姓　　名：
彭玉佳
職　　稱：
研究員 博導(dǎo)
研究領(lǐng)域：
臨床心理學(xué) 焦慮與抑郁 社會認(rèn)知 腦成像 人工智能
通信地址：
北京大學(xué)哲學(xué)樓
電子郵件：
[email protected]
個人主頁：
https://www.ypeng.org/
實驗室主頁：
https://www.www.cofsy.cn/kxyj/kysys/363505.htm

彭玉佳研究員于2014年畢業(yè)于北京大學(xué)心理學(xué)系，獲得學(xué)士學(xué)位。2019年畢業(yè)于加州大學(xué)洛杉磯分校，獲得博士學(xué)位。2019年到2021年，在加州大學(xué)洛杉磯分校Michelle Craske和Hakwan Lau組從事博士后研究。2021年9月入職北京大學(xué)心理與認(rèn)知科學(xué)學(xué)院。彭玉佳研究員的研究主要關(guān)注焦慮癥與抑郁癥的機制研究，以及社會認(rèn)知與人工智能研究。研究成果發(fā)表于Biological Psychiatry : Cognitive Neuroscience and Neuroimaging, Psychiatry Research， Psychological Science, Cognition，Vision Research等同行評議的重要學(xué)術(shù)期刊上。

彭玉佳課題組聚焦于臨床心理學(xué)的基礎(chǔ)研究，同時涉及認(rèn)知神經(jīng)和人工智能的交叉研究。課題組致力于探究焦慮癥和抑郁癥的心理與神經(jīng)機制以及治療方法。實驗方法包含人類心理物理學(xué)實驗、核磁共振成像及腦電、眼動記錄及其他生物信號記錄、計算建模和機器學(xué)習(xí)等。具體研究問題包括但不限于：

（1）針對生物運動識別、社會認(rèn)知、意圖理解等任務(wù)，臨床病人是否與常人存在行為反應(yīng)、眼動軌跡、生理信號反應(yīng)、及大腦神經(jīng)網(wǎng)絡(luò)活動上的不同；臨床病人群體內(nèi)部是否存在個體差異，以及這些個體差異如何與臨床癥狀相關(guān)聯(lián)。

（2）在縱向追蹤的時間層面上，是否存在神經(jīng)信號、環(huán)境因素、行為信號等，可以預(yù)測焦慮癥狀的發(fā)生和發(fā)展。

（3）基于多維數(shù)據(jù)維度，是否可以依賴個體差異，實現(xiàn)最優(yōu)治療方法的匹配，以及構(gòu)建個性化治療方案。

代表論著

(* Equal contribution, # Corresponding author)

Ju, Q., Chen, Z., Xu, Z., Fan, J., Zhang, H., Peng, Y. (2025). Screening Social Anxiety with the Social Artificial Intelligence Picture System. Journal of Anxiety Disorders, 109, 102955.

Liu, F., Wang, P., Hu, J., Shen, S., Wang, H., Shi, C., Peng, Y., & Zhou, A. (2025). A psychologically interpretable artificial intelligence framework for the screening of loneliness, depression, and anxiety. Applied Psychology: Health and Well‐Being, 17(1), e12639.

彭玉佳, 王愉茜, 鞠芊芊, 劉峰, 徐佳. (2025). 貝葉斯框架下社交焦慮的社會認(rèn)知特性. 心理科學(xué)進展, 33(8), 1267-1274.

Liu, F., Ju, Q. Zheng, Q., Peng, Y. (2024). AI in Mental Health: Innovations brought by AI Techniques in Stress Detection and Interventions of Building Resilience. Current Opinion in Behavioral Sciences, 60, 101452. https://doi.org/10.1016/j.cobeha.2024.101452

Peng, Y., Gong, X., Lu, H., & Fang, F. (2024). Human Visual Pathways for Action Recognition versus Deep Convolutional Neural Networks: Representation Correspondence in Late but Not Early Layers. Journal of Cognitive Neuroscience, 36(11), 2458-2480. https://doi.org/10.1162/jocn_a_02233

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). 成人社交焦慮問卷中文版的效度和信度評價. 中國心理衛(wèi)生雜志, 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). 基于生物運動的社交焦慮者情緒加工與社會意圖理解負(fù)向偏差機制.心理科學(xué)進展,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

Peng, Y., Knotts, J.D., Taylor, C.T., Craske, M.G., Stein, M.B., Bookheimer, S., Young, K.S., Simmons, A.N., Yeh, H., Ruiz, J., Paulus, P.M. (2021). Failure to identify robust latent variables of positive or negative valence processing across units of analysis. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging. 6(5), 518-526.

Shu, T., Peng, Y., Zhu, S., & Lu, H. (2021). A unified psychological space for human perception of physical and social events. Cognitive Psychology. 128. 101398.

Peng, Y. , Lu, H., & Johnson, S. P. (2021). Infant perception of causal motion produced by humans and inanimate objects. Infant Behavior and Development, 64, 101615.

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.

Keane, B. P., Peng, Y., Demmin, D., Silverstein, S. M., & Lu, L. (2018). Intact perception of coherent motion, dynamic rigid form, and biological motion in chronic schizophrenia. Psychiatry Research, 268, 53-59.

Shu, T., Peng, Y., Fan, L., Zhu, S., & Lu, H. (2017). Perception of human interaction based on motion trajectories: from aerial videos to decontextualized animations. Topics in Cognitive Science, 10(1), 225-241.

Peng, Y. , Thurman, S., & Lu, H. (2017). Causal action: A fundamental constraint on perception and inference about body movements. Psychological Science, 28(6), 798-807.

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.

Lu, J. , & Peng, Y. (2014). Brain-computer interface for cyberpsychology: components, methods, and applications. International Journal of Cyber Behavior, Psychology and Learning (IJCBPL), 4(1), 1-14.