Abstract
Many patients with traumatic brain injury (TBI) have persistent cognitive deficits, including decreased attention and working memory. This preliminary study examined fMRI data from a clinical trial implementing a 4-week virtual reality driving intervention to assess how sustained training can improve deficits related to traumatic brain injury. Previously-reported behavioral findings showed improvements in working memory and processing speed in those who received the intervention; this report explores the brain bases of these effects by comparing neural activity related to working memory (n-back task) and resting state connectivity before and after the intervention. In the baseline visit (n = 24), working memory activity was prominent in bilateral DLPFC and prefrontal cortex, anterior insula, medial superior frontal gyrus, left thalamus, bilateral supramarginal / angular gyrus, precuneus, and left posterior middle temporal gyrus. Following intervention, participants showed less global activation on the n-back task, with regions of activity only in the bilateral middle frontal cortex, posterior middle frontal gyrus, and supramarginal gyrus. Activity related to working memory load was reduced for the group that went through the intervention (n = 7) compared to the waitlist control group (n = 4). These results suggest that successful cognitive rehabilitation of working memory in TBI may be associated with increased efficiency of brain networks, evidenced by reduced activation of brain activity during cognitive processing. These results highlight the importance of examining brain activity related to cognitive rehabilitation of attention and working memory after brain injury.
Similar content being viewed by others
References
Andelic, N., Stevens, L. F., Sigurdardottir, S., Arango-Lasprilla, J. C., & Roe, C. (2012). Associations between disability and employment 1 year after traumatic brain injury in a working age population. Brain Injury, 26(3), 261–269. https://doi.org/10.3109/02699052.2012.654589.
Andersson, J. L. R., Jenkinson, M., & Smith, S. (2007). Non-linear registration aka Spatial normalisation FMRIB Technial Report TR07JA2.
Buckner, R. L., Andrews-Hanna, J. R., & Schacter, D. L. (2008). The brain’s default network: anatomy, function, and relevance to disease. Annals of the New York Academy of Sciences, 1124, 1–38. https://doi.org/10.1196/annals.1440.011.
Centers for Disease Control and Prevention. (2015). Report to Congress on Traumatic Brain Injury in the United States: Epidemiology and Rehabilitation. National Center for Injury Prevention and Control; Division of Unintentional Injury Prevention. Atlanta, GA.
Corkin, S., Rosen, T. J., Sullivan, E. V., & Clegg, R. A. (1989). Penetrating head injury in young adulthood exacerbates cognitive decline in later years. The Journal of Neuroscience: The Official Journal of the Society for Neuroscience, 9(11), 3876–3883.
Dawson, D. R., Schwartz, M. L., Winocur, G., & Stuss, D. T. (2007). Return to productivity following traumatic brain injury: cognitive, psychological, physical, spiritual, and environmental correlates. Disability and Rehabilitation, 29 (4), 301–313. https://doi.org/10.1080/09638280600756687.
De Beaumont, L., Theoret, H., Mongeon, D., Messier, J., Leclerc, S., Tremblay, S., … Lassonde, M. (2009). Brain function decline in healthy retired athletes who sustained their last sports concussion in early adulthood. Brain, 132, 695–708.
Ettenhofer, M. L., Guise, B., Brandler, B., Bittner, K., Gimbel, S. I., Cordero, E., … Chan, L. (2019). Neurocognitive driving rehabilitation in virtual environments (NeuroDRIVE): A pilot clinical trial for chronic traumatic brain injury. NeuroRehabilitation.
Hillary, F. G., Rajtmajer, S. M., Roman, C. A., Medaglia, J. D., Slocomb-Dluzen, J. E., Calhoun, V. D., Good, D. C., & Wylie, G. R. (2014). The rich get richer: Brain injury elicits hyperconnectivity in core subnetworks. Plos One, 9(8), e104021.
Hillary, F. G., Roman, C. A., Venkatesan, U., Rajtmajer, S. M., Bajo, R., & Castellanos, N. D. (2015). Hyperconnectivity is a fundamental response to neurological disruption. Neuropsychology, 29(1), 59–75.
Johnson, B., Zhang, K., Gay, M., Horovitz, S., Hallett, M., Sebastianelli, W., & Slobounov, S. (2012). Alteration of brain default network in subacute phase of injury in concussed individuals: Resting-state fMRI study. NeuroImage, 59(1), 511–518. https://doi.org/10.1016/J.NEUROIMAGE.2011.07.081.
Jolles, D. D., van Buchem, M. A., Crone, E. A., & Rombouts, A. R. B. (2013). Functional brain connectivity at rest changes after working memory training. Human Brain Mapping, 34, 396–406.
Kay, T., Harrington, D. E., Adams, R., Anderson, T., Berrol, S., Cicerone, K., … Malec, J. (1993). Definition of mild traumatic brain injury. Journal of Head Trauma Rehabilitation, 8, 86–87.
Kim, Y. H., Yoo, W. K., Ko, M. H., Park, C. H., Kim, S. T., & Na, D. L. (2009). Plasticity of the attentional network after brain injury and cognitive rehabilitation. Neurorehabil Neural Repair, 23, 468–477.
Klingberg, T. (2010). Training and plasticity of working memory. Trends in Cognitive Sciences, 14(7), 317–324. https://doi.org/10.1016/j.tics.2010.05.002.
Lawlor-Savage, L., Clark, C. M., & Goghari, V. M. (2019). No evidence that working memory training alters gray matter structure: a MRI surface -based analysis. Behavioural Brain Research, 360, 323–340. https://doi.org/10.1016/J.BBR.2018.12.008.
Leahy, B., & Lam, C. (1998). Neuropsychological testing and functional outcome for individuals with traumatic brain injury. - PubMed - NCBI. Brain injury, 12(12), 1025–1035.
Mayer, A. R., Mannell, M. V., Ling, J., Gasparovic, C., & Yeo, R. A. (2011). Functional connectivity in mild traumatic brain injury. Human Brain Mapping, 32(11), 1825–1835. https://doi.org/10.1002/hbm.21151.
McAllister, T. W., Saykin, A. J., Flashman, L. A., Sparling, M. B., Johnson, S. C., Guerin, S. J., Mamourian, A. C., Weaver, J. B., & Yanofsky, N. (1999). Brain activation during working memory 1 month after mild traumatic brain injury: a functional MRI study. Neurology, 53(6), 1300–1308.
McAllister, T. W., Sparling, M. B., Flashman, L. A., Guerin, S. J., Mamourian, A. C., & Saykin, A. J. (2001). Differential working memory load effects after mild traumatic brain injury. NeuroImage, 14(5), 1004–1012. https://doi.org/10.1006/nimg.2001.0899.
McDonald, B. C., Saykin, A. J., & McAllister, T. W. (2012). Functional MRI of mild traumatic brain injury (mTBI): Progress and perspectives from the first decade of studies. Brain Imaging and Behavior, 6(2), 193–207. https://doi.org/10.1007/s11682-012-9173-4.
Moncrief, R. L., Behensky, M. L., Harkins, T. G., & Fuller, B. A. (2014). Driving assessment and training method and apparatus.
Owen, A. M., Hampshire, A., Grahn, J. A., Stenton, R., Dajani, S., Burns, A. S., Howard, R. J., & Ballard, C. G. (2010). Putting brain training to the test. Nature, 465, 775–778. https://doi.org/10.1038/nature09042.
Owen, A. M., McMillan, K. M., Laird, A. R., & Bullmore, E. (2005). N-back working memory paradigm: a meta-analysis of normative functional neuroimaging studies. Human Brain Mapping, 25(1), 46–59. https://doi.org/10.1002/hbm.20131.
Palacios, E. M., Sala-Llonch, R., Junque, C., Roig, T., Tormos, J. M., Bargallo, N., & Vendrell, P. (2013). Resting-state functional magnetic resonance imaging activity and connectivity and cognitive outcome in traumatic brain injury. JAMA Neurology, 70(7), 845–851. https://doi.org/10.1001/jamaneurol.2013.38.
Perlstein, W. M., Cole, M. A., Demery, J. A., Seignourel, P. J., Dixit, N. K., Larson, M. J., & Briggs, R. W. (2004). Parametric manipulation of working memory load in traumatic brain injury: behavioral and neural correlates. Journal of the International Neuropsychological Society, 10, 724–741. https://doi.org/10.1017/S1355617704105110S1355617704105110.
Ponsford, J. L., Downing, M. G., Olver, J., Ponsford, M., Acher, R., Carty, M., & Spitz, G. (2014). Longitudinal follow-up of patients with traumatic brain injury: outcome at two, five, and ten years post-injury. Journal of Neurotrauma, 31(1), 64–77. https://doi.org/10.1089/neu.2013.2997.
Selassie, A. W., Zaloshnja, E., Langlois, J. A., Miller, T., Jones, P., & Steiner, C. (2008). Incidence of long-term disability following traumatic brain injury hospitalization, United States, 2003. The Journal of Head Trauma Rehabilitation, 23, 123–131. https://doi.org/10.1097/01.HTR.0000314531.30401.3900001199-200803000-00007.
Sohlberg, M. K. M., McLaughlin, K. A., Pavese, A., Heidrich, A., & Posner, M. I. (2000). Evaluation of attention process training and brain injury education in persons with acquired brain injury. Journal of Clinical and Experimental Neuropsychology, 22, 656–676.
Sours, C., Zhuo, J., Janowich, J., Aarabi, B., Shanmuganathan, K., & Gullapalli, R. P. (2013). Default mode network interference in mild traumatic brain injury – A pilot resting state study. Brain Research, 1537, 201–215. https://doi.org/10.1016/j.brainres.2013.08.034.
Sours, C., Zhuo, J., Roys, S., Shanmuganathan, K., & Gullapalli, R. P. (2015). Disruptions in resting state functional connectivity and cerebral blood flow in mild traumatic brain injury patients. https://doi.org/10.1371/journal.pone.0134019
Strenziok, M., Parasuraman, R., Clarke, E., Cisler, D. S., Thompson, J. C., & Greenwood, P. M. (2014). Neurocognitive enhancement in older adults: Comparison of three cognitive training tasks to test a hypothesis of training transfer in brain connectivity. NeuroImage, 85(3), 1027–1039.
Wehman, P., Targett, P., West, M., & Kregel, J. (2005). Productive work and employment for persons with traumatic brain injury: what have we learned after 20 years? The Journal of Head Trauma Rehabilitation, 20, 115–127.
Woolrich, M. W., Ripley, B. D., Brady, M., & Smith, S. M. (2001). Temporal autocorrelation in univariate linear modeling of FMRI data. NeuroImage, 14(6), 1370–1386. https://doi.org/10.1006/nimg.2001.0931.
Zhang, K., Johnson, B., Gay, M., Horovitz, S. G., Hallett, M., Sebastianelli, W., & Slobounov, S. (2012). Default mode network in concussed individuals in response to the YMCA physical stress test. Journal of Neurotrauma, 29, 756–765. https://doi.org/10.1089/neu.2011.2125.
Zhou, Y., Milham, M. P., Lui, Y. W., Miles, L., Reaume, J., Sodickson, D. K., Grossman, R. I., & Ge, Y. (2012). Default-mode network disruption in mild traumatic brain injury. Radiology, 265, 882–892. https://doi.org/10.1148/radiol.12120748.
Nieuwenhuis, R., Te Grotenhuis, M., & Pelzer, B. (2012). Tools for detecting influential data in mixed effects models, 4(2). Retrieved from https://repository.ubn.ru.nl//bitstream/handle/2066/103101/103101.pdf?sequence=1.
Acknowledgements
The authors would like to thank A. Safford, B. Brandler, B. Guise, S. Nelson Schmitt, M. Constanzo, D. Pham and B. Robertson for their contributions in study design, data collection and manuscript preparation. The views expressed in this manuscript reflect the views of the authors and do not necessarily reflect the official policy of the Department of the Navy, Department of Defense, or the United States Government. Support for this work has been provided by the Defense and Veterans Brain Injury Center, Uniformed Services University of the Health Sciences, the U.S. Army Medical Research and Materiel Command, and the Center for Neuroscience and Regenerative Medicine Award #306136-8.01-60855.
Author information
Authors and Affiliations
Corresponding author
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
Gimbel, S.I., Ettenhofer, M.L., Cordero, E. et al. Brain bases of recovery following cognitive rehabilitation for traumatic brain injury: a preliminary study. Brain Imaging and Behavior 15, 410–420 (2021). https://doi.org/10.1007/s11682-020-00269-8
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11682-020-00269-8