彭玉佳课题组聚焦于临床心理学的基础研究，同时涉及认知神经和人工智能的交叉研究。课题组致力于探究焦虑症和抑郁症的心理与神经机制以及治疗方法。实验方法包含人类心理物理学实验、核磁共振成像及脑电、眼动记录及其他生物信号记录、计算建模和机器学习等。具体研究问题包括但不限于：

（1）针对生物运动识别、社会认知、意图理解等任务，临床病人是否与常人存在行为反应、眼动轨迹、生理信号反应、及大脑神经网络活动上的不同；临床病人群体内部是否存在个体差异，以及这些个体差异如何与临床症状相关联。

（2）在纵向追踪的时间层面上，是否存在神经信号、环境因素、行为信号等，可以预测焦虑症状的发生和发展。

（3）基于多维数据维度，是否可以依赖个体差异，实现最优治疗方法的匹配，以及构建个性化治疗方案。

代表论著

(* Equal contribution, # Corresponding author)

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彭玉佳, 王愉茜, 鞠芊芊, 刘峰, 徐佳. (2025). 贝叶斯框架下社交焦虑的社会认知特性. 心理科学进展, 33(8), 1267-1274.

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Cushing, C. A. , Peng, Y., Anderson, Z., Young, K. S., Bookheimer, S. Y., Zinbarg, R. E., Nusslock, R., & Craske, M. G. (2024). Broadening the scope: Multiple functional connectivity networks underlying threat conditioning and extinction. Imaging Neuroscience. 2: 1–15. https://doi.org/10.1162/imag_a_00213

王愉茜, 臧寅垠, & 彭玉佳. (2024). 成人社交焦虑问卷中文版的效度和信度评价. 中国心理卫生杂志, 38(08), 730–736. DOI: 10.3969/j.issn.1000-6729.2024.08.015

Peng, Y., Burling J., Todorova G., Pollick F., & Lu, H. (2024). Patterns of Saliency and Semantic Features Distinguish Gaze of Expert and Novice Viewers of Surveillance Footage. Psychonomic Bulletin & Review. 31, 1745-1758. https://doi.org/10.3758/s13423-024-02454-y

Xu, J., Wang, Y., Peng, Y. (2024) Psychodynamic Profiles of Major Depressive Disorder and Generalized Anxiety Disorder in China. Frontiers in Psychiatry. 15:1312980. doi: 10.3389/fpsyt.2024.1312980

Peng, Y., Han J., Zhang Z., Fan L., Liu T., Qi S., Feng X., Ma Y., Wang Y., Zhu. S.C.,（2024）The Tong Test: Evaluating Artificial General Intelligence Through Dynamic Embodied Physical and Social Interactions. Engineering.34(3), 12-22. https://doi.org/10.1016/j.eng.2023.07.006

彭玉佳, 王愉茜, 路迪. (2023). 基于生物运动的社交焦虑者情绪加工与社会意图理解负向偏差机制.心理科学进展,31(6),905-914. https://doi.org/10.3724/SP.J.1042.2023.00905

Peng, Y. , Knotts, J. D. , Young, K. S., Bookheimer, S. Y., Nusslock, R., Zinbarg, R. E., ... & Craske, M. G.  (2023). Threat neurocircuitry predicts the development of anxiety and depression symptoms in a longitudinal study. Biological psychiatry: cognitive neuroscience and neuroimaging. 8(1): 102-110. https://doi.org/10.1016/j.bpsc.2021.12.013

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Peng, Y. , Lee, H., Shu, T., & Lu, H. (2020). Exploring biological motion perception in two-stream convolutional neural networks. Vision Research, 178, 28-40.

Chiang J.N. , Peng, Y., Lu, H., Holyoak, K.J., & Monti, M.M. (2020). Distributed code for semantic relations predicts neural activity during analogical reasoning. Journal of Cognitive Neuroscience, 1-13.

Peng, Y. , Ichien, N., & Lu, H. (2020). Causal actions enhance perception of continuous body movements. Cognition, 194, 104060,

Ogren, M., Kaplan, B., Peng, Y., Johnson, K. L., & Johnson, S. P. (2019). Motion or emotion: Infants discriminate emotional biological motion based on low-level visual information. Infant Behavior and Development, 57, 101324.

Tsang, T., Ogren, M., Peng, Y., Nguyen, B., Johnson, K.L. & Johnson S.P.  (2018). Infant perception of sex differences in biological motion displays. Journal of Experimental Child Psychology, 173, 338–350.

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van Boxtel, J. , Peng, Y., Su, J., & Lu, H. (2016). Individual differences in high-level biological motion tasks correlate with autistic traits. Vision Research, 141, 136-144.

Chen, J., Yu, Q., Zhu, Z., Peng, Y., & Fang, F. (2016). Spatial summation revealed in the earliest visual evoked component C1 and the effect of attention on its linearity. Journal of Neurophysiology, 115(1), 500-509.

Chen, J., He, Y., Zhu, Z., Zhou, T., Peng, Y., Zhang, X., & Fang, F. (2014). Attention-dependent early cortical suppression contributes to crowding. The Journal of Neuroscience, 34(32), 10465-10474.

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