Presented During:
Thursday, June 27, 2024: 11:30 AM - 12:45 PM
COEX
Room:
Conference Room E 1
Poster No:
749
Submission Type:
Abstract Submission
Authors:
Xianyang Gan1,2, Feng Zhou3, Ting Xu1,2, Xiaobo Liu4, Ran Zhang1,2, Zihao Zheng1,2, Xi Yang5, Xinqi Zhou6, Fangwen Yu1,2, Jialin Li7, Ruifang Cui1,2, Lan Wang1,2, Jiajin Yuan6, Dezhong Yao1,2, Benjamin Becker1,2,8,9
Institutions:
1Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China, 2The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Chengdu, China, 3Faculty of Psychology, Southwest University, Chongqing, China, 4McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Canada, 5Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, Netherlands, 6Institute of Brain and Psychological Sciences, Sichuan Normal University, Chengdu, China, 7Max Planck School of Cognition, Leipzig , Germany, 8State Key Laboratory for Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong, China, 9Department of Psychology, The University of Hong Kong, Hong Kong, China
First Author:
Xianyang Gan
Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China|The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation
Chengdu, China|Chengdu, China
Co-Author(s):
Feng Zhou
Faculty of Psychology, Southwest University
Chongqing, China
Ting Xu
Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China|The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation
Chengdu, China|Chengdu, China
Xiaobo Liu
McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University
Montreal, Canada
Ran Zhang
Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China|The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation
Chengdu, China|Chengdu, China
Zihao Zheng
Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China|The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation
Chengdu, China|Chengdu, China
Xi Yang
Faculty of Health, Medicine and Life Sciences, Maastricht University
Maastricht, Netherlands
Xinqi Zhou
Institute of Brain and Psychological Sciences, Sichuan Normal University
Chengdu, China
Fangwen Yu
Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China|The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation
Chengdu, China|Chengdu, China
Jialin Li
Max Planck School of Cognition
Leipzig , Germany
Ruifang Cui
Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China|The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation
Chengdu, China|Chengdu, China
Lan Wang
Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China|The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation
Chengdu, China|Chengdu, China
Jiajin Yuan
Institute of Brain and Psychological Sciences, Sichuan Normal University
Chengdu, China
Dezhong Yao
Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China|The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation
Chengdu, China|Chengdu, China
Benjamin Becker
Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China|The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation|State Key Laboratory for Brain and Cognitive Sciences, The University of Hong Kong|Department of Psychology, The University of Hong Kong
Chengdu, China|Chengdu, China|Hong Kong, China|Hong Kong, China
Introduction:
Recent affective and clinical neuroscience perspectives propose a paradigm shift towards subjective and conscious emotional experiences (Kyzar et al, 2023; LeDoux et al., 2017; Wager et al., 2018; Zhou et al., 2021). However, neurobiological models that accurately describe the respective neural representations are scarce. Disgust originates in the hard-wired mammalian distaste reflex, but in humans its conscious emotional experience is strongly shaped by subjective appraisal and may extend to sociomoral contexts. Here, we combined functional MRI with recent methodological advances in multivariate pattern analytic neural decoding techniques to develop an accurate and generalizable whole-brain signature predictive of momentary self-reported subjective disgust experience, and in turn utilize the neural disgust signature to test the evolutionary perspective on disgust.
Methods:
First, consistent with methods evaluated in previous studies developing neuroaffective decoders (Chang et al., 2015; Zhou et al., 2021), we employed a linear support vector regression model to identify a whole-brain signature of fMRI activation predictive of self-reported disgust experience elicited by core disgust stimuli using data from a discovery cohort (n=78). The performance of the resultant visually induced disgust signature (VIDS) was then evaluated across multiple core disgust datasets: the discovery (10×10-fold cross-validation), validation (n=30), and generalization (n=26) cohorts. Next, we determined which brain regions and systems contribute to the whole-brain disgust prediction through a bootstrap test (Kohoutová et al., 2020) and the computation of model encoding maps (Haufe et al., 2014), and we further tested whether isolated regions or networks traditionally involved in disgust such as the insula or default mode network were sufficient to predict subjective disgust experience. Moreover, functional decoding analysis based on Neurosynth was also conducted to evaluate the neurobiological validity of the developed VIDS. We next systematically examined the functional specificity of the VIDS by conducting predictive comparisons with established decoders for subjective fear (VIFS; Zhou et al., 2021) and negative affect (PINES; Chang et al., 2015), respectively. Finally, we tested the evolutionary perspective on disgust by applying the decoders in fMRI experiments on gustatory distaste (n=30) and sociomoral disgust (fairness norm violations; n=43).
Results:
The results showed that the developed VIDS (Fig. 1a) accurately predicted momentary self-reported subjective disgust across three core disgust datasets (Fig. 1b,c,d), such that the averaged within-subject correlation between predicted and true disgust ratings was ≥0.88 in all cases and classification accuracies between different disgust levels were high (≥76%). The conscious experience of disgust is represented in distributed subcortical and cortical systems (Fig. 1e), and the contribution of insula (Fig. 1f) and large-scale networks (Fig. 1g) show lower predictive accuracy compared to the VIDS. More interestingly, the functional decoding analysis supported the disgust signature as a biologically plausible disgust model (Fig. 1h). The three affective decoders most accurately predicted the respective target experience, and the VIDS moreover outperformed the VIFS and PINES in predicting disgust experience in response to both gustatory distaste and sociomoral disgust (unfair offers) as revealed by both prediction accuracy and effect size (for more details see Gan et al., 2023).
![Supporting Image: Fig1.jpg](https://files.aievolution.com/prd/hbm2401/abstracts/abs_2733/Fig1.jpg)
Conclusions:
The present study developed a sensitive neural signature for subjective disgust experience, which robustly generalizes across core disgust, gustatory distaste, and sociomoral contexts. The neural basis of subjective disgust is encoded in multiple distributed brain systems rather than isolated brain regions. We provide an accurate fMRI-signature for disgust with a high potential to resolve ongoing evolutionary debates.
Emotion, Motivation and Social Neuroscience:
Emotional Perception 1
Modeling and Analysis Methods:
Activation (eg. BOLD task-fMRI)
Classification and Predictive Modeling 2
Novel Imaging Acquisition Methods:
BOLD fMRI
Keywords:
Other - Disgust; unfairness; moral; gustatory distaste; neural decoding; fMRI; multivariate pattern analysis; emotion; subjective; neural signature
1|2Indicates the priority used for review
Provide references using author date format
Chang, L. J., Gianaros, P. J., Manuck, S. B., Krishnan, A., & Wager, T. D. (2015), 'A sensitive and specific neural signature for picture-induced negative affect', PLoS Biology, vol. 13, no. 6, pp. e1002180.
Gan, X., Zhou, F., Xu, T., Liu, X., Zhang, R., Zheng, Z., . . . Becker, B. (2023), 'Rotten to the core – a neurofunctional signature of subjective core disgust generalizes to socio-moral contexts', bioRxiv.
Haufe, S., Meinecke, F., Görgen, K., Dähne, S., Haynes, J.-D., Blankertz, B., & Bießmann, F. (2014), 'On the interpretation of weight vectors of linear models in multivariate neuroimaging', Neuroimage, vol. 87, pp. 96-110.
Kohoutová, L., Heo, J., Cha, S., Lee, S., Moon, T., Wager, T. D., & Woo, C.-W. (2020), 'Toward a unified framework for interpreting machine-learning models in neuroimaging', Nature Protocols, vol. 15, no. 4, pp. 1399-1435.
Kyzar, E. J., & Denfield, G. H. (2023), 'Taking subjectivity seriously: towards a unification of phenomenology, psychiatry, and neuroscience', Molecular Psychiatry, vol. 28, no. 1, pp. 10-16.
LeDoux, J. E., & Brown, R. (2017), 'A higher-order theory of emotional consciousness', Proceedings of the National Academy of Sciences of the United States of America, vol. 114, no.10, pp. E2016-E2025.
Wager, T. D., Krishnan, A., & Hitchcock, E. (2018), 'How are emotions organized in the brain?', In A. S. Fox, R. C. Lapate, A. J. Shackman, & R. J. Davidson (Eds.), The nature of emotion. Fundamental questions (pp. 112-118). New York, NY: Oxford University Press.
Zhou, F., Zhao, W., Qi, Z., Geng, Y., Yao, S., Kendrick, K. M., . . . Becker, B. (2021), 'A distributed fMRI-based signature for the subjective experience of fear', Nature Communications, vol. 12, no. 1, pp. 6643.