CRCNS US-German Research Proposal: Choice-induced biases in human decision-making

我们所做的选择不仅会影响我们记忆过去的方式，也会影响我们对未来的看法。在这两种情况下，我们的判断都偏向于我们之前的选择。这种由选择引发的偏见早在几个世纪前就已为人所知。它们影响我们在日常生活中的判断，包括在判断错误至关重要的情况下(例如，医学诊断、科学假设检验或政治决策)。人类大脑为什么会产生这些偏见并倾向于自我确认，长期以来一直难以捉摸。在计算神经科学合作研究计划的支持下，这项拟议的研究将着手确定人类决策中选择诱导偏见的潜在计算和神经机制。这项拟议的工作采用了一种高度跨学科的方法，将行为和大脑活动的测量与理论和计算模型结合起来。它完美地借鉴了每个PI及其实验室免费提供的实验和计算专业知识。我们的目标是开发和验证一种新的不确定性决策理论，其中选择诱导的偏差起着核心作用。解开由选择引起的偏见的来源和作用，不仅对理解人类理性的极限至关重要，而且对整个社会也具有直接和重要的影响。例如，这些见解可以帮助培训医生减少临床诊断中的判断错误，以及法律和公司部门的其他决策者的判断错误。最后，拟议研究的实验方法和结果可能有助于揭示重要大脑疾病的生物学基础，特别是精神分裂症，对这些疾病的确认偏差会加剧。拟议工作的中心焦点是测试这样一个假设，即选择产生主观预期，从而影响对过去和未来证据的后续评估过程。这项拟议的研究将记录健康受试者在执行一系列新的行为任务时的心理物理和功能神经成像(脑磁图(MEG))测量结果，这些新的行为任务是专门为评估低级知觉和高级认知中的选择诱导偏见而开发的。理论和计算模型将对解释这些信号并最终帮助推断潜在的认知操作至关重要。本研究的结果不仅有助于我们更好地理解决策中的选择偏差效应，而且有助于我们更好地理解决策过程中的选择偏差效应。同时使用行为、神经和理论/计算测量和方法的综合方法对预期结果和解释施加了强有力的限制，同时也对调查结果产生了极强的信心，因为它们在所有层面上都得到了支持。在展示选择如何影响后续证据评估的程度上，我们的结果有可能彻底改变将决策作为简单的前馈积累到约束过程的传统理解。德国联邦教育和研究部(BMBF)正在资助一个配套项目。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The choices we make not only influence how we remember the past but also how we will perceive the future. In both cases, our judgments are biased in favor of our preceding choice. Such choice-induced biases have been known for centuries. They affect our judgments in daily life including in situations where judgment errors are critical (e.g., medical diagnoses, scientific hypothesis testing, or political decisions). Why the human brain generates these biases and tends towards self-confirmation has long remained elusive. Supported by the Collaborative Research in Computational Neuroscience program, the proposed research will set out to identify the underlying computational and neural mechanisms of choice-induced biases in human decision-making. The proposed work employs a highly interdisciplinary approach that combines measures of behavior and brain activity with theory and computational modeling. It perfectly draws from the complimentary experimental and computational expertise of each PI and their laboratories. The goal is to develop and validate a novel theory of decision-making under uncertainty, in which choice-induced biases play a central role. Unraveling the source and function of choice-induced biases is not only critical for understanding the limits of human rationality but has also immediate and important implications for society at large. For example, the insights can help training of physicians to reduce judgment errors in clinical diagnostics, as well as that of other decision-makers in the legal and corporate sectors. Finally, the experimental methods and results of the proposed research may help to shed light on the biological underpinnings of important brain disorders, in particular schizophrenia, for which confirmation biases are aggravated.The central focus of the proposed work is to test the hypothesis that choices generate subjective expectations that influence the subsequent evaluation process of both past and future evidence. The proposed research will record psychophysical and functional neuroimaging (magnetoencephalography (MEG)) measurements of healthy human subjects while they are performing a range of novel behavioral tasks specifically developed to assess choice-induced biases in low-level perception as well has high-level cognition. Theory and computational modeling will be crucial to interpret these signals and ultimately to help infer the underlying cognitive operations. The results of this research will not only advance our understanding of choice-induced bias effects in decision-making, but of decision-making in general. The combined approach of simultaneously using behavioral, neural, and theoretical/computational measurements and methods imposes strong constraints on the expected results and explanations while at the same time lending also extraordinarily strong confidence to the findings as they are supported on all levels. To the degree that they demonstrate how choices influence subsequent evidence evaluation, our results have the potential to drastically change the traditional understanding of decision-making as a simple feedforward accumulation-to-bound process.A companion project is being funded by the Federal Ministry of Education and Research, Germany (BMBF).This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.