Abstract
Because of their high prevalence, heterogeneous clinical presentation, and wide-ranging sequelae, concussions are a challenging neurological condition, especially in children. Shearing forces transmitted across the brain during concussions often result in white matter damage. The neuropathological impact of concussions has been discerned from animal studies and includes inflammation, demyelination, and axonal loss. These pathologies can overlap during the sub-acute stage of recovery. However, due to the challenges of accurately modeling complex white matter structure, these neuropathologies have not yet been differentiated in children in vivo. In the present study, we leveraged recent advances in diffusion imaging modeling, tractography, and tractometry to better understand the neuropathology underlying working memory problems in concussion. Studying a sample of 16 concussed and 46 healthy youths, we used novel tractography methods to isolate 11 working memory tracks. Along these tracks, we measured fractional anisotropy, diffusivities, track volume, apparent fiber density, and free water fraction. In three tracks connecting the right thalamus to the right dorsolateral prefrontal cortex (DLPFC), we found microstructural differences suggestive of myelin alterations. In another track connecting the left anterior-cingulate cortex with the left DLPFC, we found microstructural changes suggestive of axonal loss. Structural differences and tractography reconstructions were reproduced using test–retest analyses. White matter structure in the three thalamo-prefrontal tracks, but not the cingulo-prefrontal track, appeared to play a key role in working memory function. The present results improve understanding of working memory neuropathology in concussions, which constitutes an important step toward develo** neuropathologically informed biomarkers of concussion in children.
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Notes
Throughout the manuscript we refer to real white matter bundles as “tracts”, and reconstructions of those tracts from tractography as “tracks”.
References
Abdel-Dayem HM, Abu-Judeh H, Kumar M, Atay S, Naddaf S, El-Zeftawy H, Luo JQ (1998) SPECT brain perfusion abnormalities in mild or moderate traumatic brain injury. Clin Nucl Med 23:309–317
Anderson CV, Wood DM, Bigler ED, Blatter DD (1996) Lesion volume, injury severity, and thalamic integrity following head injury. J Neurotrauma 13:59–65. https://doi.org/10.1089/neu.1996.13.59
Andersson JLR, Sotiropoulos SN (2016) An integrated approach to correction for off-resonance effects and subject movement in diffusion MR imaging. Neuroimage 125:1063–1078. https://doi.org/10.1016/j.neuroimage.2015.10.019
Avants BB, Epstein CL, Grossman M, Gee JC (2008) Symmetric diffeomorphic image registration with cross-correlation: evaluating automated labeling of elderly and neurodegenerative brain. Med Image Anal 12:26–41. https://doi.org/10.1016/j.media.2007.06.004
Avants BB, Tustison NJ, Song G, Cook PA, Klein A, Gee JC (2011) A reproducible evaluation of ANTs similarity metric performance in brain image registration. Neuroimage 54:2033–2044. https://doi.org/10.1016/j.neuroimage.2010.09.025
Bareyre F, Wahl F, McIntosh TK, Stutzmann JM (1997) Time course of cerebral edema after traumatic brain injury in rats: effects of riluzole and mannitol. J Neurotrauma 14:839–849. https://doi.org/10.1089/neu.1997.14.839
Bayly PV, Cohen TS, Leister EP, Ajo D, Leuthardt EC, Genin GM (2005) Deformation of the human brain induced by mild acceleration. J Neurotrauma 22:845–856. https://doi.org/10.1089/neu.2005.22.845
Bigler ED, Maxwell WL (2012) Neuropathology of mild traumatic brain injury: relationship to neuroimaging findings. Brain Imaging Behav 6:108–136. https://doi.org/10.1007/s11682-011-9145-0
Bolkan SS et al (2017) Thalamic projections sustain prefrontal activity during working memory maintenance. Nat Neurosci 20:987–996. https://doi.org/10.1038/nn.4568
Budde MD, Janes L, Gold E, Turtzo LC, Frank JA (2011) The contribution of gliosis to diffusion tensor anisotropy and tractography following traumatic brain injury: validation in the rat using Fourier analysis of stained tissue sections. Brain 134:2248–2260. https://doi.org/10.1093/brain/awr161
Carroll LJ et al (2004) Prognosis for mild traumatic brain injury: results of the WHO Collaborating Centre Task Force on Mild Traumatic Brain Injury. J Rehabil Med (43 Suppl):84–105
Cassidy JD et al (2004) Incidence, risk factors and prevention of mild traumatic brain injury: results of the WHO Collaborating Centre Task Force on Mild Traumatic Brain Injury. J Rehabil Med (43 Suppl):28–60
Chen JK, Johnston KM, Frey S, Petrides M, Worsley K, Ptito A (2004) Functional abnormalities in symptomatic concussed athletes: an fMRI study. Neuroimage 22:68–82. https://doi.org/10.1016/j.neuroimage.2003.12.032
Chen JK, Johnston KM, Collie A, McCrory P, Ptito A (2007) A validation of the post concussion symptom scale in the assessment of complex concussion using cognitive testing and functional MRI. J Neurol Neurosurg Psychiatry 78:1231–1238. https://doi.org/10.1136/jnnp.2006.110395
Churchill NW, Hutchison MG, Richards D, Leung G, Graham SJ, Schweizer TA (2017) Neuroimaging of sport concussion: persistent alterations in brain structure and function at medical clearance. Sci Rep 7:8297. https://doi.org/10.1038/s41598-017-07742-3
Daducci A, Canales-Rodriguez EJ, Zhang H, Dyrby TB, Alexander DC, Thiran JP (2015) Accelerated microstructure imaging via convex optimization (AMICO) from diffusion MRI data. Neuroimage 105:32–44. https://doi.org/10.1016/j.neuroimage.2014.10.026
Dean PJ, O'Neill D, Sterr A (2012) Post-concussion syndrome: prevalence after mild traumatic brain injury in comparison with a sample without head injury. Brain Inj 26:14–26. https://doi.org/10.3109/02699052.2011.635354
Dell'Acqua F, Simmons A, Williams SC, Catani M (2013) Can spherical deconvolution provide more information than fiber orientations? Hindrance modulated orientational anisotropy, a true-tract specific index to characterize white matter diffusion. Hum Brain Mapp 34:2464–2483. https://doi.org/10.1002/hbm.22080
Descoteaux M, Deriche R, Knosche TR, Anwander A (2009) Deterministic and probabilistic tractography based on complex fibre orientation distributions. IEEE Trans Med Imaging 28:269–286. https://doi.org/10.1109/TMI.2008.2004424
Dodd AB, Epstein K, Ling JM, Mayer AR (2014) Diffusion tensor imaging findings in semi-acute mild traumatic brain injury. J Neurotrauma 31:1235–1248. https://doi.org/10.1089/neu.2014.3337
Douaud G et al (2011) DTI measures in crossing-fibre areas: increased diffusion anisotropy reveals early white matter alteration in MCI and mild Alzheimer's disease. Neuroimage 55:880–890. https://doi.org/10.1016/j.neuroimage.2010.12.008
Dyrby TB, Lundell H, Burke MW, Reislev NL, Paulson OB, Ptito M, Siebner HR (2014) Interpolation of diffusion weighted imaging datasets. Neuroimage 103:202–213. https://doi.org/10.1016/j.neuroimage.2014.09.005
Fan L et al (2016) the human brainnetome atlas: a new brain atlas based on connectional architecture. Cereb Cortex 26:3508–3526. https://doi.org/10.1093/cercor/bhw157
Faul M, Xu L, Wald M, Coronado V (2010) Traumatic brain injury in the United States: emergency department visits, hospitalizations, and deaths. Centers for Disease Control and Prevention National Center for Injury Prevention and Control, Atlanta
Garyfallidis E et al (2014) Dipy, a library for the analysis of diffusion MRI data. Front Neuroinform 8:8. https://doi.org/10.3389/fninf.2014.00008
Ge Y et al (2009) Assessment of thalamic perfusion in patients with mild traumatic brain injury by true FISP arterial spin labelling MR imaging at 3T. Brain Inj 23:666–674. https://doi.org/10.1080/02699050903014899
Girard G, Whittingstall K, Deriche R, Descoteaux M (2014) Towards quantitative connectivity analysis: reducing tractography biases. Neuroimage 98:266–278. https://doi.org/10.1016/j.neuroimage.2014.04.074
Goswami R et al (2016) Frontotemporal correlates of impulsivity and machine learning in retired professional athletes with a history of multiple concussions. Brain Struct Funct 221:1911–1925. https://doi.org/10.1007/s00429-015-1012-0
Grossman EJ, Inglese M (2016) The role of thalamic damage in mild traumatic brain injury. J Neurotrauma 33:163–167. https://doi.org/10.1089/neu.2015.3965
Grossman EJ et al (2012) Thalamus and cognitive impairment in mild traumatic brain injury: a diffusional kurtosis imaging study. J Neurotrauma 29:2318–2327. https://doi.org/10.1089/neu.2011.1763
Guberman G (2019) Montreal Neurological Institute—pediatric concussion. https://doi.org/10.17605/OSF.IO/QKVS7
Harsan LA et al (2006) Brain dysmyelination and recovery assessment by noninvasive in vivo diffusion tensor magnetic resonance imaging. J Neurosci Res 83:392–402. https://doi.org/10.1002/jnr.20742
Hayes JP, Bigler ED, Verfaellie M (2016) Traumatic brain injury as a disorder of brain connectivity. J Int Neuropsychol Soc 22:120–137. https://doi.org/10.1017/S1355617715000740
Henninger N et al (2007) Differential recovery of behavioral status and brain function assessed with functional magnetic resonance imaging after mild traumatic brain injury in the rat. Crit Care Med 35:2607–2614. https://doi.org/10.1097/01.CCM.0000286395.79654.8D
Hessen E, Nestvold K, Anderson V (2007) Neuropsychological function 23 years after mild traumatic brain injury: a comparison of outcome after paediatric and adult head injuries. Brain Inj 21:963–979. https://doi.org/10.1080/02699050701528454
Holland RL (2016) What makes a good biomarker? Adv Precis Med 1:66–77
Hulkower MB, Poliak DB, Rosenbaum SB, Zimmerman ME, Lipton ML (2013) A decade of DTI in traumatic brain injury: 10 years and 100 articles later. Am J Neuroradiol 34:2064–2074. https://doi.org/10.3174/ajnr.A3395
Jantzen KJ, Anderson B, Steinberg FL, Kelso JA (2004) A prospective functional MR imaging study of mild traumatic brain injury in college football players. Am J Neuroradiol 25:738–745
Jeurissen B, Leemans A, Tournier JD, Jones DK, Sijbers J (2013) Investigating the prevalence of complex fiber configurations in white matter tissue with diffusion magnetic resonance imaging. Hum Brain Mapp 34:2747–2766. https://doi.org/10.1002/hbm.22099
Jones DK (2004) The effect of gradient sampling schemes on measures derived from diffusion tensor MRI: a Monte Carlo study. Magn Reson Med 51:807–815. https://doi.org/10.1002/mrm.20033
Jones DK, Knosche TR, Turner R (2013) White matter integrity, fiber count, and other fallacies: the do's and don'ts of diffusion MRI. Neuroimage 73:239–254. https://doi.org/10.1016/j.neuroimage.2012.06.081
Keightley ML, Saluja RS, Chen JK, Gagnon I, Leonard G, Petrides M, Ptito A (2014) A functional magnetic resonance imaging study of working memory in youth after sports-related concussion: is it still working? J Neurotrauma 31:437–451. https://doi.org/10.1089/neu.2013.3052
Kristman VL et al (2014) Methodological issues and research recommendations for prognosis after mild traumatic brain injury: results of the International Collaboration on Mild Traumatic Brain Injury Prognosis. Arch Phys Med Rehabil 95:S265–277. https://doi.org/10.1016/j.apmr.2013.04.026
Landre N, Poppe CJ, Davis N, Schmaus B, Hobbs SE (2006) Cognitive functioning and postconcussive symptoms in trauma patients with and without mild TBI. Arch Clin Neuropsychol 21:255–273. https://doi.org/10.1016/j.acn.2005.12.007
Lewine JD, Davis JT, Sloan JH, Kodituwakku PW, Orrison WW Jr (1999) Neuromagnetic assessment of pathophysiologic brain activity induced by minor head trauma. Am J Neuroradiol 20:857–866
Little DM et al (2010) Thalamic integrity underlies executive dysfunction in traumatic brain injury. Neurology 74:558–564. https://doi.org/10.1212/WNL.0b013e3181cff5d5
Lovell MR et al (2006) Measurement of symptoms following sports-related concussion: reliability and normative data for the post-concussion scale. Appl Neuropsychol 13:166–174. https://doi.org/10.1207/s15324826an1303_4
Mac Donald CL et al (2011) Detection of blast-related traumatic brain injury in U.S. military personnel. N Engl J Med 364:2091–2100. https://doi.org/10.1056/NEJMoa1008069
Mac Donald CL, Dikranian K, Bayly P, Holtzman D, Brody D (2007) Diffusion tensor imaging reliably detects experimental traumatic axonal injury and indicates approximate time of injury. J Neurosci 27:11869–11876. https://doi.org/10.1523/JNEUROSCI.3647-07.2007
Maintz JA, Viergever MA (1998) A survey of medical image registration. Med Image Anal 2:1–36
Mayer AR et al (2018) Advanced biomarkers of pediatric mild traumatic brain injury: progress and perils. Neurosci Biobehav Rev. https://doi.org/10.1016/j.neubiorev.2018.08.002
McAllister TW et al (1999) Brain activation during working memory 1 month after mild traumatic brain injury: a functional MRI study. Neurology 53:1300–1308
McAllister TW, Sparling MB, Flashman LA, Guerin SJ, Mamourian AC, Saykin AJ (2001) Differential working memory load effects after mild traumatic brain injury. Neuroimage 14:1004–1012. https://doi.org/10.1006/nimg.2001.0899
McKee AC et al (2009) Chronic traumatic encephalopathy in athletes: progressive tauopathy after repetitive head injury. J Neuropathol Exp Neurol 68:709–735
McKinlay A, Corrigan J, Horwood LJ, Fergusson DM (2014) Substance abuse and criminal activities following traumatic brain injury in childhood, adolescence, and early adulthood. J Head Trauma Rehabil 29:498–506. https://doi.org/10.1097/HTR.0000000000000001
Meehan WP 3rd, Mannix RC, O'Brien MJ, Collins MW (2013) The prevalence of undiagnosed concussions in athletes. Clin J Sport Med 23:339–342. https://doi.org/10.1097/JSM.0b013e318291d3b3
Mierzwa AJ, Marion CM, Sullivan GM, McDaniel DP, Armstrong RC (2015) Components of myelin damage and repair in the progression of white matter pathology after mild traumatic brain injury. J Neuropathol Exp Neurol 74:218–232. https://doi.org/10.1097/NEN.0000000000000165
Mito R et al (2018) Fibre-specific white matter reductions in Alzheimer's disease and mild cognitive impairment. Brain. https://doi.org/10.1093/brain/awx355
Orlovska S, Pedersen MS, Benros ME, Mortensen PB, Agerbo E, Nordentoft M (2014) Head injury as risk factor for psychiatric disorders: a nationwide register-based follow-up study of 113,906 persons with head injury. Am J Psychiatry 171:463–469
Palacios E et al (2018) The evolution of white matter changes after mild traumatic brain injury: a DTI and NODDI study. bioRxiv. https://doi.org/10.1101/345629
Pardini JE, Pardini DA, Becker JT, Dunfee KL, Eddy WF, Lovell MR, Welling JS (2010) Postconcussive symptoms are associated with compensatory cortical recruitment during a working memory task. Neurosurgery 67:1020–1027. https://doi.org/10.1227/NEU.0b013e3181ee33e2(discussion 1027–1028)
Pasternak O, Sochen N, Gur Y, Intrator N, Assaf Y (2009) Free water elimination and map** from diffusion MRI. Magn Reson Med 62:717–730. https://doi.org/10.1002/mrm.22055
Pasternak O, Shenton ME, Westin CF (2012) Estimation of extracellular volume from regularized multi-shell diffusion MRI. Med Image Comput Comput Assist Interv 15:305–312
Pasternak O, Kubicki M, Shenton ME (2016) vivo imaging of neuroinflammation in schizophrenia. Schizophr Res 173:200–212. https://doi.org/10.1016/j.schres.2015.05.034
Peeters W, van den Brande R, Polinder S, Brazinova A, Steyerberg EW, Lingsma HF, Maas AI (2015) Epidemiology of traumatic brain injury in Europe. Acta Neurochir (Wien) 157:1683–1696. https://doi.org/10.1007/s00701-015-2512-7
Petrides M, Alivisatos B, Meyer E, Evans AC (1993) Functional activation of the human frontal cortex during the performance of verbal working memory tasks. Proc Natl Acad Sci USA 90:878–882
Petrides M, Frey S, Chen J-K (2001) Increased activation of the mid-dorsolateral frontal cortex during the monitoring of abstract visual and verbal stimuli. Neuroimage 6:721
Pierpaoli C, Basser PJ (1996) Toward a quantitative assessment of diffusion anisotropy. Magn Reson Med 36:893–906
Pierpaoli C, Barnett A, Pajevic S, Chen R, Penix LR, Virta A, Basser P (2001) Water diffusion changes in Wallerian degeneration and their dependence on white matter architecture. Neuroimage 13:1174–1185. https://doi.org/10.1006/nimg.2001.0765
Powell JL, Parkes L, Kemp GJ, Sluming V, Barrick TR, Garcia-Finana M (2012) The effect of sex and handedness on white matter anisotropy: a diffusion tensor magnetic resonance imaging study. Neuroscience 207:227–242. https://doi.org/10.1016/j.neuroscience.2012.01.016
Raffelt DA et al (2012) Apparent Fibre Density: a novel measure for the analysis of diffusion-weighted magnetic resonance images. Neuroimage 59:3976–3994. https://doi.org/10.1016/j.neuroimage.2011.10.045
Raffelt DA, Tournier JD, Smith RE, Vaughan DN, Jackson G, Ridgway GR, Connelly A (2017) Investigating white matter fibre density and morphology using fixel-based analysis. Neuroimage 144:58–73. https://doi.org/10.1016/j.neuroimage.2016.09.029
Sabet AA, Christoforou E, Zatlin B, Genin GM, Bayly PV (2008) Deformation of the human brain induced by mild angular head acceleration. J Biomech 41:307–315. https://doi.org/10.1016/j.jbiomech.2007.09.016
Salter H, Holland R (2014) Biomarkers: refining diagnosis and expediting drug development—reality, aspiration and the role of open innovation. J Intern Med 276:215–228. https://doi.org/10.1111/joim.12234
Sharp DJ, Jenkins PO (2015) Concussion is confusing us all. Pract Neurol 15:172–186. https://doi.org/10.1136/practneurol-2015-001087
Shenton ME et al (2012) A review of magnetic resonance imaging and diffusion tensor imaging findings in mild traumatic brain injury. Brain Imaging Behav 6:137–192. https://doi.org/10.1007/s11682-012-9156-5
Smith SM (2002) Fast robust automated brain extraction. Hum Brain Mapp 17:143–155. https://doi.org/10.1002/hbm.10062
Spader HS et al (2018) Prospective study of myelin water fraction changes after mild traumatic brain injury in collegiate contact sports. J Neurosurg. https://doi.org/10.3171/2017.12.JNS171597
Spinos P, Sakellaropoulos G, Georgiopoulos M, Stavridi K, Apostolopoulou K, Ellul J, Constantoyannis C (2010) Postconcussion syndrome after mild traumatic brain injury in Western Greece. J Trauma 69:789–794. https://doi.org/10.1097/TA.0b013e3181edea67
Stern CE, Owen AM, Tracey I, Look RB, Rosen BR, Petrides M (2000) Activity in ventrolateral and mid-dorsolateral prefrontal cortex during nonspatial visual working memory processing: evidence from functional magnetic resonance imaging. Neuroimage 11:392–399. https://doi.org/10.1006/nimg.2000.0569
St-Jean S, Coupe P, Descoteaux M (2016) Non local spatial and angular matching: enabling higher spatial resolution diffusion MRI datasets through adaptive denoising. Med Image Anal 32:115–130. https://doi.org/10.1016/j.media.2016.02.010
Sun SW, Liang HF, Trinkaus K, Cross AH, Armstrong RC, Song SK (2006) Noninvasive detection of cuprizone induced axonal damage and demyelination in the mouse corpus callosum. Magn Reson Med 55:302–308. https://doi.org/10.1002/mrm.20774
Sun C, Wang Y, Cui R, Wu C, Li X, Bao Y, Wang Y (2018) Human thalamic-prefrontal peduncle connectivity revealed by diffusion spectrum imaging fiber tracking. Front Neuroanat 12:24. https://doi.org/10.3389/fnana.2018.00024
Sundman M, Doraiswamy PM, Morey RA (2015) Neuroimaging assessment of early and late neurobiological sequelae of traumatic brain injury: implications for CTE. Front Neurosci 9:334. https://doi.org/10.3389/fnins.2015.00334
Tournier JD, Calamante F, Connelly A (2007) Robust determination of the fibre orientation distribution in diffusion MRI: non-negativity constrained super-resolved spherical deconvolution. Neuroimage 35:1459–1472. https://doi.org/10.1016/j.neuroimage.2007.02.016
Tournier JD, Yeh CH, Calamante F, Cho KH, Connelly A, Lin CP (2008) Resolving crossing fibres using constrained spherical deconvolution: validation using diffusion-weighted imaging phantom data. Neuroimage 42:617–625. https://doi.org/10.1016/j.neuroimage.2008.05.002
Tournier JD, Mori S, Leemans A (2011) Diffusion tensor imaging and beyond. Magn Reson Med 65:1532–1556. https://doi.org/10.1002/mrm.22924
Tournier JD, Calamante F, Connelly A (2012) MRtrix: diffusion tractography in crossing fiber regions. Int J Imaging Syst Technol 22:53–66
Viano DC, Casson IR, Pellman EJ, Zhang L, King AI, Yang KH (2005) Concussion in professional football: brain responses by finite element analysis: part 9. Neurosurgery 57:891–916 (discussion 891–916)
Ware JB, Hart T, Whyte J, Rabinowitz A, Detre JA, Kim J (2017) Inter-subject variability of axonal injury in diffuse traumatic brain injury. J Neurotrauma 34:2243–2253. https://doi.org/10.1089/neu.2016.4817
Werner C, Engelhard K (2007) Pathophysiology of traumatic brain injury. Br J Anaesth 99:4–9. https://doi.org/10.1093/bja/aem131
Westfall DR, West JD, Bailey JN, Arnold TW, Kersey PA, Saykin AJ, McDonald BC (2015) Increased brain activation during working memory processing after pediatric mild traumatic brain injury (mTBI). J Pediatr Rehabil Med 8:297–308. https://doi.org/10.3233/PRM-150348
Wood DM, Bigler ED (1995) Diencephalic changes in traumatic brain injury: relationship to sensory perceptual function. Brain Res Bull 38:545–549
Woolrich MW et al (2009) Bayesian analysis of neuroimaging data in FSL. Neuroimage 45:S173–S186. https://doi.org/10.1016/j.neuroimage.2008.10.055
Yeatman JD, Dougherty RF, Myall NJ, Wandell BA, Feldman HM (2012) Tract profiles of white matter properties: automating fiber-tract quantification. PLoS ONE 7:e49790. https://doi.org/10.1371/journal.pone.0049790
You Y et al (2019) Demyelination precedes axonal loss in the transneuronal spread of human neurodegenerative disease. Brain 142:426–442. https://doi.org/10.1093/brain/awy338
Yuh EL et al (2013) Magnetic resonance imaging improves 3-month outcome prediction in mild traumatic brain injury. Ann Neurol 73:224–235. https://doi.org/10.1002/ana.23783
Zhang Y, Brady M, Smith S (2001) Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm. IEEE Trans Med Imaging 20:45–57. https://doi.org/10.1109/42.906424
Zhang L, Yang KH, King AI (2004) A proposed injury threshold for mild traumatic brain injury. J Biomech Eng 126:226–236
Acknowledgements
We want to thank the participants and their parents for lending their time for this study. We also want to thank Dr. Jen-Kai Chen and Dr. Rajeet Singh Salujah for their contribution in the acquisition of this data.
Funding
Funding for this study came from: 1. a Vanier Canada Graduate Research award, the Fonds de Recherche du Quebec—Doctoral Training for Medical Students award, and the Tomlinson Doctoral Fellowship award (G. I. Guberman); 2. an Institutional Research Chair in Neuroinformatics and National Science and Engineering Research Council Discovery Grants (Dr. Descoteaux); 3. a Canadian Institutes of Health Research Grant (Dr. Ptito, Dr. Gagnon); 4. A Fonds de Recherche du Quebec senior clinical research scholar award, and support from the Research Institute of the McGill University Health Centre (Dr. Gagnon).
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Guberman, G.I., Houde, JC., Ptito, A. et al. Structural abnormalities in thalamo-prefrontal tracks revealed by high angular resolution diffusion imaging predict working memory scores in concussed children. Brain Struct Funct 225, 441–459 (2020). https://doi.org/10.1007/s00429-019-02002-8
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DOI: https://doi.org/10.1007/s00429-019-02002-8