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Active listening.主动倾听。
Hear Res. 2021 Jan;399:107998. doi: 10.1016/j.heares.2020.107998. Epub 2020 May 20.
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Generative models, linguistic communication and active inference.生成模型、语言交流和主动推理。
Neurosci Biobehav Rev. 2020 Nov;118:42-64. doi: 10.1016/j.neubiorev.2020.07.005. Epub 2020 Jul 17.
4
Combining predictive coding and neural oscillations enables online syllable recognition in natural speech.结合预测编码和神经振荡可以实现自然语音中的在线音节识别。
Nat Commun. 2020 Jun 19;11(1):3117. doi: 10.1038/s41467-020-16956-5.
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Introducing a Bayesian model of selective attention based on active inference.基于主动推理的选择性注意贝叶斯模型介绍。
Sci Rep. 2019 Sep 26;9(1):13915. doi: 10.1038/s41598-019-50138-8.
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Perceptual awareness and active inference.感知意识与主动推理。
Neurosci Conscious. 2019 Sep 10;2019(1):niz012. doi: 10.1093/nc/niz012. eCollection 2019.
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Attention explores space periodically at the theta frequency.注意力以θ波频率周期性地探索空间。
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The computational pharmacology of oculomotion.眼球运动的计算药理学。
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Cognitive control in the cocktail party: Preparing selective attention to dichotically presented voices supports distractor suppression.鸡尾酒会中的认知控制:对双耳呈现声音的选择性注意准备有助于抑制干扰物。
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主动推断、选择性注意和鸡尾酒会问题。

Active inference, selective attention, and the cocktail party problem.

机构信息

Department of Speech Hearing and Phonetic Sciences, UCL, London, WC1N 1PF, UK; Wellcome Centre for Human Neuroimaging, UCL, London, WC1N 3AR, UK.

Wellcome Centre for Human Neuroimaging, UCL, London, WC1N 3AR, UK.

出版信息

Neurosci Biobehav Rev. 2021 Dec;131:1288-1304. doi: 10.1016/j.neubiorev.2021.09.038. Epub 2021 Oct 21.

DOI:10.1016/j.neubiorev.2021.09.038
PMID:34687699
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8643962/
Abstract

In this paper, we introduce a new generative model for an active inference account of preparatory and selective attention, in the context of a classic 'cocktail party' paradigm. In this setup, pairs of words are presented simultaneously to the left and right ears and an instructive spatial cue directs attention to the left or right. We use this generative model to test competing hypotheses about the way that human listeners direct preparatory and selective attention. We show that assigning low precision to words at attended-relative to unattended-locations can explain why a listener reports words from a competing sentence. Under this model, temporal changes in sensory precision were not needed to account for faster reaction times with longer cue-target intervals, but were necessary to explain ramping effects on event-related potentials (ERPs)-resembling the contingent negative variation (CNV)-during the preparatory interval. These simulations reveal that different processes are likely to underlie the improvement in reaction times and the ramping of ERPs that are associated with spatial cueing.

摘要

在本文中,我们在经典的“鸡尾酒会”范式背景下,引入了一种新的生成模型,用于主动推理预备性和选择性注意。在这种设置中,一对词同时呈现到左耳和右耳,而一个指导性的空间提示将注意力引导到左或右。我们使用这个生成模型来测试关于人类听众引导预备性和选择性注意的方式的竞争假设。我们表明,将注意力集中的位置的单词的精度分配得较低,而将注意力集中的位置的单词的精度分配得较低,可以解释为什么听众会报告来自竞争句子的单词。在这个模型下,不需要对感觉精度的时间变化来解释更长的提示-目标间隔时更快的反应时间,但是需要解释在预备间隔期间与条件性负变(CNV)相似的事件相关电位(ERP)的斜坡效应。这些模拟表明,可能涉及不同的过程来提高反应时间和与空间提示相关的 ERP 的斜坡效应。