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      Aberrant dynamic properties of whole‐brain functional connectivity in acute mild traumatic brain injury revealed by hidden Markov models

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          Abstract

          Objectives

          This study aimed to investigate the temporal dynamics of brain activity and characterize the spatiotemporal specificity of transitions and large‐scale networks on short timescales in acute mild traumatic brain injury (mTBI) patients and those with cognitive impairment in detail.

          Methods

          Resting‐state functional magnetic resonance imaging (rs‐fMRI) was acquired for 71 acute mTBI patients and 57 age‐, sex‐, and education‐matched healthy controls (HCs). A hidden Markov model (HMM) analysis of rs‐fMRI data was conducted to identify brain states that recurred over time and to assess the dynamic patterns of activation states that characterized acute mTBI patients and those with cognitive impairment. The dynamic parameters (fractional occupancy, lifetime, interval time, switching rate, and probability) between groups and their correlation with cognitive performance were analyzed.

          Results

          Twelve HMM states were identified in this study. Compared with HCs, acute mTBI patients and those with cognitive impairment exhibited distinct changes in dynamics, including fractional occupancy, lifetime, and interval time. Furthermore, the switching rate and probability across HMM states were significantly different between acute mTBI patients and patients with cognitive impairment (all p < 0.05). The temporal reconfiguration of states in acute mTBI patients and those with cognitive impairment was associated with several brain networks (including the high‐order cognition network [DMN], subcortical network [SUB], and sensory and motor network [SMN]).

          Conclusions

          Hidden Markov models provide additional information on the dynamic activity of brain networks in patients with acute mTBI and those with cognitive impairment. Our results suggest that brain network dynamics determined by the HMM could reinforce the understanding of the neuropathological mechanisms of acute mTBI patients and those with cognitive impairment.

          Abstract

          Alteration in switching frequency and transition probability between acute mTBI and HC. Alteration in switching frequency and transition probability between mTBI patients with and without cognitive impairment.

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          Most cited references40

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          Complex brain networks: graph theoretical analysis of structural and functional systems.

          Ed Bullmore, Olaf Sporns (2009)
          Recent developments in the quantitative analysis of complex networks, based largely on graph theory, have been rapidly translated to studies of brain network organization. The brain's structural and functional systems have features of complex networks--such as small-world topology, highly connected hubs and modularity--both at the whole-brain scale of human neuroimaging and at a cellular scale in non-human animals. In this article, we review studies investigating complex brain networks in diverse experimental modalities (including structural and functional MRI, diffusion tensor imaging, magnetoencephalography and electroencephalography in humans) and provide an accessible introduction to the basic principles of graph theory. We also highlight some of the technical challenges and key questions to be addressed by future developments in this rapidly moving field.
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            Global, regional, and national burden of neurological disorders, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016

            Valery L. Feigin, Emma Nichols, Tahiya Alam … (2020)
            Summary Background Neurological disorders are increasingly recognised as major causes of death and disability worldwide. The aim of this analysis from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016 is to provide the most comprehensive and up-to-date estimates of the global, regional, and national burden from neurological disorders. Methods We estimated prevalence, incidence, deaths, and disability-adjusted life-years (DALYs; the sum of years of life lost [YLLs] and years lived with disability [YLDs]) by age and sex for 15 neurological disorder categories (tetanus, meningitis, encephalitis, stroke, brain and other CNS cancers, traumatic brain injury, spinal cord injury, Alzheimer's disease and other dementias, Parkinson's disease, multiple sclerosis, motor neuron diseases, idiopathic epilepsy, migraine, tension-type headache, and a residual category for other less common neurological disorders) in 195 countries from 1990 to 2016. DisMod-MR 2.1, a Bayesian meta-regression tool, was the main method of estimation of prevalence and incidence, and the Cause of Death Ensemble model (CODEm) was used for mortality estimation. We quantified the contribution of 84 risks and combinations of risk to the disease estimates for the 15 neurological disorder categories using the GBD comparative risk assessment approach. Findings Globally, in 2016, neurological disorders were the leading cause of DALYs (276 million [95% UI 247–308]) and second leading cause of deaths (9·0 million [8·8–9·4]). The absolute number of deaths and DALYs from all neurological disorders combined increased (deaths by 39% [34–44] and DALYs by 15% [9–21]) whereas their age-standardised rates decreased (deaths by 28% [26–30] and DALYs by 27% [24–31]) between 1990 and 2016. The only neurological disorders that had a decrease in rates and absolute numbers of deaths and DALYs were tetanus, meningitis, and encephalitis. The four largest contributors of neurological DALYs were stroke (42·2% [38·6–46·1]), migraine (16·3% [11·7–20·8]), Alzheimer's and other dementias (10·4% [9·0–12·1]), and meningitis (7·9% [6·6–10·4]). For the combined neurological disorders, age-standardised DALY rates were significantly higher in males than in females (male-to-female ratio 1·12 [1·05–1·20]), but migraine, multiple sclerosis, and tension-type headache were more common and caused more burden in females, with male-to-female ratios of less than 0·7. The 84 risks quantified in GBD explain less than 10% of neurological disorder DALY burdens, except stroke, for which 88·8% (86·5–90·9) of DALYs are attributable to risk factors, and to a lesser extent Alzheimer's disease and other dementias (22·3% [11·8–35·1] of DALYs are risk attributable) and idiopathic epilepsy (14·1% [10·8–17·5] of DALYs are risk attributable). Interpretation Globally, the burden of neurological disorders, as measured by the absolute number of DALYs, continues to increase. As populations are growing and ageing, and the prevalence of major disabling neurological disorders steeply increases with age, governments will face increasing demand for treatment, rehabilitation, and support services for neurological disorders. The scarcity of established modifiable risks for most of the neurological burden demonstrates that new knowledge is required to develop effective prevention and treatment strategies. Funding Bill & Melinda Gates Foundation.
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              Estimating the global incidence of traumatic brain injury

              Michael Dewan, Abbas Rattani, Saksham Gupta … (2018)
              Traumatic brain injury (TBI)—the “silent epidemic”—contributes to worldwide death and disability more than any other traumatic insult. Yet, TBI incidence and distribution across regions and socioeconomic divides remain unknown. In an effort to promote advocacy, understanding, and targeted intervention, the authors sought to quantify the case burden of TBI across World Health Organization (WHO) regions and World Bank (WB) income groups. Open-source epidemiological data on road traffic injuries (RTIs) were used to model the incidence of TBI using literature-derived ratios. First, a systematic review on the proportion of RTIs resulting in TBI was conducted, and a meta-analysis of study-derived proportions was performed. Next, a separate systematic review identified primary source studies describing mechanisms of injury contributing to TBI, and an additional meta-analysis yielded a proportion of TBI that is secondary to the mechanism of RTI. Then, the incidence of RTI as published by the Global Burden of Disease Study 2015 was applied to these two ratios to generate the incidence and estimated case volume of TBI for each WHO region and WB income group. Relevant articles and registries were identified via systematic review; study quality was higher in the high-income countries (HICs) than in the low- and middle-income countries (LMICs). Sixty-nine million (95% CI 64–74 million) individuals worldwide are estimated to sustain a TBI each year. The proportion of TBIs resulting from road traffic collisions was greatest in Africa and Southeast Asia (both 56%) and lowest in North America (25%). The incidence of RTI was similar in Southeast Asia (1.5% of the population per year) and Europe (1.2%). The overall incidence of TBI per 100,000 people was greatest in North America (1299 cases, 95% CI 650–1947) and Europe (1012 cases, 95% CI 911–1113) and least in Africa (801 cases, 95% CI 732–871) and the Eastern Mediterranean (897 cases, 95% CI 771–1023). The LMICs experience nearly 3 times more cases of TBI proportionally than HICs. Sixty-nine million (95% CI 64–74 million) individuals are estimated to suffer TBI from all causes each year, with the Southeast Asian and Western Pacific regions experiencing the greatest overall burden of disease. Head injury following road traffic collision is more common in LMICs, and the proportion of TBIs secondary to road traffic collision is likewise greatest in these countries. Meanwhile, the estimated incidence of TBI is highest in regions with higher-quality data, specifically in North America and Europe.
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                Author and article information

                Contributors
                Liyan Lu:
                ORCID: https://orcid.org/0000-0002-2490-3955
                luliyan.ok@163.com
                Xinying Wu: rebeccahxt@163.com
                Fang Yuan: yf021025@126.com
                Journal
                Journal ID (nlm-ta): CNS Neurosci Ther
                Journal ID (iso-abbrev): CNS Neurosci Ther
                Journal ID (doi): 10.1111/(ISSN)1755-5949
                Journal ID (publisher-id): CNS
                Title: CNS Neuroscience & Therapeutics
                Publisher: John Wiley and Sons Inc. (Hoboken )
                ISSN (Print): 1755-5930
                ISSN (Electronic): 1755-5949
                Publication date (Electronic): 05 March 2024
                Publication date Collection: March 2024
                Volume: 30
                Issue: 3 ( doiID: 10.1002/cns.v30.3 )
                Electronic Location Identifier: e14660
                Affiliations
                [ 1 ] Department of Radiology, Nanjing First Hospital Nanjing Medical University Nanjing Jiangsu China
                [ 2 ] Department of Radiology, Nanjing Drum Tower Hospital The Affiliated Hospital of Nanjing University Medical School Nanjing China
                [ 3 ] Department of Neurosurgery, Shanghai Jiao Tong University Affiliated Sixth Peoples' Hospital, School of Medicine Shanghai Jiao Tong University Shanghai China
                Author notes
                [*] [* ] Correspondence

                Liyan Lu and Xinying Wu, Department of Radiology, Nanjing First Hospital, Nanjing Medical University, No. 68, Changle Road, Nanjing 210006, China.

                Email: luliyan.ok@ 123456163.com and rebeccahxt@ 123456163.com

                Fang Yuan, Department of Neurosurgery, Shanghai Sixth Peoples' Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, No. 600, Yishan Road, Shanghai, China.

                Email: yf021025@ 123456126.com

                Author information
                https://orcid.org/0000-0002-2490-3955
                Article
                Publisher ID: CNS14660 Other ID: CNSNT-2023-175.R1
                DOI: 10.1111/cns.14660
                PMC ID: 10912843
                PubMed ID: 38439697
                SO-VID: c5abbb38-c356-4d48-99cb-c71a90b22e3c
                Copyright © © 2024 The Authors. CNS Neuroscience & Therapeutics published by John Wiley & Sons Ltd.
                License:

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                Date revision received : 12 February 2024
                Date received : 09 February 2023
                Date accepted : 14 February 2024
                Page count
                Figures: 7, Tables: 2, Pages: 12, Words: 6172
                Funding
                Funded by: National Natural Science Foundation of China , doi 10.13039/501100001809;
                Award ID: 82102006
                Award ID: 82102012
                Categories
                Subject: Original Article
                Subject: Original Articles
                Custom metadata
                source-schema-version-number 2.0
                cover-date March 2024
                details-of-publishers-convertor Converter:WILEY_ML3GV2_TO_JATSPMC version:6.3.9 mode:remove_FC converted:05.03.2024

                ScienceOpen disciplines: Neurosciences
                Keywords: acute mild traumatic brain injury,cognitive impairment,dynamic functional connectivity,hidden markov model,resting‐state functional magnetic resonance imaging,transition probability
                Data availability:
                ScienceOpen disciplines: Neurosciences
                Keywords: acute mild traumatic brain injury, cognitive impairment, dynamic functional connectivity, hidden markov model, resting‐state functional magnetic resonance imaging, transition probability

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