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Rowland JA, Stapleton-Kotloski JR, Godwin DW, Hamilton CA, Martindale SL. The Functional Connectome and Long-Term Symptom Presentation Associated With Mild Traumatic Brain Injury and Blast Exposure in Combat Veterans. J Neurotrauma 2024. [PMID: 39150013 DOI: 10.1089/neu.2023.0315] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/17/2024] Open
Abstract
Mild traumatic brain injury (TBI) sustained in a deployment environment (deployment TBI) can be associated with increased severity of long-term symptom presentation, despite the general expectation of full recovery from a single mild TBI. The heterogeneity in the effects of deployment TBI on the brain can be difficult for a case-control design to capture. The functional connectome of the brain is an approach robust to heterogeneity that allows global measurement of effects using a common set of outcomes. The present study evaluates how differences in the functional connectome relate to remote symptom presentation following combat deployment and determines if deployment TBI, blast exposure, or post-traumatic stress disorder (PTSD) are associated with these neurological differences. Participants included 181 Iraq and Afghanistan combat-exposed Veterans, approximately 9.4 years since deployment. Structured clinical interviews provided diagnoses and characterizations of TBI, blast exposure, and PTSD. Self-report measures provided characterization of long-term symptoms (psychiatric, behavioral health, and quality of life). Resting-state magnetoencephalography was used to characterize the functional connectome of the brain individually for each participant. Linear regression identified factors contributing to symptom presentation including relevant covariates, connectome metrics, deployment TBI, blast exposure PTSD, and conditional relationships. Results identified unique contributions of aspects of the connectome to symptom presentation. Furthermore, several conditional relationships were identified, demonstrating that the connectome was related to outcomes in the presence of only deployment-related TBI (including blast-related TBI, primary blast TBI, and blast exposure). No conditional relationships were identified for PTSD; however, the main effect of PTSD on symptom presentation was significant for all models. These results demonstrate that the connectome captures aspects of brain function relevant to long-term symptom presentation, highlighting that deployment-related TBI influences symptom outcomes through a neurological pathway. These findings demonstrate that changes in the functional connectome associated with deployment-related TBI are relevant to symptom presentation over a decade past the injury event, providing a clear demonstration of a brain-based mechanism of influence.
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Affiliation(s)
- Jared A Rowland
- Research and Academic Affairs, W. G. (Bill) Hefner VA Healthcare System, Salisbury, North Carolina, USA
- Mid-Atlantic Mental Illness Research Education and Clinical Center, Durham, North Carolina, USA
- Department of Translational Neuroscience, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Jennifer R Stapleton-Kotloski
- Research and Academic Affairs, W. G. (Bill) Hefner VA Healthcare System, Salisbury, North Carolina, USA
- Department of Translational Neuroscience, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
- Department of Neurology, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Dwayne W Godwin
- Department of Translational Neuroscience, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Craig A Hamilton
- Research and Academic Affairs, W. G. (Bill) Hefner VA Healthcare System, Salisbury, North Carolina, USA
- Department of Biomedical Engineering, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Sarah L Martindale
- Research and Academic Affairs, W. G. (Bill) Hefner VA Healthcare System, Salisbury, North Carolina, USA
- Mid-Atlantic Mental Illness Research Education and Clinical Center, Durham, North Carolina, USA
- Department of Translational Neuroscience, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
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2
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Kang X, Yoon BC, Grossner E, Adamson MM. Characteristics of the Structural Connectivity in Patients with Brain Injury and Chronic Health Symptoms: A Pilot Study. Neuroinformatics 2024:10.1007/s12021-024-09681-7. [PMID: 38990502 DOI: 10.1007/s12021-024-09681-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/03/2024] [Indexed: 07/12/2024]
Abstract
Diffusion properties from diffusion tensor imaging (DTI) are exquisitely sensitive to white matter abnormalities incurred during traumatic brain injury (TBI), especially for those patients with chronic post-TBI symptoms such as headaches, dizziness, fatigue, etc. The evaluation of structural and functional connectivity using DTI has become a promising method for identifying subtle alterations in brain connectivity associated with TBI that are otherwise not visible with conventional imaging. This study assessed whether TBI patients with (n = 17) or without (n = 16) chronic symptoms (TBIcs/TBIncs) exhibit any changes in structural connectivity (SC) and mean fractional anisotropy (mFA) of intra- and inter-hemispheric connections when compared to a control group (CG) (n = 13). Reductions in SC and mFA were observed for TBIcs compared to CG, but not for TBIncs. More connections were found to have mFA reductions than SC reductions. On the whole, SC is dominated by ipsilateral connections for all the groups after the comparison of contralateral and ipsilateral connections. More contra-ipsi reductions of mFA were found for TBIcs than TBIncs compared to CG. These findings suggest that TBI patients with chronic symptoms not only demonstrate decreased global and regional mFA but also reduced structural network connectivity.
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Affiliation(s)
- Xiaojian Kang
- WRIISC-Women, VA Palo Alto Health Care System, 3801 Miranda Avenue, Palo Alto, CA, 94304, USA.
- Rehabilitation Service, VA Palo Alto Health Care System, 3801 Miranda Avenue, Palo Alto, CA, 94304, USA.
| | - Byung C Yoon
- Department of Radiology, Stanford University School of Medicine, VA Palo Alto Heath Care System, Palo Alto, CA, 94304, USA
| | - Emily Grossner
- Department of Psychology, VA Palo Alto Health Care System, 3801 Miranda Avenue, Palo Alto, CA, 94304, USA
| | - Maheen M Adamson
- WRIISC-Women, VA Palo Alto Health Care System, 3801 Miranda Avenue, Palo Alto, CA, 94304, USA
- Rehabilitation Service, VA Palo Alto Health Care System, 3801 Miranda Avenue, Palo Alto, CA, 94304, USA
- Department of Neurosurgery, Stanford University School of Medicine, 300 Pasteur Dr, Stanford, CA, 94305, USA
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3
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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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Esagoff AI, Stevens DA, Kosyakova N, Woodard K, Jung D, Richey LN, Daneshvari NO, Luna LP, Bray MJ, Bryant BR, Rodriguez CP, Krieg A, Trapp NT, Jones MB, Roper C, Goldwaser EL, Berich-Anastasio E, Pletnikova A, Lobner K, Lauterbach M, Sair HI, Peters ME. Neuroimaging Correlates of Post-Traumatic Stress Disorder in Traumatic Brain Injury: A Systematic Review of the Literature. J Neurotrauma 2023; 40:1029-1044. [PMID: 36259461 PMCID: PMC10402701 DOI: 10.1089/neu.2021.0453] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Neuroimaging is widely utilized in studying traumatic brain injury (TBI) and post-traumatic stress disorder (PTSD). The risk for PTSD is greater after TBI than after non-TBI trauma, and PTSD is associated with worse outcomes after TBI. Studying the neuroimaging correlates of TBI-related PTSD may provide insights into the etiology of both conditions and help identify those TBI patients most at risk of developing persistent symptoms. The objectives of this systematic review were to examine the current literature on neuroimaging in TBI-related PTSD, summarize key findings, and highlight strengths and limitations to guide future research. A Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA) compliant literature search was conducted in PubMed (MEDLINE®), PsycINFO, Embase, and Scopus databases prior to January 2022. The database query yielded 4486 articles, which were narrowed based on specified inclusion criteria to a final cohort of 16 studies, composed of 854 participants with TBI. There was no consensus regarding neuroimaging correlates of TBI-related PTSD among the included articles. A small number of studies suggest that TBI-related PTSD is associated with white matter tract changes, particularly in frontotemporal regions, as well as changes in whole-brain networks of resting-state connectivity. Future studies hoping to identify reliable neuroimaging correlates of TBI-related PTSD would benefit from ensuring consistent case definition, preferably with clinician-diagnosed TBI and PTSD, selection of comparable control groups, and attention to imaging timing post-injury. Prospective studies are needed and should aim to further differentiate predisposing factors from sequelae of TBI-related PTSD.
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Affiliation(s)
- Aaron I. Esagoff
- Department of Psychiatry and Behavioral Sciences and Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Daniel A. Stevens
- Department of Psychiatry and Behavioral Sciences and Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Natalia Kosyakova
- University of Connecticut, School of Medicine, Farmington, Connecticut, USA
| | - Kaylee Woodard
- Louisiana State University Health Sciences Center – New Orleans, New Orleans, Louisiana, USA
| | - Diane Jung
- Department of Psychiatry and Behavioral Sciences and Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Lisa N. Richey
- Department of Psychiatry and Behavioral Sciences and Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Nicholas O. Daneshvari
- Department of Psychiatry and Behavioral Sciences and Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Licia P. Luna
- Department of Radiology and Radiological Science, and Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Michael J.C. Bray
- Department of Psychiatry and Behavioral Sciences and Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Barry R. Bryant
- Department of Psychiatry and Behavioral Sciences and Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Carla P. Rodriguez
- Department of Psychiatry and Behavioral Sciences and Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Akshay Krieg
- Department of Psychiatry and Behavioral Sciences and Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Nicholas T. Trapp
- Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, Iowa, USA
| | - Melissa B. Jones
- Menninger Department of Psychiatry and Behavioral Sciences, Michael E. DeBakey VA Medical Center and Baylor College of Medicine, Houston, Texas, USA
| | - Carrie Roper
- VA Maryland Healthcare System, Baltimore, Maryland, USA
- Sheppard Pratt, Baltimore, Maryland, USA
- University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Eric L. Goldwaser
- Sheppard Pratt, Baltimore, Maryland, USA
- University of Maryland School of Medicine, Baltimore, Maryland, USA
| | | | - Alexandra Pletnikova
- Department of Psychiatry and Behavioral Sciences and Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Katie Lobner
- Department of Welch Medical Library, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Margo Lauterbach
- Sheppard Pratt, Baltimore, Maryland, USA
- University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Haris I. Sair
- Louisiana State University Health Sciences Center – New Orleans, New Orleans, Louisiana, USA
| | - Matthew E. Peters
- Department of Psychiatry and Behavioral Sciences and Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
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5
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Pierre K, Molina V, Shukla S, Avila A, Fong N, Nguyen J, Lucke-Wold B. Chronic traumatic encephalopathy: Diagnostic updates and advances. AIMS Neurosci 2022; 9:519-535. [PMID: 36660076 PMCID: PMC9826753 DOI: 10.3934/neuroscience.2022030] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Revised: 12/04/2022] [Accepted: 12/12/2022] [Indexed: 12/24/2022] Open
Abstract
Chronic traumatic encephalopathy (CTE) is a progressive neurodegenerative disease that occurs secondary to repetitive mild traumatic brain injury. Current clinical diagnosis relies on symptomatology and structural imaging findings which often vary widely among those with the disease. The gold standard of diagnosis is post-mortem pathological examination. In this review article, we provide a brief introduction to CTE, current diagnostic workup and the promising research on imaging and fluid biomarker diagnostic techniques. For imaging, we discuss quantitative structural analyses, DTI, fMRI, MRS, SWI and PET CT. For fluid biomarkers, we discuss p-tau, TREM2, CCL11, NfL and GFAP.
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Affiliation(s)
- Kevin Pierre
- University of Florida Department of Radiology, Gainesville 32603, Florida, USA
| | - Vanessa Molina
- Sam Houston State University of Osteopathic Medicine, Conroe 77304, Texas, USA
| | - Shil Shukla
- Sam Houston State University of Osteopathic Medicine, Conroe 77304, Texas, USA
| | - Anthony Avila
- Sam Houston State University of Osteopathic Medicine, Conroe 77304, Texas, USA
| | - Nicholas Fong
- Sam Houston State University of Osteopathic Medicine, Conroe 77304, Texas, USA
| | - Jessica Nguyen
- Sam Houston State University of Osteopathic Medicine, Conroe 77304, Texas, USA
| | - Brandon Lucke-Wold
- University of Florida Department of Neurosurgery, Gainesville 32603, Florida, USA,* Correspondence:
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Contextual Effects of Traumatic Brain Injury on the Connectome: Differential Effects of Deployment- and Non-Deployment-Acquired Injuries. J Head Trauma Rehabil 2022; 37:E449-E457. [PMID: 35862901 DOI: 10.1097/htr.0000000000000803] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
OBJECTIVE To identify differential effects of mild traumatic brain injury (TBI) occurring in a deployment or nondeployment setting on the functional brain connectome. SETTING Veterans Affairs Medical Center. PARTICIPANTS In total, 181 combat-exposed veterans of the wars in Iraq and Afghanistan (n = 74 with deployment-related mild TBI, average time since injury = 11.0 years, SD = 4.1). DESIGN Cross-sectional observational study. MAIN MEASURES Mid-Atlantic MIRECC (Mid-Atlantic Mental Illness Research, Education, and Clinical Center) Assessment of TBI, Clinician-Administered PTSD Scale, connectome metrics. RESULTS Linear regression adjusting for relevant covariates demonstrates a significant (P < .05 corrected) association between deployment mild TBI with reduced global efficiency (nonstandardized β = -.011) and degree of the K-core (nonstandardized β = -.79). Nondeployment mild TBI was significantly associated with a reduced number of modules within the connectome (nonstandardized β = -2.32). Finally, the interaction between deployment and nondeployment mild TBIs was significantly (P < .05 corrected) associated with increased mean (nonstandardized β = 9.92) and mode (nonstandardized β = 14.02) frequency at which connections occur. CONCLUSIONS These results demonstrate distinct effects of mild TBI on the functional brain connectome when sustained in a deployment versus nondeployment context. This is consistent with findings demonstrating differential effects in other areas such as psychiatric diagnoses and severity, pain, sleep, and cognitive function. Furthermore, participants were an average of 11 years postinjury, suggesting these represent chronic effects of the injury. Overall, these findings add to the growing body of evidence, suggesting the effects of mild TBI acquired during deployment are different and potentially longer lasting than those of mild TBI acquired in a nondeployment context.
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7
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Cifu DX. Clinical research findings from the long-term impact of military-relevant brain injury consortium-Chronic Effects of Neurotrauma Consortium (LIMBIC-CENC) 2013-2021. Brain Inj 2022; 36:587-597. [PMID: 35080997 DOI: 10.1080/02699052.2022.2033843] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
Abstract
This is a summary of the published research from the 14 observational, longitudinal and big-data, epidemiological studies supported by the LIMBIC-CENC program from 2013-2021 examining the long-term effects of combat-related traumatic brain injury (TBI). Findings from these 43 primary and secondary analyses include: 1) unique fluid, advanced neuroimaging and electrophysiologic biomarkers associated with mild traumatic brain injury (mTBI), number of mTBIs and related dysfunction, 2) increases in a range of chronic difficulties, including neurosensory, sleep, pain, cognitive deficits, behavioral disorders, overall symptom burden, healthcare costs and service-connected disability, associated with mTBI, all-severity traumatic brain injury (TBI), blast exposure, and number of mTBIs, and 3) increases in the risk for suicide and neurodegeneration, including dementia and Parkinson's disease, associated with mTBI and all-severity TBI. Ongoing LIMBIC-CENC longitudinal and epidemiologic research will clarify, confirm and expand upon these findings.
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Affiliation(s)
- David X Cifu
- Department of Physical Medicine and Rehabilitation, Virginia Commonwealth University, Richmond, Virginia, USA.,Department of Veterans Affairs, Washington, DC, USA
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8
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Rowland JA, Stapleton-Kotloski JR, Martindale SL, Rogers EE, Ord AS, Godwin DW, Taber KH. Alterations in the Topology of Functional Connectomes Are Associated with Post-Traumatic Stress Disorder and Blast-Related Mild Traumatic Brain Injury in Combat Veterans. J Neurotrauma 2021; 38:3086-3096. [PMID: 34435885 DOI: 10.1089/neu.2020.7450] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Post-traumatic stress disorder (PTSD) is a common condition in post-deployment service members (SM). SMs of the conflicts in Iraq and Afghanistan also frequently experience traumatic brain injury (TBI) and exposure to blasts during deployments. This study evaluated the effect of these conditions and experiences on functional brain connectomes in post-deployment, combat-exposed veterans. Functional brain connectomes were created using 5-min resting-state magnetoencephalography data. Well-established clinical interviews determined current PTSD diagnosis, as well as deployment-acquired mild TBI and history of exposure to blast. Linear regression examined the effect of these conditions on functional brain connectomes beyond covariates. There were significant interactions between blast-related mild TBI and PTSD after correction for multiple comparisons including number of nodes (non-standardized parameter estimate [PE] = -12.47), average degree (PE = 0.05), and connection strength (PE = 0.05). A main effect of blast-related mild TBI was observed on the threshold level. These results demonstrate a distinct functional connectome presentation associated with the presence of both blast-related mild TBI and PTSD. These findings suggest the possibility that blast-related mild TBI alterations in functional brain connectomes affect the presentation or progression of recovery from PTSD. The current results offer mixed support for hyper-connectivity in the chronic phase of deployment TBI.
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Affiliation(s)
- Jared A Rowland
- W. G. (Bill) Hefner VA Healthcare System, Research and Academic Affairs, Salisbury, North Carolina, USA.,Mid-Atlantic Mental Illness Research Education and Clinical Center, Durham, North Carolina, USA.,Department of Neurobiology and Anatomy, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Jennifer R Stapleton-Kotloski
- W. G. (Bill) Hefner VA Healthcare System, Research and Academic Affairs, Salisbury, North Carolina, USA.,Department of Neurobiology and Anatomy, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA.,Department of Neurology, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Sarah L Martindale
- W. G. (Bill) Hefner VA Healthcare System, Research and Academic Affairs, Salisbury, North Carolina, USA.,Mid-Atlantic Mental Illness Research Education and Clinical Center, Durham, North Carolina, USA.,Department of Physiology and Pharmacology, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Emily E Rogers
- Department of Neurobiology and Anatomy, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Anna S Ord
- W. G. (Bill) Hefner VA Healthcare System, Research and Academic Affairs, Salisbury, North Carolina, USA.,Mid-Atlantic Mental Illness Research Education and Clinical Center, Durham, North Carolina, USA.,Department of Neurology, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Dwayne W Godwin
- Department of Neurobiology and Anatomy, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Katherine H Taber
- W. G. (Bill) Hefner VA Healthcare System, Research and Academic Affairs, Salisbury, North Carolina, USA.,Mid-Atlantic Mental Illness Research Education and Clinical Center, Durham, North Carolina, USA.,Division of Biomedical Sciences, Edward Via College of Osteopathic Medicine, Blacksburg, Virginia, USA
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Echlin HV, Rahimi A, Wojtowicz M. Systematic Review of the Long-Term Neuroimaging Correlates of Mild Traumatic Brain Injury and Repetitive Head Injuries. Front Neurol 2021; 12:726425. [PMID: 34659091 PMCID: PMC8514830 DOI: 10.3389/fneur.2021.726425] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2021] [Accepted: 08/30/2021] [Indexed: 11/13/2022] Open
Abstract
Objective: To systematically review the literature on the long-term neuroimaging findings (≥10 years from exposure) for exposure in adulthood to mild traumatic brain injury (mTBI) and repetitive head impacts (RHIs) using neuroimaging across all available populations. Data sources: Four electronic databases: MEDLINE, SPORTDiscus, PsycINFO, and EMBASE. Study selection: All articles were original research and published in English. Studies examined adults with remote exposure to mTBI and/or RHIs from ten or more years ago in addition to any associated neuroimaging findings. Data extraction: Parameters mainly included participants' population, age, years since head injury, race, sex, education level, and any neuroimaging findings. Scores for the level of evidence and risk of bias were calculated independently by two authors. Results: 5,521 studies were reviewed, of which 34 met inclusion criteria and were included in this study. The majority of adults in these studies showed positive neuroimaging findings one or more decades following mTBI/RHI exposure. This was consistent across study populations (i.e., veterans, athletes, and the general population). There was evidence for altered protein deposition patterns, micro- and macro-structural, functional, neurochemical, and blood flow-related differences in the brain for those with remote mTBI/RHI exposure. Conclusion: Findings from these studies suggest that past mTBI/RHI exposure may be associated with neuroimaging findings. However, given the methodological constraints related to relatively small sample sizes and the heterogeneity in injury types/exposure and imaging techniques used, conclusions drawn from this review are limited. Well-designed longitudinal studies with multimodal imaging and in-depth health and demographic information will be required to better understand the potential for having positive neuroimaging findings following remote mTBI/RHI.
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10
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Bigler ED, Allder S. Improved neuropathological identification of traumatic brain injury through quantitative neuroimaging and neural network analyses: Some practical approaches for the neurorehabilitation clinician. NeuroRehabilitation 2021; 49:235-253. [PMID: 34397432 DOI: 10.3233/nre-218023] [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: 12/19/2022]
Abstract
BACKGROUND Quantitative neuroimaging analyses have the potential to provide additional information about the neuropathology of traumatic brain injury (TBI) that more thoroughly informs the neurorehabilitation clinician. OBJECTIVE Quantitative neuroimaging is typically not covered in the standard radiological report, but often can be extracted via post-processing of clinical neuroimaging studies, provided that the proper volume acquisition sequences were originally obtained. METHODS Research and commercially available quantitative neuroimaging methods provide region of interest (ROI) quantification metrics, lesion burden volumetrics and cortical thickness measures, degree of focal encephalomalacia, white matter (WM) abnormalities and residual hemorrhagic pathology. If present, diffusion tensor imaging (DTI) provides a variety of techniques that aid in evaluating WM integrity. Using quantitatively identified structural and ROI neuropathological changes are most informative when done from a neural network approach. RESULTS Viewing quantitatively identifiable damage from a neural network perspective provides the neurorehabilitation clinician with an additional tool for linking brain pathology to understand symptoms, problems and deficits as well as aid neuropsychological test interpretation. All of these analyses can be displayed in graphic form, including3-D image analysis. A case study approach is used to demonstrate the utility of quantitative neuroimaging and network analyses in TBI. CONCLUSIONS Quantitative neuroimaging may provide additional useful information for the neurorehabilitation clinician.
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Affiliation(s)
- Erin D Bigler
- Department of Neurology and Psychiatry, University of Utah, Salt Lake City, UT, USA.,Department of Psychology and Neuroscience Center, Brigham Young University, Provo, UT, USA.,Department of Neurology, University of California-Davis, Sacramento, CA, USA
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11
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Poor speech recognition, sound localization and reorganization of brain activity in children with unilateral microtia-atresia. Brain Imaging Behav 2021; 16:78-90. [PMID: 34245431 PMCID: PMC8825362 DOI: 10.1007/s11682-021-00478-9] [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] [Accepted: 05/17/2021] [Indexed: 10/31/2022]
Abstract
Microtia-atresia is a congenital malformation of the external ear, often affecting one side and being associated with severe-to-profound unilateral conductive hearing loss (UCHL). Although the impact of unilateral hearing loss (UHL) on speech recognition, sound localization and brain plasticity has been intensively investigated, less is known about the subjects with unilateral microtia-atresia (UMA). Considering these UMA subjects have hearing loss from birth, we hypothesize it has a great effect on brain organization. A questionnaire on speech recognition and spatial listening ability was administered to 40 subjects with UMA and 40 age- and sex-matched controls. UMA subjects showed poorer speech recognition in laboratory and poorer spatial listening ability. However, cognitive scores determined by the Montreal Cognitive Assessment (MoCA) and Wechsler Intelligence Scale for Children (WISC-IV) did not differ significantly in these two groups. The impact of hearing loss in UMA on brain functional organization was examined by comparing resting-state fMRIs (rs-fMRI) in 27 subjects with right-sided UMA and 27 matched controls. UMA subjects had increased nodal betweenness in visual networks and DMN but decreases in auditory and attention networks. These results indicate that UCHL in UMA causes significant abnormalities in brain organization. The impact of UCHL on cognition should be further examined with a battery of tests that are more challenging and better focused on the cognitive networks identified.
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Altered Small-World Functional Network Topology in Patients with Optic Neuritis: A Resting-State fMRI Study. DISEASE MARKERS 2021; 2021:9948751. [PMID: 34221189 PMCID: PMC8219459 DOI: 10.1155/2021/9948751] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/21/2021] [Revised: 04/26/2021] [Accepted: 05/26/2021] [Indexed: 12/17/2022]
Abstract
Aim This study investigated changes in small-world topology and brain functional connectivity in patients with optic neuritis (ON) by resting-state functional magnetic resonance imaging (rs-fMRI) and based on graph theory. Methods A total of 21 patients with ON (8 males and 13 females) and 21 matched healthy control subjects (8 males and 13 females) were enrolled and underwent rs-fMRI. Data were preprocessed and the brain was divided into 116 regions of interest. Small-world network parameters and area under the integral curve (AUC) were calculated from pairwise brain interval correlation coefficients. Differences in brain network parameter AUCs between the 2 groups were evaluated with the independent sample t-test, and changes in brain connection strength between ON patients and control subjects were assessed by network-based statistical analysis. Results In the sparsity range from 0.08 to 0.48, both groups exhibited small-world attributes. Compared to the control group, global network efficiency, normalized clustering coefficient, and small-world value were higher whereas the clustering coefficient value was lower in ON patients. There were no differences in characteristic path length, local network efficiency, and normalized characteristic path length between groups. In addition, ON patients had lower brain functional connectivity strength among the rolandic operculum, medial superior frontal gyrus, insula, median cingulate and paracingulate gyri, amygdala, superior parietal gyrus, inferior parietal gyrus, supramarginal gyrus, angular gyrus, lenticular nucleus, pallidum, superior temporal gyrus, and cerebellum compared to the control group (P < 0.05). Conclusion Patients with ON show typical "small world" topology that differed from that detected in HC brain networks. The brain network in ON has a small-world attribute but shows reduced and abnormal connectivity compared to normal subjects and likely causes symptoms of cognitive impairment.
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Rowland JA, Stapleton-Kotloski JR, Alberto GE, Davenport AT, Epperly PM, Godwin DW, Daunais JB. Rich Club Characteristics of Alcohol-Naïve Functional Brain Networks Predict Future Drinking Phenotypes in Rhesus Macaques. Front Behav Neurosci 2021; 15:673151. [PMID: 34149371 PMCID: PMC8206638 DOI: 10.3389/fnbeh.2021.673151] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2021] [Accepted: 04/28/2021] [Indexed: 11/30/2022] Open
Abstract
Purpose: A fundamental question for Alcohol use disorder (AUD) is how and when naïve brain networks are reorganized in response to alcohol consumption. The current study aimed to determine the progression of alcohol’s effect on functional brain networks during transition from the naïve state to chronic consumption. Procedures: Resting-state brain networks of six female rhesus macaque (Macaca mulatta) monkeys were acquired using magnetoencephalography (MEG) prior to alcohol exposure and after free-access to alcohol using a well-established model of chronic heavy alcohol consumption. Functional brain network metrics were derived at each time point. Results: The average connection frequency (p < 0.024) and membership of the Rich Club (p < 0.022) changed significantly over time. Metrics describing network topology remained relatively stable from baseline to free-access drinking. The minimum degree of the Rich Club prior to alcohol exposure was significantly predictive of future free-access drinking (r = −0.88, p < 0.001). Conclusions: Results suggest naïve brain network characteristics may be used to predict future alcohol consumption, and that alcohol consumption alters functional brain networks, shifting hubs and Rich Club membership away from previous regions in a non-systematic manner. Further work to refine these relationships may lead to the identification of a high-risk drinking phenotype.
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Affiliation(s)
- Jared A Rowland
- Research and Academic Affairs Service Line, Mid-Atlantic Mental Illness Research Education and Clinical Center, Salisbury VA Medical Center, Salisbury, NC, United States.,Department of Neurobiology and Anatomy, Wake Forest School of Medicine, Winston-Salem, NC, United States.,Department of Psychiatry and Behavioral Medicine, Wake Forest School of Medicine, Winston-Salem, NC, United States
| | - Jennifer R Stapleton-Kotloski
- Research and Academic Affairs Service Line, Mid-Atlantic Mental Illness Research Education and Clinical Center, Salisbury VA Medical Center, Salisbury, NC, United States.,Department of Neurology, Wake Forest School of Medicine, Winston-Salem, NC, United States
| | - Greg E Alberto
- Department of Neurobiology and Anatomy, Wake Forest School of Medicine, Winston-Salem, NC, United States
| | - April T Davenport
- Department of Physiology and Pharmacology, Wake Forest School of Medicine, Winston-Salem, NC, United States
| | - Phillip M Epperly
- Department of Physiology and Pharmacology, Wake Forest School of Medicine, Winston-Salem, NC, United States
| | - Dwayne W Godwin
- Department of Neurobiology and Anatomy, Wake Forest School of Medicine, Winston-Salem, NC, United States.,Department of Neurology, Wake Forest School of Medicine, Winston-Salem, NC, United States.,Department of Physiology and Pharmacology, Wake Forest School of Medicine, Winston-Salem, NC, United States
| | - James B Daunais
- Department of Physiology and Pharmacology, Wake Forest School of Medicine, Winston-Salem, NC, United States
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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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Kundu S, Ming J, Stevens J. Developing Multimodal Dynamic Functional Connectivity as a Neuroimaging Biomarker. Brain Connect 2021; 11:529-542. [PMID: 33544014 DOI: 10.1089/brain.2020.0900] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022] Open
Abstract
Background: In spite of increasing evidence highlighting the role of dynamic functional connectivity (FC) in characterizing mental disorders, there is a lack of (a) reliable statistical methods to compute dynamic connectivity and (b) rigorous dynamic FC-based approaches for predicting mental health outcomes in heterogeneous disorders such as post-traumatic stress disorder (PTSD). Methods: In one of the first such efforts, we develop a reliable and accurate approach for estimating dynamic FC guided by brain structural connectivity (SC) computed using diffusion tensor imaging data and investigate the potential of the proposed multimodal dynamic FC to predict continuous mental health outcomes. We develop concrete measures of temporal network variability that are predictive of PTSD resilience, and identify regions whose temporal connectivity fluctuations are significantly related to resilience. Results: Our results illustrate that the multimodal approach is more sensitive to connectivity change points, it can clearly detect localized brain regions with the dynamic network features such as small-worldedness, clustering coefficients, and efficiency associated with resilience, and that it has superior predictive performance compared with existing static and dynamic network models when modeling PTSD resilience. Discussion: While the majority of resting-state network modeling in psychiatry has focused on static FC, our novel multimodal dynamic network analyses that are sensitive to network fluctuations allowed us to provide a model of neural correlates of resilience with high accuracy compared with existing static connectivity approaches or those that do not use brain SC information, and provided us with an expanded understanding of the neurobiological causes for PTSD. Impact statement The methods developed in this article provide reliable and accurate dynamic functional connectivity (FC) approaches by fusing multimodal imaging data that are highly predictive of continuous clinical phenotypes in heterogeneous mental disorders. Currently, there is very little theoretical work to explain how network dynamics might contribute to individual differences in behavior or psychiatric symptoms. Our analysis conclusively discovers localized brain resting-state networks, regions, and connections where variations in dynamic FC (that is estimated after incorporating brain structural connectivity information) are associated with post-traumatic stress disorder resilience, which could potentially provide valuable tools for the development of neural circuit modeling in psychiatry in the future.
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Affiliation(s)
- Suprateek Kundu
- Department of Biostatistics and Bioinformatics, Emory University, Atlanta, Georgia, USA
| | - Jin Ming
- Department of Biostatistics and Bioinformatics, Emory University, Atlanta, Georgia, USA
| | - Jennifer Stevens
- Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, Georgia, USA
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Yang L, Zhang C, Chen Z, Li C, Wu T. Functional and network analyses of human exposure to long-term evolution signal. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2021; 28:5755-5773. [PMID: 32974829 DOI: 10.1007/s11356-020-10728-w] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/08/2020] [Accepted: 09/02/2020] [Indexed: 06/11/2023]
Abstract
Human exposure to the electromagnetic field emitted by wireless communication systems has raised public concerns. There were claims of the potential association of some neurophysiological disorders with the exposure, but the mechanism is yet to be established. The wireless networks, recently, experience a transition from the 4th generation (4G) to 5th generation (5G), while 4G long-term evolution (LTE) is still the frequently used signal in wireless communication. In the study, exposure experiments were conducted using the LTE signal. The subjects were divided into sham and real exposure groups. Before and after the exposure experiments, they underwent functional magnetic resonance imaging. Within-session and between-session comparisons have been executed for functional connectivity and network properties. Individual specific absorption rate (SAR) was also calculated. The results indicated that acute LTE exposure beneath the safety limits modulated both the functional connection and graph-based properties. To characterize the effect of functional activity, SAR averaged over a certain tissue mass was not an appropriate metric. The potential neurophysiological effect of 5G exposure has also been discussed in the study.
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Affiliation(s)
- Lei Yang
- China Academy of Information and Communications Technology, Beijing, China
| | - Chen Zhang
- China Academy of Information and Communications Technology, Beijing, China
| | - Zhiye Chen
- Hainan Hospital of Chinese People's Liberation Army General Hospital, Beijing, China
| | - Congsheng Li
- China Academy of Information and Communications Technology, Beijing, China
| | - Tongning Wu
- China Academy of Information and Communications Technology, Beijing, China.
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Proessl F, Dretsch MN, Connaboy C, Lovalekar M, Dunn-Lewis C, Canino MC, Sterczala AJ, Deshpande G, Katz JS, Denney TS, Flanagan SD. Structural Connectome Disruptions in Military Personnel with Mild Traumatic Brain Injury and Post-Traumatic Stress Disorder. J Neurotrauma 2020; 37:2102-2112. [DOI: 10.1089/neu.2020.6999] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
Affiliation(s)
- Felix Proessl
- Department of Sports Medicine and Nutrition, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Michael N. Dretsch
- U.S. Army Medical Research Directorate-West, Walter Reed Army Institute of Research, Joint Base Lewis-McChord, Washington, USA
- U.S. Army Aeromedical Research Laboratory, Fort Rucker, Alabama, USA
- Department of Psychological Sciences, Auburn University, Auburn, Alabama, USA
| | - Chris Connaboy
- Department of Sports Medicine and Nutrition, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Mita Lovalekar
- Department of Sports Medicine and Nutrition, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Courtenay Dunn-Lewis
- Department of Sports Medicine and Nutrition, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Maria C. Canino
- Department of Sports Medicine and Nutrition, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Adam J. Sterczala
- Department of Sports Medicine and Nutrition, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Gopikrishna Deshpande
- Department of Psychological Sciences, Auburn University, Auburn, Alabama, USA
- Department of Electrical and Computer Engineering, Auburn University, Auburn, Alabama, USA
- Alabama Advanced Imaging Consortium, Alabama, USA
- Center for Neuroscience, Auburn University, Auburn, Alabama, USA
- School of Psychology, Capital Normal University, Beijing, China
| | - Jeffrey S. Katz
- Department of Psychological Sciences, Auburn University, Auburn, Alabama, USA
- Department of Electrical and Computer Engineering, Auburn University, Auburn, Alabama, USA
- Alabama Advanced Imaging Consortium, Alabama, USA
- Center for Neuroscience, Auburn University, Auburn, Alabama, USA
| | - Thomas S. Denney
- Department of Psychological Sciences, Auburn University, Auburn, Alabama, USA
- Department of Electrical and Computer Engineering, Auburn University, Auburn, Alabama, USA
- Alabama Advanced Imaging Consortium, Alabama, USA
- Center for Neuroscience, Auburn University, Auburn, Alabama, USA
| | - Shawn D. Flanagan
- Department of Sports Medicine and Nutrition, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
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Magnetoencephalography: Clinical and Research Practices. Brain Sci 2018; 8:brainsci8080157. [PMID: 30126121 PMCID: PMC6120049 DOI: 10.3390/brainsci8080157] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2018] [Revised: 08/07/2018] [Accepted: 08/11/2018] [Indexed: 11/25/2022] Open
Abstract
Magnetoencephalography (MEG) is a neurophysiological technique that detects the magnetic fields associated with brain activity. Synthetic aperture magnetometry (SAM), a MEG magnetic source imaging technique, can be used to construct both detailed maps of global brain activity as well as virtual electrode signals, which provide information that is similar to invasive electrode recordings. This innovative approach has demonstrated utility in both clinical and research settings. For individuals with epilepsy, MEG provides valuable, nonredundant information. MEG accurately localizes the irritative zone associated with interictal spikes, often detecting epileptiform activity other methods cannot, and may give localizing information when other methods fail. These capabilities potentially greatly increase the population eligible for epilepsy surgery and improve planning for those undergoing surgery. MEG methods can be readily adapted to research settings, allowing noninvasive assessment of whole brain neurophysiological activity, with a theoretical spatial range down to submillimeter voxels, and in both humans and nonhuman primates. The combination of clinical and research activities with MEG offers a unique opportunity to advance translational research from bench to bedside and back.
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