Rowland JA, Godwin DW, Flashman LA, Couture D, Stapleton-Kotloski JR. Use of magnetic source imaging to assess recovery after severe traumatic brain injury-an MEG pilot study. Front Neurol 2023; 14:1257886. [PMID: 38020602 PMCID: PMC10656620 DOI: 10.3389/fneur.2023.1257886] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Accepted: 10/13/2023] [Indexed: 12/01/2023] Open
Abstract
Rationale Severe TBI (sTBI) is a devastating neurological injury that comprises a significant global trauma burden. Early comprehensive neurocritical care and rehabilitation improve outcomes for such patients, although better diagnostic and prognostic tools are necessary to guide personalized treatment plans. Methods In this study, we explored the feasibility of conducting resting state magnetoencephalography (MEG) in a case series of sTBI patients acutely after injury (~7 days), and then about 1.5 and 8 months after injury. Synthetic aperture magnetometry (SAM) was utilized to localize source power in the canonical frequency bands of delta, theta, alpha, beta, and gamma, as well as DC-80 Hz. Results At the first scan, SAM source maps revealed zones of hypofunction, islands of preserved activity, and hemispheric asymmetry across bandwidths, with markedly reduced power on the side of injury for each patient. GCS scores improved at scan 2 and by scan 3 the patients were ambulatory. The SAM maps for scans 2 and 3 varied, with most patients showing increasing power over time, especially in gamma, but a continued reduction in power in damaged areas and hemispheric asymmetry and/or relative diminishment in power at the site of injury. At the group level for scan 1, there was a large excess of neural generators operating within the delta band relative to control participants, while the number of neural generators for beta and gamma were significantly reduced. At scan 2 there was increased beta power relative to controls. At scan 3 there was increased group-wise delta power in comparison to controls. Conclusion In summary, this pilot study shows that MEG can be safely used to monitor and track the recovery of brain function in patients with severe TBI as well as to identify patient-specific regions of decreased or altered brain function. Such MEG maps of brain function may be used in the future to tailor patient-specific rehabilitation plans to target regions of altered spectral power with neurostimulation and other treatments.
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Affiliation(s)
- Anand Karthik Sarma
- Department of Neurology, Wake Forest University School of Medicine, Winston-Salem, NC, United States
- Neurocritical Care, Piedmont Atlanta Hospital, Atlanta, GA, United States
| | - Gautam Popli
- Department of Neurology, Wake Forest University School of Medicine, Winston-Salem, NC, United States
| | - Anthony Anzalone
- Wake Forest University School of Medicine, Winston-Salem, NC, United States
- Department of Neurosurgery, Henry Ford Health System, Detroit, MI, United States
| | - Nicholas Contillo
- Wake Forest University School of Medicine, Winston-Salem, NC, United States
| | - Cassandra Cornell
- Department of Neurology, Wake Forest University School of Medicine, Winston-Salem, NC, United States
| | - Andrew M. Nunn
- Department of Surgery, Wake Forest University School of Medicine, Winston-Salem, NC, United States
| | - Jared A. Rowland
- Department of Neurobiology and Anatomy, Wake Forest University School of Medicine, Winston-Salem, NC, United States
- Research and Education Department, W.G. (Bill) Hefner VA Healthcare System, Salisbury, NC, United States
| | - Dwayne W. Godwin
- Department of Neurology, Wake Forest University School of Medicine, Winston-Salem, NC, United States
- Department of Neurobiology and Anatomy, Wake Forest University School of Medicine, Winston-Salem, NC, United States
- Research and Education Department, W.G. (Bill) Hefner VA Healthcare System, Salisbury, NC, United States
| | - Laura A. Flashman
- Department of Neurology, Wake Forest University School of Medicine, Winston-Salem, NC, United States
| | - Daniel Couture
- Department of Neurosurgery, Wake Forest University School of Medicine, Winston-Salem, NC, United States
| | - Jennifer R. Stapleton-Kotloski
- Department of Neurology, Wake Forest University School of Medicine, Winston-Salem, NC, United States
- Department of Neurobiology and Anatomy, Wake Forest University School of Medicine, Winston-Salem, NC, United States
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Aaltonen J, Heikkinen V, Kaltiainen H, Salmelin R, Renvall H. Sensor-level MEG combined with machine learning yields robust classification of mild traumatic brain injury patients. Clin Neurophysiol 2023; 153:79-87. [PMID: 37459668 DOI: 10.1016/j.clinph.2023.06.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 05/06/2023] [Accepted: 06/09/2023] [Indexed: 08/21/2023]
Abstract
OBJECTIVE Diagnosis of mild traumatic brain injury (mTBI) is challenging despite its high incidence, due to the unspecificity and variety of symptoms and the frequent lack of structural imaging findings. There is a need for reliable and simple-to-use diagnostic tools that would be feasible across sites and patient populations. METHODS We evaluated linear machine learning (ML) methods' ability to separate mTBI patients from healthy controls, based on their sensor-level magnetoencephalographic (MEG) power spectra in the subacute phase (<2 months) after a head trauma. We recorded resting-state MEG data from 25 patients and 25 age-sex matched controls and utilized a previously collected data set of 20 patients and 20 controls from a different site. The data sets were analyzed separately with three ML methods. RESULTS The median classification accuracies varied between 80 and 95%, without significant differences between the applied ML methods or data sets. The classification accuracies were significantly higher with ML than with traditional sensor-level MEG analysis based on detecting pathological low-frequency activity. CONCLUSIONS Easily applicable linear ML methods provide reliable and replicable classification of mTBI patients using sensor-level MEG data. SIGNIFICANCE Power spectral estimates combined with ML can classify mTBI patients with high accuracy and have high promise for clinical use.
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Affiliation(s)
- Juho Aaltonen
- BioMag Laboratory, HUS Medical Imaging Center, Helsinki University Hospital, Helsinki University and Aalto University School of Science, P.O. Box 340, 00029 HUS Helsinki, Finland; Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Aalto University, P.O. Box 12200, 00760 AALTO, Finland.
| | - Verna Heikkinen
- BioMag Laboratory, HUS Medical Imaging Center, Helsinki University Hospital, Helsinki University and Aalto University School of Science, P.O. Box 340, 00029 HUS Helsinki, Finland; Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Aalto University, P.O. Box 12200, 00760 AALTO, Finland
| | - Hanna Kaltiainen
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Aalto University, P.O. Box 12200, 00760 AALTO, Finland; Department of Neurology, Helsinki University Hospital and Clinical Neurosciences, Neurology, University of Helsinki, P.O. Box 340, 00029 HUS, Helsinki, Finland
| | - Riitta Salmelin
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Aalto University, P.O. Box 12200, 00760 AALTO, Finland
| | - Hanna Renvall
- BioMag Laboratory, HUS Medical Imaging Center, Helsinki University Hospital, Helsinki University and Aalto University School of Science, P.O. Box 340, 00029 HUS Helsinki, Finland; Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Aalto University, P.O. Box 12200, 00760 AALTO, Finland; Department of Neurology, Helsinki University Hospital and Clinical Neurosciences, Neurology, University of Helsinki, P.O. Box 340, 00029 HUS, Helsinki, Finland
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3
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Huang MX, Harrington DL, Angeles-Quinto A, Ji Z, Robb-Swan A, Huang CW, Shen Q, Hansen H, Baumgartner J, Hernandez-Lucas J, Nichols S, Jacobus J, Song T, Lerman I, Bazhenov M, Krishnan GP, Baker DG, Rao R, Lee RR. EMG-projected MEG High-Resolution Source Imaging of Human Motor Execution: Brain-Muscle Coupling above Movement Frequencies. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.06.23.23291825. [PMID: 37425691 PMCID: PMC10327237 DOI: 10.1101/2023.06.23.23291825] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
Magnetoencephalography (MEG) is a non-invasive functional imaging technique for pre-surgical mapping. However, movement-related MEG functional mapping of primary motor cortex (M1) has been challenging in presurgical patients with brain lesions and sensorimotor dysfunction due to the large numbers of trails needed to obtain adequate signal to noise. Moreover, it is not fully understood how effective the brain communication is with the muscles at frequencies above the movement frequency and its harmonics. We developed a novel Electromyography (EMG)-projected MEG source imaging technique for localizing M1 during ~1 minute recordings of left and right self-paced finger movements (~1 Hz). High-resolution MEG source images were obtained by projecting M1 activity towards the skin EMG signal without trial averaging. We studied delta (1-4 Hz), theta (4-7 Hz), alpha (8-12 Hz), beta (15-30 Hz), and gamma (30-90 Hz) bands in 13 healthy participants (26 datasets) and two presurgical patients with sensorimotor dysfunction. In healthy participants, EMG-projected MEG accurately localized M1 with high accuracy in delta (100.0%), theta (100.0%), and beta (76.9%) bands, but not alpha (34.6%) and gamma (0.0%) bands. Except for delta, all other frequency bands were above the movement frequency and its harmonics. In both presurgical patients, M1 activity in the affected hemisphere was also accurately localized, despite highly irregular EMG movement patterns in one patient. Altogether, our EMG-projected MEG imaging approach is highly accurate and feasible for M1 mapping in presurgical patients. The results also provide insight into movement related brain-muscle coupling above the movement frequency and its harmonics.
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Affiliation(s)
- Ming-Xiong Huang
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA
- Department of Radiology, University of California, San Diego, CA, USA
- Department of Electrical and Computer Engineering, University of California, San Diego, CA, USA
| | - Deborah L. Harrington
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA
- Department of Radiology, University of California, San Diego, CA, USA
| | | | - Zhengwei Ji
- Department of Radiology, University of California, San Diego, CA, USA
| | - Ashley Robb-Swan
- Department of Radiology, University of California, San Diego, CA, USA
| | - Charles W. Huang
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Qian Shen
- Department of Radiology, University of California, San Diego, CA, USA
| | - Hayden Hansen
- Department of Radiology, University of California, San Diego, CA, USA
| | - Jared Baumgartner
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA
| | | | - Sharon Nichols
- Department of Neurosciences, University of California, San Diego, CA, USA
| | - Joanna Jacobus
- Department of Psychiatry, University of California, San Diego, CA, USA
| | - Tao Song
- Department of Radiology, University of California, San Diego, CA, USA
| | - Imanuel Lerman
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA
| | - Maksim Bazhenov
- Department of Medicine, University of California, San Diego, CA, USA
| | - Giri P Krishnan
- Department of Medicine, University of California, San Diego, CA, USA
| | - Dewleen G. Baker
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA
- Department of Psychiatry, University of California, San Diego, CA, USA
- VA Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA, USA
| | - Ramesh Rao
- Department of Electrical and Computer Engineering, University of California, San Diego, CA, USA
| | - Roland R. Lee
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA
- Department of Radiology, University of California, San Diego, CA, USA
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4
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Pathological Slow-Wave Activity and Impaired Working Memory Binding in Post-Traumatic Amnesia. J Neurosci 2022; 42:9193-9210. [PMID: 36316155 PMCID: PMC9761692 DOI: 10.1523/jneurosci.0564-22.2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Revised: 10/02/2022] [Accepted: 10/04/2022] [Indexed: 11/06/2022] Open
Abstract
Associative binding is key to normal memory function and is transiently disrupted during periods of post-traumatic amnesia (PTA) following traumatic brain injury (TBI). Electrophysiological abnormalities, including low-frequency activity, are common following TBI. Here, we investigate associative memory binding during PTA and test the hypothesis that misbinding is caused by pathological slowing of brain activity disrupting cortical communication. Thirty acute moderate to severe TBI patients (25 males; 5 females) and 26 healthy controls (20 males; 6 females) were tested with a precision working memory paradigm requiring the association of object and location information. Electrophysiological effects of TBI were assessed using resting-state EEG in a subsample of 17 patients and 21 controls. PTA patients showed abnormalities in working memory function and made significantly more misbinding errors than patients who were not in PTA and controls. The distribution of localization responses was abnormally biased by the locations of nontarget items for patients in PTA, suggesting a specific impairment of object and location binding. Slow-wave activity was increased following TBI. Increases in the δ-α ratio indicative of an increase in low-frequency power specifically correlated with binding impairment in working memory. Connectivity changes in TBI did not correlate with binding impairment. Working memory and electrophysiological abnormalities normalized at 6 month follow-up. These results show that patients in PTA show high rates of misbinding that are associated with a pathological shift toward lower-frequency oscillations.SIGNIFICANCE STATEMENT How do we remember what was where? The mechanism by which information (e.g., object and location) is integrated in working memory is a central question for cognitive neuroscience. Following significant head injury, many patients will experience a period of post-traumatic amnesia (PTA) during which this associative binding is disrupted. This may be because of electrophysiological changes in the brain. Using a precision working memory test and resting-state EEG, we show that PTA patients demonstrate impaired binding ability, and this is associated with a shift toward slower-frequency activity on EEG. Abnormal EEG connectivity was observed but was not specific to PTA or binding ability. These findings contribute to both our mechanistic understanding of working memory binding and PTA pathophysiology.
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5
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Maldjian JA, Lee R, Jordan J, Davenport EM, Proskovec AL, Wintermark M, Stufflebeam S, Anderson J, Mukherjee P, Nagarajan SS, Ferrari P, Gaetz W, Schwartz E, Roberts TPL. ACR White Paper on Magnetoencephalography and Magnetic Source Imaging: A Report from the ACR Commission on Neuroradiology. AJNR Am J Neuroradiol 2022; 43:E46-E53. [PMID: 36456085 DOI: 10.3174/ajnr.a7714] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Accepted: 10/04/2022] [Indexed: 12/04/2022]
Abstract
Magnetoencephalography, the extracranial detection of tiny magnetic fields emanating from intracranial electrical activity of neurons, and its source modeling relation, magnetic source imaging, represent a powerful functional neuroimaging technique, able to detect and localize both spontaneous and evoked activity of the brain in health and disease. Recent years have seen an increased utilization of this technique for both clinical practice and research, in the United States and worldwide. This report summarizes current thinking, presents recommendations for clinical implementation, and offers an outlook for emerging new clinical indications.
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Affiliation(s)
- J A Maldjian
- From the Advanced Neuroscience Imaging Research Laboratory (J.A.M., E.M.D., A.L.P.) .,MEG Center of Excellence (J.A.M., E.M.D., A.L.P.).,Department of Radiology (J.A.M., E.M.D., A.L.P.), University of Texas Southwestern Medical Center, Dallas, Texas
| | - R Lee
- Department of Neuroradiology (R.L.), University of California San Diego, San Diego, California
| | - J Jordan
- ACR Commission on Neuroradiology (J.J.), American College of Radiology, Reston, Virginia.,Stanford University School of Medicine (J.J.), Stanford, California
| | - E M Davenport
- From the Advanced Neuroscience Imaging Research Laboratory (J.A.M., E.M.D., A.L.P.).,MEG Center of Excellence (J.A.M., E.M.D., A.L.P.).,Department of Radiology (J.A.M., E.M.D., A.L.P.), University of Texas Southwestern Medical Center, Dallas, Texas
| | - A L Proskovec
- From the Advanced Neuroscience Imaging Research Laboratory (J.A.M., E.M.D., A.L.P.).,MEG Center of Excellence (J.A.M., E.M.D., A.L.P.).,Department of Radiology (J.A.M., E.M.D., A.L.P.), University of Texas Southwestern Medical Center, Dallas, Texas
| | - M Wintermark
- Department of Neuroradiology (M.W.), University of Texas MD Anderson Center, Houston, Texas
| | - S Stufflebeam
- Athinoula A. Martinos Center for Biomedical Imaging (S.S.), Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts
| | - J Anderson
- Department of Radiology and Imaging Sciences (J.A.), University of Utah School of Medicine, Salt Lake City, Utah
| | - P Mukherjee
- Department of Radiology and Biomedical Imaging (P.M., S.S.N.), University of California, San Francisco, San Francisco, California
| | - S S Nagarajan
- Department of Radiology and Biomedical Imaging (P.M., S.S.N.), University of California, San Francisco, San Francisco, California
| | - P Ferrari
- Pediatric Neurosciences (P.F.), Helen DeVos Children's Hospital, Grand Rapids, Michigan.,Department of Pediatrics and Human Development (P.F.), College of Human Medicine, Michigan State University, Grand Rapids, Michigan
| | - W Gaetz
- Department of Radiology (W.G., E.S., T.P.L.R.), Children's Hospital of Philadelphia, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania
| | - E Schwartz
- Department of Radiology (W.G., E.S., T.P.L.R.), Children's Hospital of Philadelphia, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania
| | - T P L Roberts
- Department of Radiology (W.G., E.S., T.P.L.R.), Children's Hospital of Philadelphia, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania
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6
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Davenport EM, Urban JE, Vaughan C, DeSimone JC, Wagner B, Espeland MA, Powers AK, Whitlow CT, Stitzel JD, Maldjian JA. MEG measured delta waves increase in adolescents after concussion. Brain Behav 2022; 12:e2720. [PMID: 36053126 PMCID: PMC9480906 DOI: 10.1002/brb3.2720] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Revised: 05/22/2022] [Accepted: 06/24/2022] [Indexed: 11/22/2022] Open
Abstract
INTRODUCTION The purpose of this study is to determine if delta waves, measured by magnetoencephalography (MEG), increase in adolescents due to a sports concussion. METHODS Twenty-four adolescents (age 14-17) completed pre- and postseason MRI and MEG scanning. MEG whole-brain delta power was calculated for each subject and normalized by the subject's total power. In eight high school football players diagnosed with a concussion during the season (mean age = 15.8), preseason delta power was subtracted from their postseason scan. In eight high school football players without a concussion (mean age = 15.7), preseason delta power was subtracted from postseason delta power and in eight age-matched noncontact controls (mean age = 15.9), baseline delta power was subtracted from a 4-month follow-up scan. ANOVA was used to compare the mean differences between preseason and postseason scans for the three groups of players, with pairwise comparisons based on Student's t-test method. RESULTS Players with concussions had significantly increased delta wave power at their postseason scans than nonconcussed players (p = .018) and controls (p = .027). CONCLUSION We demonstrate that a single concussion during the season in adolescent subjects can increase MEG measured delta frequency power at their postseason scan. This adds to the growing body of literature indicating increased delta power following a concussion.
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Affiliation(s)
- Elizabeth M Davenport
- Advanced Neuroscience Imaging Research (ANSIR) Laboratory, University of Texas Southwestern Medical Center, Dallas, Texas.,Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Jillian E Urban
- Department of Biomedical Engineering, Wake Forest School of Medicine, Winston-Salem, North Carolina.,Virginia Tech-Wake Forest School of Biomedical Engineering, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Christopher Vaughan
- Department of Neurosurgery, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Jesse C DeSimone
- Advanced Neuroscience Imaging Research (ANSIR) Laboratory, University of Texas Southwestern Medical Center, Dallas, Texas.,Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Ben Wagner
- Advanced Neuroscience Imaging Research (ANSIR) Laboratory, University of Texas Southwestern Medical Center, Dallas, Texas.,Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Mark A Espeland
- Department of Radiology-Neuroradiology, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Alexander K Powers
- Clinical and Translational Science Institute, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Christopher T Whitlow
- Department of Biomedical Engineering, Wake Forest School of Medicine, Winston-Salem, North Carolina.,Childress Institute for Pediatric Trauma, Wake Forest School of Medicine, Winston-Salem, North Carolina.,Division of Pediatric Neuropsychology, Children's National Health System, Washington, District of Columbia
| | - Joel D Stitzel
- Department of Biomedical Engineering, Wake Forest School of Medicine, Winston-Salem, North Carolina.,Virginia Tech-Wake Forest School of Biomedical Engineering, Wake Forest School of Medicine, Winston-Salem, North Carolina.,Division of Pediatric Neuropsychology, Children's National Health System, Washington, District of Columbia.,Division of Gerontology and Geriatric Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Joseph A Maldjian
- Advanced Neuroscience Imaging Research (ANSIR) Laboratory, University of Texas Southwestern Medical Center, Dallas, Texas.,Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Texas
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Franke LM, Gitchel GT, Perera RA, Hadimani RL, Holloway KL, Walker WC. Randomized trial of rTMS in traumatic brain injury: improved subjective neurobehavioral symptoms and increases in EEG delta activity. Brain Inj 2022; 36:683-692. [PMID: 35143365 DOI: 10.1080/02699052.2022.2033845] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
PRIMARY OBJECTIVE While repetitive transcranial magnetic stimulation (rTMS) has shown efficacy for cognitive difficulties accompanying depression, it is unknown if it can improve cognition in persons with traumatic brain injury. RESEARCH DESIGN Using a sham-controlled crossover design, we tested the capacity of high frequency rTMS of the prefrontal cortex to improve neuropsychological performance in attention, learning and memory, and executive function. METHODS Twenty-six participants with cognitive complaints and a history of mild-to-moderate traumatic brain injury were randomly assigned to receive first either active or sham 10 Hz stimulation for 20 minutes (1200 pulses) per session for five consecutive days. After a one-week washout, the other condition (active or sham) was applied. Pre- and post-treatment measures included neuropsychological tests, cognitive and emotional symptoms, and EEG. MAIN OUTCOMES AND RESULTS Results indicated no effect of treatment on cognitive function. Subjective measures of depression, sleep dysfunction, post-concussive symptoms (PCS), and executive function showed significant improvement with stimulation, retaining improved levels at two-week follow-up. EEG delta power exhibited elevation one week after stimulation cessation. CONCLUSIONS While there is no indication that rTMS is beneficial for neuropsychological performance, it may improve PCS and subjective cognitive dysfunction. Long-term alterations in cortical oscillations may underlie the therapeutic effects of rTMS.
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Affiliation(s)
- Laura M Franke
- Department of Physical Medicine and Rehabilitation, Virginia Commonwealth University, Richmond, Virginia, USA.,Hunter Holmes McGuire Veterans Affairs Medical Center, Richmond, Virginia, USA
| | - George T Gitchel
- Hunter Holmes McGuire Veterans Affairs Medical Center, Richmond, Virginia, USA.,Department of Biomedical Engineering, Virginia Commonwealth University, Richmond, Virginia, USA
| | - Robert A Perera
- Department of Biostatistics, Virginia Commonwealth University, Richmond, Virginia, USA
| | - Ravi L Hadimani
- Department of Mechanical and Nuclear Engineering, Virginia Commonwealth University, Richmond, Virginia, USA
| | - Kathryn L Holloway
- Hunter Holmes McGuire Veterans Affairs Medical Center, Richmond, Virginia, USA.,Department of Neurosurgery, Virginia Commonwealth University, Richmond, Virginia, USA
| | - William C Walker
- Department of Physical Medicine and Rehabilitation, Virginia Commonwealth University, Richmond, Virginia, USA.,Hunter Holmes McGuire Veterans Affairs Medical Center, Richmond, Virginia, USA
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8
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Monsour M, Ebedes D, Borlongan CV. A review of the pathology and treatment of TBI and PTSD. Exp Neurol 2022; 351:114009. [PMID: 35150737 DOI: 10.1016/j.expneurol.2022.114009] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2021] [Revised: 12/25/2021] [Accepted: 02/05/2022] [Indexed: 02/07/2023]
Abstract
This literature review focuses on the underlying pathophysiology of TBI and PTSD symptoms, while also examining the plethora of stem cell treatment options to ameliorate these neuronal and functional changes. As more veterans return suffering from TBI and/or PTSD, it is vital that researchers discover novel therapies to mitigate the detrimental symptoms of both diagnoses. A variety of stem cell treatments have been studied and offer hopeful options for TBI and PTSD recovery.
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Affiliation(s)
- Molly Monsour
- Center of Excellence for Aging and Brain Repair, University of South Florida Morsani College of Medicine, 12901 Bruce B Downs Blvd, Tampa, FL 33612, USA
| | - Dominique Ebedes
- Center of Excellence for Aging and Brain Repair, University of South Florida Morsani College of Medicine, 12901 Bruce B Downs Blvd, Tampa, FL 33612, USA
| | - Cesario V Borlongan
- Center of Excellence for Aging and Brain Repair, University of South Florida Morsani College of Medicine, 12901 Bruce B Downs Blvd, Tampa, FL 33612, USA.
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9
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Rier L, Zamyadi R, Zhang J, Emami Z, Seedat ZA, Mocanu S, Gascoyne LE, Allen CM, Scadding JW, Furlong PL, Gooding-Williams G, Woolrich MW, Evangelou N, Brookes MJ, Dunkley BT. Mild traumatic brain injury impairs the coordination of intrinsic and motor-related neural dynamics. NEUROIMAGE-CLINICAL 2021; 32:102841. [PMID: 34653838 PMCID: PMC8517919 DOI: 10.1016/j.nicl.2021.102841] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Revised: 09/01/2021] [Accepted: 09/23/2021] [Indexed: 11/23/2022]
Abstract
MTBI is poorly understood and lacks objective diagnostic and prognostic tools. Abnormal neural oscillations are found in subjects with a history of mTBI. We identify transient bursts in MEG data using a Hidden Markov Model. We explain a deficit in beta connectivity and power in terms of transient bursts. Data-driven feature selection identifies symptom-relevant functional connections.
Mild traumatic brain injury (mTBI) poses a considerable burden on healthcare systems. Whilst most patients recover quickly, a significant number suffer from sequelae that are not accompanied by measurable structural damage. Understanding the neural underpinnings of these debilitating effects and developing a means to detect injury, would address an important unmet clinical need. It could inform interventions and help predict prognosis. Magnetoencephalography (MEG) affords excellent sensitivity in probing neural function and presents significant promise for assessing mTBI, with abnormal neural oscillations being a potential specific biomarker. However, growing evidence suggests that neural dynamics are (at least in part) driven by transient, pan-spectral bursting and in this paper, we employ this model to investigate mTBI. We applied a Hidden Markov Model to MEG data recorded during resting state and a motor task and show that previous findings of diminished intrinsic beta amplitude in individuals with mTBI are largely due to the reduced beta band spectral content of bursts, and that diminished beta connectivity results from a loss in the temporal coincidence of burst states. In a motor task, mTBI results in diminished burst amplitude, altered modulation of burst probability during movement, and a loss in connectivity in motor networks. These results suggest that, mechanistically, mTBI disrupts the structural framework underlying neural synchrony, which impairs network function. Whilst the damage may be too subtle for structural imaging to see, the functional consequences are detectable and persist after injury. Our work shows that mTBI impairs the dynamic coordination of neural network activity and proposes a potent new method for understanding mTBI.
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Affiliation(s)
- Lukas Rier
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham NG7 2RD, UK
| | - Rouzbeh Zamyadi
- Diagnostic Imaging, Hospital for Sick Children, Toronto, Canada
| | - Jing Zhang
- Diagnostic Imaging, Hospital for Sick Children, Toronto, Canada; Neurosciences & Mental Health, Hospital for Sick Children Research Institute, Toronto, Canada
| | - Zahra Emami
- Neurosciences & Mental Health, Hospital for Sick Children Research Institute, Toronto, Canada; Faculty of Medicine, University of Toronto, Toronto, Canada
| | - Zelekha A Seedat
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham NG7 2RD, UK
| | - Sergiu Mocanu
- Diagnostic Imaging, Hospital for Sick Children, Toronto, Canada; Neurosciences & Mental Health, Hospital for Sick Children Research Institute, Toronto, Canada
| | - Lauren E Gascoyne
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham NG7 2RD, UK
| | - Christopher M Allen
- Mental Health and Clinical Neurosciences Academic Unit, School of Medicine, University of Nottingham, Queen's Medical Centre, Nottingham, UK
| | - John W Scadding
- National Hospital for Neurology and Neurosurgery, London, UK
| | - Paul L Furlong
- Institute of Health and Neurodevelopment, Aston University, Birmingham, UK
| | | | - Mark W Woolrich
- Oxford Centre for Human Brain Activity, Warneford Hospital, University of Oxford, Oxford, UK
| | - Nikos Evangelou
- Mental Health and Clinical Neurosciences Academic Unit, School of Medicine, University of Nottingham, Queen's Medical Centre, Nottingham, UK
| | - Matthew J Brookes
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham NG7 2RD, UK
| | - Benjamin T Dunkley
- Diagnostic Imaging, Hospital for Sick Children, Toronto, Canada; Neurosciences & Mental Health, Hospital for Sick Children Research Institute, Toronto, Canada; Medical Imaging, University of Toronto, Toronto, Canada
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10
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Mortaheb S, Filippini MM, Kaux JF, Annen J, Lejeune N, Martens G, Calderón MAF, Laureys S, Thibaut A. Neurophysiological Biomarkers of Persistent Post-concussive Symptoms: A Scoping Review. Front Neurol 2021; 12:687197. [PMID: 34566837 PMCID: PMC8459021 DOI: 10.3389/fneur.2021.687197] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Accepted: 07/28/2021] [Indexed: 11/25/2022] Open
Abstract
Background and Objectives: Persistent post-concussive symptoms (PCS) consist of neurologic and psychological complaints persisting after a mild traumatic brain injury (mTBI). It affects up to 50% of mTBI patients, may cause long-term disability, and reduce patients' quality of life. The aim of this review was to examine the possible use of different neuroimaging modalities in PCS. Methods: Articles from Pubmed database were screened to extract studies that investigated the relationship between any neuroimaging features and symptoms of PCS. Descriptive statistics were applied to report the results. Results: A total of 80 out of 939 papers were included in the final review. Ten examined conventional MRI (30% positive finding), 24 examined diffusion weighted imaging (54.17% positive finding), 23 examined functional MRI (82.61% positive finding), nine examined electro(magneto)encephalography (77.78% positive finding), and 14 examined other techniques (71% positive finding). Conclusion: MRI was the most widely used technique, while functional techniques seem to be the most sensitive tools to evaluate PCS. The common functional patterns associated with symptoms of PCS were a decreased anti-correlation between the default mode network and the task positive network and reduced brain activity in specific areas (most often in the prefrontal cortex). Significance: Our findings highlight the importance to use functional approaches which demonstrated a functional alteration in brain connectivity and activity in most studies assessing PCS.
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Affiliation(s)
- Sepehr Mortaheb
- Coma Science Group, GIGA-Consciousness, University of Liège, Liège, Belgium.,Brain Clinic, University Hospital of Liège, Liège, Belgium.,Physiology of Cognition Lab., GIGA-Consciousness, University of Liège, Liège, Belgium
| | - Maria Maddalena Filippini
- Coma Science Group, GIGA-Consciousness, University of Liège, Liège, Belgium.,Brain Clinic, University Hospital of Liège, Liège, Belgium.,Neuromotor and Rehabilitation Department, Azienda Unita Sanitaria Locale-Istituto di Ricovero e Cura a Carattere Scientifico (USL-IRCSS) di Reggio Emilia, Reggio Emilia, Italy
| | - Jean-François Kaux
- Physical Medicine and Sport Traumatology Department, Sports, FIFA Medical Centre of Excellence, IOC Research Centre for Prevention of Injury and Protection of Athletes Health, FIMS Collaborative Centre of Sport Medicine, University and University Hospital of Liège, Liège, Belgium
| | - Jitka Annen
- Coma Science Group, GIGA-Consciousness, University of Liège, Liège, Belgium.,Brain Clinic, University Hospital of Liège, Liège, Belgium
| | - Nicolas Lejeune
- Coma Science Group, GIGA-Consciousness, University of Liège, Liège, Belgium.,Brain Clinic, University Hospital of Liège, Liège, Belgium.,Institute of NeuroScience, University of Louvain, Brussels, Belgium
| | - Géraldine Martens
- Coma Science Group, GIGA-Consciousness, University of Liège, Liège, Belgium.,Physical Medicine and Sport Traumatology Department, Sports, FIFA Medical Centre of Excellence, IOC Research Centre for Prevention of Injury and Protection of Athletes Health, FIMS Collaborative Centre of Sport Medicine, University and University Hospital of Liège, Liège, Belgium
| | | | - Steven Laureys
- Coma Science Group, GIGA-Consciousness, University of Liège, Liège, Belgium.,Brain Clinic, University Hospital of Liège, Liège, Belgium
| | - Aurore Thibaut
- Coma Science Group, GIGA-Consciousness, University of Liège, Liège, Belgium.,Brain Clinic, University Hospital of Liège, Liège, Belgium
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11
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Reddy DD, Davenport EM, Yu FF, Wagner B, Urban JE, Whitlow CT, Stitzel JD, Maldjian JA. Alterations in the Magnetoencephalography Default Mode Effective Connectivity following Concussion. AJNR Am J Neuroradiol 2021; 42:1776-1782. [PMID: 34503943 DOI: 10.3174/ajnr.a7232] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2020] [Accepted: 05/05/2021] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE Magnetoencephalography is sensitive to functional connectivity changes associated with concussion. However, the directional influences between functionally related regions remain unexplored. In this study, we therefore evaluated concussion-related magnetoencephalography-based effective connectivity changes within resting-state default mode network regions. MATERIALS AND METHODS Resting-state magnetoencephalography was acquired for 8 high school football players with concussion at 3 time points (preseason, postconcussion, postseason), as well as 8 high school football players without concussion and 8 age-matched controls at 2 time points (preseason, postseason). Time-series from the default mode network regions were extracted, and effective connectivity between them was computed for 5 different frequency bands. The default mode network regions were grouped into anterior and posterior default mode networks. The combined posterior-to-anterior and anterior-to-posterior effective connectivity values were averaged to generate 2 sets of values for each subject. The effective connectivity values were compared using a repeated measures ANOVA across time points for the concussed, nonconcussed, and control groups, separately. RESULTS A significant increase in posterior-to-anterior effective connectivity from preseason to postconcussion (corrected P value = .013) and a significant decrease in posterior-to-anterior effective connectivity from postconcussion to postseason (corrected P value = .028) were observed in the concussed group. Changes in effective connectivity were only significant within the delta band. Anterior-to-posterior connectivity demonstrated no significant change. Effective connectivity in the nonconcussed group and controls did not show significant differences. CONCLUSIONS The unidirectional increase in effective connectivity postconcussion may elucidate compensatory processes, invoking use of posterior regions to aid the function of susceptible anterior regions following brain injury. These findings support the potential value of magnetoencephalography in exploring directional changes of the brain network following concussion.
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Affiliation(s)
- D D Reddy
- From the Department of Radiology (D.D.R., E.M.D., F.F.Y., B.W., J.A.M.), University of Texas Southwestern, Dallas, Texas
| | - E M Davenport
- From the Department of Radiology (D.D.R., E.M.D., F.F.Y., B.W., J.A.M.), University of Texas Southwestern, Dallas, Texas
| | - F F Yu
- From the Department of Radiology (D.D.R., E.M.D., F.F.Y., B.W., J.A.M.), University of Texas Southwestern, Dallas, Texas
| | - B Wagner
- From the Department of Radiology (D.D.R., E.M.D., F.F.Y., B.W., J.A.M.), University of Texas Southwestern, Dallas, Texas
| | - J E Urban
- Wake Forest School of Medicine (J.E.U. C.T.W., J.D.S.), Winston-Salem, North Carolina
| | - C T Whitlow
- Wake Forest School of Medicine (J.E.U. C.T.W., J.D.S.), Winston-Salem, North Carolina
| | - J D Stitzel
- Wake Forest School of Medicine (J.E.U. C.T.W., J.D.S.), Winston-Salem, North Carolina
| | - J A Maldjian
- From the Department of Radiology (D.D.R., E.M.D., F.F.Y., B.W., J.A.M.), University of Texas Southwestern, Dallas, Texas
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12
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Pieper J, Chang DG, Mahasin SZ, Swan AR, Quinto AA, Nichols S, Diwakar M, Huang C, Swan J, Lee R, Baker DG, Huang M. Brain Amygdala Volume Increases in Veterans and Active-Duty Military Personnel With Combat-Related Posttraumatic Stress Disorder and Mild Traumatic Brain Injury. J Head Trauma Rehabil 2021; 35:E1-E9. [PMID: 31033749 PMCID: PMC6814512 DOI: 10.1097/htr.0000000000000492] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
OBJECTIVE To identify amygdalar volumetric differences associated with posttraumatic stress disorder (PTSD) in individuals with comorbid mild traumatic brain injury (mTBI) compared with those with mTBI-only and to examine the effects of intracranial volume (ICV) on amygdala volumetric measures. SETTING Marine Corps Base and VA Healthcare System. PARTICIPANTS A cohort of veterans and active-duty military personnel with combat-related mTBI (N = 89). DESIGN Twenty-nine participants were identified with comorbid PTSD and mTBI. The remaining 60 formed the mTBI-only control group. Structural images of brains were obtained with a 1.5-T MRI scanner using a T1-weighted 3D-IR-FSPGR pulse sequence. Automatic segmentation was performed in Freesurfer. MAIN MEASURES Amygdala volumes with/without normalizations to ICV. RESULTS The comorbid mTBI/PTSD group had significantly larger amygdala volumes, when normalized to ICV, compared with the mTBI-only group. The right and left amygdala volumes after normalization to ICV were 0.122% ± 0.012% and 0.118% ± 0.011%, respectively, in the comorbid group compared with 0.115% ± 0.012% and 0.112% ± 0.009%, respectively, in the mTBI-only group (corrected P < .05). CONCLUSIONS The ICV normalization analysis performed here may resolve previous literature discrepancies. This is an intriguing structural finding, given the role of the amygdala in the challenging neuroemotive symptoms witnessed in casualties of combat-related mTBI and PTSD.
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Affiliation(s)
- Joel Pieper
- Department of Internal Medicine, University of California, San Diego, CA, USA
| | - Douglas G. Chang
- Department of Orthopaedic Surgery, University of California, San Diego, CA, USA
| | | | - Ashley Robb Swan
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA
- Department of Radiology, University of California, San Diego, CA, USA
| | - Annemarie Angeles Quinto
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA
- Department of Radiology, University of California, San Diego, CA, USA
| | - Sharon Nichols
- Department of Neuroscience, University of California, San Diego, CA, USA
| | - Mithun Diwakar
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA
| | - Charles Huang
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - James Swan
- Department of Management Information Systems, San Diego State University, San Diego, CA, USA
| | - Roland Lee
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA
- Department of Radiology, University of California, San Diego, CA, USA
| | - Dewleen G. Baker
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA
- Department of Psychiatry, University of California, San Diego, CA, USA
- VA Center of Excellence for Stress and Mental Health, San Diego, CA, USA
| | - Mingxiong Huang
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA
- Department of Radiology, University of California, San Diego, CA, USA
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13
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Teasing apart trauma: neural oscillations differentiate individual cases of mild traumatic brain injury from post-traumatic stress disorder even when symptoms overlap. Transl Psychiatry 2021; 11:345. [PMID: 34088901 PMCID: PMC8178364 DOI: 10.1038/s41398-021-01467-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/28/2020] [Revised: 05/08/2021] [Accepted: 05/19/2021] [Indexed: 01/21/2023] Open
Abstract
Post-traumatic stress disorder (PTSD) and mild traumatic brain injury (mTBI) are highly prevalent and closely related disorders. Affected individuals often exhibit substantially overlapping symptomatology - a major challenge for differential diagnosis in both military and civilian contexts. According to our symptom assessment, the PTSD group exhibited comparable levels of concussion symptoms and severity to the mTBI group. An objective and reliable system to uncover the key neural signatures differentiating these disorders would be an important step towards translational and applied clinical use. Here we explore use of MEG (magnetoencephalography)-multivariate statistical learning analysis in identifying the neural features for differential PTSD/mTBI characterisation. Resting state MEG-derived regional neural activity and coherence (or functional connectivity) across seven canonical neural oscillation frequencies (delta to high gamma) were used. The selected features were consistent and largely confirmatory with previously established neurophysiological markers for the two disorders. For regional power from theta, alpha and high gamma bands, the amygdala, hippocampus and temporal areas were identified. In line with regional activity, additional connections within the occipital, parietal and temporal regions were selected across a number of frequency bands. This study is the first to employ MEG-derived neural features to reliably and differentially stratify the two disorders in a multi-group context. The features from alpha and beta bands exhibited the best classification performance, even in cases where distinction by concussion symptom profiles alone were extremely difficult. We demonstrate the potential of using 'invisible' neural indices of brain functioning to understand and differentiate these debilitating conditions.
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14
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Allen CM, Halsey L, Topcu G, Rier L, Gascoyne LE, Scadding JW, Furlong PL, Dunkley BT, das Nair R, Brookes MJ, Evangelou N. Magnetoencephalography abnormalities in adult mild traumatic brain injury: A systematic review. Neuroimage Clin 2021; 31:102697. [PMID: 34010785 PMCID: PMC8141472 DOI: 10.1016/j.nicl.2021.102697] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2021] [Revised: 04/28/2021] [Accepted: 05/06/2021] [Indexed: 12/30/2022]
Abstract
BACKGROUND The global incidence of traumatic brain injuries is rising, with at least 80% being classified as mild. These mild injuries are not visible on routine clinical imaging. The potential clinical role of a specific imaging biomarker be it diagnostic, prognostic or directing and monitoring progress of personalised treatment and rehabilitation has driven the exploration of several new neuroimaging modalities. This systematic review examined the evidence for magnetoencephalography (MEG) to provide an imaging biomarker in mild traumatic brain injury (mTBI). METHODS Our review was prospectively registered on PROSPERO: CRD42019151387. We searched EMBASE, MEDLINE, trial registers, PsycINFO, Cochrane Library and conference abstracts and identified 37 papers describing MEG changes in mTBI eligible for inclusion. Since meta-analysis was not possible, based on the heterogeneity of reported outcomes, we provide a narrative synthesis of results. RESULTS The two most promising MEG biomarkers are excess resting state low frequency power, and widespread connectivity changes in all frequency bands. These may represent biomarkers with potential for diagnostic application, which reflect time sensitive changes, or may be capable of offering clinically relevant prognostic information. In addition, the rich data that MEG produces are well-suited to new methods of machine learning analysis, which is now being actively explored. INTERPRETATION MEG reveals several promising biomarkers, in the absence of structural abnormalities demonstrable with either computerised tomography or magnetic resonance imaging. This review has not identified sufficient evidence to support routine clinical use of MEG in mTBI currently. However, verifying MEG's potential would help meet an urgent clinical need within civilian, sports and military medicine.
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Affiliation(s)
- Christopher M Allen
- Mental Health and Clinical Neurosciences Academic Unit, School of Medicine, University of Nottingham, Queen's Medical Centre, Nottingham NG7 2UH, United Kingdom.
| | - Lloyd Halsey
- Mental Health and Clinical Neurosciences Academic Unit, School of Medicine, University of Nottingham, Queen's Medical Centre, Nottingham NG7 2UH, United Kingdom
| | - Gogem Topcu
- Mental Health and Clinical Neurosciences Academic Unit, School of Medicine, University of Nottingham, Jubilee Campus, Nottingham NG8 1BB, United Kingdom
| | - Lukas Rier
- Sir Peter Mansfield Imaging Centre, School of Physics & Astronomy, University of Nottingham, University Park, Nottingham NG7 2RD, United Kingdom
| | - Lauren E Gascoyne
- Sir Peter Mansfield Imaging Centre, School of Physics & Astronomy, University of Nottingham, University Park, Nottingham NG7 2RD, United Kingdom
| | - John W Scadding
- National Hospital for Neurology and Neurosurgery, Queen Square, London WC1N 3BG, United Kingdom
| | - Paul L Furlong
- College of Health and Life Sciences, Institute of Health and Neurodevelopment, Aston University, The Aston Triangle, Birmingham B4 7ET, United Kingdom
| | - Benjamin T Dunkley
- Department of Medical Imaging, University of Toronto. 263 McCaul Street, Toronto M5T 1W7, Canada
| | - Roshan das Nair
- Mental Health and Clinical Neurosciences Academic Unit, School of Medicine, University of Nottingham, Jubilee Campus, Nottingham NG8 1BB, United Kingdom
| | - Matthew J Brookes
- Sir Peter Mansfield Imaging Centre, School of Physics & Astronomy, University of Nottingham, University Park, Nottingham NG7 2RD, United Kingdom
| | - Nikos Evangelou
- Mental Health and Clinical Neurosciences Academic Unit, School of Medicine, University of Nottingham, Queen's Medical Centre, Nottingham NG7 2UH, United Kingdom
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15
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Huang MX, Huang CW, Harrington DL, Nichols S, Robb-Swan A, Angeles-Quinto A, Le L, Rimmele C, Drake A, Song T, Huang JW, Clifford R, Ji Z, Cheng CK, Lerman I, Yurgil KA, Lee RR, Baker DG. Marked Increases in Resting-State MEG Gamma-Band Activity in Combat-Related Mild Traumatic Brain Injury. Cereb Cortex 2021; 30:283-295. [PMID: 31041986 DOI: 10.1093/cercor/bhz087] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2019] [Revised: 03/29/2019] [Accepted: 04/01/2019] [Indexed: 01/08/2023] Open
Abstract
Combat-related mild traumatic brain injury (mTBI) is a leading cause of sustained impairments in military service members and veterans. Recent animal studies show that GABA-ergic parvalbumin-positive interneurons are susceptible to brain injury, with damage causing abnormal increases in spontaneous gamma-band (30-80 Hz) activity. We investigated spontaneous gamma activity in individuals with mTBI using high-resolution resting-state magnetoencephalography source imaging. Participants included 25 symptomatic individuals with chronic combat-related blast mTBI and 35 healthy controls with similar combat experiences. Compared with controls, gamma activity was markedly elevated in mTBI participants throughout frontal, parietal, temporal, and occipital cortices, whereas gamma activity was reduced in ventromedial prefrontal cortex. Across groups, greater gamma activity correlated with poorer performances on tests of executive functioning and visuospatial processing. Many neurocognitive associations, however, were partly driven by the higher incidence of mTBI participants with both higher gamma activity and poorer cognition, suggesting that expansive upregulation of gamma has negative repercussions for cognition particularly in mTBI. This is the first human study to demonstrate abnormal resting-state gamma activity in mTBI. These novel findings suggest the possibility that abnormal gamma activities may be a proxy for GABA-ergic interneuron dysfunction and a promising neuroimaging marker of insidious mild head injuries.
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Affiliation(s)
- Ming-Xiong Huang
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA.,Department of Radiology, University of California, San Diego, CA, USA
| | - Charles W Huang
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Deborah L Harrington
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA.,Department of Radiology, University of California, San Diego, CA, USA
| | - Sharon Nichols
- Department of Neuroscience, University of California, San Diego, CA, USA
| | - Ashley Robb-Swan
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA.,Department of Radiology, University of California, San Diego, CA, USA
| | - Annemarie Angeles-Quinto
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA.,Department of Radiology, University of California, San Diego, CA, USA
| | - Lu Le
- ASPIRE Center, VASDHS Residential Rehabilitation Treatment Program, San Diego, CA, USA
| | - Carl Rimmele
- ASPIRE Center, VASDHS Residential Rehabilitation Treatment Program, San Diego, CA, USA
| | - Angela Drake
- Cedar Sinai Medical Group Chronic Pain Program, Beverly Hills, CA, USA
| | - Tao Song
- Department of Radiology, University of California, San Diego, CA, USA
| | - Jeffrey W Huang
- Department of Computer Science, Columbia University, New York, NY, USA
| | - Royce Clifford
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA.,Department of Psychiatry, University of California, San Diego, CA, USA.,VA Center of Excellence for Stress and Mental Health, San Diego, CA, USA
| | - Zhengwei Ji
- Department of Radiology, University of California, San Diego, CA, USA
| | - Chung-Kuan Cheng
- Department of Computer Science and Engineering, University of California, San Diego, CA, USA
| | - Imanuel Lerman
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA
| | - Kate A Yurgil
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA.,VA Center of Excellence for Stress and Mental Health, San Diego, CA, USA.,Department of Psychological Sciences, Loyola University, New Orleans, LA, USA
| | - Roland R Lee
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA.,Department of Radiology, University of California, San Diego, CA, USA
| | - Dewleen G Baker
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA.,Department of Psychiatry, University of California, San Diego, CA, USA.,VA Center of Excellence for Stress and Mental Health, San Diego, CA, USA
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16
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Safar K, Zhang J, Emami Z, Gharehgazlou A, Ibrahim G, Dunkley BT. Mild traumatic brain injury is associated with dysregulated neural network functioning in children and adolescents. Brain Commun 2021; 3:fcab044. [PMID: 34095832 PMCID: PMC8176148 DOI: 10.1093/braincomms/fcab044] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2020] [Revised: 12/10/2020] [Accepted: 01/04/2021] [Indexed: 11/23/2022] Open
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.
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Affiliation(s)
- Kristina Safar
- Department of Diagnostic Imaging, Hospital for Sick Children, Toronto, ON, Canada M5G 0A4.,Neurosciences & Mental Health, SickKids Research Institute, Toronto, ON, Canada M5G 0A4
| | - Jing Zhang
- Department of Diagnostic Imaging, Hospital for Sick Children, Toronto, ON, Canada M5G 0A4.,Neurosciences & Mental Health, SickKids Research Institute, Toronto, ON, Canada M5G 0A4
| | - Zahra Emami
- Department of Diagnostic Imaging, Hospital for Sick Children, Toronto, ON, Canada M5G 0A4.,Neurosciences & Mental Health, SickKids Research Institute, Toronto, ON, Canada M5G 0A4
| | - Avideh Gharehgazlou
- Department of Diagnostic Imaging, Hospital for Sick Children, Toronto, ON, Canada M5G 0A4.,Neurosciences & Mental Health, SickKids Research Institute, Toronto, ON, Canada M5G 0A4.,Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto, ON, Canada M5S 1A8
| | - George Ibrahim
- Department of Diagnostic Imaging, Hospital for Sick Children, Toronto, ON, Canada M5G 0A4.,Neurosciences & Mental Health, SickKids Research Institute, Toronto, ON, Canada M5G 0A4.,Department of Surgery, University of Toronto, Toronto, ON, Canada M5T 1P5.,Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, ON, M5S 3G9 Canada
| | - Benjamin T Dunkley
- Department of Diagnostic Imaging, Hospital for Sick Children, Toronto, ON, Canada M5G 0A4.,Neurosciences & Mental Health, SickKids Research Institute, Toronto, ON, Canada M5G 0A4.,Department of Medical Imaging, University of Toronto, Toronto, ON, Canada M5T 1W7
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17
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Hämäläinen M, Huang M, Bowyer SM. Magnetoencephalography Signal Processing, Forward Modeling, Magnetoencephalography Inverse Source Imaging, and Coherence Analysis. Neuroimaging Clin N Am 2021; 30:125-143. [PMID: 32336402 DOI: 10.1016/j.nic.2020.02.001] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Magnetoencephalography (MEG) is a noninvasive functional imaging technique for the brain. MEG directly measures the magnetic signal due to neuronal activation in gray matter with high spatial localization accuracy. The first part of this article covers the overall concepts of MEG and the forward and inverse modeling techniques. It is followed by examples of analyzing evoked and resting-state MEG signals using a high-resolution MEG source imaging technique. Next, different techniques for connectivity and network analysis are reviewed with examples showing connectivity estimates from resting-state and epileptic activity.
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Affiliation(s)
- Matti Hämäläinen
- Department of Radiology, Athinoula A. Martinos Center, Massachusetts General Hospital, 149 13th Street, Charlestown, MA 02129, USA; Harvard Medical School, Boston, MA, USA
| | - Mingxiong Huang
- Department of Radiology, UCSD Radiology Imaging Lab, University of California, San Diego, 3510 Dunhill Street, San Diego, CA 92121, USA
| | - Susan M Bowyer
- Department of Neurology, MEG Lab, Henry Ford Hospital, 2799 West Grand Boulevard, CFP 079, Detroit, MI 48202, USA; Wayne State University School of Medicine, Detroit, MI, USA; Department of Physics, Oakland University, Rochester, MI, USA.
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18
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Kim JA, Davis KD. Magnetoencephalography: physics, techniques, and applications in the basic and clinical neurosciences. J Neurophysiol 2021; 125:938-956. [PMID: 33567968 DOI: 10.1152/jn.00530.2020] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Magnetoencephalography (MEG) is a technique used to measure the magnetic fields generated from neuronal activity in the brain. MEG has a high temporal resolution on the order of milliseconds and provides a more direct measure of brain activity when compared with hemodynamic-based neuroimaging methods such as magnetic resonance imaging and positron emission tomography. The current review focuses on basic features of MEG such as the instrumentation and the physics that are integral to the signals that can be measured, and the principles of source localization techniques, particularly the physics of beamforming and the techniques that are used to localize the signal of interest. In addition, we review several metrics that can be used to assess functional coupling in MEG and describe the advantages and disadvantages of each approach. Lastly, we discuss the current and future applications of MEG.
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Affiliation(s)
- Junseok A Kim
- Division of Brain, Imaging and Behaviour, Krembil Brain Institute, Krembil Research Institute, University Health Network, Toronto, Ontario, Canada.,Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Karen D Davis
- Division of Brain, Imaging and Behaviour, Krembil Brain Institute, Krembil Research Institute, University Health Network, Toronto, Ontario, Canada.,Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada.,Department of Surgery, University of Toronto, Toronto, Ontario, Canada
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19
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A New Recognition Method for the Auditory Evoked Magnetic Fields. COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE 2021; 2021:6645270. [PMID: 33628215 PMCID: PMC7892250 DOI: 10.1155/2021/6645270] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/14/2020] [Revised: 01/15/2021] [Accepted: 01/21/2021] [Indexed: 11/17/2022]
Abstract
Magnetoencephalography (MEG) is a persuasive tool to study the human brain in physiology and psychology. It can be employed to obtain the inference of change between the external environment and the internal psychology, which requires us to recognize different single trial event-related magnetic fields (ERFs) originated from different functional areas of the brain. Current recognition methods for the single trial data are mainly used for event-related potentials (ERPs) in the electroencephalography (EEG). Although the MEG shares the same signal sources with the EEG, much less interference from the other brain tissues may give the MEG an edge in recognition of the ERFs. In this work, we propose a new recognition method for the single trial auditory evoked magnetic fields (AEFs) through enhancing the signal. We find that the signal strength of the single trial AEFs is concentrated in the primary auditory cortex of the temporal lobe, which can be clearly displayed in the 2D images. These 2D images are then recognized by an artificial neural network (ANN) with 100% accuracy, which realizes the automatic recognition for the single trial AEFs. The method not only may be combined with the source estimation algorithm to improve its accuracy but also paves the way for the implementation of the brain-computer interface (BCI) with the MEG.
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20
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Magnetoencephalography in the Detection and Characterization of Brain Abnormalities Associated with Traumatic Brain Injury: A Comprehensive Review. Med Sci (Basel) 2021; 9:medsci9010007. [PMID: 33557219 PMCID: PMC7930962 DOI: 10.3390/medsci9010007] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2020] [Revised: 01/08/2021] [Accepted: 01/29/2021] [Indexed: 01/18/2023] Open
Abstract
Magnetoencephalography (MEG) is a functional brain imaging technique with high temporal resolution compared with techniques that rely on metabolic coupling. MEG has an important role in traumatic brain injury (TBI) research, especially in mild TBI, which may not have detectable features in conventional, anatomical imaging techniques. This review addresses the original research articles to date that have reported on the use of MEG in TBI. Specifically, the included studies have demonstrated the utility of MEG in the detection of TBI, characterization of brain connectivity abnormalities associated with TBI, correlation of brain signals with post-concussive symptoms, differentiation of TBI from post-traumatic stress disorder, and monitoring the response to TBI treatments. Although presently the utility of MEG is mostly limited to research in TBI, a clinical role for MEG in TBI may become evident with further investigation.
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21
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Huang MX, Huang CW, Harrington DL, Robb-Swan A, Angeles-Quinto A, Nichols S, Huang JW, Le L, Rimmele C, Matthews S, Drake A, Song T, Ji Z, Cheng CK, Shen Q, Foote E, Lerman I, Yurgil KA, Hansen HB, Naviaux RK, Dynes R, Baker DG, Lee RR. Resting-state magnetoencephalography source magnitude imaging with deep-learning neural network for classification of symptomatic combat-related mild traumatic brain injury. Hum Brain Mapp 2021; 42:1987-2004. [PMID: 33449442 PMCID: PMC8046098 DOI: 10.1002/hbm.25340] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2020] [Revised: 11/16/2020] [Accepted: 12/23/2020] [Indexed: 12/20/2022] Open
Abstract
Combat‐related mild traumatic brain injury (cmTBI) is a leading cause of sustained physical, cognitive, emotional, and behavioral disabilities in Veterans and active‐duty military personnel. Accurate diagnosis of cmTBI is challenging since the symptom spectrum is broad and conventional neuroimaging techniques are insensitive to the underlying neuropathology. The present study developed a novel deep‐learning neural network method, 3D‐MEGNET, and applied it to resting‐state magnetoencephalography (rs‐MEG) source‐magnitude imaging data from 59 symptomatic cmTBI individuals and 42 combat‐deployed healthy controls (HCs). Analytic models of individual frequency bands and all bands together were tested. The All‐frequency model, which combined delta‐theta (1–7 Hz), alpha (8–12 Hz), beta (15–30 Hz), and gamma (30–80 Hz) frequency bands, outperformed models based on individual bands. The optimized 3D‐MEGNET method distinguished cmTBI individuals from HCs with excellent sensitivity (99.9 ± 0.38%) and specificity (98.9 ± 1.54%). Receiver‐operator‐characteristic curve analysis showed that diagnostic accuracy was 0.99. The gamma and delta‐theta band models outperformed alpha and beta band models. Among cmTBI individuals, but not controls, hyper delta‐theta and gamma‐band activity correlated with lower performance on neuropsychological tests, whereas hypo alpha and beta‐band activity also correlated with lower neuropsychological test performance. This study provides an integrated framework for condensing large source‐imaging variable sets into optimal combinations of regions and frequencies with high diagnostic accuracy and cognitive relevance in cmTBI. The all‐frequency model offered more discriminative power than each frequency‐band model alone. This approach offers an effective path for optimal characterization of behaviorally relevant neuroimaging features in neurological and psychiatric disorders.
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Affiliation(s)
- Ming-Xiong Huang
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, California, USA.,Department of Radiology, University of California, San Diego, California, USA
| | - Charles W Huang
- Department of Bioengineering, Stanford University, Stanford, California, USA
| | - Deborah L Harrington
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, California, USA.,Department of Radiology, University of California, San Diego, California, USA
| | - Ashley Robb-Swan
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, California, USA.,Department of Radiology, University of California, San Diego, California, USA
| | - Annemarie Angeles-Quinto
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, California, USA.,Department of Radiology, University of California, San Diego, California, USA
| | - Sharon Nichols
- Department of Neurosciences, University of California, San Diego, California, USA
| | - Jeffrey W Huang
- Department of Computer Science, Columbia University, New York, New York, USA
| | - Lu Le
- ASPIRE Center, VASDHS Residential Rehabilitation Treatment Program, San Diego, California, USA
| | - Carl Rimmele
- ASPIRE Center, VASDHS Residential Rehabilitation Treatment Program, San Diego, California, USA
| | - Scott Matthews
- ASPIRE Center, VASDHS Residential Rehabilitation Treatment Program, San Diego, California, USA
| | - Angela Drake
- Cedar Sinai Medical Group Chronic Pain Program, Beverly Hills, California, USA
| | - Tao Song
- Department of Radiology, University of California, San Diego, California, USA
| | - Zhengwei Ji
- Department of Radiology, University of California, San Diego, California, USA
| | - Chung-Kuan Cheng
- Department of Computer Science and Engineering, University of California, San Diego, California, USA
| | - Qian Shen
- Department of Radiology, University of California, San Diego, California, USA
| | - Ericka Foote
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, California, USA
| | - Imanuel Lerman
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, California, USA
| | - Kate A Yurgil
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, California, USA.,Department of Psychological Sciences, Loyola University New Orleans, Louisiana, USA
| | - Hayden B Hansen
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, California, USA
| | - Robert K Naviaux
- Department of Medicine, University of California, San Diego, California, USA.,Department of Pediatrics, University of California, San Diego, California, USA.,Department of Pathology, University of California, San Diego, California, USA
| | - Robert Dynes
- Department of Physics, University of California, San Diego, California, USA
| | - Dewleen G Baker
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, California, USA.,VA Center of Excellence for Stress and Mental Health, San Diego, California, USA.,Department of Psychiatry, University of California, San Diego, California, USA
| | - Roland R Lee
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, California, USA.,Department of Radiology, University of California, San Diego, California, USA
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22
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Abstract
Due to the growing number of chronic traumatic encephalopathy (CTE) cases in the military and contact sports, defining the cellular and molecular substrate of this disorder is crucial. Most classic neuropathological investigations describe cortical tau and, to a lesser extent, amyloid lesions, which may underlie the clinical sequela associated with CTE. The application of modern molecular biologic technology to postmortem human brain tissue has made it possible to evaluate the genetic signature of specific neuronal phenotypes at different stages of CTE pathology. Most recently, molecular pathobiology has been used in the field of CTE, with an emphasis on the cholinergic neurons located within the nucleus basalis of Meynert, which develop tau pathology and are associated with cognitive dysfunction similar to that found in Alzheimer's disease (AD). Quantitative findings derived from single-cell transcript investigations provide clues to our understanding of the selective vulnerability of neurons containing AD-like tau pathology at different stages of CTE. Since human tissue-based studies provide a gold standard for the field of CTE, continued molecular pathological studies are needed to reveal novel drug targets for the treatment of this disorder.
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23
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Januszko P, Gmaj B, Piotrowski T, Kopera M, Klimkiewicz A, Wnorowska A, Wołyńczyk-Gmaj D, Brower KJ, Wojnar M, Jakubczyk A. Delta resting-state functional connectivity in the cognitive control network as a prognostic factor for maintaining abstinence: An eLORETA preliminary study. Drug Alcohol Depend 2021; 218:108393. [PMID: 33158664 DOI: 10.1016/j.drugalcdep.2020.108393] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/23/2020] [Revised: 10/11/2020] [Accepted: 10/26/2020] [Indexed: 12/28/2022]
Abstract
BACKGROUND Cortical regions that support cognitive control are increasingly well recognized, but the functional mechanisms that promote such control over emotional and behavioral hyperreactivity to alcohol in recently abstinent alcohol-dependent patients are still insufficiently understood. This study aimed to identify neurophysiological biomarkers of maintaining abstinence in alcohol-dependent individuals after alcohol treatment by investigating the resting-state EEG-based functional connectivity in the cognitive control network (CCN). METHODS Lagged phase synchronization between CCN areas by means of eLORETA as well as the Barratt Impulsiveness Scale (BIS-11) and Beck Depression Inventory (BDI) were assessed in abstinent alcohol-dependent patients recruited from treatment centers. A preliminary prospective study design was used to classify participants into those who did and did not maintain abstinence during a follow-up period (median 12 months) after discharge from residential treatment. RESULTS Alcohol-dependent individuals, who maintained abstinence (N = 18), showed significantly increased lagged phase synchronization between the left dorsolateral prefrontal cortex (DLPFC) and the left posterior parietal cortex (IPL) as well as between the right anterior insula cortex/frontal operculum (IA/FO) and the right inferior frontal junction (IFJ) in the delta band compared to those who later relapsed (N = 16). Regression analysis showed that the increased left frontoparietal delta connectivity in the early period of abstinence significantly predicted maintaining abstinence over the ensuing 12 months. Furthermore, right frontoinsular delta connectivity correlated negatively with impulsivity and depression measures. CONCLUSIONS These results suggest that the increased delta resting-state functional connectivity in the CCN may be a promising neurophysiological predictor of maintaining abstinence in individuals with alcohol dependence.
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Affiliation(s)
- Piotr Januszko
- Department of Psychiatry, Medical University of Warsaw, Nowowiejska 27, 00-665 Warsaw, Poland
| | - Bartłomiej Gmaj
- Department of Psychiatry, Medical University of Warsaw, Nowowiejska 27, 00-665 Warsaw, Poland.
| | - Tadeusz Piotrowski
- Department of Psychiatry, Medical University of Warsaw, Nowowiejska 27, 00-665 Warsaw, Poland
| | - Maciej Kopera
- Department of Psychiatry, Medical University of Warsaw, Nowowiejska 27, 00-665 Warsaw, Poland
| | - Anna Klimkiewicz
- Department of Psychiatry, Medical University of Warsaw, Nowowiejska 27, 00-665 Warsaw, Poland
| | - Anna Wnorowska
- Department of Psychiatry, Medical University of Warsaw, Nowowiejska 27, 00-665 Warsaw, Poland
| | - Dorota Wołyńczyk-Gmaj
- Department of Psychiatry, Medical University of Warsaw, Nowowiejska 27, 00-665 Warsaw, Poland
| | - Kirk J Brower
- Department of Psychiatry, Addiction Center, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Marcin Wojnar
- Department of Psychiatry, Medical University of Warsaw, Nowowiejska 27, 00-665 Warsaw, Poland; Department of Psychiatry, Addiction Center, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Andrzej Jakubczyk
- Department of Psychiatry, Medical University of Warsaw, Nowowiejska 27, 00-665 Warsaw, Poland
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24
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Östberg A, Ledig C, Katila A, Maanpää HR, Posti JP, Takala R, Tallus J, Glocker B, Rueckert D, Tenovuo O. Volume Change in Frontal Cholinergic Structures After Traumatic Brain Injury and Cognitive Outcome. Front Neurol 2020; 11:832. [PMID: 32903569 PMCID: PMC7438550 DOI: 10.3389/fneur.2020.00832] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2020] [Accepted: 07/03/2020] [Indexed: 01/02/2023] Open
Abstract
The cholinergic nuclei in the basal forebrain innervate frontal cortical structures regulating attention. Our aim was to investigate if cognitive test results measuring attention relate to the longitudinal volume change of cholinergically innervated structures following traumatic brain injury (TBI). During the prospective, observational TBIcare project patients with all severities of TBI (n = 114) and controls with acute orthopedic injuries (n = 17) were recruited. Head MRI was obtained in both acute (mean 2 weeks post-injury) and late (mean 8 months) time points. T1-weighted 3D MR images were analyzed with an automatic segmentation method to evaluate longitudinal, structural brain volume change. The cognitive outcome was assessed with the Cambridge Neuropsychological Test Automated Battery (CANTAB). Analyses included 16 frontal cortical structures, of which four showed a significant correlation between post-traumatic volume change and the CANTAB test results. The strongest correlation was found between the volume loss of the supplementary motor cortex and motor screening task results (R-sq 0.16, p < 0.0001), where poorer test results correlated with greater atrophy. Of the measured sum structures, greater cortical gray matter atrophy rate showed a significant correlation with the poorer CANTAB test results. TBI caused volume loss of frontal cortical structures that are heavily innervated by cholinergic neurons is associated with neuropsychological test results measuring attention.
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Affiliation(s)
- Anna Östberg
- Division of Clinical Neurosciences, Turku Brain Injury Centre, Turku University Hospital, Turku, Finland.,Department of Neurology, Institute of Clinical Medicine, University of Turku, Turku, Finland.,Department of Neurosurgery, Neurocenter, Turku University Hospital, Turku, Finland
| | - Christian Ledig
- Department of Computing, Imperial College London, London, United Kingdom
| | - Ari Katila
- Department of Perioperative Services, Intensive Care and Pain Medicine, Turku University Hospital, Turku, Finland
| | - Henna-Riikka Maanpää
- Department of Neurology, Institute of Clinical Medicine, University of Turku, Turku, Finland.,Department of Neurosurgery, Neurocenter, Turku University Hospital, Turku, Finland
| | - Jussi P Posti
- Division of Clinical Neurosciences, Turku Brain Injury Centre, Turku University Hospital, Turku, Finland.,Department of Neurology, Institute of Clinical Medicine, University of Turku, Turku, Finland.,Department of Neurosurgery, Neurocenter, Turku University Hospital, Turku, Finland
| | - Riikka Takala
- Department of Perioperative Services, Intensive Care and Pain Medicine, Turku University Hospital, Turku, Finland
| | - Jussi Tallus
- Department of Neurology, Institute of Clinical Medicine, University of Turku, Turku, Finland
| | - Ben Glocker
- Department of Computing, Imperial College London, London, United Kingdom
| | - Daniel Rueckert
- Department of Computing, Imperial College London, London, United Kingdom
| | - Olli Tenovuo
- Division of Clinical Neurosciences, Turku Brain Injury Centre, Turku University Hospital, Turku, Finland.,Department of Neurology, Institute of Clinical Medicine, University of Turku, Turku, Finland
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25
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Huang MX, Nichols S, Robb-Swan A, Angeles-Quinto A, Harrington DL, Drake A, Huang CW, Song T, Diwakar M, Risbrough VB, Matthews S, Clifford R, Cheng CK, Huang JW, Sinha A, Yurgil KA, Ji Z, Lerman I, Lee RR, Baker DG. MEG Working Memory N-Back Task Reveals Functional Deficits in Combat-Related Mild Traumatic Brain Injury. Cereb Cortex 2020; 29:1953-1968. [PMID: 29668852 DOI: 10.1093/cercor/bhy075] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2017] [Revised: 03/11/2018] [Accepted: 03/13/2018] [Indexed: 12/24/2022] Open
Abstract
Combat-related mild traumatic brain injury (mTBI) is a leading cause of sustained cognitive impairment in military service members and Veterans. However, the mechanism of persistent cognitive deficits including working memory (WM) dysfunction is not fully understood in mTBI. Few studies of WM deficits in mTBI have taken advantage of the temporal and frequency resolution afforded by electromagnetic measurements. Using magnetoencephalography (MEG) and an N-back WM task, we investigated functional abnormalities in combat-related mTBI. Study participants included 25 symptomatic active-duty service members or Veterans with combat-related mTBI and 20 healthy controls with similar combat experiences. MEG source-magnitude images were obtained for alpha (8-12 Hz), beta (15-30 Hz), gamma (30-90 Hz), and low-frequency (1-7 Hz) bands. Compared with healthy combat controls, mTBI participants showed increased MEG signals across frequency bands in frontal pole (FP), ventromedial prefrontal cortex, orbitofrontal cortex (OFC), and anterior dorsolateral prefrontal cortex (dlPFC), but decreased MEG signals in anterior cingulate cortex. Hyperactivations in FP, OFC, and anterior dlPFC were associated with slower reaction times. MEG activations in lateral FP also negatively correlated with performance on tests of letter sequencing, verbal fluency, and digit symbol coding. The profound hyperactivations from FP suggest that FP is particularly vulnerable to combat-related mTBI.
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Affiliation(s)
- Ming-Xiong Huang
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA.,Department of Radiology, University of California, San Diego, CA, USA
| | - Sharon Nichols
- Department of Neuroscience, University of California, San Diego, CA, USA
| | - Ashley Robb-Swan
- Department of Radiology, University of California, San Diego, CA, USA
| | | | - Deborah L Harrington
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA.,Department of Radiology, University of California, San Diego, CA, USA
| | - Angela Drake
- Cedar Sinai Medical Group Chronic Pain Program, Beverly Hills, CA, USA
| | - Charles W Huang
- Department of Bioengineering, University of California, San Diego, CA, USA
| | - Tao Song
- Department of Radiology, University of California, San Diego, CA, USA
| | - Mithun Diwakar
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA
| | - Victoria B Risbrough
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA.,Department of Psychiatry, University of California, San Diego, CA, USA.,VA Center of Excellence for Stress and Mental Health, San Diego, CA, USA
| | - Scott Matthews
- ASPIRE Center, VASDHS Residential Rehabilitation Treatment Program, San Diego, CA, USA
| | - Royce Clifford
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA.,Department of Psychiatry, University of California, San Diego, CA, USA.,VA Center of Excellence for Stress and Mental Health, San Diego, CA, USA
| | - Chung-Kuan Cheng
- Department of Computer Science and Engineering, University of California, San Diego, CA, USA
| | | | - Anusha Sinha
- California Institute of Technology, Pasadena, CA, USA
| | - Kate A Yurgil
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA.,VA Center of Excellence for Stress and Mental Health, San Diego, CA, USA.,Loyola University New Orleans, LA, USA
| | - Zhengwei Ji
- Department of Radiology, University of California, San Diego, CA, USA
| | - Imanuel Lerman
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA
| | - Roland R Lee
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA.,Department of Radiology, University of California, San Diego, CA, USA
| | - Dewleen G Baker
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA.,Department of Psychiatry, University of California, San Diego, CA, USA.,VA Center of Excellence for Stress and Mental Health, San Diego, CA, USA
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26
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Hill RM, Boto E, Rea M, Holmes N, Leggett J, Coles LA, Papastavrou M, Everton SK, Hunt BAE, Sims D, Osborne J, Shah V, Bowtell R, Brookes MJ. Multi-channel whole-head OPM-MEG: Helmet design and a comparison with a conventional system. Neuroimage 2020; 219:116995. [PMID: 32480036 PMCID: PMC8274815 DOI: 10.1016/j.neuroimage.2020.116995] [Citation(s) in RCA: 86] [Impact Index Per Article: 21.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2020] [Revised: 05/20/2020] [Accepted: 05/23/2020] [Indexed: 12/18/2022] Open
Abstract
Magnetoencephalography (MEG) is a powerful technique for functional
neuroimaging, offering a non-invasive window on brain electrophysiology. MEG
systems have traditionally been based on cryogenic sensors which detect the
small extracranial magnetic fields generated by synchronised current in neuronal
assemblies, however, such systems have fundamental limitations. In recent years,
non-cryogenic quantum-enabled sensors, called optically-pumped magnetometers
(OPMs), in combination with novel techniques for accurate background magnetic
field control, have promised to lift those restrictions offering an adaptable,
motion-robust MEG system, with improved data quality, at reduced cost. However,
OPM-MEG remains a nascent technology, and whilst viable systems exist, most
employ small numbers of sensors sited above targeted brain regions. Here,
building on previous work, we construct a wearable OPM-MEG system with
‘whole-head’ coverage based upon commercially available OPMs, and
test its capabilities to measure alpha, beta and gamma oscillations. We design
two methods for OPM mounting; a flexible (EEG-like) cap and rigid
(additively-manufactured) helmet. Whilst both designs allow for high quality
data to be collected, we argue that the rigid helmet offers a more robust option
with significant advantages for reconstruction of field data into 3D images of
changes in neuronal current. Using repeat measurements in two participants, we
show signal detection for our device to be highly robust. Moreover, via
application of source-space modelling, we show that, despite having 5 times
fewer sensors, our system exhibits comparable performance to an established
cryogenic MEG device. While significant challenges still remain, these
developments provide further evidence that OPM-MEG is likely to facilitate a
step change for functional neuroimaging.
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Affiliation(s)
- Ryan M Hill
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK.
| | - Elena Boto
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK
| | - Molly Rea
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK
| | - Niall Holmes
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK
| | - James Leggett
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK
| | - Laurence A Coles
- Added Scientific Limited, No 4, The Isaac Newton Centre, Nottingham Science Park, Nottingham, NG72RH, UK
| | - Manolis Papastavrou
- Added Scientific Limited, No 4, The Isaac Newton Centre, Nottingham Science Park, Nottingham, NG72RH, UK
| | - Sarah K Everton
- Added Scientific Limited, No 4, The Isaac Newton Centre, Nottingham Science Park, Nottingham, NG72RH, UK
| | - Benjamin A E Hunt
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK
| | - Dominic Sims
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK
| | - James Osborne
- QuSpin Inc. 331 South 104th Street, Suite 130, Louisville, CO, 80027, USA
| | - Vishal Shah
- QuSpin Inc. 331 South 104th Street, Suite 130, Louisville, CO, 80027, USA
| | - Richard Bowtell
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK
| | - Matthew J Brookes
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK
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27
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Huang M, Lewine JD, Lee RR. Magnetoencephalography for Mild Traumatic Brain Injury and Posttraumatic Stress Disorder. Neuroimaging Clin N Am 2020; 30:175-192. [DOI: 10.1016/j.nic.2020.02.003] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
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28
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Antonakakis M, Dimitriadis SI, Zervakis M, Papanicolaou AC, Zouridakis G. Aberrant Whole-Brain Transitions and Dynamics of Spontaneous Network Microstates in Mild Traumatic Brain Injury. Front Comput Neurosci 2020; 13:90. [PMID: 32009921 PMCID: PMC6974679 DOI: 10.3389/fncom.2019.00090] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2019] [Accepted: 12/19/2019] [Indexed: 12/18/2022] Open
Abstract
Dynamic Functional Connectivity (DFC) analysis is a promising approach for the characterization of brain electrophysiological activity. In this study, we investigated abnormal alterations due to mild Traumatic Brain Injury (mTBI) using DFC of the source reconstructed magnetoencephalographic (MEG) resting-state recordings. Brain activity in several well-known frequency bands was first reconstructed using beamforming of the MEG data to determine ninety anatomical brain regions of interest. A DFC graph was formulated using the imaginary part of phase-locking values, which were obtained from 30 mTBI patients and 50 healthy controls (HC). Subsequently, we estimated normalized Laplacian transformations of individual, statistically and topologically filtered quasi-static graphs. The corresponding eigenvalues of each node synchronization were then computed and through the neural-gas algorithm, we quantized the evolution of the eigenvalues resulting in distinct network microstates (NMstates). The discrimination level between the two groups was assessed using an iterative cross-validation classification scheme with features either the NMstates in each frequency band, or the combination of the so-called chronnectomics (flexibility index, occupancy time of NMstate, and Dwell time) with the complexity index over the evolution of the NMstates across all frequency bands. Classification performance based on chronnectomics showed 80% accuracy, 99% sensitivity, and 49% specificity. However, performance was much higher (accuracy: 91-97%, sensitivity: 100%, and specificity: 77-93%) when focusing on the microstates. Exploring the mean node degree within and between brain anatomical networks (default mode network, frontoparietal, occipital, cingulo-opercular, and sensorimotor), a reduced pattern occurred from lower to higher frequency bands, with statistically significant stronger degrees for the HC than the mTBI group. A higher entropic profile on the temporal evolution of the modularity index was observed for both NMstates for the mTBI group across frequencies. A significant difference in the flexibility index was observed between the two groups for the β frequency band. The latter finding may support a central role of the thalamus impairment in mTBI. The current study considers a complete set of frequency-dependent connectomic markers of mTBI-caused alterations in brain connectivity that potentially could serve as markers to assess the return of an injured subject back to normality.
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Affiliation(s)
- Marios Antonakakis
- Institute for Biomagnetism and Biosignal Analysis, University of Muenster, Muenster, Germany
- Digital Image and Signal Processing Laboratory, School of Electronic and Computer Engineering, Technical University of Crete, Chania, Greece
- Neuroinformatics Group, Cardiff University Brain Research Imaging Center (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom
| | - Stavros I. Dimitriadis
- Institute of Psychological Medicine and Clinical Neurosciences, Cardiff University School of Medicine, Cardiff, United Kingdom
- Cardiff University Brain Research Imaging Center (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom
- School of Psychology, Cardiff University, Cardiff, United Kingdom
- Neuroscience and Mental Health Research Institute, Cardiff University, Cardiff, United Kingdom
- MRC Centre for Neuropsychiatric Genetics and Genomics, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - Michalis Zervakis
- Digital Image and Signal Processing Laboratory, School of Electronic and Computer Engineering, Technical University of Crete, Chania, Greece
| | - Andrew C. Papanicolaou
- Departments of Pediatrics, and Anatomy and Neurobiology, Neuroscience Institute, University of Tennessee Health Science Center, Le Bonheur Children's Hospital, Memphis, TN, United States
| | - George Zouridakis
- Biomedical Imaging Lab, Departments of Engineering Technology, Computer Science, Biomedical Engineering, and Electrical and Computer Engineering, University of Houston, Houston, TX, United States
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Huang MX, Robb Swan A, Angeles Quinto A, Huang JW, De-la-Garza BG, Huang CW, Hesselink JR, Bigler ED, Wilde EA, Max JE. Resting-State Magnetoencephalography Source Imaging Pilot Study in Children with Mild Traumatic Brain Injury. J Neurotrauma 2019; 37:994-1001. [PMID: 31724480 DOI: 10.1089/neu.2019.6417] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Mild traumatic brain injury (mTBI) accounts for the vast majority of all pediatric TBI. An important minority of children who have suffered an mTBI have enduring cognitive and emotional symptoms. However, the mechanisms of chronic symptoms in children with pediatric mTBI are not fully understood. This is in part due to the limited sensitivity of conventional neuroimaging technologies. The present study examined resting-state magnetoencephalography (rs-MEG) source images in 12 children who had mTBI and 12 age-matched control children. The rs-MEG exams were performed in children with mTBI 6 months after injury when they reported no clinically significant post-injury psychiatric changes and few if any somatic sensorimotor symptoms but did report cognitive symptoms. MEG source magnitude images were obtained for different frequency bands in alpha (8-12 Hz), beta (15-30 Hz), gamma (30-90 Hz), and low-frequency (1-7 Hz) bands. In contrast to the control participants, rs-MEG source imaging in the children with mTBI showed: 1) hyperactivity from the bilateral insular cortices in alpha, beta, and low-frequency bands, from the left amygdala in alpha band, and from the left precuneus in beta band; 2) hypoactivity from the bilateral dorsolateral prefrontal cortices (dlPFC) in alpha and beta bands, from the ventromedial prefrontal cortex (vmPFC) in beta band, from the ventrolateral prefrontal cortex (vlPFC) in gamma band, from the anterior cingulate cortex (ACC) in alpha band, and from the right precuneus in alpha band. The present study showed that MEG source imaging technique revealed abnormalities in the resting-state electromagnetic signals from the children with mTBI.
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Affiliation(s)
- Ming-Xiong Huang
- Department of Radiology, University of California, San Diego, California.,Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, California
| | - Ashley Robb Swan
- Department of Radiology, University of California, San Diego, California.,Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, California
| | - Annemarie Angeles Quinto
- Department of Radiology, University of California, San Diego, California.,Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, California
| | - Jeffrey W Huang
- Department of Computer Sciences, Columbia University, New York, New York
| | | | - Charles W Huang
- Department of Bioengineering, Stanford University, Stanford, California
| | - John R Hesselink
- Department of Radiology, University of California, San Diego, California
| | - Erin D Bigler
- Department of Neurology, University of Utah, Salt Lake City, Utah
| | | | - Jeffrey E Max
- Department of Psychiatry, University of California, San Diego, California.,Department of Psychiatry, Rady Children's Hospital, San Diego, California
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30
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Brain Cholinergic Function and Response to Rivastigmine in Patients With Chronic Sequels of Traumatic Brain Injury: A PET Study. J Head Trauma Rehabil 2019; 33:25-32. [PMID: 28060207 DOI: 10.1097/htr.0000000000000279] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
OBJECTIVE To investigate quantitative positron emission tomography (PET) findings and to study whether the cholinergic function differs between respondents to cholinergic medication versus nonrespondents. SETTING Outpatient clinic and university PET imaging center. PARTICIPANTS We studied 17 subjects for more than 1 year after at least moderate traumatic brain injury. Ten of the subjects were respondents and 7 nonrespondents to cholinergic medication. DESIGN Cholinergic function was assessed with [methyl-C] N-methylpiperidyl-4-acetate-PET (C-MP4A-PET), which reflects the activity of the acetylcholinesterase (AChE) enzyme. The subjects were PET scanned twice: without medication and after a 4-week treatment with rivastigmine 1.5 mg twice a day. MEASURES Regional cerebral AChE activity was measured with PET. RESULTS At baseline Statistical Parametric Mapping analyses showed significantly lower AChE activity in respondents bilaterally in the frontal cortex as compared with nonrespondents. Region of interest (ROI) analysis revealed that the difference was most pronounced in the lateral frontal cortex (-9.4%, P = .034) and anterior cingulate (-6.0%, P = .049). After rivastigmine treatment, AChE activity was notably lower throughout the cortex in both respondents and nonrespondents, without significant differences between them. CONCLUSION Our study suggests that frontal cholinergic dysfunction is associated with the clinical response to cholinergic stimulation in patients with traumatic brain injury.
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31
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Lewine JD, Plis S, Ulloa A, Williams C, Spitz M, Foley J, Paulson K, Davis J, Bangera N, Snyder T, Weaver L. Quantitative EEG Biomarkers for Mild Traumatic Brain Injury. J Clin Neurophysiol 2019; 36:298-305. [DOI: 10.1097/wnp.0000000000000588] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023] Open
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32
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Spadoni AD, Huang M, Simmons AN. Emerging Approaches to Neurocircuits in PTSD and TBI: Imaging the Interplay of Neural and Emotional Trauma. Curr Top Behav Neurosci 2019; 38:163-192. [PMID: 29285732 PMCID: PMC8896198 DOI: 10.1007/7854_2017_35] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Posttraumatic stress disorder (PTSD) and traumatic brain injury (TBI) commonly co-occur in general and military populations and have a number of overlapping symptoms. While research suggests that TBI is risk factor for PTSD and that PTSD may mediate TBI-related outcomes, the mechanisms of these relationships are not well understood. Neuroimaging may help elucidate patterns of neurocircuitry both specific and common to PTSD and TBI and thus help define the nature of their interaction, refine diagnostic classification, and may potentially yield opportunities for targeted treatments. In this review, we provide a summary of some of the most common and the most innovative neuroimaging approaches used to characterize the neural circuits associated with PTSD, TBI, and their comorbidity. We summarize the state of the science for each disorder and describe the few studies that have explicitly attempted to characterize the neural substrates of their shared and dissociable influence. While some promising targets in the medial frontal lobes exist, there is not currently a comprehensive understanding of the neurocircuitry mediating the interaction of PTSD and TBI. Future studies should exploit innovative neuroimaging approaches and longitudinal designs to specifically target the neural mechanisms driving PTSD-TBI-related outcomes.
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Affiliation(s)
- Andrea D Spadoni
- Research Service, VA San Diego Healthcare System, San Diego, CA, USA.
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA.
| | - Mingxiong Huang
- Radiology and Research Services, VA San Diego Healthcare System, San Diego, CA, USA
- Department of Radiology, University of California, San Diego, La Jolla, CA, USA
| | - Alan N Simmons
- Research Service, VA San Diego Healthcare System, San Diego, CA, USA
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
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33
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Kaltiainen H, Helle L, Liljeström M, Renvall H, Forss N. Theta-Band Oscillations as an Indicator of Mild Traumatic Brain Injury. Brain Topogr 2018; 31:1037-1046. [PMID: 30097835 PMCID: PMC6182433 DOI: 10.1007/s10548-018-0667-2] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2017] [Accepted: 07/28/2018] [Indexed: 11/30/2022]
Abstract
Mild traumatic brain injury (mTBI) patients continue to pose a diagnostic challenge due to their diverse symptoms without trauma-specific changes in structural imaging. We addressed here the possible early changes in spontaneous oscillatory brain activity after mTBI, and their feasibility as an indicator of injury in clinical evaluation. We recorded resting-state magnetoencephalography (MEG) data in both eyes-open and eyes-closed conditions from 26 patients (11 females and 15 males, aged 20–59) with mTBI 6 days–6 months after the injury, and compared their spontaneous oscillatory activity to corresponding data from 139 healthy controls. Twelve of the patients underwent a follow-up measurement at 6 months. Ten of all patients were without structural lesions in MRI. At single-subject level, aberrant 4–7 Hz (theta) band activity exceeding the + 2 SD limit of the healthy subjects was visible in 7 out of 26 patients; three out of the seven patients with abnormal theta activity were without any detectable lesions in MRI. Of the patients that participated in the follow-up measurements, five showed abnormal theta activity in the first recording, but only two in the second measurement. Our results suggest that aberrant theta-band oscillatory activity can provide an early objective sign of brain dysfunction after mTBI. In 3/7 patients, the slow-wave activity was transient and visible only in the first recording, urging prompt timing for the measurements in clinical settings.
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Affiliation(s)
- Hanna Kaltiainen
- Department of Neuroscience and Biomedical Engineering, School of Science, Aalto University, P.O. Box 12200, 00076, Aalto, Espoo, Finland.
- Aalto Neuroimaging, MEG Core, Aalto University, Espoo, Finland.
- Department of Neurology, Lohja District Hospital, Sairaalatie 8, 08200, Lohja, Finland.
- Clinical Neurosciences and Department of Neurology, University of Helsinki and Helsinki University Central Hospital, P.O. Box 340, 00029, HUS, Helsinki, Finland.
| | - Liisa Helle
- Department of Neuroscience and Biomedical Engineering, School of Science, Aalto University, P.O. Box 12200, 00076, Aalto, Espoo, Finland
- Aalto Neuroimaging, MEG Core, Aalto University, Espoo, Finland
- Elekta Oy, P.O. Box 34, 00531, Helsinki, Finland
| | - Mia Liljeström
- Department of Neuroscience and Biomedical Engineering, School of Science, Aalto University, P.O. Box 12200, 00076, Aalto, Espoo, Finland
- Aalto Neuroimaging, MEG Core, Aalto University, Espoo, Finland
| | - Hanna Renvall
- Department of Neuroscience and Biomedical Engineering, School of Science, Aalto University, P.O. Box 12200, 00076, Aalto, Espoo, Finland
- Aalto Neuroimaging, MEG Core, Aalto University, Espoo, Finland
- Clinical Neurosciences and Department of Neurology, University of Helsinki and Helsinki University Central Hospital, P.O. Box 340, 00029, HUS, Helsinki, Finland
| | - Nina Forss
- Department of Neuroscience and Biomedical Engineering, School of Science, Aalto University, P.O. Box 12200, 00076, Aalto, Espoo, Finland
- Aalto Neuroimaging, MEG Core, Aalto University, Espoo, Finland
- Clinical Neurosciences and Department of Neurology, University of Helsinki and Helsinki University Central Hospital, P.O. Box 340, 00029, HUS, Helsinki, Finland
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34
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Maldjian JA. Football and the Brain: Does Career Duration Provide Protective Effects? Radiology 2018; 286:978-980. [PMID: 29461951 DOI: 10.1148/radiol.2018172614] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- Joseph A Maldjian
- From the Advanced Neuroscience Imaging Research (ANSIR) Laboratory and Department of Radiology, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX 75390-9178
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35
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Structural imaging of mild traumatic brain injury may not be enough: overview of functional and metabolic imaging of mild traumatic brain injury. Brain Imaging Behav 2018; 11:591-610. [PMID: 28194558 DOI: 10.1007/s11682-017-9684-0] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
A majority of patients with traumatic brain injury (TBI) present as mild injury with no findings on conventional clinical imaging methods. Due to this difficulty of imaging assessment on mild TBI patients, there has been much emphasis on the development of diffusion imaging modalities such as diffusion tensor imaging (DTI). However, basic science research in TBI shows that many of the functional and metabolic abnormalities in TBI may be present even in the absence of structural damage. Moreover, structural damage may be present at a microscopic and molecular level that is not detectable by structural imaging modality. The use of functional and metabolic imaging modalities can provide information on pathological changes in mild TBI patients that may not be detected by structural imaging. Although there are various differences in protocols of positron emission tomography (PET), single photon emission computed tomography (SPECT), functional magnetic resonance imaging (fMRI), electroencephalography (EEG), and magnetoencephalography (MEG) methods, these may be important modalities to be used in conjunction with structural imaging in the future in order to detect and understand the pathophysiology of mild TBI. In this review, studies of mild TBI patients using these modalities that detect functional and metabolic state of the brain are discussed. Each modality's advantages and disadvantages are compared, and potential future applications of using combined modalities are explored.
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36
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Alpha desynchronization/synchronization during working memory testing is compromised in acute mild traumatic brain injury (mTBI). PLoS One 2018; 13:e0188101. [PMID: 29444081 PMCID: PMC5812562 DOI: 10.1371/journal.pone.0188101] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2017] [Accepted: 10/17/2017] [Indexed: 11/19/2022] Open
Abstract
Diagnosing and monitoring recovery of patients with mild traumatic brain injury (mTBI) is challenging because of the lack of objective, quantitative measures. Diagnosis is based on description of injuries often not witnessed, subtle neurocognitive symptoms, and neuropsychological testing. Since working memory (WM) is at the center of cognitive functions impaired in mTBI, this study was designed to define objective quantitative electroencephalographic (qEEG) measures of WM processing that may correlate with cognitive changes associated with acute mTBI. First-time mTBI patients and mild peripheral (limb) trauma controls without head injury were recruited from the emergency department. WM was assessed by a continuous performance task (N-back). EEG recordings were obtained during N-back testing on three occasions: within five days, two weeks, and one month after injury. Compared with controls, mTBI patients showed abnormal induced and evoked alpha activity including event-related desynchronization (ERD) and synchronization (ERS). For induced alpha power, TBI patients had excessive frontal ERD on their first and third visit. For evoked alpha, mTBI patients had lower parietal ERD/ERS at the second and third visits. These exploratory qEEG findings offer new and non-invasive candidate measures to characterize the evolution of injury over the first month, with potential to provide much-needed objective measures of brain dysfunction to diagnose and monitor the consequences of mTBI.
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Abstract
Computed tomography (CT) and magnetic resonance imaging (MRI) have revolutionized the assessment of traumatic brain injury (TBI) by permitting rapid detection and localization of acute intracranial injuries. In concussion, the most common presentation of sports-related head trauma, CT and MRI are unrevealing. This normal appearance of the brain on standard neuroimaging, however, belies the structural and functional pathology that underpins concussion-related symptoms and dysfunction. Advances in neuroimaging have expanded our ability to gain insight into this microstructural and functional brain pathology. This chapter will present both conventional and more advanced imaging approaches (e.g., diffusion tensor imaging, magnetization transfer imaging, magnetic resonance spectroscopy, functional MRI, arterial spin labeling, magnetoencephalography) to the assessment of TBI in sports and discuss some of the current and potential future roles of brain imaging in the assessment of injured athletes.
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38
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Kaplan GB, Leite-Morris KA, Wang L, Rumbika KK, Heinrichs SC, Zeng X, Wu L, Arena DT, Teng YD. Pathophysiological Bases of Comorbidity: Traumatic Brain Injury and Post-Traumatic Stress Disorder. J Neurotrauma 2017; 35:210-225. [PMID: 29017388 DOI: 10.1089/neu.2016.4953] [Citation(s) in RCA: 78] [Impact Index Per Article: 11.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
The high rates of traumatic brain injury (TBI) and post-traumatic stress disorder (PTSD) diagnoses encountered in recent years by the United States Veterans Affairs Healthcare System have increased public awareness and research investigation into these conditions. In this review, we analyze the neural mechanisms underlying the TBI/PTSD comorbidity. TBI and PTSD present with common neuropsychiatric symptoms including anxiety, irritability, insomnia, personality changes, and memory problems, and this overlap complicates diagnostic differentiation. Interestingly, both TBI and PTSD can be produced by overlapping pathophysiological changes that disrupt neural connections termed the "connectome." The neural disruptions shared by PTSD and TBI and the comorbid condition include asymmetrical white matter tract abnormalities and gray matter changes in the basolateral amygdala, hippocampus, and prefrontal cortex. These neural circuitry dysfunctions result in behavioral changes that include executive function and memory impairments, fear retention, fear extinction deficiencies, and other disturbances. Pathophysiological etiologies can be identified using experimental models of TBI, such as fluid percussion or blast injuries, and for PTSD, using models of fear conditioning, retention, and extinction. In both TBI and PTSD, there are discernible signs of neuroinflammation, excitotoxicity, and oxidative damage. These disturbances produce neuronal death and degeneration, axonal injury, and dendritic spine dysregulation and changes in neuronal morphology. In laboratory studies, various forms of pharmacological or psychological treatments are capable of reversing these detrimental processes and promoting axonal repair, dendritic remodeling, and neurocircuitry reorganization, resulting in behavioral and cognitive functional enhancements. Based on these mechanisms, novel neurorestorative therapeutics using anti-inflammatory, antioxidant, and anticonvulsant agents may promote better outcomes for comorbid TBI and PTSD.
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Affiliation(s)
- Gary B Kaplan
- 1 Mental Health Service , VA Boston Healthcare System, Brockton, Massachusetts.,2 Department of Psychiatry, Boston University School of Medicine , Boston, Massachusetts.,3 Department of Pharmacology and Experimental Therapeutics, Boston University School of Medicine , Boston, Massachusetts
| | - Kimberly A Leite-Morris
- 2 Department of Psychiatry, Boston University School of Medicine , Boston, Massachusetts.,3 Department of Pharmacology and Experimental Therapeutics, Boston University School of Medicine , Boston, Massachusetts.,4 Research Service, VA Boston Healthcare System , Jamaica Plain, Massachusetts
| | - Lei Wang
- 5 Division of Spinal Cord Injury Research, VA Boston Healthcare System , West Roxbury, Massachusetts.,6 Departments of Physical Medicine and Rehabilitation and Neurosurgery, Harvard Medical School , Boston, Massachusetts
| | - Kendra K Rumbika
- 7 Research Service, VA Boston Healthcare System , West Roxbury, Massachusetts
| | - Stephen C Heinrichs
- 7 Research Service, VA Boston Healthcare System , West Roxbury, Massachusetts
| | - Xiang Zeng
- 5 Division of Spinal Cord Injury Research, VA Boston Healthcare System , West Roxbury, Massachusetts.,6 Departments of Physical Medicine and Rehabilitation and Neurosurgery, Harvard Medical School , Boston, Massachusetts
| | - Liquan Wu
- 5 Division of Spinal Cord Injury Research, VA Boston Healthcare System , West Roxbury, Massachusetts.,6 Departments of Physical Medicine and Rehabilitation and Neurosurgery, Harvard Medical School , Boston, Massachusetts
| | - Danielle T Arena
- 7 Research Service, VA Boston Healthcare System , West Roxbury, Massachusetts
| | - Yang D Teng
- 5 Division of Spinal Cord Injury Research, VA Boston Healthcare System , West Roxbury, Massachusetts.,6 Departments of Physical Medicine and Rehabilitation and Neurosurgery, Harvard Medical School , Boston, Massachusetts
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Huang MX, Swan AR, Quinto AA, Matthews S, Harrington DL, Nichols S, Bruder BJ, Snook CC, Huang CW, Baker DG, Lee RR. A pilot treatment study for mild traumatic brain injury: Neuroimaging changes detected by MEG after low-intensity pulse-based transcranial electrical stimulation. Brain Inj 2017; 31:1951-1963. [DOI: 10.1080/02699052.2017.1363409] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Affiliation(s)
- Ming-Xiong Huang
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA
- Department of Radiology, University of California San Diego, La Jolla, CA, USA
| | - Ashley Robb Swan
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA
- Department of Radiology, University of California San Diego, La Jolla, CA, USA
| | - Annemarie Angeles Quinto
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA
- Department of Radiology, University of California San Diego, La Jolla, CA, USA
| | - Scott Matthews
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- ASPIRE Center, VASDHS Residential Rehabilitation Treatment Program, San Diego, CA, USA
| | - Deborah L. Harrington
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA
- Department of Radiology, University of California San Diego, La Jolla, CA, USA
| | - Sharon Nichols
- Department of Neurosciences, University of California San Diego, La Jolla, CA, USA
| | | | | | - Charles W. Huang
- Department of Bioengineering, University of California San Diego, La Jolla, CA, USA
| | - Dewleen G. Baker
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- VA Center of Excellence for Stress and Mental Health, San Diego, CA, USA
| | - Roland R. Lee
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, CA, USA
- Department of Radiology, University of California San Diego, La Jolla, CA, USA
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40
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Antonakakis M, Dimitriadis SI, Zervakis M, Papanicolaou AC, Zouridakis G. Altered Rich-Club and Frequency-Dependent Subnetwork Organization in Mild Traumatic Brain Injury: A MEG Resting-State Study. Front Hum Neurosci 2017; 11:416. [PMID: 28912698 PMCID: PMC5582079 DOI: 10.3389/fnhum.2017.00416] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2017] [Accepted: 08/03/2017] [Indexed: 12/19/2022] Open
Abstract
Functional brain connectivity networks exhibit “small-world” characteristics and some of these networks follow a “rich-club” organization, whereby a few nodes of high connectivity (hubs) tend to connect more densely among themselves than to nodes of lower connectivity. The Current study followed an “attack strategy” to compare the rich-club and small-world network organization models using Magnetoencephalographic (MEG) recordings from mild traumatic brain injury (mTBI) patients and neurologically healthy controls to identify the topology that describes the underlying intrinsic brain network organization. We hypothesized that the reduction in global efficiency caused by an attack targeting a model's hubs would reveal the “true” underlying topological organization. Connectivity networks were estimated using mutual information as the basis for cross-frequency coupling. Our results revealed a prominent rich-club network organization for both groups. In particular, mTBI patients demonstrated hyper-synchronization among rich-club hubs compared to controls in the δ band and the δ-γ1, θ-γ1, and β-γ2 frequency pairs. Moreover, rich-club hubs in mTBI patients were overrepresented in right frontal brain areas, from θ to γ1 frequencies, and underrepresented in left occipital regions in the δ-β, δ-γ1, θ-β, and β-γ2 frequency pairs. These findings indicate that the rich-club organization of resting-state MEG, considering its role in information integration and its vulnerability to various disorders like mTBI, may have a significant predictive value in the development of reliable biomarkers to help the validation of the recovery from mTBI. Furthermore, the proposed approach might be used as a validation tool to assess patient recovery.
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Affiliation(s)
- Marios Antonakakis
- Institute of Biomagnetism and Biosignal Analysis, Westfalian Wilhelms-University MuensterMuenster, Germany.,Digital Image and Signal Processing Laboratory, School of Electronic and Computer Engineering, Technical University of CreteChania, Greece
| | - Stavros I Dimitriadis
- Institute of Psychological Medicine and Clinical Neurosciences, Cardiff University School of MedicineCardiff, United Kingdom.,Cardiff University Brain Research Imaging Center (CUBRIC), School of Psychology, Cardiff UniversityCardiff, United Kingdom.,Neuroinformatics Group, Cardiff University Brain Research Imaging Center (CUBRIC), School of Psychology, Cardiff UniversityCardiff, United Kingdom.,School of Psychology, Cardiff UniversityCardiff, United Kingdom
| | - Michalis Zervakis
- Digital Image and Signal Processing Laboratory, School of Electronic and Computer Engineering, Technical University of CreteChania, Greece
| | - Andrew C Papanicolaou
- Departments of Pediatrics, and Anatomy and Neurobiology, Neuroscience Institute, University of Tennessee Health Science Center, Le Bonheur Children's HospitalMemphis, TN, United States
| | - George Zouridakis
- Biomedical Imaging Lab, Departments of Engineering Technology, Computer Science, Biomedical Engineering, and Electrical and Computer Engineering, University of HoustonHouston, TX, United States
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41
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Glenn DE, Acheson DT, Geyer MA, Nievergelt CM, Baker DG, Risbrough VB. Fear learning alterations after traumatic brain injury and their role in development of posttraumatic stress symptoms. Depress Anxiety 2017; 34:723-733. [PMID: 28489272 DOI: 10.1002/da.22642] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/24/2017] [Revised: 03/20/2017] [Accepted: 04/02/2017] [Indexed: 01/05/2023] Open
Abstract
BACKGROUND It is unknown how traumatic brain injury (TBI) increases risk for posttraumatic stress disorder (PTSD). One potential mechanism is via alteration of fear-learning processes that could affect responses to trauma memories and cues. We utilized a prospective, longitudinal design to determine if TBI is associated with altered fear learning and extinction, and if fear processing mediates effects of TBI on PTSD symptom change. METHODS Eight hundred fifty two active-duty Marines and Navy Corpsmen were assessed before and after deployment. Assessments included TBI history, PTSD symptoms, combat trauma and deployment stress, and a fear-potentiated startle task of fear acquisition and extinction. Startle response and self-reported expectancy and anxiety served as measures of fear conditioning, and PTSD symptoms were measured with the Clinician-Administered PTSD Scale. RESULTS Individuals endorsing "multiple hit" exposure (both deployment TBI and a prior TBI) showed the strongest fear acquisition and highest fear expression compared to groups without multiple hits. Extinction did not differ across groups. Endorsing a deployment TBI was associated with higher anxiety to the fear cue compared to those without deployment TBI. The association of deployment TBI with increased postdeployment PTSD symptoms was mediated by postdeployment fear expression when recent prior-TBI exposure was included as a moderator. TBI associations with increased response to threat cues and PTSD symptoms remained when controlling for deployment trauma and postdeployment PTSD diagnosis. CONCLUSIONS Deployment TBI, and multiple-hit TBI in particular, are associated with increases in conditioned fear learning and expression that may contribute to risk for developing PTSD symptoms.
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Affiliation(s)
- Daniel E Glenn
- Center of Excellence for Stress and Mental Health, San Diego Veterans Affairs Health Services, CA, USA.,Department of Psychiatry, University of California San Diego, CA, USA
| | - Dean T Acheson
- Center of Excellence for Stress and Mental Health, San Diego Veterans Affairs Health Services, CA, USA.,Department of Psychiatry, University of California San Diego, CA, USA
| | - Mark A Geyer
- Department of Psychiatry, University of California San Diego, CA, USA.,Research Service, VA San Diego Healthcare System, CA, USA
| | - Caroline M Nievergelt
- Center of Excellence for Stress and Mental Health, San Diego Veterans Affairs Health Services, CA, USA.,Department of Psychiatry, University of California San Diego, CA, USA
| | - Dewleen G Baker
- Center of Excellence for Stress and Mental Health, San Diego Veterans Affairs Health Services, CA, USA.,Department of Psychiatry, University of California San Diego, CA, USA
| | - Victoria B Risbrough
- Center of Excellence for Stress and Mental Health, San Diego Veterans Affairs Health Services, CA, USA.,Department of Psychiatry, University of California San Diego, CA, USA
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- Center of Excellence for Stress and Mental Health, San Diego Veterans Affairs Health Services, CA, USA.,Department of Psychiatry, University of California San Diego, CA, USA
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42
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Antonakakis M, Dimitriadis SI, Zervakis M, Papanicolaou AC, Zouridakis G. Reconfiguration of dominant coupling modes in mild traumatic brain injury mediated by δ-band activity: A resting state MEG study. Neuroscience 2017; 356:275-286. [DOI: 10.1016/j.neuroscience.2017.05.032] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2016] [Revised: 05/15/2017] [Accepted: 05/22/2017] [Indexed: 12/28/2022]
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Gardner AJ, Shih SL, Adamov EV, Zafonte RD. Research Frontiers in Traumatic Brain Injury. Phys Med Rehabil Clin N Am 2017; 28:413-431. [DOI: 10.1016/j.pmr.2016.12.014] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
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Huang MX, Harrington DL, Robb Swan A, Angeles Quinto A, Nichols S, Drake A, Song T, Diwakar M, Huang CW, Risbrough VB, Dale A, Bartsch H, Matthews S, Huang JW, Lee RR, Baker DG. Resting-State Magnetoencephalography Reveals Different Patterns of Aberrant Functional Connectivity in Combat-Related Mild Traumatic Brain Injury. J Neurotrauma 2016; 34:1412-1426. [PMID: 27762653 DOI: 10.1089/neu.2016.4581] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
Blast mild traumatic brain injury (mTBI) is a leading cause of sustained impairment in military service members and veterans. However, the mechanism of persistent disability is not fully understood. The present study investigated disturbances in brain functioning in mTBI participants using a source-imaging-based approach to analyze functional connectivity (FC) from resting-state magnetoencephalography (rs-MEG). Study participants included 26 active-duty service members or veterans who had blast mTBI with persistent post-concussive symptoms, and 22 healthy control active-duty service members or veterans. The source time courses from regions of interest (ROIs) were used to compute ROI to whole-brain (ROI-global) FC for different frequency bands using two different measures: 1) time-lagged cross-correlation and 2) phase-lock synchrony. Compared with the controls, blast mTBI participants showed increased ROI-global FC in beta, gamma, and low-frequency bands, but not in the alpha band. Sources of abnormally increased FC included the: 1) prefrontal cortex (right ventromedial prefrontal cortex [vmPFC], right rostral anterior cingulate cortex [rACC]), and left ventrolateral and dorsolateral prefrontal cortex; 2) medial temporal lobe (bilateral parahippocampus, hippocampus, and amygdala); and 3) right putamen and cerebellum. In contrast, the blast mTBI group also showed decreased FC of the right frontal pole. Group differences were highly consistent across the two different FC measures. FC of the left ventrolateral prefrontal cortex correlated with executive functioning and processing speed in mTBI participants. Altogether, our findings of increased and decreased regionalpatterns of FC suggest that disturbances in intrinsic brain connectivity may be the result of multiple mechanisms, and are associated with cognitive sequelae of the injury.
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Affiliation(s)
- Ming-Xiong Huang
- 1 Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System , San Diego, California.,2 Department of Radiology, University of California , San Diego, California
| | - Deborah L Harrington
- 1 Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System , San Diego, California.,2 Department of Radiology, University of California , San Diego, California
| | - Ashley Robb Swan
- 1 Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System , San Diego, California.,2 Department of Radiology, University of California , San Diego, California
| | - Annemarie Angeles Quinto
- 1 Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System , San Diego, California.,2 Department of Radiology, University of California , San Diego, California
| | - Sharon Nichols
- 3 Department of Neuroscience, University of California , San Diego, California
| | | | - Tao Song
- 2 Department of Radiology, University of California , San Diego, California
| | - Mithun Diwakar
- 2 Department of Radiology, University of California , San Diego, California
| | - Charles W Huang
- 5 Department of Bioengineering, University of California , San Diego, California
| | - Victoria B Risbrough
- 6 Department of Psychiatry, University of California , San Diego, California.,7 VA Center of Excellence for Stress and Mental Health , San Diego, California
| | - Anders Dale
- 2 Department of Radiology, University of California , San Diego, California
| | - Hauke Bartsch
- 2 Department of Radiology, University of California , San Diego, California
| | - Scott Matthews
- 1 Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System , San Diego, California.,6 Department of Psychiatry, University of California , San Diego, California.,8 Aspire Center , VASDHS Residential Rehabilitation Treatment Program, San Diego, California
| | | | - Roland R Lee
- 1 Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System , San Diego, California.,2 Department of Radiology, University of California , San Diego, California
| | - Dewleen G Baker
- 1 Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System , San Diego, California.,6 Department of Psychiatry, University of California , San Diego, California.,7 VA Center of Excellence for Stress and Mental Health , San Diego, California
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Vakorin VA, Doesburg SM, da Costa L, Jetly R, Pang EW, Taylor MJ. Detecting Mild Traumatic Brain Injury Using Resting State Magnetoencephalographic Connectivity. PLoS Comput Biol 2016; 12:e1004914. [PMID: 27906973 PMCID: PMC5131899 DOI: 10.1371/journal.pcbi.1004914] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2015] [Accepted: 04/11/2016] [Indexed: 01/05/2023] Open
Abstract
Accurate means to detect mild traumatic brain injury (mTBI) using objective and quantitative measures remain elusive. Conventional imaging typically detects no abnormalities despite post-concussive symptoms. In the present study, we recorded resting state magnetoencephalograms (MEG) from adults with mTBI and controls. Atlas-guided reconstruction of resting state activity was performed for 90 cortical and subcortical regions, and calculation of inter-regional oscillatory phase synchrony at various frequencies was performed. We demonstrate that mTBI is associated with reduced network connectivity in the delta and gamma frequency range (>30 Hz), together with increased connectivity in the slower alpha band (8–12 Hz). A similar temporal pattern was associated with correlations between network connectivity and the length of time between the injury and the MEG scan. Using such resting state MEG network synchrony we were able to detect mTBI with 88% accuracy. Classification confidence was also correlated with clinical symptom severity scores. These results provide the first evidence that imaging of MEG network connectivity, in combination with machine learning, has the potential to accurately detect and determine the severity of mTBI. Detecting concussion is typically not possible using currently clinically used brain imaging, such as MRI and CT scans. Magnetoencephalographic (MEG) imaging is able to directly measure brain activity at fast time scales, and this can be used to map how various areas of the brain interact. We recorded MEG from individuals who had suffered a concussion, as well as control subjects who had not. We found characteristic alterations of inter-regional interactions associated with concussion. Moreover, using a machine learning approach, we were able to detect concussion with 88% accuracy from MEG connectivity, and confidence of classification correlated with symptom severity. This potentially provides new quantitative and objective methods for detecting and assessing the severity of concussion using neuroimaging.
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Affiliation(s)
- Vasily A. Vakorin
- Department of Biomedical Physiology and Kinesiology, Simon Fraser University, Burnaby, British Columbia, Canada
- Behavioural and Cognitive Neuroscience Institute, Simon Fraser University, Burnaby, British Columbia, Canada
- * E-mail:
| | - Sam M. Doesburg
- Department of Biomedical Physiology and Kinesiology, Simon Fraser University, Burnaby, British Columbia, Canada
- Behavioural and Cognitive Neuroscience Institute, Simon Fraser University, Burnaby, British Columbia, Canada
- Department of Diagnostic Imaging, Hospital for Sick Children Research Institute, Toronto, Ontario, Canada
- Neuroscience and Mental Health, Hospital for Sick Children Research Institute, Toronto, Ontario, Canada
| | - Leodante da Costa
- Department of Surgery, Division of Neurosurgery, Sunnybrook Hospital, University of Toronto, Toronto, Ontario, Canada
- Department of Medical Imaging, Sunnybrook Hospital, Toronto, Ontario, Canada
| | - Rakesh Jetly
- Canadian Forces Health Services, Directorate of Mental Health, Ottawa, Ontario, Canada
| | - Elizabeth W. Pang
- Neuroscience and Mental Health, Hospital for Sick Children Research Institute, Toronto, Ontario, Canada
- Department of Neurology, Hospital for Sick Children, Toronto, Ontario, Canada
| | - Margot J. Taylor
- Department of Diagnostic Imaging, Hospital for Sick Children Research Institute, Toronto, Ontario, Canada
- Neuroscience and Mental Health, Hospital for Sick Children Research Institute, Toronto, Ontario, Canada
- Department of Neurology, Hospital for Sick Children, Toronto, Ontario, Canada
- Department of Medical Imaging, University of Toronto, Toronto, Ontario, Canada
- Department of Psychology, University of Toronto, Toronto, Ontario, Canada
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Pagnotta MF, Arakaki X, Tran T, Strickland D, Harrington M, Zouridakis G. Brain activation profiles in mTBI: Evidence from combined resting-state EEG and MEG activity. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2016; 2015:6963-6. [PMID: 26737894 DOI: 10.1109/embc.2015.7319994] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
In this study, we compared the brain activation profiles obtained from resting state Electroencephalographic (EEG) and Magnetoencephalographic (MEG) activity in six mild traumatic brain injury (mTBI) patients and five orthopedic controls, using power spectral density (PSD) analysis. We first estimated intracranial dipolar EEG/MEG sources on a dense grid on the cortical surface and then projected these sources on a standardized atlas with 68 regions of interest (ROIs). Averaging the PSD values of all sources in each ROI across all control subjects resulted in a normative database that was used to convert the PSD values of mTBI patients into z-scores in eight distinct frequency bands. We found that mTBI patients exhibited statistically significant overactivation in the delta, theta, and low alpha bands. Additionally, the MEG modality seemed to better characterize the group of individual subjects. These findings suggest that resting-state EEG/MEG activation maps may be used as specific biomarkers that can help with the diagnosis of and assess the efficacy of intervention in mTBI patients.
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Abstract
There is a paucity of accurate and reliable biomarkers to detect traumatic brain injury, grade its severity, and model post-traumatic brain injury (TBI) recovery. This gap could be addressed via advances in brain mapping which define injury signatures and enable tracking of post-injury trajectories at the individual level. Mapping of molecular and anatomical changes and of modifications in functional activation supports the conceptual paradigm of TBI as a disorder of large-scale neural connectivity. Imaging approaches with particular relevance are magnetic resonance techniques (diffusion weighted imaging, diffusion tensor imaging, susceptibility weighted imaging, magnetic resonance spectroscopy, functional magnetic resonance imaging, and positron emission tomographic methods including molecular neuroimaging). Inferences from mapping represent unique endophenotypes which have the potential to transform classification and treatment of patients with TBI. Limitations of these methods, as well as future research directions, are highlighted.
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Beamer M, Tummala SR, Gullotti D, Kopil C, Gorka S, Bass CRD, Morrison B, Cohen AS, Meaney DF. Primary blast injury causes cognitive impairments and hippocampal circuit alterations. Exp Neurol 2016. [PMID: 27246999 DOI: 10.1016/j.expneurol.2016] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/30/2023]
Abstract
Blast-induced traumatic brain injury (bTBI) and its long term consequences are a major health concern among veterans. Despite recent work enhancing our knowledge about bTBI, very little is known about the contribution of the blast wave alone to the observed sequelae. Herein, we isolated its contribution in a mouse model by constraining the animals' heads during exposure to a shockwave (primary blast). Our results show that exposure to primary blast alone results in changes in hippocampus-dependent behaviors that correspond with electrophysiological changes in area CA1 and are accompanied by reactive gliosis. Specifically, five days after exposure, behavior in an open field and performance in a spatial object recognition (SOR) task were significantly different from sham. Network electrophysiology, also performed five days after injury, demonstrated a significant decrease in excitability and increase in inhibitory tone. Immunohistochemistry for GFAP and Iba1 performed ten days after injury showed a significant increase in staining. Interestingly, a threefold increase in the impulse of the primary blast wave did not exacerbate these measures. However, we observed a significant reduction in the contribution of the NMDA receptors to the field EPSP at the highest blast exposure level. Our results emphasize the need to account for the effects of primary blast loading when studying the sequelae of bTBI.
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Affiliation(s)
- Matthew Beamer
- Department of Bioengineering(1), University of Pennsylvania, Philadelphia, PA, USA
| | - Shanti R Tummala
- Department of Bioengineering(1), University of Pennsylvania, Philadelphia, PA, USA
| | - David Gullotti
- Department of Bioengineering(1), University of Pennsylvania, Philadelphia, PA, USA
| | - Catherine Kopil
- Department of Bioengineering(1), University of Pennsylvania, Philadelphia, PA, USA
| | - Samuel Gorka
- Department of Bioengineering(1), University of Pennsylvania, Philadelphia, PA, USA
| | | | - Barclay Morrison
- Department of Biomedical Engineering, Columbia University, New York, NY, USA
| | - Akiva S Cohen
- Department of Anesthesiology and Critical Care Medicine, University of Pennsylvania, Philadelphia, PA, USA; Division of Critical Care Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - David F Meaney
- Department of Bioengineering(1), University of Pennsylvania, Philadelphia, PA, USA; Department of Neurosurgery, University of Pennsylvania, Philadelphia, PA, USA.
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Alhourani A, Wozny TA, Krishnaswamy D, Pathak S, Walls SA, Ghuman AS, Krieger DN, Okonkwo DO, Richardson RM, Niranjan A. Magnetoencephalography-based identification of functional connectivity network disruption following mild traumatic brain injury. J Neurophysiol 2016; 116:1840-1847. [PMID: 27466136 DOI: 10.1152/jn.00513.2016] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2016] [Accepted: 07/25/2016] [Indexed: 12/30/2022] Open
Abstract
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.
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Affiliation(s)
- Ahmad Alhourani
- Department of Neurological Surgery, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Thomas A Wozny
- Department of Neurological Surgery, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Deepa Krishnaswamy
- Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Sudhir Pathak
- Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Shawn A Walls
- University of Pittsburgh Medical Center Brain Mapping Center, Pittsburgh, Pennsylvania
| | - Avniel S Ghuman
- Department of Neurological Surgery, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania; Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania; Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania; Center for the Neural Basis of Cognition and University of Pittsburgh Brain Institute, University of Pittsburgh, Pittsburgh, Pennsylvania; and
| | - Donald N Krieger
- Department of Neurological Surgery, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - David O Okonkwo
- Department of Neurological Surgery, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - R Mark Richardson
- Department of Neurological Surgery, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania; Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania; Center for the Neural Basis of Cognition and University of Pittsburgh Brain Institute, University of Pittsburgh, Pittsburgh, Pennsylvania; and
| | - Ajay Niranjan
- Department of Neurological Surgery, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania;
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