Connectome-based predictive modeling of empathy in adolescents with and without the low-prosocial emotion specifier

被引:0
|
作者
Winters, Drew E. [1 ]
Guha, Anika [1 ]
Sakai, Joseph T. [1 ]
机构
[1] Univ Colorado, Dept Psychiat, Sch Med, Anschutz Med Campus, Aurora, CO 80045 USA
关键词
Connectome-based predictive modeling; Functional connectivity; Empathy; Callous -unemotional traits; Adolescents; CALLOUS-UNEMOTIONAL TRAITS; BRAIN; BEHAVIOR; SYSTEM;
D O I
10.1016/j.neulet.2023.137371
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Empathy impairments are an important part of a broader affective impairments defining the youth antisocial phenotype callous-unemotional (CU) traits and the DSM-5 low prosocial emotion (LPE) specifier. While functional connectivity underlying empathy and CU traits have been well studied, less is known about what functional connections underly differences in empathy amongst adolescents qualifying for the LPE specifier. Such information can provide mechanistic distinctions for this clinically relevant specifier. The present study uses connectome-based predictive modeling that uses whole-brain resting-state functional connectivity data to predict cognitive and affective empathy for those meeting the LPE specifier (n = 29) and those that do not (n = 57). Additionally, we tested if models of empathy generalized between groups as well as density differences for each model of empathy between groups. Results indicate the LPE group had lower cognitive and affective empathy as well as higher CU traits and conduct problems. Negative and positive models were identified for affective empathy for both groups, but only the negative model for the LPE and positive model for the normative group reliably predicted cognitive empathy. Models predicting empathy did not generalize between groups. Density differences within the default mode, salience, executive control, limbic, and cerebellar networks were found as well as between the executive control, salience, and default mode networks. And, importantly, connections between the executive control and default mode networks characterized empathy differences the LPE group such that more positive connections characterized cognitive differences and less negative connections characterized affective differences. These findings indicate neural differences in empathy for those meeting LPE criteria that may explain decrements in empathy amongst these youth. These findings support theoretical accounts of empathy decrements in the LPE clinical specifier and extend them to identify specific circuits accounting for variation in empathy impairments. The identified negative models help understand what connections inhibit empathy whereas the positive models reveal what brain patterns are being used to support empathy in those with the LPE specifier. LPE differences from the normative group and could be an appropriate biomarker for predicting CU trait severity. Replication and validation using other large datasets are important next steps.
引用
收藏
页数:8
相关论文
共 45 条
  • [31] Multi-modality connectome-based predictive modeling of individualized compulsions in obsessive-compulsive disorder
    Zhu, Chunyan
    Fu, Zhao
    Chen, Lu
    Yu, Fengqiong
    Zhang, Junfeng
    Zhang, Yuxuan
    Ai, Hui
    Chen, Lu
    Sui, Pengjiao
    Wu, Qianqian
    Luo, Yudan
    Xu, Pengfei
    Wang, Kai
    JOURNAL OF AFFECTIVE DISORDERS, 2022, 311 : 595 - 603
  • [32] Resting-state connectome-based support-vector-machine predictive modeling of internet gaming disorder
    Song, Kun-Ru
    Potenza, Marc N.
    Fang, Xiao-Yi
    Gong, Gao-Lang
    Yao, Yuan-Wei
    Wang, Zi-Liang
    Liu, Lu
    Ma, Shan-Shan
    Xia, Cui-Cui
    Lan, Jing
    Deng, Lin-Yuan
    Wu, Lu-Lu
    Zhang, Jin-Tao
    ADDICTION BIOLOGY, 2021, 26 (04)
  • [33] Shared and distinct structural brain networks related to childhood maltreatment and social support: connectome-based predictive modeling
    Winter, Alexandra
    Gruber, Marius
    Thiel, Katharina
    Flinkenfluegel, Kira
    Meinert, Susanne
    Goltermann, Janik
    Winter, Nils R.
    Borgers, Tiana
    Stein, Frederike
    Jansen, Andreas
    Brosch, Katharina
    Wroblewski, Adrian
    Thomas-Odenthal, Florian
    Usemann, Paula
    Straube, Benjamin
    Alexander, Nina
    Jamalabadi, Hamidreza
    Nenadic, Igor
    Bonnekoh, Linda M.
    Dohm, Katharina
    Leehr, Elisabeth J.
    Opel, Nils
    Grotegerd, Dominik
    Hahn, Tim
    van den Heuvel, Martijn P.
    Kircher, Tilo
    Repple, Jonathan
    Dannlowski, Udo
    MOLECULAR PSYCHIATRY, 2023,
  • [34] Connectome-based predictive modeling of attention: Comparing different functional connectivity features and prediction methods across datasets
    Yoo, Kwangsun
    Rosenberg, Monica D.
    Hsu, Wei-Ting
    Zhang, Sheng
    Li, Chiang-Shan R.
    Scheinost, Dustin
    Constable, R. Todd
    Chun, Marvin M.
    NEUROIMAGE, 2018, 167 : 11 - 22
  • [35] Brain Functional Connectivity Predicts Depression and Anxiety During Childhood and Adolescence: A Connectome-Based Predictive Modeling Approach
    Morfini, Francesca
    Kucyi, Aaron
    Zhang, Jiahe
    Bauer, Clemens
    Bloom, Paul Alexander
    Pagliaccio, David
    Auerbach, Randy P.
    Whitfield-Gabrieli, Susan
    BIOLOGICAL PSYCHIATRY, 2023, 93 (09) : S327 - S328
  • [36] Large-scale functional brain networks of maladaptive childhood aggression identified by connectome-based predictive modeling
    Ibrahim, Karim
    Noble, Stephanie
    He, George
    Lacadie, Cheryl
    Crowley, Michael J.
    McCarthy, Gregory
    Scheinost, Dustin
    Sukhodolsky, Denis G.
    MOLECULAR PSYCHIATRY, 2022, 27 (02) : 985 - 999
  • [37] Shared and distinct structural brain networks related to childhood maltreatment and social support: connectome-based predictive modeling
    Alexandra Winter
    Marius Gruber
    Katharina Thiel
    Kira Flinkenflügel
    Susanne Meinert
    Janik Goltermann
    Nils R. Winter
    Tiana Borgers
    Frederike Stein
    Andreas Jansen
    Katharina Brosch
    Adrian Wroblewski
    Florian Thomas-Odenthal
    Paula Usemann
    Benjamin Straube
    Nina Alexander
    Hamidreza Jamalabadi
    Igor Nenadić
    Linda M. Bonnekoh
    Katharina Dohm
    Elisabeth J. Leehr
    Nils Opel
    Dominik Grotegerd
    Tim Hahn
    Martijn P. van den Heuvel
    Tilo Kircher
    Jonathan Repple
    Udo Dannlowski
    Molecular Psychiatry, 2023, 28 : 4613 - 4621
  • [38] Large-scale functional brain networks of maladaptive childhood aggression identified by connectome-based predictive modeling
    Karim Ibrahim
    Stephanie Noble
    George He
    Cheryl Lacadie
    Michael J. Crowley
    Gregory McCarthy
    Dustin Scheinost
    Denis G. Sukhodolsky
    Molecular Psychiatry, 2022, 27 : 985 - 999
  • [39] Transdiagnostic Prediction of Memory and Cognitive Abilities From Functional Connectivity Data: A Multidimensional Connectome-Based Predictive Modeling Study
    Scheinost, Dustin
    Gao, Siyuan
    Greene, Abigail
    Constable, R. Todd
    BIOLOGICAL PSYCHIATRY, 2018, 83 (09) : S33 - S33
  • [40] Using modular connectome-based predictive modeling to reveal brain-behavior relationships of individual differences in working memory
    Yang, Huayi
    Zhang, Junjun
    Jin, Zhenlan
    Bashivan, Pouya
    Li, Ling
    BRAIN STRUCTURE & FUNCTION, 2023, 228 (06): : 1479 - 1492