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不确定性下感觉学习的计算、药理学和生理学决定因素。

The Computational, Pharmacological, and Physiological Determinants of Sensory Learning under Uncertainty.

机构信息

Department of Psychology, Downing Street, University of Cambridge, Cambridge CB2 3EB, UK; MRC Cognition & Brain Sciences Unit, Chaucer Road, University of Cambridge, Cambridge CB2 7EF, UK.

Institute of Cognitive Neuroscience, Queen Square, University College London, London WC1N 3AZ, UK; Division of Psychiatry, Tottenham Court Road, University College London, London W1T 7NF, UK.

出版信息

Curr Biol. 2021 Jan 11;31(1):163-172.e4. doi: 10.1016/j.cub.2020.10.043. Epub 2020 Nov 13.

Abstract

The ability to represent and respond to uncertainty is fundamental to human cognition and decision-making. Noradrenaline (NA) is hypothesized to play a key role in coordinating the sensory, learning, and physiological states necessary to adapt to a changing world, but direct evidence for this is lacking in humans. Here, we tested the effects of attenuating noradrenergic neurotransmission on learning under uncertainty. We probed the effects of the β-adrenergic receptor antagonist propranolol (40 mg) using a between-subjects, double-blind, placebo-controlled design. Participants performed a probabilistic associative learning task, and we employed a hierarchical learning model to formally quantify prediction errors about cue-outcome contingencies and changes in these associations over time (volatility). Both unexpectedness and noise slowed down reaction times, but propranolol augmented the interaction between these main effects such that behavior was influenced more by prior expectations when uncertainty was high. Computationally, this was driven by a reduction in learning rates, with people slower to update their beliefs in the face of new information. Attenuating the global effects of NA also eliminated the phasic effects of prediction error and volatility on pupil size, consistent with slower belief updating. Finally, estimates of environmental volatility were predicted by baseline cardiac measures in all participants. Our results demonstrate that NA underpins behavioral and computational responses to uncertainty. These findings have important implications for understanding the impact of uncertainty on human biology and cognition.

摘要

人类认知和决策的基本能力是代表和应对不确定性。去甲肾上腺素(NA)被假设在协调适应不断变化的世界所需的感觉、学习和生理状态方面发挥关键作用,但这在人类中缺乏直接证据。在这里,我们测试了减弱去甲肾上腺素能神经传递对不确定性下学习的影响。我们使用了一种基于参与者的、双盲、安慰剂对照设计来探测β-肾上腺素受体拮抗剂普萘洛尔(40mg)的影响。参与者执行概率联想学习任务,我们采用分层学习模型来正式量化关于线索-结果关联的预测误差以及随时间变化(波动性)的这些关联的变化。出乎意料和噪音都会减慢反应时间,但普萘洛尔增强了这些主要效应之间的相互作用,使得当不确定性较高时,行为受到先前期望的影响更大。从计算角度来看,这是由于学习率降低所致,面对新信息,人们更新信念的速度较慢。减弱 NA 的全局效应也消除了预测误差和波动性对瞳孔大小的相位效应,这与较慢的信念更新一致。最后,所有参与者的基线心脏测量值都预测了环境波动性的估计值。我们的结果表明,NA 是对不确定性的行为和计算反应的基础。这些发现对于理解不确定性对人类生物学和认知的影响具有重要意义。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/883e/7808754/ccebc49aa065/gr1.jpg

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