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Functional Brain Alterations Associated With Cognitive Control in Blast-Related Mild Traumatic Brain Injury

Published online by Cambridge University Press:  29 June 2018

Danielle R. Sullivan Open the ORCID record for Danielle R. Sullivan [Opens in a new window] ,
Jasmeet P. Hayes ,
Ginette Lafleche ,
David H. Salat  and
Mieke Verfaellie
Danielle R. Sullivan*
Affiliation:
Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, Massachusetts Memory Disorders Research Center, VA Boston Healthcare System, Boston, Massachusetts
Jasmeet P. Hayes
Affiliation:
National Center for PTSD, VA Boston Healthcare System, Boston, Massachusetts Department of Psychiatry, Boston University School of Medicine, Boston, Massachusetts Neuroimaging Research for Veterans Center, VA Boston Healthcare System, Boston, Massachusetts
Ginette Lafleche
Affiliation:
Memory Disorders Research Center, VA Boston Healthcare System, Boston, Massachusetts Department of Psychiatry, Boston University School of Medicine, Boston, Massachusetts
David H. Salat
Affiliation:
Neuroimaging Research for Veterans Center, VA Boston Healthcare System, Boston, Massachusetts Harvard Medical School, Harvard University, Boston, Massachusetts
Mieke Verfaellie
Affiliation:
Memory Disorders Research Center, VA Boston Healthcare System, Boston, Massachusetts Department of Psychiatry, Boston University School of Medicine, Boston, Massachusetts
*
Correspondence and reprint requests to: Danielle R. Sullivan, Memory Disorders Research Center, VA Boston Healthcare System (151A), 150 S. Huntington Avenue, Boston, MA 02130. E-mail: drsulliv@bu.edu
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Abstract

Objectives: Research on the cognitive sequelae of mild traumatic brain injury (mTBI) suggests that, despite generally rapid recovery, difficulties may persist in the domain of cognitive control. The goal of this study was to examine whether individuals with chronic blast-related mTBI show behavioral or neural alterations associated with cognitive control. Methods: We collected event-related functional magnetic resonance imaging (fMRI) data during a flanker task in 17 individuals with blast-related mTBI and 16 individuals with blast-exposure without TBI (control). Results: Groups did not significantly differ in behavioral measures of cognitive control. Relative to the control group, the mTBI group showed greater deactivation of regions associated with the default mode network during the processing of errors. Additionally, error processing in the mTBI group was associated with enhanced negative coupling between the default mode network and the dorsal anterior cingulate cortex as well as the dorsolateral prefrontal cortex, regions of the salience and central executive networks that are associated with cognitive control. Conclusions: These results suggest that deactivation of default mode network regions and associated enhancements of connectivity with cognitive control regions may act as a compensatory mechanism for successful cognitive control task performance in mTBI. (JINS, 2018, 24, 1–11)

Keywords

mTBITask fMRIDefault mode networkSalience networkCentral executive networkOEF/OIF
Type
Research Articles
Information
Journal of the International Neuropsychological Society , Volume 24 , Issue 7 , August 2018 , pp. 662 - 672
Copyright
Copyright © The International Neuropsychological Society 2018 

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References

REFERENCES

American Congress of Rehabilitation Medicine. (1993). Definition of mild traumatic brain injury. The Journal of Head Trauma Rehabilitation, 8(3), 86–87.Google Scholar
Andrews-Hanna, J.R., Reidler, J.S., Sepulcre, J., Poulin, R., & Buckner, R.L. (2010). Functional-anatomic fractionation of the brain’s default network. Neuron, 65(4), 550–562.Google Scholar
Aoki, Y., Inokuchi, R., Gunshin, M., Yahagi, N., & Suwa, H. (2012). Diffusion tensor imaging studies of mild traumatic brain injury: A meta-analysis. Journal of Neurology, Neurosurgery, & Psychiatry, 83, 870–876.Google Scholar
Beckmann, C.F., Jenkinson, M., & Smith, S.M. (2003). General multilevel linear modeling for group analysis in FMRI. NeuroImage, 20(2), 1052–1063. doi: 10.1016/S1053-8119(03)00435-X Google Scholar
Belanger, H.G., & Vanderploeg, R.D. (2005). The neuropsychological impact of sports-related concussion: A meta-analysis. Journal of the International Neuropsychological Society, 11(04), 345–357. doi: 10.1017/S1355617705050411 Google Scholar
Blake, D.D., Weathers, F.W., Nagy, L.M., Kaloupek, D.G., Gusman, F.D., Charney, D.S., &&Keane, T.M. (1995). The development of a clinician-adminstered PTSD Scale. Journal of Traumatic Stress, 8(1), 75–90.Google Scholar
Bonnelle, V., Ham, T.E., Leech, R., Kinnunen, K.M., Mehta, M.A., Greenwood, R.J., && Sharp, D.J. (2012). Salience network integrity predicts default mode network function after traumatic brain injury. Proceedings of the National Academy of Sciences of the United States of America, 109(12), 4690–4695. doi: 1113455109 Google Scholar
Botvinick, M.M., Braver, T.S., Barch, D.M., Carter, C.S., & Cohen, J.D. (2001). Conflict monitoring and cognitive control. Psychology Review, 108(3), 624–652.Google Scholar
Broglio, S.P., Pontifex, M.B., O’Connor, P., & Hillman, C.H. (2009). The persistent effects of concussion on neuroelectric indices of attention. J Neurotrauma, 26(9), 1463–1470. doi: 10.1089/neu.2008-0766 Google Scholar
Bunge, S.A., Hazeltine, E., Scanlon, M.D., Rosen, A.C., & Gabrieli, J.D. (2002). Dissociable contributions of prefrontal and parietal cortices to response selection. NeuroImage, 17(3), 1562–1571. doi: S1053811902912528 Google Scholar
Corrigan, J.D., & Bogner, J. (2007). Screening and identification of TBI. Journal of Head Trauma Rehabilitation, 22(6), 315–317.Google Scholar
Dosenbach, N.U., Fair, D.A., Cohen, A.L., Schlaggar, B.L., & Petersen, S.E. (2008). A dual-networks architecture of top-down control. Trends in Cognitive Sciences, 12(3), 99–105.Google Scholar
Fischer, B.L., Parsons, M., Durgerian, S., Reece, C., Mourany, L., Lowe, M.J., & Rao, S.M. (2014). Neural activation during response inhibition differentiates blast from mechanical causes of mild to moderate traumatic brain injury. Journal of Neurotrauma, 31(2), 169–179. doi: 10.1089/neu.2013.2877 Google Scholar
Fox, M.D., Snyder, A.Z., Vincent, J.L., Corbetta, M., Van Essen, D.C., & Raichle, M.E. (2005). The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proceedings of the National Academy of Sciences of the United States of America, 102(27), 9673–9678. doi: 0504136102 Google Scholar
Fransson, P. (2006). How default is the default mode of brain function? Further evidence from intrinsic BOLD signal fluctuations. Neuropsychologia, 44(14), 2836–2845. doi: 10.1016/j.neuropsychologia.2006.06.017 Google Scholar
Frencham, K.A., Fox, A.M., & Maybery, M.T. (2005). Neuropsychological studies of mild traumatic brain injury: A meta-analytic review of research since 1995. Journal of Clinical and Experimental Neuropsychology, 27(3), 334–351. doi: 10.1080/13803390490520328 Google Scholar
Friston, K.J., Buechel, C., Fink, G.R., Morris, J., Rolls, E., & Dolan, R.J. (1997). Psychophysiological and modulatory interactions in neuroimaging. NeuroImage, 6(3), 218–229. doi: 10.1006/nimg.1997.0291 Google Scholar
Gusnard, D.A., Akbudak, E., Shulman, G.L., & Raichle, M.E. (2001). Medial prefrontal cortex and self-referential mental activity: Relation to a default mode of brain function. Proceedings of the National Academy of Sciences of the United States of America, 98(7), 4259–4264. doi: 10.1073/pnas.071043098 Google Scholar
Hayes, J.P., Bigler, E.D., & Verfaellie, M. (2016). Traumatic brain injury as a disorder of brain connectivity. Journal of the International Neuropsychological Society, 22(2), 120–137.Google Scholar
Hayes, J.P., Miller, D.R., Lafleche, G., Salat, D.H., & Verfaellie, M. (2015). The nature of white matter abnormalities in blast-related mild traumatic brain injury. NeuroImage: Clinical, 8, 148–156.Google Scholar
Hazeltine, E., Bunge, S.A., Scanlon, M.D., & Gabrieli, J.D. (2003). Material-dependent and material-independent selection processes in the frontal and parietal lobes: An event-related fMRI investigation of response competition. Neuropsychologia, 41(9), 1208–1217.Google Scholar
Jenkinson, M., Bannister, P., Brady, M., & Smith, S. (2002). Improved optimization for the robust and accurate linear registration and motion correction of brain images. NeuroImage, 17(2), 825–841.Google Scholar
Kelly, A.C., Uddin, L.Q., Biswal, B.B., Castellanos, F.X., & Milham, M.P. (2008). Competition between functional brain networks mediates behavioral variability. NeuroImage, 39(1), 527–537.Google Scholar
Kerns, J.G., Cohen, J.D., MacDonald, A.W. III, Cho, R.Y., Stenger, V.A., & Carter, C.S. (2004). Anterior cingulate conflict monitoring and adjustments in control. Science, 303(5660), 1023–1026. doi: 10.1126/science.1089910303/5660/1023 Google Scholar
MacDonald, A.W. III, Cohen, J.D., Stenger, V.A., & Carter, C.S. (2000). Dissociating the role of the dorsolateral prefrontal and anterior cingulate cortex in cognitive control. Science, 288(5472), 1835–1838. doi: 8537 Google Scholar
Matthews, S., Simmons, A., & Strigo, I. (2011). The effects of loss versus alteration of consciousness on inhibition-related brain activity among individuals with a history of blast-related concussion. Psychiatry Research: Neuroimaging, 191(1), 76–79.Google Scholar
Mayer, A.R., Yang, Z., Yeo, R.A., Pena, A., Ling, J.M., Mannell, M.V., Stippler, M., && Mojtahed, K. (2012). A functional MRI study of multimodal selective attention following mild truamatic brain injury. Brain Imaging and Behavior, 6(2), 343–354. doi: http://dx.doi.org/10.1007/s11682-012-9178-z Google Scholar
Mayer, A.R., Hanlon, F.M., Dodd, A.B., Ling, J.M., Klimaj, S.D., & Meier, T.B. (2015). A functional magnetic resonance imaging study of cognitive control and neurosensory deficits in mild traumatic brain injury. Human Brain Mapping, 36(11), 4394–4406. doi: 10.1002/hbm.22930 Google Scholar
McCrea, M.A. (2008). Mild traumatic brain injury and postconcussion syndrome. New York: Oxford University Press.Google Scholar
McKiernan, K.A., Kaufman, J.N., Kucera-Thompson, J., & Binder, J.R. (2003). A parametric manipulation of factors affecting task-induced deactivation in functional neuroimaging. Journal of Cognitive Neuroscience, 15(3), 394–408. doi: 10.1162/089892903321593117 Google Scholar
Menon, V., Adleman, N.E., White, C.D., Glover, G.H., & Reiss, A.L. (2001). Error-related brain activation during a Go/NoGo response inhibition task. Human Brain Mapping, 12, 131–143.Google Scholar
Menon, V., & Uddin, L.Q. (2010). Saliency, switching, attention and control: A network model of insula function. Brain Structure & Function, 214(5-6), 655–667. doi: 10.1007/s00429-010-0262-0 Google Scholar
Miller, D.R., Hayes, J.P., Lafleche, G., Salat, D.H., & Verfaellie, M. (2016). White matter abnormalities are associated with chronic postconcussion symptoms in blast-related mild traumatic brain injury. Human Brain Mapping, 37(1), 220–229.Google Scholar
Nee, D.E., Wager, T.D., & Jonides, J. (2007). Interference resolution: Insights from a meta-analysis of neuroimaging tasks. Cognitive, Affective & Behavioral Neuroscience, 7(1), 1–17.Google Scholar
O’Reilly, J.X., Woolrich, M.W., Behrens, T.E., Smith, S.M., & Johansen-Berg, H. (2012). Tools of the trade: Psychophysiological interactions and functional connectivity. Social Cognitive and Affective Neuroscience, 7(5), 604–609. doi: 10.1093/scan/nss055 Google Scholar
Pontifex, M.B., O’Connor, P.M., Broglio, S.P., & Hillman, C.H. (2009). The association between mild traumatic brain injury history and cognitive control. Neuropsychologia, 47(14), 3210–3216.Google Scholar
Pruim, R.H., Mennes, M., Buitelaar, J.K., & Beckmann, C.F. (2015). Evaluation of ICA-AROMA and alternative strategies for motion artifact removal in resting state fMRI. NeuroImage, 112, 278–287. doi: 10.1016/j.neuroimage.2015.02.063 Google Scholar
Pruim, R.H.R., Mennes, M., van Rooij, D., Llera, A., Buitelaar, J.K., & Beckmann, C.F. (2015). ICA-AROMA: A robust ICA-based strategy for removing motion artifacts from fMRI data. NeuroImage, 112, 267–277. doi: http://dx.doi.org/10.1016/j.neuroimage.2015.02.064 Google Scholar
Raichle, M.E., MacLeod, A.M., Snyder, A.Z., Powers, W.J., Gusnard, D.A., & Shulman, G.L. (2001). A default mode of brain function. Proceedings of the National Academy of Sciences of the United States of America, 98(2), 676–682. doi: 10.1073/pnas.98.2.676 Google Scholar
Robinson, M.E., Lindemer, E.R., Fonda, J.R., Milberg, W.P., McGlinchey, R.E., & Salat, D.H. (2015). Close-range blast exposure is associated with altered functional connectivity in Veterans independent of concussion symptoms at time of exposure. Human Brain Mapping, 36(3), 911–922. doi: 10.1002/hbm.22675 Google Scholar
Scheibel, R.S., Newsome, M.R., Troyanskaya, M., Lin, X., Steinberg, J.L., Radaideh, M., && Levin, H.S. (2012). Altered brain activation in military personnel with one or more traumatic brain injuries following blast. Journal of the International Neuropsychological Society, 18(1), 89–100. doi: S1355617711001433 Google Scholar
Seeley, W.W., Menon, V., Schatzberg, A.F., Keller, J., Glover, G.H., Kenna, H., & Greicius, M.D. (2007). Dissociable intrinsic connectivity networks for salience processing and executive control. The Journal of Neuroscience, 27(9), 2349–2356. doi: 27/9/2349 Google Scholar
Seignourel, P.J., Robins, D.L., Larson, M.J., Demery, J.A., Cole, M., & Perlstein, W.M. (2005). Cognitive control in closed head injury: Context maintenance dysfunction or prepotent response inhibition deficit? Neuropsychology, 19(5), 578–590. doi: 2005-11412-003 Google Scholar
Singh, K.D., & Fawcett, I. (2008). Transient and linearly graded deactivation of the human default-mode network by a visual detection task. NeuroImage, 41(1), 100–112.Google Scholar
Smith, S.M. (2002). Fast robust automated brain extraction. Human Brain Mapping, 17(3), 143–155. doi: 10.1002/hbm.10062 Google Scholar
Sridharan, D., Levitin, D.J., & Menon, V. (2008). A critical role for the right fronto-insular cortex in switching between central-executive and default-mode networks. Proceedings of the National Academy of Sciences of the United States of America, 105(34), 12569–12574. doi: 0800005105 Google Scholar
Taber, K.H., Hurley, R.A., Haswell, C.C., Rowland, J.A., Hurt, S.D., Lamar, C.D., && Morey, R.A. (2015). White matter compromise in veterans exposed to primary blast forces. The Journal of Head Trauma Rehabilitation, 30(1), E15–E25. doi: 10.1097/HTR.0000000000000030 Google Scholar
Taylor, S.F., Stern, E.R., & Gehring, W.J. (2007). Neural systems for error monitoring: Recent findings and theoretical perspectives. Neuroscientist, 13(2), 160–172. doi: 10.1177/1073858406298184 Google Scholar
Tombaugh, T.N., & Tombaugh, P.W. (1996). Test of Memory Malingering: TOMM. Tonawanda, NY: Multi-Health Systems.Google Scholar
Uddin, L.Q., Kelly, A.M., Biswal, B.B., Castellanos, F.X., & Milham, M.P. (2009). Functional connectivity of default mode network components: Correlation, anticorrelation, and causality. Human Brain Mapping, 30(2), 625–637. doi: 10.1002/hbm.20531 Google Scholar
Ullsperger, M., & von Cramon, D.Y. (2001). Subprocesses of performance monitoring: A dissociation of error processing and response competition revealed by event-related fMRI and ERPs. NeuroImage, 14(6), 1387–1401. doi: 10.1006/nimg.2001.0935S1053-8119(01)90935-8 Google Scholar
Verfaellie, M., Lafleche, G., Spiro, A. III, Tun, C., & Bousquet, K. (2013). Chronic postconcussion symptoms and functional outcomes in OEF/OIF veterans with self-report of blast exposure. Journal of the International Neuropsychological Society, 19(1), 1–10. doi: S1355617712000902 Google Scholar
Weathers, F., Huska, J., & Keane, T. (1991). The PTSD Checklist Military Version (PCL-M). Boston, MA: National Center for PTSD.Google Scholar
Wilkins, K.C., Lang, A.J., & Norman, S.B. (2011). Synthesis of the psychometric properties of the PTSD checklist (PCL) military, civilian, and specific versions. Depression and Anxiety, 28(7), 596–606.Google Scholar
Woolrich, M. (2008). Robust group analysis using outlier inference. NeuroImage, 41(2), 286–301. doi: 10.1016/j.neuroimage.2008.02.042 Google Scholar
Woolrich, M.W., Behrens, T.E., Beckmann, C.F., Jenkinson, M., & Smith, S.M. (2004). Multilevel linear modelling for FMRI group analysis using Bayesian inference. NeuroImage, 21(4), 1732–1747. doi: 10.1016/j.neuroimage.2003.12.023 Google Scholar
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