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Big-team science does not guarantee generalizability
A new era of global ‘big-team science’studies has transformed human behaviour research.
Sakshi Ghai, Patrick S. Forscher, Hu Chuan-Peng
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Big-team science does not guarantee generalizability
Replication study on the role of dopamine-dependent prefrontal reactivations in human extinction memory retrieval
Even after successful extinction, conditioned fear can return. Strengthening the consolidation of the fear-inhibitory safety memory formed during extinction is one way to counteract return of fear.
Andres, Elena, Chuan-Peng, Hu, Meyer, Benjamin, Tuescher, Oliver, Kalisch, Raffael
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自我参照的神经成像认知本体论数据集
Self-reference (or self-referentialprocessing) refers to the cognitive processes underlying self-related information processing.
孙淑婷, 王楠, 温佳慧, 胡传鹏
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自我参照的神经成像认知本体论数据集
Sampling inequalities affect generalization of neuroimaging-based diagnostic classifiers in psychiatry
Background The development of machine learning models for aiding in the diagnosis of mental disorder is recognized as a significant …
Zhiyi Chen, Bowen Hu, Xuerong Liu, Benjamin Becker, ... Chuan-Peng, H
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Sampling inequalities affect generalization of neuroimaging-based diagnostic classifiers in psychiatry
The Chinese Open Science Network (COSN) Building an Open Science Community From Scratch
Open Science is becoming a mainstream scientific ideology in psychology and related fields. However, researchers, especially early-career researchers (ECRs) in developing countries, are facing significant hurdles in engaging in Open Science and moving it forward.
Jin, H, Wang, Q, Yang, Y-F, Zhang, H, Gao, M, Jin, S, Chen, S, Xu, T, YuanRui, Z, Chen, J, Xiao, Q, Yang, J, Wang, X, Geng, H, Ge, J, Wang, W-W, Chen, X, Zhang, L, Zuo X-N, Chuan-Peng, Hu
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The Chinese Open Science Network (COSN) Building an Open Science Community From Scratch
贝叶斯因子序列分析：实验设计中平衡信息与效率的新方法
实验设计的关键是平衡信息量与效率。贝叶斯因子序列分析利用贝叶斯因子不断更新证据的特点，通过贝叶斯因子标准和在收集数据过程的序列分析来平衡信息量与效率.
Yuanrui Zheng, Hu Chuan-Peng
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Evaluation of Risk of Bias in Neuroimaging-Based Artificial Intelligence Models for Psychiatric Diagnosis
In this systematic review of 517 studies presenting 555 neuroimaging-based AI models for psychiatric diagnostics, most models had a high overall risk of bias and had poor clinical applicability. All articles provided incomplete reports for validation.
Chen, Z, Liu, X, Yang, Q, Wang, Y. J, Miao, K, Gong, Z, Chuan-Peng, H
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Evaluation of Risk of Bias in Neuroimaging-Based Artificial Intelligence Models for Psychiatric Diagnosis
The Psychological Science Accelerator's COVID-19 rapid-response dataset
In response to the COVID-19 pandemic, the Psychological Science Accelerator coordinated three large-scale psychological studies to examine the effects of loss-gain framing, cognitive reappraisals, and autonomy framing manipulations on behavioral intentions and affective measures.
Erin M. Buchanan, Savannah C. Lewis, Bastien Paris, Patrick S. Forscher, ... Chuan-Peng, H, ... Maximilian A. Primbs
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The Psychological Science Accelerator's COVID-19 rapid-response dataset
Engaging the open science framework in quantifying and tracing scientists' research credits
Debates on how to determine positions in research authorship have not subsided. An institution funded by the United States National Institute of Environmental Health Sciences (NIEHS) provided reports for investigating authorship disputes from 6,700 researchers in the world.
Chen, Z, Liu, X, Miao, K, Liao, X, Zhang, X, Feng, Z, Chuan-Peng, H
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Engaging the open science framework in quantifying and tracing scientists' research credits
In COVID-19 Health Messaging, Loss Framing Increases Anxiety with Little-to-No Concomitant Benefits:Experimental Evidence from 84 Countries
The COVID-19 pandemic (and its aftermath) highlights a critical need to communicate health information effectively to the global public.
Dorison, C A, Lerner, J S, Heller, B H, Rothman, A J, ... Chuan-Peng, H, ... Pinto, I
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In COVID-19 Health Messaging, Loss Framing Increases Anxiety with Little-to-No Concomitant Benefits:Experimental Evidence from 84 Countries