Neuroanatomical and functional alterations of insula in mild traumatic brain injury patients at the acute stage

  • Fengfang Li
  • Liyan Lu
  • Huiyou Chen
  • Peng Wang
  • Hong Zhang
  • Yu-Chen ChenEmail author
  • Xindao YinEmail author


Cognitive impairment is a major cause of disability and decline in quality of life in mild traumatic brain injury (mTBI) survivors, but the underlying pathophysiology is still poorly understood. The insula has extensive connections to other cortex and is believed to responsible for integrating external and internal processes and controlling cognitive functions. To explore this hypothesis, we investigated early alterations in the gray matter volume (GMV) and brain functional connectivity (FC) of insula in mTBI patients within 7 days after injury and any possible correlations with cognitive function. A total of 58 mTBI patients at the acute stage and 32 matched healthy controls were recruited and underwentT1-weighted magnetic resonance imaging (MRI)andresting-state functional MRI scans within 7 days of injury. FC was characterized using seed-based region of interest analysis method. The patients’ cognitive function was evaluated with Montreal Cognitive Assessment (MoCA) score. The resulting of GMV and FC of insula were correlated with cognitive alterations. We found that the GMV was significantly reduced only in the right insula in mTBI patients and no significant GMV increase was observed in either hemisphere. mTBI patients demonstrated decreased FC in the right parahippocampal gyrus and increased FC in the right supramargianl gyrus. In addition, compared to the healthy controls, the mTBI patients in the acute stage presented a decline in the visuospatial/executive (p = 0.013) and attention (p = 0.038) subcategories. In the mTBI group, the changes in GMV in the right insula were positively correlated with poor attention performance (r = 0.316, p = 0.016). Our data demonstrated alterations of the GMV and resting-stateFC of the right insula in mTBI patients at the acute stage. These early changes in GMV and resting-state FC perhaps serve as a potential biomarker for improving the understanding of cognitive decline for mTBI in the acute setting.


Mild traumatic brain injury Gray matter volume Functional connectivity Cognitive function MRI 



This work was supported by the National Natural Science Foundation of China (No.81870563), Jiangsu Provincial Special Program of Medical Science (BE2017614), Youth Medical Talents of Jiangsu Province (No. QNRC2016062), 14th “Six Talent Peaks” Project of Jiangsu Province (No. YY-079), and the Nanjing Medical University grant (No. 2017NJMU123).

Compliance with ethical standards

Conflict of interests

The authors declare that there is no potential conflict of interests regarding the publication of this paper.

Ethical approval

The current study was approved by the Research Ethics Committee of the Nanjing Medical University.

Informed consent

Informed consent was obtained from all individual participants included in the study.


  1. Augustine, J. R. (1996). Circuitry and functional aspects of the insular lobe in primates including humans. Brain Research. Brain Research Reviews, 22, 229–244.CrossRefGoogle Scholar
  2. Bigler, E. D. (2013). Traumatic brain injury, neuroimaging, and neurodegeneration. Frontiers in Human Neuroscience, 7, 395.CrossRefGoogle Scholar
  3. 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, 4690–4695.CrossRefGoogle Scholar
  4. Carlozzi, N. E., Kirsch, N. L., Kisala, P. A., & Tulsky, D. S. (2015). An examination of the Wechsler adult intelligence scales, fourth edition (WAIS-IV) in individuals with complicated mild, moderate and severe traumatic brain injury (TBI). The Clinical Neuropsychologist, 29, 21–37.CrossRefGoogle Scholar
  5. Chao-Gan, Y., & Yu-Feng, Z. (2010). DPARSF: A MATLAB toolbox for "pipeline" data analysis of resting-state fMRI. Frontiers in Systems Neuroscience, 4, 13.Google Scholar
  6. Dall'Acqua, P., Johannes, S., Mica, L., Simmen, H. P., Glaab, R., Fandino, J., Schwendinger, M., Meier, C., Ulbrich, E. J., Muller, A., Jancke, L., & Hanggi, J. (2016). Connectomic and surface-based morphometric correlates of acute mild traumatic brain injury. Frontiers in Human Neuroscience, 10, 127.CrossRefGoogle Scholar
  7. Dall'Acqua, P., Johannes, S., Mica, L., Simmen, H. P., Glaab, R., Fandino, J., Schwendinger, M., Meier, C., Ulbrich, E. J., Muller, A., Jancke, L., & Hanggi, J. (2017). Prefrontal cortical thickening after mild traumatic brain injury: A one-year magnetic resonance imaging study. Journal of Neurotrauma, 34, 3270–3279.CrossRefGoogle Scholar
  8. de Guise, E., Alturki, A. Y., LeBlanc, J., Champoux, M. C., Couturier, C., Lamoureux, J., Desjardins, M., Marcoux, J., Maleki, M., & Feyz, M. (2014). The Montreal cognitive assessment in persons with traumatic brain injury. Applied Neuropsychology. Adult, 21, 128–135.CrossRefGoogle Scholar
  9. Duning, T., Kloska, S., Steinstrater, O., Kugel, H., Heindel, W., & Knecht, S. (2005). Dehydration confounds the assessment of brain atrophy. Neurology, 64, 548–550.CrossRefGoogle Scholar
  10. Floden, D., & Stuss, D. T. (2006). Inhibitory control is slowed in patients with right superior medial frontal damage. Journal of Cognitive Neuroscience, 18, 1843–1849.CrossRefGoogle Scholar
  11. Gao, X., & Chen, J. (2011). Mild traumatic brain injury results in extensive neuronal degeneration in the cerebral cortex. Journal of Neuropathology and Experimental Neurology, 70, 183–191.CrossRefGoogle Scholar
  12. Good, C. D., Johnsrude, I. S., Ashburner, J., Henson, R. N., Friston, K. J., & Frackowiak, R. S. (2001). A voxel-based morphometric study of ageing in 465 normal adult human brains. NeuroImage, 14, 21–36.CrossRefGoogle Scholar
  13. Govindarajan, K. A., Narayana, P. A., Hasan, K. M., Wilde, E. A., Levin, H. S., Hunter, J. V., Miller, E. R., Patel, V. K., Robertson, C. S., & McCarthy, J. J. (2016). Cortical thickness in mild traumatic brain injury. Journal of Neurotrauma, 33, 1809–1817.CrossRefGoogle Scholar
  14. Hasan, K. M., Wilde, E. A., Miller, E. R., Kumar Patel, V., Staewen, T. D., Frisby, M. L., Garza, H. M., McCarthy, J. J., Hunter, J. V., Levin, H. S., Robertson, C. S., & Narayana, P. A. (2014). Serial atlas-based diffusion tensor imaging study of uncomplicated mild traumatic brain injury in adults. Journal of Neurotrauma, 31, 466–475.CrossRefGoogle Scholar
  15. Hillary, F. G., Slocomb, J., Hills, E. C., Fitzpatrick, N. M., Medaglia, J. D., Wang, J., Good, D. C., & Wylie, G. R. (2011). Changes in resting connectivity during recovery from severe traumatic brain injury. International journal of psychophysiology : official journal of the International Organization of Psychophysiology, 82, 115–123.CrossRefGoogle Scholar
  16. Iraji, A., Benson, R. R., Welch, R. D., O'Neil, B. J., Woodard, J. L., Ayaz, S. I., Kulek, A., Mika, V., Medado, P., Soltanian-Zadeh, H., Liu, T., Haacke, E. M., & Kou, Z. (2015). Resting state functional connectivity in mild traumatic brain injury at the acute stage: Independent component and seed-based analyses. Journal of Neurotrauma, 32, 1031–1045.CrossRefGoogle Scholar
  17. Jagoda, A. S., Bazarian, J. J., Bruns, J. J., Jr., Cantrill, S. V., Gean, A. D., Howard, P. K., Ghajar, J., Riggio, S., Wright, D. W., Wears, R. L., Bakshy, A., Burgess, P., Wald, M. M., & Whitson, R. R. (2008). Clinical policy: Neuroimaging and decisionmaking in adult mild traumatic brain injury in the acute setting. Annals of Emergency Medicine, 52, 714–748.CrossRefGoogle Scholar
  18. Jamora, C. W., Young, A., & Ruff, R. M. (2012). Comparison of subjective cognitive complaints with neuropsychological tests in individuals with mild vs more severe traumatic brain injuries. Brain Injury, 26, 36–47.CrossRefGoogle Scholar
  19. Jarrett, M., Tam, R., Hernandez-Torres, E., Martin, N., Perera, W., Zhao, Y., Shahinfard, E., Dadachanji, S., Taunton, J., Li, D. K., & Rauscher, A. (2016). A prospective pilot investigation of brain volume, white matter Hyperintensities, and hemorrhagic lesions after mild traumatic brain injury. Frontiers in Neurology, 7, 11.CrossRefGoogle Scholar
  20. Killgore, W. D. S., Singh, P., Kipman, M., Pisner, D., Fridman, A., & Weber, M. (2016). Gray matter volume and executive functioning correlate with time since injury following mild traumatic brain injury. Neuroscience Letters, 612, 238–244.CrossRefGoogle Scholar
  21. Kou, Z., Wu, Z., Tong, K. A., Holshouser, B., Benson, R. R., Hu, J., & Haacke, E. M. (2010). The role of advanced MR imaging findings as biomarkers of traumatic brain injury. The Journal of Head Trauma Rehabilitation, 25, 267–282.CrossRefGoogle Scholar
  22. Lamm, C., Decety, J., & Singer, T. (2011). Meta-analytic evidence for common and distinct neural networks associated with directly experienced pain and empathy for pain. NeuroImage, 54, 2492–2502.CrossRefGoogle Scholar
  23. Lange, R. T., Brickell, T. A., French, L. M., Merritt, V. C., Bhagwat, A., Pancholi, S., & Iverson, G. L. (2012). Neuropsychological outcome from uncomplicated mild, complicated mild, and moderate traumatic brain injury in US military personnel. Archives of clinical neuropsychology : the official journal of the National Academy of Neuropsychologists, 27, 480–494.CrossRefGoogle Scholar
  24. Ledberg, A., Akerman, S., & Roland, P. E. (1998). Estimation of the probabilities of 3D clusters in functional brain images. NeuroImage, 8, 113–128.CrossRefGoogle Scholar
  25. Len, T. K., & Neary, J. P. (2011). Cerebrovascular pathophysiology following mild traumatic brain injury. Clinical Physiology and Functional Imaging, 31, 85–93.Google Scholar
  26. Lipton, M. L., Gulko, E., Zimmerman, M. E., Friedman, B. W., Kim, M., Gellella, E., Gold, T., Shifteh, K., Ardekani, B. A., & Branch, C. A. (2009). Diffusion-tensor imaging implicates prefrontal axonal injury in executive function impairment following very mild traumatic brain injury. Radiology, 252, 816–824.CrossRefGoogle Scholar
  27. List, J., Ott, S., Bukowski, M., Lindenberg, R., & Floel, A. (2015). Cognitive function and brain structure after recurrent mild traumatic brain injuries in young-to-middle-aged adults. Frontiers in Human Neuroscience, 9, 228.CrossRefGoogle Scholar
  28. Livny, A., Biegon, A., Kushnir, T., Harnof, S., Hoffmann, C., Fruchter, E., & Weiser, M. (2017). Cognitive deficits post-traumatic brain injury and their association with injury severity and gray matter volumes. Journal of Neurotrauma, 34, 1466–1472.CrossRefGoogle Scholar
  29. Lu, L., Wei, X., Li, M., Li, Y., & Li, W. (2014). Emerging MRI and metabolic neuroimaging techniques in mild traumatic brain injury. Neurology India, 62, 487–491.CrossRefGoogle Scholar
  30. Marquez de la Plata, C. D., Garces, J., Shokri Kojori, E., Grinnan, J., Krishnan, K., Pidikiti, R., Spence, J., Devous, M. D., Sr., Moore, C., McColl, R., Madden, C., & Diaz-Arrastia, R. (2011). Deficits in functional connectivity of hippocampal and frontal lobe circuits after traumatic axonal injury. Archives of Neurology, 68, 74–84.CrossRefGoogle Scholar
  31. Mayer, A. R., Hanlon, F. M., & Ling, J. M. (2015). Gray matter abnormalities in pediatric mild traumatic brain injury. Journal of Neurotrauma, 32, 723–730.CrossRefGoogle Scholar
  32. McCrory, P., Meeuwisse, W., Aubry, M., Cantu, B., Dvorak, J., Echemendia, R., Engebretsen, L., Johnston, K., Kutcher, J., Raftery, M., Sills, A., Benson, B., Davis, G., Ellenbogen, R., Guskiewicz, K., Herring, S. A., Iverson, G., Jordan, B., Kissick, J., McCrea, M., McIntosh, A., Maddocks, D., Makdissi, M., Purcell, L., Putukian, M., Schneider, K., Tator, C., & Turner, M. (2013). Consensus statement on concussion in sport - the 4th international conference on concussion in sport held in Zurich, November 2012. Physical therapy in sport : official journal of the Association of Chartered Physiotherapists in Sports Medicine, 14, e1–e13.CrossRefGoogle Scholar
  33. Menon, V., & Uddin, L. Q. (2010). Saliency, switching, attention and control: A network model of insula function. Brain Structure & Function, 214, 655–667.CrossRefGoogle Scholar
  34. Metting, Z., Rodiger, L. A., De Keyser, J., & van der Naalt, J. (2007). Structural and functional neuroimaging in mild-to-moderate head injury. The Lancet. Neurology, 6, 699–710.CrossRefGoogle Scholar
  35. Narayana, P. A., Yu, X., Hasan, K. M., Wilde, E. A., Levin, H. S., Hunter, J. V., Miller, E. R., Patel, V. K., Robertson, C. S., & McCarthy, J. J. (2015). Multi-modal MRI of mild traumatic brain injury. NeuroImage. Clinical, 7, 87–97.CrossRefGoogle Scholar
  36. Nasreddine, Z. S., Phillips, N. A., Bedirian, V., Charbonneau, S., Whitehead, V., Collin, I., Cummings, J. L., & Chertkow, H. (2005). The Montreal cognitive assessment, MoCA: A brief screening tool for mild cognitive impairment. Journal of the American Geriatrics Society, 53, 695–699.CrossRefGoogle Scholar
  37. Piras, F., Piras, F., Chiapponi, C., Girardi, P., Caltagirone, C., & Spalletta, G. (2015). Widespread structural brain changes in OCD: A systematic review of voxel-based morphometry studies. Cortex; a journal devoted to the study of the nervous system and behavior, 62, 89–108.CrossRefGoogle Scholar
  38. Rigg, J. L., & Mooney, S. R. (2011). Concussions and the military: Issues specific to service members. PM & R : The Journal of Injury, Function, and Rehabilitation, 3, 380–386.CrossRefGoogle Scholar
  39. Rutland-Brown, W., Langlois, J. A., Thomas, K. E., & Xi, Y. L. (2006). Incidence of traumatic brain injury in the United States, 2003. The Journal of Head Trauma Rehabilitation, 21, 544–548.CrossRefGoogle Scholar
  40. Seeley, W. W., Menon, V., Schatzberg, A. F., Keller, J., Glover, G. H., Kenna, H., Reiss, A. L., & Greicius, M. D. (2007). Dissociable intrinsic connectivity networks for salience processing and executive control. The Journal of neuroscience : the official journal of the Society for Neuroscience, 27, 2349–2356.CrossRefGoogle Scholar
  41. Shumskaya, E., Andriessen, T. M., Norris, D. G., & Vos, P. E. (2012). Abnormal whole-brain functional networks in homogeneous acute mild traumatic brain injury. Neurology, 79, 175–182.CrossRefGoogle Scholar
  42. Slobounov, S. M., Zhang, K., Pennell, D., Ray, W., Johnson, B., & Sebastianelli, W. (2010). Functional abnormalities in normally appearing athletes following mild traumatic brain injury: A functional MRI study. Experimental Brain Research, 202, 341–354.CrossRefGoogle Scholar
  43. 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.CrossRefGoogle Scholar
  44. Stam, C. J. (2014). Modern network science of neurological disorders. Nature Reviews. Neuroscience, 15, 683–695.CrossRefGoogle Scholar
  45. Stevens, M. C., Lovejoy, D., Kim, J., Oakes, H., Kureshi, I., & Witt, S. T. (2012). Multiple resting state network functional connectivity abnormalities in mild traumatic brain injury. Brain Imaging and Behavior, 6, 293–318.CrossRefGoogle Scholar
  46. Tops, M., & Boksem, M. A. (2011). A potential role of the inferior frontal gyrus and anterior insula in cognitive control, brain rhythms, and event-related potentials. Frontiers in Psychology, 2, 330.CrossRefGoogle Scholar
  47. Tu, Y., Yu, T., Wei, Y., Sun, K., Zhao, W., & Yu, B. (2016). Structural brain alterations in hemifacial spasm: A voxel-based morphometry and diffusion tensor imaging study. Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology, 127, 1470–1474.CrossRefGoogle Scholar
  48. Uddin, L. Q., Kinnison, J., Pessoa, L., & Anderson, M. L. (2014). Beyond the tripartite cognition-emotion-interoception model of the human insular cortex. Journal of Cognitive Neuroscience, 26, 16–27.CrossRefGoogle Scholar
  49. Vakhtin, A. A., Calhoun, V. D., Jung, R. E., Prestopnik, J. L., Taylor, P. A., & Ford, C. C. (2013). Changes in intrinsic functional brain networks following blast-induced mild traumatic brain injury. Brain Injury, 27, 1304–1310.CrossRefGoogle Scholar
  50. 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.CrossRefGoogle Scholar
  51. Zhou, Y., Kierans, A., Kenul, D., Ge, Y., Rath, J., Reaume, J., Grossman, R. I., & Lui, Y. W. (2013). Mild traumatic brain injury: Longitudinal regional brain volume changes. Radiology, 267, 880–890.CrossRefGoogle Scholar
  52. Zhu, D. C., Covassin, T., Nogle, S., Doyle, S., Russell, D., Pearson, R. L., Monroe, J., Liszewski, C. M., DeMarco, J. K., & Kaufman, D. I. (2015). A potential biomarker in sports-related concussion: Brain functional connectivity alteration of the default-mode network measured with longitudinal resting-state fMRI over thirty days. Journal of Neurotrauma, 32, 327–341.CrossRefGoogle Scholar

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Authors and Affiliations

  1. 1.Department of Radiology, Nanjing First HospitalNanjing Medical UniversityNanjingChina
  2. 2.Department of RadiologyThe Affiliated Jiangning Hospital of Nanjing Medical UniversityNanjingChina

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