Abstract
This study aimed to detect alterations in intra- and inter-network functional connectivity (FC) of multiple networks in acute brainstem ischemic stroke patients, and the relationship between FC and movement assessment scores to assess their ability to predict upper extremity motor impairment. Resting-state functional magnetic resonance imaging (rs-fMRI) data were acquired from acute brainstem ischemic stroke patients (n = 50) and healthy controls (HCs) (n = 45). Resting-state networks (RSNs) were established based on independent component analysis (ICA) and the functional network connectivity (FNC) analysis was performed. Subsequently, correlation analysis was subsequently used to explore the relationship between FNC abnormalities and upper extremity motor impairment. Altered FC within default mode network (DMN), executive control network (ECN), the salience network (SN), auditory network (AN), and cerebellum network (CN) were found in the acute brainstem ischemic stroke group relative to HCs. Moreover, different patterns of altered network interactions were found between the patients and HCs, including the SN-CN, SN-AN, and ECN-DMN connections. Correlations between functional disconnection and upper limb dysfunction measurements in acute brainstem ischemic stroke patients were also found. This study intimated that widespread FNC impairment and altered integration existed in brainstem ischemic stroke at acute stage, suggesting that FNC disruption may be applied for early diagnosis and prediction of upper limb dysfunction in acute brainstem ischemic stroke.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Data availability
Imaging data could be provided upon request.
References
Adamaszek, M., D'Agata, F., Ferrucci, R., Habas, C., Keulen, S., Kirkby, K. C., et al. (2017). Consensus paper: Cerebellum and emotion. Cerebellum, 16(2), 552–576. https://doi.org/10.1007/s12311-016-0815-8
Bai, F., Shi, Y., Yuan, Y., Wang, Y., Yue, C., Teng, Y., et al. (2012). Altered self-referential network in resting-state amnestic type mild cognitive impairment. Cortex, 48(5), 604–613. https://doi.org/10.1016/j.cortex.2011.02.011
Biswal, B. B., Van Kylen, J., & Hyde, J. S. (1997). Simultaneous assessment of flow and BOLD signals in resting-state functional connectivity maps. NMR in Biomedicine, 10(4–5), 165–170. https://doi.org/10.1002/(sici)1099-1492(199706/08)10:4/5<165::aid-nbm454>3.0.co;2-7
Biswal, B. B., Mennes, M., Zuo, X. N., Gohel, S., Kelly, C., Smith, S. M., et al. (2010). Toward discovery science of human brain function. Proceedings of the National Academy of Sciences of the United States of America, 107(10), 4734–4739. https://doi.org/10.1073/pnas.0911855107
Broyd, S. J., Demanuele, C., Debener, S., Helps, S. K., James, C. J., & Sonuga-Barke, E. J. (2009). Default-mode brain dysfunction in mental disorders: A systematic review. Neuroscience and Biobehavioral Reviews, 33(3), 279–296. https://doi.org/10.1016/j.neubiorev.2008.09.002
Buckner, R. L., Krienen, F. M., & Yeo, B. T. (2013). Opportunities and limitations of intrinsic functional connectivity MRI. Nature Neuroscience, 16(7), 832–837. https://doi.org/10.1038/nn.3423
Carter, A. R., Astafiev, S. V., Lang, C. E., Connor, L. T., Rengachary, J., Strube, M. J., et al. (2010). Resting interhemispheric functional magnetic resonance imaging connectivity predicts performance after stroke. Annals of Neurology, 67(3), 365–375. https://doi.org/10.1002/ana.21905
Carter, A. R., Shulman, G. L., & Corbetta, M. (2012). Why use a connectivity-based approach to study stroke and recovery of function? NeuroImage, 62(4), 2271–2280. https://doi.org/10.1016/j.neuroimage.2012.02.070
Cerliani, L., Mennes, M., Thomas, R. M., Di Martino, A., Thioux, M., & Keysers, C. (2015). Increased functional connectivity between subcortical and cortical resting-state networks in autism Spectrum disorder. JAMA Psychiatry, 72(8), 767–777. https://doi.org/10.1001/jamapsychiatry.2015.0101
Chen, T., Cai, W., Ryali, S., Supekar, K., & Menon, V. (2016). Distinct global brain dynamics and spatiotemporal Organization of the Salience Network. PLoS Biology, 14(6), e1002469. https://doi.org/10.1371/journal.pbio.1002469
Damoiseaux, J. S., Rombouts, S. A., Barkhof, F., Scheltens, P., Stam, C. J., Smith, S. M., et al. (2006). Consistent resting-state networks across healthy subjects. Proceedings of the National Academy of Sciences of the United States of America, 103(37), 13848–13853. https://doi.org/10.1073/pnas.0601417103
De Luca, M., Beckmann, C. F., De Stefano, N., Matthews, P. M., & Smith, S. M. (2006). fMRI resting state networks define distinct modes of long-distance interactions in the human brain. NeuroImage, 29(4), 1359–1367. https://doi.org/10.1016/j.neuroimage.2005.08.035
Fan, J., McCandliss, B. D., Fossella, J., Flombaum, J. I., & Posner, M. I. (2005). The activation of attentional networks. Neuroimage, 26(2), 471–479. https://doi.org/10.1016/j.neuroimage.2005.02.004
Fan, L., Hu, J., Ma, W., Wang, D., Yao, Q., & Shi, J. (2019). Altered baseline activity and connectivity associated with cognitive impairment following acute cerebellar infarction: A resting-state fMRI study. Neuroscience Letters, 692, 199–203. https://doi.org/10.1016/j.neulet.2018.11.007
Fox, M. D., & Raichle, M. E. (2007). Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging. Nature Reviews Neuroscience, 8(9), 700–711. https://doi.org/10.1038/nrn2201
Golestani, A. M., Tymchuk, S., Demchuk, A., Goodyear, B. G., & Group V-S. (2013). Longitudinal evaluation of resting-state FMRI after acute stroke with hemiparesis. Neurorehabilitation and Neural Repair, 27(2), 153–163. https://doi.org/10.1177/1545968312457827
Grefkes, C., & Ward, N. S. (2014). Cortical reorganization after stroke: How much and how functional? The Neuroscientist : a Review Journal Bringing Neurobiology, Neurology and Psychiatry, 20(1), 56–70. https://doi.org/10.1177/1073858413491147
Guerra-Carrillo, B., Mackey, A. P., & Bunge, S. A. (2014). Resting-state fMRI: A window into human brain plasticity. The Neuroscientist : a Review Journal Bringing Neurobiology, Neurology and Psychiatry, 20(5), 522–533. https://doi.org/10.1177/1073858414524442
Hampson, M., Peterson, B. S., Skudlarski, P., Gatenby, J. C., & Gore, J. C. (2002). Detection of functional connectivity using temporal correlations in MR images. Human Brain Mapping, 15(4), 247–262. https://doi.org/10.1002/hbm.10022
Iyer, D. G., Shah, N. S., Hastings, K. G., Hu, J., Rodriguez, F., Boothroyd, D. B. et al. (2019). Years of Potential Life Lost Because of Cardiovascular Disease in Asian-American Subgroups, 2003–2012. Journal of the American Heart Association, e010744.
Jafri, M. J., Pearlson, G. D., Stevens, M., & Calhoun, V. D. (2008). A method for functional network connectivity among spatially independent resting-state components in schizophrenia. NeuroImage, 39(4), 1666–1681. https://doi.org/10.1016/j.neuroimage.2007.11.001
Jiang, L., Geng, W., Chen, H., Zhang, H., Bo, F., Mao, C. N., et al. (2018). Decreased functional connectivity within the default-mode network in acute brainstem ischemic stroke. European Journal of Radiology, 105, 221–226. https://doi.org/10.1016/j.ejrad.2018.06.018
Keren-Happuch, E., Chen, S. H., Ho, M. H., & Desmond, J. E. (2014). A meta-analysis of cerebellar contributions to higher cognition from PET and fMRI studies. Human Brain Mapping, 35(2), 593–615. https://doi.org/10.1002/hbm.22194
Li, Y. O., Adali, T., & Calhoun, V. D. (2007). Estimating the number of independent components for functional magnetic resonance imaging data. Human Brain Mapping, 28(11), 1251–1266. https://doi.org/10.1002/hbm.20359
Mantini, D., & Vanduffel, W. (2013). Emerging roles of the brain’s default network. The Neuroscientist : a Review Journal Bringing Neurobiology, Neurology and Psychiatry, 19(1), 76–87. https://doi.org/10.1177/1073858412446202
Mantini, D., Perrucci, M. G., Del Gratta, C., Romani, G. L., & Corbetta, M. (2007). Electrophysiological signatures of resting state networks in the human brain. Proceedings of the National Academy of Sciences of the United States of America, 104(32), 13170–13175. https://doi.org/10.1073/pnas.0700668104
McHugh, M. J., Gu, H., Yang, Y., Adinoff, B., & Stein, E. A. (2017). Executive control network connectivity strength protects against relapse to cocaine use. Addiction Biology, 22(6), 1790–1801. https://doi.org/10.1111/adb.12448
Mortality GBD. (2016). Causes of death C. global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980-2015: A systematic analysis for the global burden of disease study 2015. Lancet, 388(10053), 1459–1544. https://doi.org/10.1016/S0140-6736(16)31012-1
Northoff, G., Heinzel, A., de Greck, M., Bermpohl, F., Dobrowolny, H., & Panksepp, J. (2006). Self-referential processing in our brain--a meta-analysis of imaging studies on the self. Neuroimage, 31(1), 440–457. https://doi.org/10.1016/j.neuroimage.2005.12.002
Ogawa, S., Lee, T. M., Kay, A. R., & Tank, D. W. (1990). Brain magnetic resonance imaging with contrast dependent on blood oxygenation. Proceedings of the National Academy of Sciences of the United States of America, 87(24), 9868–9872. https://doi.org/10.1073/pnas.87.24.9868
Park, C. H., Chang, W. H., Ohn, S. H., Kim, S. T., Bang, O. Y., Pascual-Leone, A., et al. (2011). Longitudinal changes of resting-state functional connectivity during motor recovery after stroke. Stroke, 42(5), 1357–1362. https://doi.org/10.1161/STROKEAHA.110.596155
Platz, T., Eickhof, C., van Kaick, S., Engel, U., Pinkowski, C., Kalok, S., et al. (2005). Impairment-oriented training or Bobath therapy for severe arm paresis after stroke: A single-blind, multicentre randomized controlled trial. Clinical Rehabilitation, 19(7), 714–724. https://doi.org/10.1191/0269215505cr904oa
Pohjasvaara, T., Vataja, R., Leppavuori, A., Kaste, M., & Erkinjuntti, T. (2002). Cognitive functions and depression as predictors of poor outcome 15 months after stroke. Cerebrovascular Diseases, 14(3–4), 228–233. https://doi.org/10.1159/000065667
Poole, J. L., & Whitney, S. L. (1988). Motor assessment scale for stroke patients: Concurrent validity and interrater reliability. Archives of Physical Medicine and Rehabilitation, 69(3 Pt 1), 195–197.
Powers, W. J., Derdeyn, C. P., Biller, J., Coffey, C. S., Hoh, B. L., Jauch, E. C., et al. (2015). 2015 American Heart Association/American Stroke Association focused update of the 2013 guidelines for the early Management of Patients with Acute Ischemic Stroke Regarding Endovascular Treatment: A guideline for healthcare professionals from the American Heart Association/American Stroke Association. Stroke, 46(10), 3020–3035. https://doi.org/10.1161/STR.0000000000000074
Qin, Y., Li, Y., Sun, B., He, H., Peng, R., Zhang, T., et al. (2018). Functional connectivity alterations in children with spastic and Dyskinetic cerebral palsy. Neural Plasticity, 2018, 7058953. https://doi.org/10.1155/2018/7058953
Raichle, M. E. (2001). Cognitive neuroscience. Bold insights. Nature, 412(6843), 128–130. https://doi.org/10.1038/35084300
Rosenberg, M. D., Finn, E. S., Scheinost, D., Constable, R. T., & Chun, M. M. (2017). Characterizing attention with predictive network models. Trends in Cognitive Sciences, 21(4), 290–302. https://doi.org/10.1016/j.tics.2017.01.011
Shi, M., Liu, S., Chen, H., Geng, W., Yin, X., Chen, Y. C., et al. (2021). Disrupted brain functional network topology in unilateral acute brainstem ischemic stroke. Brain Imaging and Behavior, 15(1), 444–452.
Skipper, J. I., Devlin, J. T., & Lametti, D. R. (2017). The hearing ear is always found close to the speaking tongue: Review of the role of the motor system in speech perception. Brain and Language, 164, 77–105. https://doi.org/10.1016/j.bandl.2016.10.004
Stoodley, C. J. (2016). The cerebellum and neurodevelopmental disorders. Cerebellum, 15(1), 34–37. https://doi.org/10.1007/s12311-015-0715-3
Tuladhar, A. M., Snaphaan, L., Shumskaya, E., Rijpkema, M., Fernandez, G., Norris, D. G., et al. (2013). Default mode network connectivity in stroke patients. PLoS One, 8(6), e66556. https://doi.org/10.1371/journal.pone.0066556
Uddin, L. Q. (2015). Salience processing and insular cortical function and dysfunction. Nature Reviews Neuroscience, 16(1), 55–61. https://doi.org/10.1038/nrn3857
Wang, L., Yu, C., Chen, H., Qin, W., He, Y., Fan, F., et al. (2010). Dynamic functional reorganization of the motor execution network after stroke. Brain: a Journal of Neurology, 133(Pt 4), 1224–1238. https://doi.org/10.1093/brain/awq043
Wang, J., Wang, X., Xia, M., Liao, X., Evans, A., & He, Y. (2015). GRETNA: A graph theoretical network analysis toolbox for imaging connectomics. Frontiers in Human Neuroscience, 9, 386. https://doi.org/10.3389/fnhum.2015.00386
Yao, G., Li, J., Liu, S., Wang, J., Cao, X., Li, X., et al. (2020). Alterations of functional connectivity in stroke patients with basal ganglia damage and cognitive impairment. Frontiers in Neurology, 11, 980. https://doi.org/10.3389/fneur.2020.00980
Zhao, Z., Wu, J., Fan, M., Yin, D., Tang, C., Gong, J., et al. (2018). Altered intra- and inter-network functional coupling of resting-state networks associated with motor dysfunction in stroke. Human Brain Mapping, 39(8), 3388–3397. https://doi.org/10.1002/hbm.24183
Zhao, D., Liu, J., Wang, M., Zhang, X., & Zhou, M. (2019). Epidemiology of cardiovascular disease in China: Current features and implications. Nature Reviews Cardiology, 16(4), 203–212. https://doi.org/10.1038/s41569-018-0119-4
Funding
This work was supported by the Jiangsu Provincial Special Program of Medical Science (No. BE2021604), Natural Science Foundation of Jiangsu Province (No. BK20201118) and 333 High-level Talents Training Project of Jiangsu Province (No. BRA2019122).
Author information
Authors and Affiliations
Contributions
WG. and JZ. are co-first authors of this paper, they design the experiment, analyze the data and draft the paper for the work. SS., HC. and MS. help to acquire the clinical and fMRI data. LJ. helps to revise the paper critically for important intellectual content. XY. and YCC. are co-corresponding authors of this paper, they did the financial support, review and final approval of the paper to be published. All authors read and approved the final manuscript.
Corresponding authors
Ethics declarations
Ethical approval
The current study was approved by the Research Ethics Committee of the Nanjing Medical University.
Consent to participate
All participants provided written informed consent before undergoing MR imaging.
Consent to publish
Not applicable.
Competing interests
The authors declare that there is no potential conflict of interests regarding the publication of this paper.
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Geng, W., Zhang, J., Shang, S. et al. Reduced functional network connectivity is associated with upper limb dysfunction in acute ischemic brainstem stroke. Brain Imaging and Behavior 16, 802–810 (2022). https://doi.org/10.1007/s11682-021-00554-0
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11682-021-00554-0