Decoding fear of negative evaluation from brain morphology: A machine-learning study on structural neuroimaging data

Abstract

Background: Fear of negative evaluation (FNE), referring to negative expectation and feelings toward other people’s social evaluation, is closely associated with social anxiety that plays an important role in our social life. Exploring the neural markers of FNE may be of theoretical and practical significance to psychiatry research (e.g., studies on social anxiety).

Methods: To search for potentially relevant biomarkers of FNE in human brain, the current study applied multivariate relevance vector regression, a machine-learning and data-driven approach, on brain morphological features (e.g., cortical thickness) derived from structural imaging data; further, we used these features as indexes to predict self-reported FNE score in each participant.

Results: Our results confirm the predictive power of multiple brain regions, including those engaged in negative emotional experience (e.g., amygdala, insula), regulation and inhibition of emotional feeling (e.g., frontal gyrus, anterior cingulate gyrus), and encoding and retrieval of emotional memory (e.g., posterior cingulate cortex, parahippocampal gyrus).

Conclusions: The current findings suggest that anxiety represents a complicated construct that engages multiple brain systems, from primitive subcortical mechanisms to sophisticated cortical processes.

Author summary

The current findings indicate that fear of negative evaluation, an anxiety-related trait, could be decoded from the structural features of individual brains. These findings advance our understanding on the neural signatures of anxiety and implicate potential clinical applications of brain imaging measures.

Graphical abstract

Keywords

fear of negative evaluation / social anxiety / structural magnetic resonance imaging / machine learning / relevance vector regression

References

[1] American-Psychiatric-Association. ( 2013) Diagnostic and Statistical Manual of Mental Disorders (DSM-5®). Arlington, VA: American Psychiatric Publishing

[2] ClarkD. M.. ( 1995) A cognitive model of social phobia. In: Social phobia: Diagnosis, Assessment, and Treatment, Heimberg, R. G., Liebowitz, M. R., Hope, D. A. and Schneier, F. R. (Eds.), pp. 69– 93, New York: Guilford Press

[3] Rapee,R. M. Heimberg,R. ( 1997). A cognitive-behavioral model of anxiety in social phobia. Behav. Res. Ther., 35 : 741– 756

[4] Watson,D. ( 1969). Measurement of social-evaluative anxiety. J. Consult. Clin. Psychol., 33 : 448– 457

[5] Carleton,R. N., Collimore,K. C., McCabe,R. E. Antony,M. ( 2011). Addressing revisions to the brief fear of negative evaluation scale: measuring fear of negative evaluation across anxiety and mood disorders. J. Anxiety Disord., 25 : 822– 828

[6] Winton,E. C., Clark,D. M. Edelmann,R. ( 1995). Social anxiety, fear of negative evaluation and the detection of negative emotion in others. Behav. Res. Ther., 33 : 193– 196

[7] Wells,A., Clark,D. M., Salkovskis,P., Ludgate,J., Hackmann,A. ( 1995). Social phobia: The role of in-situation safety behaviors in maintaining anxiety and negative beliefs. Behav. Ther., 26 : 153– 161

[8] Weeks,J. W., Heimberg,R. G., Fresco,D. M., Hart,T. A., Turk,C. L., Schneier,F. R. Liebowitz,M. ( 2005). Empirical validation and psychometric evaluation of the brief fear of negative evaluation scale in patients with social anxiety disorder. Psychol. Assess., 17 : 179– 190

[9] Miskovic,V. Schmidt,L. ( 2012). Social fearfulness in the human brain. Neurosci. Biobehav. Rev., 36 : 459– 478

[10] LeDoux,J. ( 2000). Emotion circuits in the brain. Annu. Rev. Neurosci., 23 : 155– 184

[11] LeDoux,J. ( 2003). The emotional brain, fear, and the amygdala. Cell. Mol. Neurobiol., 23 : 727– 738

[12] Marek,R., Strobel,C., Bredy,T. W. ( 2013). The amygdala and medial prefrontal cortex: partners in the fear circuit. J. Physiol., 591 : 2381– 2391

[13] Bishop,S., Duncan,J., Brett,M. Lawrence,A. ( 2004). Prefrontal cortical function and anxiety: controlling attention to threat-related stimuli. Nat. Neurosci., 7 : 184– 188

[14] Bishop,S. ( 2007). Neurocognitive mechanisms of anxiety: an integrative account. Trends Cogn. Sci., 11 : 307– 316

[15] Bishop,S. ( 2009). Trait anxiety and impoverished prefrontal control of attention. Nat. Neurosci., 12 : 92– 98

[16] Kim,M. J., Gee,D. G., Loucks,R. A., Davis,F. C. Whalen,P. ( 2011). Anxiety dissociates dorsal and ventral medial prefrontal cortex functional connectivity with the amygdala at rest. Cereb. Cortex, 21 : 1667– 1673

[17] Kim,M. J. Whalen,P. ( 2009). The structural integrity of an amygdala-prefrontal pathway predicts trait anxiety. J. Neurosci., 29 : 11614– 11618

[18] Paulus,M. P. Stein,M. ( 2006). An insular view of anxiety. Biol. Psychiatry, 60 : 383– 387

[19] Stein,M. B., Simmons,A. N., Feinstein,J. S. Paulus,M. ( 2007). Increased amygdala and insula activation during emotion processing in anxiety-prone subjects. Am. J. Psychiatry, 164 : 318– 327

[20] Baur,V., nggi,J., Langer,N. ( 2013). Resting-state functional and structural connectivity within an insula-amygdala route specifically index state and trait anxiety. Biol. Psychiatry, 73 : 85– 92

[21] Straube,T., Kolassa,I. T., Glauer,M., Mentzel,H. J. Miltner,W. ( 2004). Effect of task conditions on brain responses to threatening faces in social phobics: an event-related functional magnetic resonance imaging study. Biol. Psychiatry, 56 : 921– 930

[22] Lira Yoon,K., Fitzgerald,D. A., Angstadt,M., McCarron,R. A. Phan,K. ( 2007). Amygdala reactivity to emotional faces at high and low intensity in generalized social phobia: a 4-Tesla functional MRI study. Psychiatry Res., 154 : 93– 98

[23] Stein,M. B., Goldin,P. R., Sareen,J., Zorrilla,L. T. Brown,G. ( 2002). Increased amygdala activation to angry and contemptuous faces in generalized social phobia. Arch. Gen. Psychiatry, 59 : 1027– 1034

[24] Blair,K. S., Geraci,M., Otero,M., Majestic,C., Odenheimer,S., Jacobs,M., Blair,R. J. Pine,D. ( 2011). Atypical modulation of medial prefrontal cortex to self-referential comments in generalized social phobia. Psychiatry Res., 193 : 38– 45

[25] Boehme,S., Ritter,V., Tefikow,S., Stangier,U., Strauss,B., Miltner,W. H. ( 2014). Brain activation during anticipatory anxiety in social anxiety disorder. Soc. Cogn. Affect. Neurosci., 9 : 1413– 1418

[26] Izuma,K., Saito,D. N. ( 2008). Processing of social and monetary rewards in the human striatum. Neuron, 58 : 284– 294

[27] Izuma,K., Saito,D. N. ( 2010). Processing of the incentive for social approval in the ventral striatum during charitable donation. J. Cogn. Neurosci., 22 : 621– 631

[28] Nutt,D. J., Bell,C. J. Malizia,A. ( 1998). Brain mechanisms of social anxiety disorder. J. Clin. Psychiatry, 59 : 4– 11

[29] Blackford,J. U. Pine,D. ( 2012). Neural substrates of childhood anxiety disorders: a review of neuroimaging findings. Child Adolesc. Psychiatr. Clin. N. Am., 21 : 501– 525

[30] Mochcovitch,M. D., da Rocha Freire,R. C., Garcia,R. F. Nardi,A. ( 2014). A systematic review of fMRI studies in generalized anxiety disorder: evaluating its neural and cognitive basis. J. Affect. Disord., 167 : 336– 342

[31] Domschke,K. ( 2010). Imaging genetics of anxiety disorders. Neuroimage, 53 : 822– 831

[32] Grupe,D. W. Nitschke,J. ( 2013). Uncertainty and anticipation in anxiety: an integrated neurobiological and psychological perspective. Nat. Rev. Neurosci., 14 : 488– 501

[33] Xia,F. Kheirbek,M. ( 2020). Circuit-based biomarkers for mood and anxiety disorders. Trends Neurosci., 43 : 902– 915

[34] Dafflon,J., Pinaya,W. H. L., Turkheimer,F., Cole,J. H., Leech,R., Harris,M. A., Cox,S. R., Whalley,H. C., McIntosh,A. M. Hellyer,P. ( 2020). An automated machine learning approach to predict brain age from cortical anatomical measures. Hum. Brain Mapp., 41 : 3555– 3566

[35] Tipping,M. ( 2001). Sparse Bayesian learning and the relevance vector machine. J. Mach. Learn. Res., 1 : 211– 244

[36] Li,S., Yuan,X., Pu,F., Li,D., Fan,Y., Wu,L., Chao,W., Chen,N., He,Y. ( 2014). Abnormal changes of multidimensional surface features using multivariate pattern classification in amnestic mild cognitive impairment patients. J. Neurosci., 34 : 10541– 10553

[37] Ecker,C., Marquand,A., o-Miranda,J., Johnston,P., Daly,E. M., Brammer,M. J., Maltezos,S., Murphy,C. M., Robertson,D., Williams,S. C. . ( 2010). Describing the brain in autism in five dimensions-magnetic resonance imaging-assisted diagnosis of autism spectrum disorder using a multiparameter classification approach. J. Neurosci., 30 : 10612– 10623

[38] Westman,E., Aguilar,C., Muehlboeck,J. S. ( 2013). Regional magnetic resonance imaging measures for multivariate analysis in Alzheimer’s disease and mild cognitive impairment. Brain Topogr., 26 : 9– 23

[39] Sui,J., Jiang,R., Bustillo,J. ( 2020). Neuroimaging-based individualized prediction of cognition and behavior for mental disorders and health: Methods and promises. Biol. Psychiatry, 88 : 818– 828

[40] Cheng,B., Zhang,D., Chen,S., Kaufer,D. I., Shen,D. ( 2013). Semi-supervised multimodal relevance vector regression improves cognitive performance estimation from imaging and biological biomarkers. Neuroinformatics, 11 : 339– 353

[41] Feng,C., Cui,Z., Cheng,D., Xu,R. ( 2019). Individualized prediction of dispositional worry using white matter connectivity. Psychol. Med., 49 : 1999– 2008

[42] Xu,J., Van Dam,N. T., Feng,C., Luo,Y., Ai,H., Gu,R. ( 2019). Anxious brain networks: A coordinate-based activation likelihood estimation meta-analysis of resting-state functional connectivity studies in anxiety. Neurosci. Biobehav. Rev., 96 : 21– 30

[43] Yeo,B. T., Krienen,F. M., Sepulcre,J., Sabuncu,M. R., Lashkari,D., Hollinshead,M., Roffman,J. L., Smoller,J. W., llei,L., Polimeni,J. R. . ( 2011). The organization of the human cerebral cortex estimated by intrinsic functional connectivity. J. Neurophysiol., 106 : 1125– 1165

[44] Sheline,Y. I., Price,J. L., Yan,Z. Mintun,M. ( 2010). Resting-state functional MRI in depression unmasks increased connectivity between networks via the dorsal nexus. Proc. Natl. Acad. Sci. USA, 107 : 11020– 11025

[45] Choi,E. Y., Yeo,B. T. Buckner,R. ( 2012). The organization of the human striatum estimated by intrinsic functional connectivity. J. Neurophysiol., 108 : 2242– 2263

[46] Buckner,R. L., Krienen,F. M., Castellanos,A., Diaz,J. C. Yeo,B. ( 2011). The organization of the human cerebellum estimated by intrinsic functional connectivity. J. Neurophysiol., 106 : 2322– 2345

[47] Sang,L., Qin,W., Liu,Y., Han,W., Zhang,Y., Jiang,T. ( 2012). Resting-state functional connectivity of the vermal and hemispheric subregions of the cerebellum with both the cerebral cortical networks and subcortical structures. Neuroimage, 61 : 1213– 1225

[48] Amaral,D. ( 2002). The primate amygdala and the neurobiology of social behavior: implications for understanding social anxiety. Biol. Psychiatry, 51 : 11– 17

[49] Hahn,A., Stein,P., Windischberger,C., Weissenbacher,A., Spindelegger,C., Moser,E., Kasper,S. ( 2011). Reduced resting-state functional connectivity between amygdala and orbitofrontal cortex in social anxiety disorder. Neuroimage, 56 : 881– 889

[50] Duval,E. R., Joshi,S. A., Russman Block,S., Abelson,J. L. ( 2018). Insula activation is modulated by attention shifting in social anxiety disorder. J. Anxiety Disord., 56 : 56– 62

[51] Klumpp,H., Post,D., Angstadt,M., Fitzgerald,D. A. Phan,K. ( 2013). Anterior cingulate cortex and insula response during indirect and direct processing of emotional faces in generalized social anxiety disorder. Biol. Mood Anxiety Disord., 3 : 7

[52] Phan,K. L., Fitzgerald,D. A., Nathan,P. J. Tancer,M. ( 2006). Association between amygdala hyperactivity to harsh faces and severity of social anxiety in generalized social phobia. Biol. Psychiatry, 59 : 424– 429

[53] Bas-Hoogendam,J. M., van Steenbergen,H., van der Wee,N. J. A. Westenberg,P. ( 2020). Amygdala hyperreactivity to faces conditioned with a social-evaluative meaning− a multiplex, multigenerational fMRI study on social anxiety endophenotypes. Neuroimage Clin., 26 : 102247

[54] Klumpp,H., Angstadt,M. Phan,K. ( 2012). Insula reactivity and connectivity to anterior cingulate cortex when processing threat in generalized social anxiety disorder. Biol. Psychol., 89 : 273– 276

[55] Shah,S. G., Klumpp,H., Angstadt,M., Nathan,P. J. Phan,K. ( 2009). Amygdala and insula response to emotional images in patients with generalized social anxiety disorder. J. Psychiatry Neurosci., 34 : 296– 302

[56] Rossignol,M., Campanella,S., Bissot,C. ( 2013). Fear of negative evaluation and attentional bias for facial expressions: an event-related study. Brain Cogn., 82 : 344– 352

[57] Birk,S. L., Horenstein,A., Weeks,J., Olino,T., Heimberg,R., Goldin,P. R. Gross,J. ( 2019). Neural responses to social evaluation: The role of fear of positive and negative evaluation. J. Anxiety Disord., 67 : 102114

[58] Gu,R., Ao,X., Mo,L. ( 2020). Neural correlates of negative expectancy and impaired social feedback processing in social anxiety. Soc. Cogn. Affect. Neurosci., 15 : 285– 291

[59] Syal,S., Hattingh,C. J., Spottiswoode,B., Carey,P. D., Lochner,C. Stein,D. ( 2012). Grey matter abnormalities in social anxiety disorder: a pilot study. Metab. Brain Dis., 27 : 299– 309

[60] Kawaguchi,A., Nemoto,K., Nakaaki,S., Kawaguchi,T., Kan,H., Arai,N., Shiraishi,N., Hashimoto,N. ( 2016). Insular volume reduction in patients with social anxiety disorder. Front. Psychiatry, 7 : 3

[61] Papousek,I. ( 2001). Associations between EEG asymmetries and electrodermal lability in low vs. high depressive and anxious normal individuals. Int. J. Psychophysiol., 41 : 105– 117

[62] Blackhart,G. C., Minnix,J. A. Kline,J. ( 2006). Can EEG asymmetry patterns predict future development of anxiety and depression? A preliminary study.. Biol. Psychol., 72 : 46– 50

[63] Aftanas,L. I. Pavlov,S. ( 2005). Trait anxiety impact on posterior activation asymmetries at rest and during evoked negative emotions: EEG investigation. Int. J. Psychophysiol., 55 : 85– 94

[64] Davidson,R. J. Fox,N. ( 1982). Asymmetrical brain activity discriminates between positive and negative affective stimuli in human infants. Science, 218 : 1235– 1237

[65] Davidson,R. J. Fox,N. ( 1989). Frontal brain asymmetry predicts infants’ response to maternal separation. J. Abnorm. Psychol., 98 : 127– 131

[66] Kalin,N. H., Larson,C., Shelton,S. E. Davidson,R. ( 1998). Asymmetric frontal brain activity, cortisol, and behavior associated with fearful temperament in rhesus monkeys. Behav. Neurosci., 112 : 286– 292

[67] Wheeler,R. E., Davidson,R. J. Tomarken,A. ( 1993). Frontal brain asymmetry and emotional reactivity: a biological substrate of affective style. Psychophysiology, 30 : 82– 89

[68] Geiger,M. J., Domschke,K., Ipser,J., Hattingh,C., Baldwin,D. S., Lochner,C. Stein,D. ( 2016). Altered executive control network resting-state connectivity in social anxiety disorder. World J. Biol. Psychiatry, 17 : 47– 57

[69] Seeley,W. W., Menon,V., Schatzberg,A. F., Keller,J., Glover,G. H., Kenna,H., Reiss,A. L. Greicius,M. ( 2007). Dissociable intrinsic connectivity networks for salience processing and executive control. J. Neurosci., 27 : 2349– 2356

[70] Morillas-Romero,A., Tortella-Feliu,M., Balle,M. ( 2015). Spontaneous emotion regulation and attentional control. Emotion, 15 : 162– 175

[71] Tully,L. M., Lincoln,S. H. Hooker,C. ( 2012). Impaired executive control of emotional information in social anhedonia. Psychiatry Res., 197 : 29– 35

[72] Jacob,Y., Shany,O., Goldin,P. R., Gross,J. J. ( 2019). Reappraisal of interpersonal criticism in social anxiety disorder: A brain network hierarchy perspective. Cereb. Cortex, 29 : 3154– 3167

[73] Binder,J. R. Desai,R. ( 2011). The neurobiology of semantic memory. Trends Cogn. Sci., 15 : 527– 536

[74] Zhang,D., Lin,Y., Jing,Y., Feng,C. ( 2019). The dynamics of belief updating in human cooperation: Findings from inter-brain ERP hyperscanning. Neuroimage, 198 : 1– 12

[75] Nielsen,F. A., Balslev,D. Hansen,L. ( 2005). Mining the posterior cingulate: segregation between memory and pain components. Neuroimage, 27 : 520– 532

[76] Murty,V. P., Ritchey,M., Adcock,R. A. LaBar,K. ( 2010). fMRI studies of successful emotional memory encoding: A quantitative meta-analysis. Neuropsychologia, 48 : 3459– 3469

[77] Medford,N., Phillips,M. L., Brierley,B., Brammer,M., Bullmore,E. T. David,A. ( 2005). Emotional memory: separating content and context. Psychiatry Res., 138 : 247– 258

[78] Erk,S., Kiefer,M., Grothe,J., Wunderlich,A. P., Spitzer,M. ( 2003). Emotional context modulates subsequent memory effect. Neuroimage, 18 : 439– 447

[79] Mitelman,S. ( 2019). Transdiagnostic neuroimaging in psychiatry: A review. Psychiatry Res., 277 : 23– 38

[80] Etkin,A. ( 2019). A reckoning and research agenda for neuroimaging in psychiatry. Am. J. Psychiatry, 176 : 507– 511

[81] Linden,D. ( 2012). The challenges and promise of neuroimaging in psychiatry. Neuron, 73 : 8– 22

[82] Tang,H., Lu,X., Cui,Z., Feng,C., Lin,Q., Cui,X., Su,S. ( 2018). Resting-state functional connectivity and deception: Exploring individualized deceptive propensity by machine learning. Neuroscience, 395 : 101– 112

[83] Lu,X., Li,T., Xia,Z., Zhu,R., Wang,L., Luo,Y. J., Feng,C. ( 2019). Connectome-based model predicts individual differences in propensity to trust. Hum. Brain Mapp., 40 : 1942– 1954

[84] Stonnington,C. M., Chu,C., ppel,S., Jack,C. R. Ashburner,J. Frackowiak,R. S. ( 2010). Predicting clinical scores from magnetic resonance scans in Alzheimer’s disease. Neuroimage, 51 : 1405– 1413

[85] Liu,F., Guo,W., Fouche,J. P., Wang,Y., Wang,W., Ding,J., Zeng,L., Qiu,C., Gong,Q., Zhang,W. . ( 2015). Multivariate classification of social anxiety disorder using whole brain functional connectivity. Brain Struct. Funct., 220 : 101– 115

[86] Whitfield-Gabrieli,S., Ghosh,S. S., Nieto-Castanon,A., Saygin,Z., Doehrmann,O., Chai,X. J., Reynolds,G. O., Hofmann,S. G., Pollack,M. H. Gabrieli,J. ( 2016). Brain connectomics predict response to treatment in social anxiety disorder. Mol. Psychiatry, 21 : 680– 685

[87] Liu,F., Zhu,C., Wang,Y., Guo,W., Li,M., Wang,W., Long,Z., Meng,Y., Cui,Q., Zeng,L. . ( 2015). Disrupted cortical hubs in functional brain networks in social anxiety disorder. Clin. Neurophysiol., 126 : 1711– 1716

[88] Fox,R. S., Kwakkenbos,L., Carrier,M. E., Mills,S. D., Gholizadeh,S., Jewett,L. R., Roesch,S. C., Merz,E. L., Assassi,S., Furst,D. E. . ( 2018). Reliability and validity of three versions of the brief fear of negative evaluation scale in patients with systemic sclerosis: A scleroderma patient-centered intervention network cohort study. Arthritis Care Res. (Hoboken), 70 : 1646– 1652

[89] Wong,Q. J. Moulds,M. ( 2014). An examination of the measurement equivalence of the brief fear of negative evaluation scale across individuals who identify with an asian ethnicity and individuals who identify with a European ethnicity. Assessment, 21 : 713– 722

[90] Bach,D. R., Hoffmann,M., Finke,C., Hurlemann,R. Ploner,C. ( 2019). Disentangling hippocampal and amygdala contribution to human anxiety-like behavior. J. Neurosci., 39 : 8517– 8526

[91] Berry,A. S., White,R. L. Furman,D. J., Naskolnakorn,J. R., Shah,V. D., Esposito,M. Jagust,W. ( 2019). Dopaminergic mechanisms underlying normal variation in trait anxiety. J. Neurosci., 39 : 2735– 2744

[92] Fung,B. J., Qi,S., Hassabis,D., Daw,N. ( 2019). Slow escape decisions are swayed by trait anxiety. Nat. Hum. Behav., 3 : 702– 708

[93] Geng,H., Wang,Y., Gu,R., Luo,Y. J., Xu,P., Huang,Y. ( 2018). Altered brain activation and connectivity during anticipation of uncertain threat in trait anxiety. Hum. Brain Mapp., 39 : 3898– 3914

[94] McNaughton,N. ( 2019). Brain maps of fear and anxiety. Nat. Hum. Behav., 3 : 662– 663

[95] Leary,M. ( 1983). A brief version of the fear of negative evaluation scale. Pers. Soc. Psychol. Bull., 9 : 371– 375

[96] Collins,K. A., Westra,H. A., Dozois,D. J. Stewart,S. ( 2005). The validity of the brief version of the fear of negative evaluation scale. J. Anxiety Disord., 19 : 345– 359

[97] Rodebaugh,T. L., Woods,C. M., Thissen,D. M., Heimberg,R. G., Chambless,D. L. Rapee,R. ( 2004). More information from fewer questions: the factor structure and item properties of the original and brief fear of negative evaluation scale. Psychol. Assess., 16 : 169– 181

[98] Dale,A. M., Fischl,B. Sereno,M. ( 1999). Cortical surface-based analysis. I. Segmentation and surface reconstruction. Neuroimage, 9 : 179– 194

[99] Destrieux,C., Fischl,B., Dale,A. ( 2010). Automatic parcellation of human cortical gyri and sulci using standard anatomical nomenclature. Neuroimage, 53 : 1– 15

[100] Gong,Q., Li,L., Du,M., Pettersson-Yeo,W., Crossley,N., Yang,X., Li,J., Huang,X. ( 2014). Quantitative prediction of individual psychopathology in trauma survivors using resting-state FMRI. Neuropsychopharmacology, 39 : 681– 687

[101] Franke,K., Ziegler,G., ppel,S., Gaser,C. ( 2010). Estimating the age of healthy subjects from T1-weighted MRI scans using kernel methods: exploring the influence of various parameters. Neuroimage, 50 : 883– 892

[102] Feng,C., Zhu,Z., Cui,Z., Ushakov,V., Dreher,J. Luo,W., Gu,R., Wu,X. ( 2021). Prediction of trust propensity from intrinsic brain morphology and functional connectome. Hum Brain Mapp. 42, 175– 191

[103] Cui,Z. ( 2018). The effect of machine learning regression algorithms and sample size on individualized behavioral prediction with functional connectivity features. Neuroimage, 178 : 622– 637

[104] Erus,G., Battapady,H., Satterthwaite,T. D., Hakonarson,H., Gur,R. E., Davatzikos,C. Gur,R. ( 2015). Imaging patterns of brain development and their relationship to cognition. Cereb. Cortex, 25 : 1676– 1684

AUTHOR CONTRIBUTIONS

CF conceived the experiment, performed the experiment, collected the data, and analyzed the data. CF, FK, RG, and WL wrote the manuscript.

ACKNOWLEDGEMENTS

This work was supported by the National Natural Science Foundation of China (Nos. 31900757, 32071083 and 32020103008), the Major Program of the Chinese National Social Science Foundation (No. 17ZDA324), and the Youth Innovation Promotion Association, CAS (No. 2019088).

COMPLIANCE WITH ETHICS GUIDELINES

The authors Chunliang Feng, Frank Krueger, Ruolei Gu and Wenbo Luo declare that they have no conflict of interest.

All procedures performed in this study were in accordance with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. The local ethics committee approved the experimental protocol.

RIGHTS & PERMISSIONS

2022 The Authors (2022). Published by Higher Education Press.