Abstract
Some of the most disabling aspects of mild traumatic brain injury (mTBI) include lingering deficits in executive functioning. It is known that mTBI can damage white matter tracts, but it remains unknown how this structural brain damage translates into cognitive deficits. This experiment utilized theta band phase synchrony to identify the dysfunctional neural operations that contribute to cognitive problems following mTBI. Sub-acute stage (< 2 weeks) mTBI patients (N = 52) and healthy matched controls (N = 32) completed a control-demanding task with concurrent EEG. Structural MRI was also collected. While there were no performance-specific behavioral differences between groups in the dot probe expectancy task, the degree of theta band phase synchrony immediately following injury predicted the degree of symptom recovery two months later. Although there were no differences in fractional anisotropy (FA) between groups, joint independent components analysis revealed that a smaller network of lower FA-valued voxels contributed to a diminished frontal theta phase synchrony network in the mTBI group. This finding suggests that frontal theta band markers of cognitive control are sensitive to sub-threshold structural aberrations following mTBI.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Data availability
Data and code for this experiment are available on the PRED+CT website: www.predictsite.com; Accession #d010.
Notes
Although the NSI is sometimes reported with a three factor structure (Caplan et al. 2010), the somatic, cognitive, and affective dimensions were highly correlated here (r values from .78 to .84). Given that the somatic dimension has the most items (11 out of 22 items) and there are somatic features in the other dimensions (headache, fatigue), in this sample these sub-scales appear to reflect common variance in a somatic-dominant dimension.
References
Aoki, Y., & Inokuchi, R. (2016). A voxel-based meta-analysis of diffusion tensor imaging in mild traumatic brain injury. Neuroscience and Biobehavioral Reviews, 66, 119–126. https://doi.org/10.1016/j.neubiorev.2016.04.021.
Barch, D. M., Berman, M. G., Engle, R., Jones, J. H., Jonides, J., Macdonald, A., et al. (2009). CNTRICS final task selection: Working memory. Schizophrenia Bulletin, 35(1), 136–152. https://doi.org/10.1093/schbul/sbn153.
Bigler, E. D. (2008). Neuropsychology and clinical neuroscience of persistent post-concussive syndrome. Journal of the International Neuropsychological Society : JINS, 14(1), 1–22.
Blackman, R. K., Crowe, D. A., DeNicola, A. L., Sakellaridi, S., MacDonald, A. W., & Chafee, M. V. (2016). Monkey prefrontal neurons reflect logical operations for cognitive control in a variant of the AX continuous performance task (AX-CPT). The Journal of neuroscience : the official journal of the Society for Neuroscience, 36(14), 4067–4079. https://doi.org/10.1523/JNEUROSCI.3578-15.2016.
Brainard, D. H. (1997). The psychophysics toolbox. Spatial Vision, 10(4), 433–436. https://doi.org/10.1163/156856897X00357.
Busch, R. M., McBride, A., Curtiss, G., & Vanderploeg, R. D. (2005). The components of executive functioning in traumatic brain injury. Journal of Clinical and Experimental Neuropsychology, 27(8), 1022–1032. https://doi.org/10.1080/13803390490919263.
Calhoun, V. (2006). A feature-based approach to combine multimodal brain imaging data. Proceedings 14th Scientific Meeting, International Society for Magnetic Resonance in Medicine, 832. https://doi.org/10.1109/CISS.2014.6814108.
Calhoun, V. D., Liu, J., & Adali, T. (2009). A review of group ICA for fMRI data and ICA for joint inference of imaging, genetic, and ERP data. NeuroImage, 45(1 Suppl), 163–172. https://doi.org/10.1016/j.neuroimage.2008.10.057.
Caplan, L. J., Ivins, B., Poole, J. H., Vanderploeg, R. D., Jaffee, M. S., & Schwab, K. (2010). The structure of postconcussive symptoms in 3 us military samples. Journal of Head Trauma Rehabilitation, 25(6), 447–458. https://doi.org/10.1097/HTR.0b013e3181d5bdbd.
Carney, N., Chesnut, R. M., Maynard, H., Mann, N. C., Patterson, P., & Helfand, M. (1999). Effect of cognitive rehabilitation on outcomes for persons with traumatic brain injury: A systematic review. Journal of Head Trauma Rehabilitation, 14(3), 277–307.
Carroll, L., Cassidy, J. D., Peloso, P., Borg, J., von Holst, H., Holm, L., Paniak, C., & Pépin, M. (2004). Prognosis for mild traumatic brain injury: Results of the who collaborating Centre task force on mild traumatic brain injury. Journal of Rehabilitation Medicine, 36, 84–105. https://doi.org/10.1080/16501960410023859.
Cavanagh, J. F., & Cohen, M. X. (2019). Frontal theta as a model specimen for cortical theta. In P. A. Gable, M. W. Miller, & E. Bernat (Eds.), Handbook of EEG frequency. New York, NY: Oxford University Press.
Cavanagh, J. F., Wilson, J. K., Rieger, R. E., Gill, D., Broadway, J. M., Story-Remer, J. H., et al. (in press). ERPs predict symptomatic distress and recovery in sub-acute mild traumatic brain injury. Neuropsychologia.
Cavanagh, J. F. (2019). Electrophysiology as a theoretical and methodological hub for the neural sciences. In Electrophysiology as a theoretical and methodological hub for the neural sciences, (November 2018), 1–13. https://doi.org/10.1111/psyp.13314.
Cavanagh, J. F., & Frank, M. J. (2014). Frontal theta as a mechanism for cognitive control. Trends in Cognitive Sciences, 18(8), 1–8. https://doi.org/10.1016/j.tics.2014.04.012.
Cavanagh, J. F., Meyer, A., & Hajcak, G. (2017). Error-specific cognitive control alterations in generalized anxiety disorder. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 2(5), 413–420. https://doi.org/10.1016/j.bpsc.2017.01.004.
Chang, L. J., Yarkoni, T., Khaw, M. W., & Sanfey, A. G. (2013). Decoding the role of the insula in human cognition: Functional Parcellation and large-scale reverse inference. Cerebral Cortex, 23(3), 739–749. https://doi.org/10.1093/cercor/bhs065.
Cohen, M. X. (2011). Error-related medial frontal theta activity predicts cingulate-related structural connectivity. NeuroImage, 55(3), 1373–1383. https://doi.org/10.1016/j.neuroimage.2010.12.072.
Cohen, M. X. (2014). Analyzing neural time series data: Theory and practice. Cambridge, MA: MIT Press.
Cooper, P. S., Karayanidis, F., McKewen, M., McLellan-Hall, S., Wong, A. S. W., Skippen, P., & Cavanagh, J. F. (2019). Frontal theta predicts specific cognitive control-induced behavioural changes beyond general reaction time slowing. NeuroImage, 189(November 2018), 130–140. https://doi.org/10.1016/j.neuroimage.2019.01.022.
Cooper, S. R., Gonthier, C., Barch, D. M., & Braver, T. S. (2017). The role of psychometrics in individual differences research in cognition: A case study of the AX-CPT. Frontiers in Psychology, 8(SEP), 1–16. https://doi.org/10.3389/fpsyg.2017.01482.
De La Vega, A., Chang, L. J., Banich, M. T., Wager, T. D., & Yarkoni, T. (2016). Large-Scale Meta-Analysis of Human Medial Frontal Cortex Reveals Tripartite Functional Organization. In Large-scale meta-analysis of human medial frontal cortex reveals tripartite functional organization. https://doi.org/10.1523/JNEUROSCI.4402-15.2016.
Delorme, A., & Makeig, S. (2004). EEGLAB: An open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. Journal of Neuroscience Methods, 134(1), 9–21. https://doi.org/10.1016/j.jneumeth.2003.10.009S0165027003003479 [pii].
Dimoska-Di Marco, A., McDonald, S., Kelly, M., Tate, R., & Johnstone, S. (2011). A meta-analysis of response inhibition and Stroop interference control deficits in adults with traumatic brain injury (TBI). Journal of Clinical and Experimental Neuropsychology, 33(4), 471–485. https://doi.org/10.1080/13803395.2010.533158.
Dockree, P. M., & Robertson, I. H. (2011). Electrophysiological markers of cognitive deficits in traumatic brain injury: a review. International journal of psychophysiology : official journal of the International Organization of Psychophysiology, 82(1), 53–60. https://doi.org/10.1016/j.ijpsycho.2011.01.004.
Dodd, A. B., Epstein, K., Ling, J. M., & Mayer, A. R. (2014). Diffusion tensor imaging findings in semi-acute mild traumatic brain injury. Journal of Neurotrauma, 31(14), 1235–1248. https://doi.org/10.1089/neu.2014.3337.
Dupuis, F., Johnston, K. M., Lavoie, M., Lepore, F., & Lassonde, M. (2000). Concussions in athletes produce brain dysfunction as revealed by event-related potentials. Clinical Neuroscience and Neuropathology, 11(18), 4087–4092. https://doi.org/10.1097/00001756-200012180-00035.
Eierud, C., Craddock, R. C., Fletcher, S., Aulakh, M., King-Casas, B., Kuehl, D., & Laconte, S. M. (2014). Neuroimaging after mild traumatic brain injury: Review and meta-analysis. NeuroImage: Clinical, 4, 283–294. https://doi.org/10.1016/j.nicl.2013.12.009.
Folmer, R. L., Billings, C. J., Diedesch-Rouse, A. C., Gallun, F. J., & Lew, H. L. (2011). Electrophysiological assessments of cognition and sensory processing in TBI: Applications for diagnosis, prognosis and rehabilitation. International Journal of Psychophysiology, 82(1), 4–15. https://doi.org/10.1016/j.ijpsycho.2011.03.005.
Frencham, K. A. R., 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. https://doi.org/10.1080/13803390490520328.
Fries, P. (2009). Neuronal gamma-band synchronization as a fundamental process in cortical computation. Annual Review of Neuroscience, 32, 209–224. https://doi.org/10.1146/annurev.neuro.051508.135603.
Grace, J., & Malloy, P. F. (2001). Frontal systems behavior scale. Professional manual.
Hanley, D., Prichep, L. S., Badjatia, N., Bazarian, J., Chiacchierini, R., Curley, K. C., et al. (2017). A brain electrical activity (EEG) based biomarker of functional impairment in traumatic head injury: a multisite validation trial. Journal of Neurotrauma, 47, neu.2017.5004. https://doi.org/10.1089/neu.2017.5004.
Huang, M.-X., Theilmann, R. J., Robb, A., Angeles, A., Nichols, S., Drake, A., D'Andrea, J., Levy, M., Holland, M., Song, T., Ge, S., Hwang, E., Yoo, K., Cui, L., Baker, D. G., Trauner, D., Coimbra, R., & Lee, R. R. (2009). Integrated imaging approach with MEG and DTI to detect mild traumatic brain injury in military and civilian patients. Journal of Neurotrauma, 26(8), 1213–1226. https://doi.org/10.1089/neu.2008.0672.
Hulkower, M. B., Poliak, D. B., Rosenbaum, S. B., Zimmerman, M. E., & Lipton, M. L. (2013). A decade of DTI in traumatic brain injury: 10 years and 100 articles later. American Journal of Neuroradiology, 34(11), 2064–2074. https://doi.org/10.3174/ajnr.A3395.
Insel, T., Cuthbert, B., Garvey, M., Heinssen, R., Pine, D. S., Quinn, K., Sanislow, C., & Wang, P. (2010). Research domain criteria (RDoC): Toward a new classification framework for research on mental disorders. The American Journal of Psychiatry, 167(7), 748–751.
Kaltiainen, H., Helle, L., Liljeström, M., Renvall, H., & Forss, N. (2018). Theta-band oscillations as an Indicator of mild traumatic brain injury. Brain Topography, 31(6), 1037–1046. https://doi.org/10.1007/s10548-018-0667-2.
Kamins, J., Bigler, E., Covassin, T., Henry, L., Kemp, S., Leddy, J. J., Mayer, A., McCrea, M., Prins, M., Schneider, K. J., Valovich McLeod, T. C., Zemek, R., & Giza, C. C. (2017). What is the physiological time to recovery after concussion? A systematic review. British Journal of Sports Medicine, 51(12), 935–940. https://doi.org/10.1136/bjsports-2016-097464.
Karr, J. E., Areshenkoff, C. N., & Garcia-barrera, M. A. (2014). The Neuropsychological Outcomes of Concussion : A Systematic Review of Meta-Analyses on the Cognitive Sequelae of Mild Traumatic. Brain Injury, 28(3), 321–336. https://doi.org/10.1037/neu0000037.
King, N. S., Crawford, S., Wenden, F. J., Moss, N. E., & Wade, D. T. (1995). The Rivermead post concussion symptoms questionnaire: a measure of symptoms commonly experienced after head injury and its reliability. Journal of Neurology, 242(9), 587–592 http://www.ncbi.nlm.nih.gov/pubmed/8551320. Accessed 20 December 2018.
Kleiner, M., Brainard, D. H., & Pelli, D. (2007). What’s new in Psychtoolbox-3? Perception 36 ECVP Abstract Supplement.
Koo, T. K., & Li, M. Y. (2016). A guideline of selecting and reporting Intraclass correlation coefficients for reliability research. Journal of Chiropractic Medicine, 15(2), 155–163. https://doi.org/10.1016/j.jcm.2016.02.012.
Kreuter, M., Sullivan, M., Dahllöf, A. G., & Siösteen, A. (1998). Partner relationships, functioning, mood and global quality of life in persons with spinal cord injury and traumatic brain injury. Spinal Cord, 36(4), 252–261 http://www.ncbi.nlm.nih.gov/pubmed/9589525.
Larson, M. J., Farrer, T. J., & Clayson, P. E. (2011). Cognitive control in mild traumatic brain injury: Conflict monitoring and conflict adaptation. International journal of psychophysiology : official journal of the International Organization of Psychophysiology, 82(1), 69–78. https://doi.org/10.1016/j.ijpsycho.2011.02.018.
Larson, M. J., Perlstein, W. M., Demery, J. A., & Stigge-Kaufman, D. A. (2006). Cognitive control impairments in traumatic brain injury. Journal of Clinical and Experimental Neuropsychology, 28(6), 968–986. https://doi.org/10.1080/13803390600646860.
Lavoie, M. E., Johnston, K. M., Leclerc, S., Lassonde, M., & Dupuis, F. (2004). Visual P300 effects beyond symptoms in concussed college athletes. Journal of Clinical and Experimental Neuropsychology (Neuropsychology, Development and Cognition: Section A), 26(1), 55–73. https://doi.org/10.1076/jcen.26.1.55.23936.
Ling, J. M., Peña, A., Yeo, R. A., Merideth, F. L., Klimaj, S., Gasparovic, C., & Mayer, A. R. (2012). Biomarkers of increased diffusion anisotropy in semi-acute mild traumatic brain injury: A longitudinal perspective. Brain, 135(Pt 4), 1281–1292. https://doi.org/10.1093/brain/aws073.
Liu, P., Yu, Y., Gao, S., Sun, J., Yang, X., Liu, P., & Qin, W. (2017). Structural integrity in the genu of Corpus callosum predicts conflict-induced functional connectivity between medial frontal cortex and right posterior parietal cortex. Neuroscience, 366(October), 162–171. https://doi.org/10.1016/j.neuroscience.2017.10.017.
MacDonald, A. W., Goghari, V. M., Hicks, B. M., Flory, J. D., Carter, C. S., & Manuck, S. B. (2005). A convergent-divergent approach to context processing, general intellectual functioning, and the genetic liability to schizophrenia. Neuropsychology, 19(6), 814–821. https://doi.org/10.1037/0894-4105.19.6.814.
Mayer, A. R., Ling, J., Mannell, M. V., Gasparovic, C., Phillips, J. P., Doezema, D., et al. (2010). A prospective diffusion tensor imaging study in mild traumatic brain injury. Neurology, 74(8), 643–650. https://doi.org/10.1212/WNL.0b013e3181d0ccdd.
Mayer, A. R., Dodd, A. B., Ling, J. M., Wertz, C. J., Shaff, N. A., Bedrick, E. J., & Viamonte, C. (2017). An evaluation of Z-transform algorithms for identifying subject-specific abnormalities in neuroimaging data. https://doi.org/10.1007/s11682-017-9702-2.
Mayer, A. R., Hanlon, F. M., Claus, E. D., Dodd, A. B., Miller, B., Mickey, J., Quinn, D. K., Hagerty, S. L., Seaman, B., & Hutchison, K. E. (2018). An examination of behavioral and neuronal effects of comorbid traumatic brain injury and alcohol use. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 3(3), 294–302. https://doi.org/10.1016/j.bpsc.2017.09.012.
Mayer, A. R., Ling, J. M., Yang, Z., Pena, A., Yeo, R. A., & Klimaj, S. (2012). Diffusion abnormalities in pediatric mild traumatic brain injury. The Journal of neuroscience : the official journal of the Society for Neuroscience, 32(50), 17961–17969. https://doi.org/10.1523/JNEUROSCI.3379-12.2012.
McDonald, B. C., Flashman, L. A., & Saykin, A. J. (2002). Executive dysfunction following traumatic brain injury: Neural substrates and treatment strategies. NeuroRehabilitation, 17(4), 333–344 http://www.ncbi.nlm.nih.gov/pubmed/12547981.
McMahon, P. J., Hricik, A., Yue, J. K., Puccio, A. M., Inoue, T., Lingsma, H. F., Beers, S. R., Gordon, W. A., Valadka, A. B., Manley, G. T., Okonkwo and the TRACK-TBI investiga D. O, Casey, S. S., Cooper, S. R., Dams-O'Connor, K., Menon, D. K., Sorani, M. D., Yuh, E. L., Mukherjee, P., Schnyer, D. M., & Vassar, M. J. (2014). Symptomatology and functional outcome in mild traumatic brain injury: Results from the prospective TRACK-TBI study. Journal of Neurotrauma, 31(1), 26–33. https://doi.org/10.1089/neu.2013.2984.
Montague, P. R., Dolan, R. J., Friston, K. J., & Dayan, P. (2012). Computational psychiatry. Trends in Cognitive Sciences, 16(1), 72–80. https://doi.org/10.1016/j.tics.2011.11.018.
Moore, R. D., Hillman, C. H., & Broglio, S. P. (2014). The persistent influence of concussive injuries on cognitive control and neuroelectric function. Journal of Athletic Training, 49(1), 24–35. https://doi.org/10.4085/1062-6050-49.1.01.
Moosmann, M., Eichele, T., Nordby, H., Hugdahl, K., & Calhoun, V. D. (2008). Joint independent component analysis for simultaneous EEG-fMRI: Principle and simulation. International Journal of Psychophysiology, 67(3), 212–221. https://doi.org/10.1016/j.ijpsycho.2007.05.016.
Mori, S., & van Zijl, P. (2007). Human White matter atlas. American Journal of Psychiatry, 164(7), 1005–1005. https://doi.org/10.1176/ajp.2007.164.7.1005.
Naunheim, R. S., Treaster, M., English, J., Casner, T., & Chabot, R. (2010). Use of brain electrical activity to quantify traumatic brain injury in the emergency department. Brain Injury, 24(11), 1324–1329. https://doi.org/10.3109/02699052.2010.506862.
Niendam, T. A., Laird, A. R., Ray, K. L., Dean, Y. M., Glahn, D. C., & Carter, C. S. (2012). Meta-analytic evidence for a superordinate cognitive control network subserving diverse executive functions. Cognitive, Affective, & Behavioral Neuroscience, 12(2), 241–268. https://doi.org/10.3758/s13415-011-0083-5.
Nolan, H., Whelan, R., & Reilly, R. B. (2010). FASTER: Fully automated statistical thresholding for EEG artifact rejection. Journal of Neuroscience Methods, 192(1), 152–162. https://doi.org/10.1016/j.jneumeth.2010.07.015.
Nuwer, M. R., Hovda, D. A., Schrader, L. M., & Vespa, P. M. (2005). Routine and quantitative EEG in mild traumatic brain injury. Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology, 116(9), 2001–2025. https://doi.org/10.1016/j.clinph.2005.05.008.
Pelli, D. G. (1997). The VideoToolbox software for visual psychophysics: Transforming numbers into movies. Spatial Vision, 10, 437–442. https://doi.org/10.1163/156856897X00366.
Prichep, L. S., Ghosh Dastidar, S., Jacquin, A., Koppes, W., Miller, J., Radman, T., O׳Neil, B., Naunheim, R., & Huff, J. S. (2014). Classification algorithms for the identification of structural injury in TBI using brain electrical activity. Computers in Biology and Medicine, 53, 125–133. https://doi.org/10.1016/j.compbiomed.2014.07.011.
Quinn, D. K., Mayer, A. R., Master, C. L., & Fann, J. R. (2018). Prolonged postconcussive symptoms. American Journal of Psychiatry, 175(2), 103–111. https://doi.org/10.1176/appi.ajp.2017.17020235.
Roberts, R. M., Mathias, J. L., & Rose, S. E. (2016). Relationship between diffusion tensor imaging (DTI) findings and cognition following pediatric TBI: A meta-analytic review. Developmental Neuropsychology, 41(3), 176–200. https://doi.org/10.1080/87565641.2016.1186167.
Rohling, M. L., Larrabee, G. J., Millis, S. R., Rohling, M. L., Larrabee, G. J., & Millis, S. R. (2012). The “ miserable minority ” following mild traumatic brain injury : Who are they and do meta-analyses Hide them ?, 4046. https://doi.org/10.1080/13854046.2011.647085.
Rose, S. C., Fischer, A. N., & Heyer, G. L. (2015). How long is too long? The lack of consensus regarding the post-concussion syndrome diagnosis. Brain Injury, 29(7–8), 798–803.https://doi.org/10.3109/02699052.2015.1004756, 798.
Ruff, R. (2005). Two Decades of Advances in Understanding of Mild Traumatic Brain Injury, 20(1), 5–18.
Ryman, S. G., Cavanagh, J. F., Wertz, C. J., Shaff, N. A., Dodd, A. B., Stevens, B., Ling, J., Yeo, R. A., Hanlon, F. M., Bustillo, J., Stromberg, S. F., Lin, D. S., Abrams, S., & Mayer, A. R. (2018). Impaired midline Theta power and connectivity during proactive cognitive control in schizophrenia. Biological Psychiatry, 84(9), 675–683. https://doi.org/10.1016/j.biopsych.2018.04.021.
Sander, A. M., & Struchen, M. a. (2011). Interpersonal relationships and traumatic brain injury. The Journal of Head Trauma Rehabilitation, 26(1), 1–3. https://doi.org/10.1097/HTR.0b013e3182068588.
Serino, A., Ciaramelli, E., Di Santantonio, A., Malagù, S., Servadei, F., & Làdavas, E. (2006). Central executive system impairment in traumatic brain injury. Brain injury : [BI], 20(1), 23–32. https://doi.org/10.1080/02699050500309627.
Shackman, A. J., Salomons, T. V., Slagter, H. A., Fox, A. S., Winter, J. J., & Davidson, R. J. (2011). The integration of negative affect, pain and cognitive control in the cingulate cortex. Nature reviews. Neuroscience, 12(3), 154–167. https://doi.org/10.1038/nrn2994.
Siegel, M., Donner, T. H., & Engel, A. K. (2012). Spectral fingerprints of large-scale neuronal interactions. Nature reviews. Neuroscience, 13(2), 121–134. https://doi.org/10.1038/nrn3137.
Singh, A., Pirio Richardson, S., Narayanan, N., & Cavanagh, J. F. (2018). Mid-frontal theta activity is diminished during cognitive control in Parkinson’s disease. Neuropsychologia, 117, 113–122. https://doi.org/10.1016/J.NEUROPSYCHOLOGIA.2018.05.020.
Smith, E. E., & Allen, J. J. B. (2019). Theta-band functional connectivity and single-trial cognitive control in sports-related concussion : Demonstration of proof-of- concept for a potential biomarker of concussion, 1–10. https://doi.org/10.1017/S135561771800108X.
Smith, S. M., Jenkinson, M., Woolrich, M. W., Beckmann, C. F., Behrens, T. E. J., Johansen-Berg, H., Bannister, P. R., de Luca, M., Drobnjak, I., Flitney, D. E., Niazy, R. K., Saunders, J., Vickers, J., Zhang, Y., de Stefano, N., Brady, J. M., & Matthews, P. M. (2004). Advances in functional and structural MR image analysis and implementation as FSL. NeuroImage, 23(Suppl 1), S208–S219. https://doi.org/10.1016/j.neuroimage.2004.07.051.
Souza, A. D., Mollayeva, S., Pacheco, N., & Javed, F. (2019). Measuring change over time : A systematic review of evaluative measures of cognitive functioning in traumatic brain injury, 10(may). https://doi.org/10.3389/fneur.2019.00353.
Stephen, J. M., Coffman, B. A., Jung, R. E., Bustillo, J. R., Aine, C. J., & Calhoun, V. D. (2013). Using joint ICA to link function and structure using MEG and DTI in schizophrenia. NeuroImage, 83, 418–430. https://doi.org/10.1016/j.neuroimage.2013.06.038.
Strauss, S. B., Kim, N., Branch, C. A., Kahn, M. E., Kim, M., Lipton, R. B., Provataris, J. M., Scholl, H. F., Zimmerman, M. E., & Lipton, M. L. (2016). Bidirectional changes in anisotropy are associated with outcomes in mild traumatic brain injury. American Journal of Neuroradiology, 37(11), 1983–1991. https://doi.org/10.3174/ajnr.A4851.
Sui, J., Adali, T., Pearlson, G., Yang, H., Sponheim, S. R., White, T., Calhoun, V. D., & V. D. (2010). A CCA+ICA based model for multi-task brain imaging data fusion and its application to schizophrenia. NeuroImage, 51(1), 123–134. https://doi.org/10.1016/j.neuroimage.2010.01.069.
Thatcher, R. W., Walker, R. A., Gerson, I., & Geisler, F. H. (1989). EEG discriminant analyses of mild head trauma. Electroencephalography and Clinical Neurophysiology, 73(2), 94–106. https://doi.org/10.1016/0013-4694(89)90188-0.
van der Naalt, J., Timmerman, M. E., de Koning, M. E., van der Horn, H. J., Scheenen, M. E., Jacobs, B., Hageman, G., Yilmaz, T., Roks, G., & Spikman, J. M. (2017). Early predictors of outcome after mild traumatic brain injury (UPFRONT): An observational cohort study. The Lancet Neurology, 16(7), 532–540. https://doi.org/10.1016/S1474-4422(17)30117-5.
Wallace, E. J., Mathias, J. L., & Ward, L. (2018). The relationship between diffusion tensor imaging findings and cognitive outcomes following adult traumatic brain injury: A meta-analysis. Neuroscience and Biobehavioral Reviews, 92(March), 93–103. https://doi.org/10.1016/j.neubiorev.2018.05.023.
Weinberg, M. G. H. (2000). Electrophysiological indices of persistent post-concussion symptoms. Brain Injury, 14(9), 815–832. https://doi.org/10.1080/026990500421921.
Wilson, M. J., Harkrider, A. W., & King, K. A. (2014). The effects of visual distracter complexity on auditory evoked p3b in contact sports athletes. Developmental Neuropsychology, 39(2), 113–130. https://doi.org/10.1080/87565641.2013.870177.
Wozniak, J. R., Krach, L., Ward, E., Mueller, B. A., Muetzel, R., Schnoebelen, S., et al. (2007). Neurocognitive and neuroimaging correlates of pediatric traumatic brain injury: A diffusion tensor imaging (DTI) study. Archives of Clinical Neuropsychology, 22(5), 555–568. https://doi.org/10.1016/j.acn.2007.03.004.
Zhao, W., Wu, R., Wang, S., Qi, H., Qian, Y., & Wang, S. (2018). Behavioral and neurophysiological abnormalities during cued continuous performance tasks in patients with mild traumatic brain injury, (November 2017), 1–11. https://doi.org/10.1002/brb3.966.
Acknowledgements
The authors thank Jacqueline Hope Story-Remer, Violet Fratzke, Davin Quinn, Rick Campbell, Ron Yeo, and Jacki Janowich for help with this project and Vince Calhoun for helpful discussions of jICA. This research was supported by an Institutional Development Award (IDeA) from the National Institute of General Medical Sciences of the National Institutes of Health under grant number P20GM109089.
Funding
This study was funded by an Institutional Development Award (IDeA) from the National Institute of General Medical Sciences of the National Institutes of Health under grant number P20GM109089.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
All authors declare that they have no conflicts of interest.
Ethical approval
All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
Informed consent
Informed consent was obtained from all individual participants included in the study.
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Electronic supplementary material
ESM 1
(DOCX 3391 kb)
Rights and permissions
About this article
Cite this article
Cavanagh, J.F., Rieger, R.E., Wilson, J.K. et al. Joint analysis of frontal theta synchrony and white matter following mild traumatic brain injury. Brain Imaging and Behavior 14, 2210–2223 (2020). https://doi.org/10.1007/s11682-019-00171-y
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11682-019-00171-y