Health  Vol.10 No.4 , April 2018
Brain Mechanisms of College Students’ Social Adjustment: Evidence from Multimodal Magnetic Resonance Imaging (MRI)
Abstract: This study investigated the neural basis of social adjustment using multimodal brain imaging and social-adjustment measurements to analyze functional and structural brain features during social adjustment in college students. The results showed that, regarding brain function, some dimensions of social adjustment were associated with the insula, and some regions of the frontal and occipital lobes. Self-adjustment and satisfaction required activation of the middle frontal gyrus, while career adjustment and academic adjustment required inhibition of the inferior frontal gyrus and lingual gyrus, respectively. Decreased metabolic activity of the lingual gyrus was beneficial for obtaining satisfaction. Regarding brain structure, the total score and some dimensions of social adaptation were associated with the gray matter of portions of the temporal and parietal lobes. The superior temporal gyrus was associated with the total social adjustment and satisfaction score, the middle temporal gyrus with campus-life adjustment and satisfaction, and the post central gyrus and the inferior parietal lobule with emotional adjustment. The changes in the gray matter volume of these brain regions to a certain extent reflected socially adaptive behaviors. The results suggest that social adaptability is associated with various brain regions dispersed among both hemispheres of the brain, and requires synergistic inter-actions between multiple brain regions and both brain hemispheres.
Cite this paper: Ge, Y. , Pan, W. and Wang, T. (2018) Brain Mechanisms of College Students’ Social Adjustment: Evidence from Multimodal Magnetic Resonance Imaging (MRI). Health, 10, 442-457. doi: 10.4236/health.2018.104036.

[1]   Zhang, C. (1992) Zhang’s Psychology Dictionary. Shanghai Lexicographic Publishing House, Shanghai.

[2]   Montgomery, E. and Foldspang, A. (2008) Discrimination, Mental Problems and Social Adaptation in Young Refugees. European Journal of Public Health, 18, 156-161.

[3]   Kolaitis, G., Tsiantis, J., Madianos, M. and Kotsopoulos, S. (2013) Psychosocial Adaptation of Immigrant Greek Children from the Former Soviet Union. European Child & Adolescent Psychiatry, 12, 67-74.

[4]   Bhattacharga, G. (2000) The School Adjustment of South Asian Immigrant Children in the U.S. Adolescence, 35, 77-85.

[5]   Black, A.E. and Deci, E.C. (2000) The Effects of Instructors, Autonomy Support and Students. Autonomous Motivation on Learning Organic Chemistry: A Self-Determination Theory Perspective. Science Education, 84, 740-756.<740::AID-SCE4>3.0.CO;2-3

[6]   Gong, C. and Li, C. (2012) Analysis and Countermeasures for Campus Adaptation of College Freshmen. Youth Exploration, 171, 42-47.

[7]   Jiang, Q. and Xu, N. (2010) Effect of Coping Style and Social Adjustment on Mental Health of Undergraduates. Chinese Journal of Health Statistics, 27, 25-27.

[8]   Li, C. and Zhou, W. (2009) A Research on the Relationship between Social Adjustment of College Students and Five-Factor Personality. Chinese Journal of Clinical Psychology, 17, 78-80.

[9]   Si, X. and Li, H. (2008) Designing of Freshmen’s Role Adjustment Questionnaire. Journal of Shenyang Normal University, 11, 64-67.

[10]   Liu, Y. (2014) A Study on Campus Adaptation of Minority College Students. Master’s Thesis, Beijing Technology and Business University, Beijing.

[11]   Zou, X. (2013) A Study on Undergraduates’ Adjustment to College in China. Master’s Thesis, Xiamen University, Xiamen.

[12]   Zang, Y., Jiang, T., Lu, Y., He, Y. and Tian, L. (2004) Regional Homogeneity Approach to fMRI Data Analysis. NeuroImage, 22, 394-400.

[13]   Ashburner, J. and Friston, K.J. (2000) Voxel-Based Morphometry—The Methods. NeuroImage, 11, 805-851.

[14]   Goodadnd, C., Ashburner, J. and Frackowiak, R.S. (2001) Computational Neuroanatomy: New Perspectives for Neuroradiology. Revue Neurologique (Paris), 157, 797-806.

[15]   Hahn, T., Dresler, T., Ehlis, A.C., Pyka, M., Dieler, A.C., Saathoff, C., Fallgatter, A.J., et al. (2012) Randomness of Resting-State Brain Oscillations Encodes Gray’s Personality Trait. NeuroImage, 59, 1842-1845.

[16]   Gao, Q., Wu, Q., Duan, X.J., Liao, W., Zhang, Z., Li, Y., Chen, H., et al. (2013) Extraversion and Neuroticism Relate to Topological Properties of Resting-State Brain Networks. Frontiers in Human Neuro-science, 7, 257.

[17]   Aghajani, M., Veer, I.M., van Tol, M.J., Aleman, A., van Buchem, M.A., Veltman, D.J., van der Wee, N.J., et al. (2014) Neuroticism and Extraversion Are Associated with Amygdala Resting-State Functional Connectivity. Cognitive, Affective, & Behavioral Neuroscience, 14, 836-848.

[18]   Xu, J. and Potenza, M.N. (2012) White Matter Integrity and Five-Factor Personality Measures in Healthy Adults. NeuroImage, 59, 800-807.

[19]   Coutinho, J., Sampaio, A., Ferreira, M., Soares, J. and Goncalves, O. (2013) Brain Correlates of Pro-Social Personality Traits: A Voxel-Based Morphometry Study. Brain Imaging and Behavior, 7, 293-299.

[20]   Liu, W.-Y., Weber, B., Reuter, M., Markett, S., Chu, W.-C. and Montag, C. (2013) The Big Five of Personality and Structural Imaging Revisited: A VBM-DARTEL Study. Neuroreport, 24, 375-380.

[21]   Fang, X., Wo, J. and Lin, X. (2005) The Development of “Chinese College Student Adaptation Scale”. Studies of Psychology and Behavior, 3, 95-101.

[22]   Wang, Z., Yan, C., Zhao, C., Qi, Z., Zhou, W., Lu, J. and Li, K. (2011) Spatial Patterns of Intrinsic Brain Activity in Mild Cognitive Impairment and Alzheimer’s Disease: A Resting-State Functional MRI Study. Human Brain Mapping, 32, 1720-1740.

[23]   Yan, C.G., Wang, X.D., Zuo, X.N. and Zang, Y.F. (2016) DPABI: Data Processing & Analysis for (Resting-State) Brain Imaging. Neuroinformatics, 14, 339-351.

[24]   Ashbumer, J. (2007) A Fast Diffeomorphic Image Registration Algorithm. NeuroImage, 55, 95-113.

[25]   Abutalebi, J., Della Rosa, P.A., Green, D.W., Hernandez, M., Scifo, P., Keim, R. and Costa, A. (2012) Bilingualism Tunes the Anterior Cingulate Cortex for Conflict Monitoring. Cerebral Cortex, 22, 2076-2086.

[26]   Frodl, T., Koutsouleris, N., Bottlender, R., Born, C., Jager M., Morgenthaler, M., Meisenzahl, E.M., et al. (2008) Reduced Gray Matter Brain Volumes Are Associated with Variants of the Serotonin Transporter Gene in Major Depression. Molecular Psychiatry, 13, 1093-1101.

[27]   Ashbumer, J. and Friston, K.J. (2005) Unified Segmentation. NeuroImage, 26, 839-851.

[28]   Bryant, D.M., Hoeft, F., Lai, S., Lackey, J., Roeltgen, D., Ross, J. and Reiss, A.L. (2011) Neuroanatomical Phenotype of Klinefelter Syndrome in Childhood: A Voxel-Based Morphometry Study. The Journal of Neuroscience, 31, 6654-6660.

[29]   Tregellas, J.R., Ellis, J., Shatti, S., Du, Y.P. and Rojas, D.C. (2009) Increased Hippocampal, Thalamic, and Prefrontal Hemodynamic Response to an Urban Noise Stimulus in Schizophrenia. American Journal of Psychiatry, 166, 354-360.

[30]   Wu, Q., Li, H., Xiao, H., Xiao-yang, W. and Bai-qian, C. (2015) An Investigation on the Regional Homogeneity in Resting-State fMRI in the Patients with Recruits’ Adjustment Disorder. Functional and Molecular Medical Imaging (Electronic Edition), 4, 712-716.

[31]   Zhang, H., Ran, S. and Li, H. (2015) Regional Homogeneity of Brain in Generalized Anxiety Disorder: A Resting State Functional MRI Study. Radiology Practice, 29, 1387-1391.

[32]   Guo, W.B., Sun, X.L., Liu, L., Xu, Q., Wu, R.R., Liu, Z.N., Zhao, J.P., et al. (2011) Disrupted Regional Homogeneity in Treatment-Resistant Depression: A Resting-State fMRI Study. Progress in Neuro-Psychopharmacology & Biological Psychiatry, 35, 1297-1302.

[33]   Krain, A.L., Wilson, A.M., Arbuckle, R., Castellanos, F.X. and Milham, M.P. (2006) Distinct Neural Mechanisms of Risk and Ambiguity: A Meta-Analysis of Decision-Making. NeuroImage, 32, 477-484.

[34]   Cox, C.L., Gotimer, K., Roy, A.K., Castellanon, F.X., Milham, M.P., Kelly, C., et al. (2010) Your Resting Brain CAREs about Your Risky Behavior. PLoS ONE, 5, e12296.

[35]   Haldane, M., Cunningham, G., Androutsos, C. and Frangou, S. (2008) Structural Brain Correlates of Response Inhibition in Bipolar Disorder. Journal of Psychopharmacology, 22, 138-143.

[36]   Raichle, M.E., MacLeod, A.M., Snyder, A.Z., Powers, W.J., Gusnard, D.A. and Shulman, G.L. (2001) A Default Mode of Brain Function. Proceedings of the National Academy of Sciences USA, 98, 676-682.

[37]   Qin, L., Zhou, Y., Zhao, Z., Lu, Q., Ge, Z., Li, L., Gui, Y. and Xu, J. (2011) Preliminary Study of Brain Activity in Internet Addiction Adolescents: Revealed by Resting State Functional MRI. Journal of Clinical Radiology, 30, 7-10.

[38]   Wu, D., Loke, I.C., Xu, F. and Lee, K. (2011) Neural Correlates of Evaluations of Lying and Truth-Telling in Different Social Contexts. Brain Research, 1389, 115-124.

[39]   Nagai, M., Kishi, K. and Kato, S. (2007) Insular Cortex and Neuropsychiatric Disorders: A Review of Recent Literature. European Psychiatry, 22, 387-394.

[40]   Franklin, T.R., Wang, Z., Wang, J., Sciortino, N., Harper, D., Li, Y., Childress, A.R., et al. (2007) Limbic Activation to Cigarette Smoking Cues Independent of Nicotine Withdrawal: A Perfusion fMRI Study. Neuropsychopharmacology, 32, 2301-2309.

[41]   Wang, Z., Faith, M., Patterson, F., Tang, K., Kerrin, K., Wileyto, E.P. and Lerman, C. (2007) Neural Substrates of Abstinence-Induced Cigarette Cravings in Chronic Smokers. The Journal of Neuroscience, 27, 14035-14040.

[42]   Nakic, M., Smith. W., Busis, S., Vythilingam, M. and Blair, R.J.R. (2006) The Impact of Affect and Frequency on Lexical Decision: The Role of the Amygdala and Inferior Frontal Cortex. NeuroImage, 31, 1752-1761.

[43]   Nasur, H.N. and Antoine, B. (2009) The Hidden Island of Addiction: The Insula. Trends in Neurosciences, 32, 56-67.

[44]   Ding, J. (2010) Magnetic Resonance Imaging Case Control Study on Brain Structural and Functional Abnormalities of First-Episode Medication-Naive Adolescents with Major Depressive Disorder. Master D. Thesis, Central South University, Changsha.

[45]   Zhang, X. (2014) The Magnetic Resonance Imaging Study on Brain Structure and Resting-State Function in Depressive Patients. PhD Thesis, Central South University, Changsha.

[46]   Kalat, J.W. (2009) Biological Psychology. 10th Edition, Cengage Learning, Wadsworth.

[47]   Allison, T., Puce, A. and McCarthy, G. (2000) Social Perception from Visual Cues: Institutional Role of the STS Region. Trends in Cognitive Science, 4, 267-278.

[48]   Gallagher, H.L. and Frith, C.D. (2003) Functional Imaging of Theory of Mind. Trends in Cognitive Science, 7, 77-83.

[49]   Viard, A., Piolino, P., Desgranges, B., Chételat, G., Lebreton, K., Landeau, B. and Eustache, F. (2007) Hippocampal Activation for Autobiographical Memories over the Entire Lifetime in Healthy Aged Subjects: An fMRI Study. Cerebral Cortex, 17, 2453-2467.

[50]   Selvaraj, S., Amone, D., Job, D., Stanfield, A., Farrow, T.F., Nugent, A.C., McIntosh, A.M., et al. (2012) Grey Matter Differences in Bipolar Disorder: A Meta-Analysis of Voxel-Based Morphometry Studies. Bipolar Disorders, 14, 135-145.

[51]   Cui, L., Deng, W., Lijun, J., Zhao-hua, H., Zhuang-fei, C., Ming-li, L., Tao, L., et al. (2010) Comparative Analysis of Brain Grey Matter Volume between Patients with Paranoid Schizophrenia and Patients with Bipolar Mania. Journal of Sichuan University (Medical Science Edition), 41, 5-9.

[52]   Cobia, D.J., Smith, M.J., Wang, L. and Csernansky, J.G. (2012) Longitudinal Progression of Frontal and Temporal Lobe Changes in Schizophrenia. Schizophrenia Research, 139, 1-6.

[53]   Yüksel, C., McCarthy, J., Shinn, A., Pfaff, D.L., Baker, J.T, Heckers, S., Ongür, D., et al. (2012) Gray Matter Volume in Schizophrenia and Bipolar Disorder with Psychotic Features. Schizophrenia Research, 138, 177-182.

[54]   Sandok, E.K., O’Brien, T.J., Jack, C.R. and So, E.L. (2000) Significance of Cerebellar Atrophy Intractable Temporal Lobe Epilepsy: A Quantitative MRI Study. Epilepsia, 41, 1315-1320.

[55]   Yu, A., Li, K., Li, L., Bao-ci, S. and Yuping, W. (2008) Whole-Brain Voxel-Based MRI Morphometric Study of Grey Matter in Medical Temporal Lobe Epilepsy. Chinese Journal of Medical Imaging Technology, 24, 1011-1014.

[56]   Ihme, K., Dannlowski., U., Lichev, V., Stuhrmann, A., Grotegerd, D., Rosenberg, N., Suslow, T., et al. (2013) Alexithymia Is Related to Differences in Gray Matter Volume: A Voxel-Based Morphometry Study. Brain Research, 1491, 60-67.

[57]   Zuo, J., Xiong, J., Zhou, B. and Wang, B. (2015) Study of Functional Magnetic Resonance Imaging at Resting State for Patients in Sub-Health Status. Journal of Biomedical Engineering, 32, 635-639.

[58]   Wu, X. (2014) The Voxel-Based Morphometry Research of Grey and White Matter in Patients with Temporal Lobe Epilepsy. Master D. Thesis, Xiamen University, Xiamen.

[59]   Liu, H., Zhao, X., Wang, X., Lele, Z. and Xi, Y. (2015) Grey Matter Volume in Mild Cognitive Impairment Patients: A Longitudinal Study Based on VBM. Journal of Tongji University (Medical Science), 36, 53-56.

[60]   Lawrence, E.J., Shaw, P., Giampietro, V.P., Surguladze, S., Brammer, M.J. and David, A.S. (2006) The Role of “Shared Representations” in Social Perception and Empathy: An fMRI Study. NeuroImage, 29, 1173-1184.

[61]   Van Haren, N.E., Schnack, H.G., Cahn, W., van den Heuvel, M.P., Lepage, C., Collins, L., Kahn, R.S., et al. (2011) Changes in Cortical Thickness during the Course of Illness in Schizophrenia. Archives of General Psychiatry, 68, 871-880.

[62]   Heuser, M., Thomann, P.A., Essig, M., Bachmann, S. and Schroder, J. (2011) Neurological Signs and Morphological Cerebral Changes in Schizophrenia: An Analysis of NSS Subscales in Patients with First Episode Psychosis. Psychiatry Research Neuroimaging, 192, 69-76.