Stage-specific Neural Signatures Representing Threats During Dynamic Predator-prey Interaction
Poster No:
711
Submission Type:
Abstract Submission
Authors:
Yanan Qing1,2, Yuanyuan Zhang1,2, Jiayuan Wang1,2, Wenjie Chen1,2, Song Qi3, Xianyang Gan1,2, Keith Kendrick1,2, Shuxia Yao1,2
Institutions:
1The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, China, 2The MOE Key Laboratory for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China, 3Section on Development and Affective Neuroscience, National Institute of Mental Health, Bethesda, United States
First Author:
Yanan Qing
The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China|The MOE Key Laboratory for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China
Chengdu, China|Chengdu, China
The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China|The MOE Key Laboratory for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China
Chengdu, China|Chengdu, China
Co-Author(s):
Yuanyuan Zhang
The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China|The MOE Key Laboratory for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China
Chengdu, China|Chengdu, China
The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China|The MOE Key Laboratory for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China
Chengdu, China|Chengdu, China
Jiayuan Wang
The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China|The MOE Key Laboratory for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China
Chengdu, China|Chengdu, China
The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China|The MOE Key Laboratory for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China
Chengdu, China|Chengdu, China
Wenjie Chen
The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China|The MOE Key Laboratory for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China
Chengdu, China|Chengdu, China
The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China|The MOE Key Laboratory for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China
Chengdu, China|Chengdu, China
Song Qi
Section on Development and Affective Neuroscience, National Institute of Mental Health
Bethesda, United States
Section on Development and Affective Neuroscience, National Institute of Mental Health
Bethesda, United States
Xianyang Gan
The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China|The MOE Key Laboratory for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China
Chengdu, China|Chengdu, China
The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China|The MOE Key Laboratory for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China
Chengdu, China|Chengdu, China
Keith Kendrick
The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China|The MOE Key Laboratory for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China
Chengdu, China|Chengdu, China
The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China|The MOE Key Laboratory for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China
Chengdu, China|Chengdu, China
Shuxia Yao
The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China|The MOE Key Laboratory for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China
Chengdu, China|Chengdu, China
The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China|The MOE Key Laboratory for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China
Chengdu, China|Chengdu, China
Introduction:
In evolutionary ecology, the interaction between predators and prey constitutes an essential process that drives organism evolution (Cooper & Blumstein, 2015). To survive, individuals have evolved highly adaptive defensive behaviors to address environmental threats (Bolles, 1971). Note that predator-prey interaction is normally dynamic and thus requires real-time evaluation of the spatiotemporal relationship between threat, safe refuge, and themselves. However, how humans make escape decisions during such dynamic predator-prey interaction and its neural underpinnings are unclear. There is also a lack of evidence for how humans continuously assess the threat following escape decisions. Here, we developed a dynamic predator-prey interaction (DPPI) paradigm combining with the functional magnetic resonance imaging (fMRI) to address these issues.
Methods:
The dynamic predator-prey interaction paradigm included 4 different stages: monitoring, decision, chase, and outcome anticipation. Participants were instructed to make escape decisions based on the evaluation of relative distance between themselves (i.e., the prey), the predator and the refuge when encountering different threat levels of predators. Threat levels were manipulated by different attacking speeds (slow, medium and fast) and participants would receive a shock if they were caught by a predator. For behavioral data, in addition to success rates of escape, confidence ratings were collected to measure individuals' pre-task confidence in escaping from predators while anxiety ratings measured their anxious levels during performing the task. For neural responses, we employed the machine learning-based multivariate pattern analysis (a support vector machine algorithm) to obtain stage-specific whole-brain pattern classifiers for high- vs. low-level threats (Kohoutová et al., 2020), which were termed as escape stage-specific predator signatures (ESSPS). The performance of ESSPS were evaluated by a leave-one-out validation procedure. Next, we determined brain regions that contributed to the ESSPS based on a bootstrap test (10000 samples with replacement). Finally, we generalized ESSPS to fear conditioning and pain perception datasets to test the specificity and sensitivity of the ESSPS.
Results:
Behavioral results revealed significant differences of confidence and anxiety ratings and success rates between different predators (Fig. 1A), validating the experimental manipulation. Neural results showed that the developed ESSPS (Fig. 1B) could accurately classify fast vs. slow predators in different defensive stages, with the lowest accuracy of 71.79% (p < 0.001) in the monitoring stage. By applying the thresholding bootstrap procedures, results showed that ESSPS were involved in distributed subcortical and cortical systems (Fig. 1C) and varied across different stages. ESSPS could also distinguish different threat levels in fear conditioning and pain perception datasets (Fig. 1D).
Conclusions:
Our study developed a dynamic predator-prey interaction paradigm that can successfully induce different defensive responses to different levels of threats. More importantly, we further tracked how humans represented threats in different defensive stages and determined different neural signatures classifying high vs. low threats in different stages. These signatures are involved in distributed cortical and sub-cortical brain systems consistent with previous signatures developed for fear and pain perception classification. We provide new insight into neural substrates underpinning threat representation during dynamic interaction and may extend our understanding of how anxiety and fear processing become dysfunctional in humans.
Emotion, Motivation and Social Neuroscience:
Emotional Perception
Higher Cognitive Functions:
Decision Making 1
Novel Imaging Acquisition Methods:
BOLD fMRI 2
Keywords:
Other - Denfenisve Decision-making, Threat Processing, Dynamic interaction
1|2Indicates the priority used for review
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Were any human subjects research approved by the relevant Institutional Review Board or ethics panel? NOTE: Any human subjects studies without IRB approval will be automatically rejected.
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Provide references using APA citation style.
Bolles, R. C. (1971). Species-Specific Defense Reactions. In F. R. Brush (Ed.), Aversive Conditioning and Learning (pp. 183-233). Academic Press.
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, 15(4), 1399-1435.