The respiratory cycle modulates distinct dynamics of affective and perceptual decision-making.

IF 3.8 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
Malthe Brændholt, Niia Nikolova, Melina Vejlø, Leah Banellis, Francesca Fardo, Daniel S Kluger, Micah Allen
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引用次数: 0

Abstract

Breathing plays a critical role not only in homeostatic survival, but also in modulating other non-interoceptive perceptual and affective processes. Recent evidence from both human and rodent models indicates that neural and behavioural oscillations are influenced by respiratory state as breathing cycles from inspiration to expiration. To explore the mechanisms behind these effects, we carried out a psychophysical experiment where 41 participants categorised dot motion and facial emotion stimuli in a standardised discrimination task. When comparing behaviour across respiratory states, we found that inspiration accelerated responses in both domains. We applied a hierarchical evidence accumulation model to determine which aspects of the latent decision process best explained this acceleration. Computational modelling showed that inspiration reduced evidential decision boundaries, such that participants prioritised speed over accuracy in the motion task. In contrast, inspiration shifted the starting point of affective evidence accumulation, inducing a bias towards categorising facial expressions as more positive. These findings provide a novel computational account of how breathing modulate distinct aspects of perceptual and affective decision-dynamics.

呼吸周期调节着情感和感知决策的不同动态。
呼吸不仅在体内平衡生存中起着关键作用,而且在调节其他非内感受性知觉和情感过程中也起着关键作用。最近来自人类和啮齿动物模型的证据表明,从吸气到呼气的呼吸周期中,神经和行为振荡受到呼吸状态的影响。为了探索这些效应背后的机制,我们进行了一项心理物理实验,让41名参与者在一个标准化的辨别任务中对点运动和面部情绪刺激进行分类。当比较不同呼吸状态的行为时,我们发现吸气加速了两个领域的反应。我们应用了一个分层证据积累模型来确定潜在决策过程的哪些方面最好地解释了这种加速。计算模型显示,灵感减少了证据决策边界,因此参与者在运动任务中优先考虑速度而不是准确性。相比之下,灵感改变了情感证据积累的起点,导致人们倾向于将面部表情归类为更积极的表情。这些发现提供了呼吸如何调节知觉和情感决策动力学的不同方面的新颖计算帐户。
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来源期刊
PLoS Computational Biology
PLoS Computational Biology BIOCHEMICAL RESEARCH METHODS-MATHEMATICAL & COMPUTATIONAL BIOLOGY
CiteScore
7.10
自引率
4.70%
发文量
820
审稿时长
2.5 months
期刊介绍: PLOS Computational Biology features works of exceptional significance that further our understanding of living systems at all scales—from molecules and cells, to patient populations and ecosystems—through the application of computational methods. Readers include life and computational scientists, who can take the important findings presented here to the next level of discovery. Research articles must be declared as belonging to a relevant section. More information about the sections can be found in the submission guidelines. Research articles should model aspects of biological systems, demonstrate both methodological and scientific novelty, and provide profound new biological insights. Generally, reliability and significance of biological discovery through computation should be validated and enriched by experimental studies. Inclusion of experimental validation is not required for publication, but should be referenced where possible. Inclusion of experimental validation of a modest biological discovery through computation does not render a manuscript suitable for PLOS Computational Biology. Research articles specifically designated as Methods papers should describe outstanding methods of exceptional importance that have been shown, or have the promise to provide new biological insights. The method must already be widely adopted, or have the promise of wide adoption by a broad community of users. Enhancements to existing published methods will only be considered if those enhancements bring exceptional new capabilities.
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