Disrupted modular organization of resting-state cortical functional connectivity in U.S. military personnel following concussive ‘mild’ blast-related traumatic brain injury
Open accessAbstract
Blast-related traumatic brain injury (TBI) has been one of the "signature injuries" of the wars in Iraq and Afghanistan. However, neuroimaging studies in concussive 'mild' blast-related TBI have been challenging due to the absence of abnormalities in computed tomography or conventional magnetic resonance imaging (MRI) and the heterogeneity of the blast-related injury mechanisms. The goal of this study was to address these challenges utilizing single-subject, module-based graph theoretic analysis of resting-state functional MRI (fMRI) data. We acquired 20min of resting-state fMRI in 63 U.S. military personnel clinically diagnosed with concussive blast-related TBI and 21 U.S. military controls who had blast exposures but no diagnosis of TBI. All subjects underwent an initial scan within 90days post-injury and 65 subjects underwent a follow-up scan 6 to 12months later. A second independent cohort of 40 U.S. military personnel with concussive blast-related TBI served as a validation dataset. The second independent cohort underwent an initial scan within 30days post-injury. 75% of the scans were of good quality, with exclusions primarily due to excessive subject motion. Network analysis of the subset of these subjects in the first cohort with good quality scans revealed spatially localized reductions in the participation coefficient, a measure of between-module connectivity, in the TBI patients relative to the controls at the time of the initial scan. These group differences were less prominent on the follow-up scans. The 15 brain areas with the most prominent reductions in the participation coefficient were next used as regions of interest (ROIs) for single-subject analyses. In the first TBI cohort, more subjects than would be expected by chance (27/47 versus 2/47 expected, p<0.0001) had 3 or more brain regions with abnormally low between-module connectivity relative to the controls on the initial scans. On the follow-up scans, more subjects than expected by chance (5/37, p=0.044) but fewer subjects than on the initial scans had 3 or more brain regions with abnormally low between-module connectivity. Analysis of the second TBI cohort validation dataset with no free parameters provided a partial replication; again more subjects than expected by chance (8/31, p=0.006) had 3 or more brain regions with abnormally low between-module connectivity on the initial scans, but the numbers were not significant (2/27, p=0.276) on the follow-up scans. A single-subject, multivariate analysis by probabilistic principal component analysis of the between-module connectivity in the 15 identified ROIs, showed that 31/47 subjects in the first TBI cohort were found to be abnormal relative to the controls on the initial scans. In the second TBI cohort, 9/31 patients were found to be abnormal in identical multivariate analysis with no free parameters. Again, there were not substantial differences on the follow-up scans. Taken together, these results indicate that single-subject, module-based graph theoretic analysis of resting-state fMRI provides potentially useful information for concussive blast-related TBI if high quality scans can be obtained. The underlying biological mechanisms and consequences of disrupted between-module connectivity are unknown, thus further studies are required.
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In patients with blast-related head injuries, network measures are grossly deranged, with higher modularity and lower average participation coefficient.
“network measures are grossly deranged, with higher modularity and lower average participation coefficient in patients with these injuries.”
From Graph theory analysis of complex brain networks: new concepts in brain mapping applied to neurosurgery (2016) · cites this paper as [47]
Results §3.4 reports higher modularity and lower average participation coefficient in the TBI cohort on the initial scans. The claim omits that timing qualification: the modularity difference was not statistically significant on follow-up scans. (LLM, conf=0.84)
Experimental — accuracy not yet measuredBlast-related head injuries are characterized by minimal abnormalities on standard structural MRI.
“blast-related head injuries are a relatively recent phenomenon characterized by minimal abnormalities on standard structural MRI.47”
From Graph theory analysis of complex brain networks: new concepts in brain mapping applied to neurosurgery (2016) · cites this paper as [47]
The Abstract says conventional MRI shows no abnormalities in concussive ‘mild’ blast-related TBI, and Materials and Methods §2.1 says the study’s patients had no abnormalities on conventional MRI or CT. This supports the MRI point for mild blast-related TBI, but the claim extends it to blast-related head injuries generally. (LLM, conf=0.84)
Experimental — accuracy not yet measuredThose with a history of concussion may have unique disruptions in functional networks and a complex neurobehavioral clinical presentation, making standard scalp-based DLPFC targeting even less optimal for this population.
“Compounding the variability in functional brain circuitry seen in the general population, those with a history of concussion may have unique disruptions in functional networks and a complex neurobehavioral clinical presentation (16, 33, 34) making standard scalp-based DLPFC targeting even less optimal for this population.”
From Adaptive trial for the treatment of depressive symptoms associated with concussion using accelerated intermittent theta burst stimulation (ADEPT): rationale, design and methods (2025) · cites this paper as [34]
The Discussion (§4.1; page unavailable) reports disrupted connectivity across multiple regions in patients with concussive blast-related TBI, supporting the functional-network portion of the cited statement. The paper does not establish a complex neurobehavioral clinical presentation, and its findings concern blast-related TBI rather than concussion histories generally. The scalp-based DLPFC targeting conclusion follows the citations and appears to be the citing authors’ inference. (LLM, conf=0.82)
Experimental — accuracy not yet measured
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- Authors
- Han, K., Mac Donald, C. L., Johnson, A. M., Barnes, Y., Wierzechowski, L., Zonies, D., Oh, J., Flaherty, S., Fang, R., Raichle, M. E., & Brody, D. L.
- Affiliations
- Washington University in St. Louis (US)
- Landstuhl Regional Medical Center (DE)
- Corresponding author
- Brody, David L.
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2014-01
- Volume
- 84
- Pages
- 76-96
- ISSN
- 1053-8119 (ISSN-L)
- PMC
- PMC3849319
- OpenAlex
- W2012214808
- Cited by
- 123
- References
- 123
- Citations by year
- 2026: 4 · 2025: 4 · 2024: 5 · 2023: 11 · 2022: 11 · 2021: 7 · 2020: 8 · 2019: 7 · 2018: 13 · 2017: 13 · 2016: 16 · 2015: 15 · 2014: 8 · 2012: 1
- FWCI
- 7.13
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- Department of Defense CDMRP (PT075299, PT090444)
- NCRR (1S10RR022984-01A1)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Epidemiology › Traumatic Brain Injury Research
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Keywords
- blast-related traumatic brain injury, concussion, resting-state functional connectivity, participation coefficient, graph theory, military personnel, longitudinal follow-up, region of interest
- MeSH terms
- Adult, Blast Injuries, Brain Concussion, Brain Injuries, Cerebral Cortex, Humans, Male, Middle Aged, Military Personnel, Nerve Net, Neural Pathways, Rest, United States, Iraq War, 2003-2011, Young Adult, Afghan Campaign 2001-, Connectome
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