人类和小鼠的感官处理在外部和内部模式之间波动

IF 7.8 1区 生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY PLoS Biology Pub Date : 2023-12-08 DOI:10.1371/journal.pbio.3002410
V. Weilnhammer, Heiner Stuke, K. Standvoss, Philipp Sterzer
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引用次数: 0

摘要

我们知道,感知是在对外部信息的敏感度增强和降低的周期中循环的。在这里,我们询问这种缓慢的波动是作为有限处理能力的噪声相关的附带现象出现的,还是代表了感知推理的结构化机制。使用2个大规模的数据集,我们发现人类和小鼠在外部和内部导向的感官分析模式之间交替。在外部模式下,感知与外部感官信息更紧密地联系在一起,而内部模式的特点是对感知历史的偏见增强。计算模型表明,模式的动态变化是由两个相互关联的因素实现的:(i)随着时间的推移整合后续输入;(ii)外部感官信息对感知影响的缓慢反相位振荡,而不是由感知历史提供的内部预测。我们提出,模间波动产生明确的误差信号,使最优推理在多变的环境。
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Sensory processing in humans and mice fluctuates between external and internal modes
Perception is known to cycle through periods of enhanced and reduced sensitivity to external information. Here, we asked whether such slow fluctuations arise as a noise-related epiphenomenon of limited processing capacity or, alternatively, represent a structured mechanism of perceptual inference. Using 2 large-scale datasets, we found that humans and mice alternate between externally and internally oriented modes of sensory analysis. During external mode, perception aligns more closely with the external sensory information, whereas internal mode is characterized by enhanced biases toward perceptual history. Computational modeling indicated that dynamic changes in mode are enabled by 2 interlinked factors: (i) the integration of subsequent inputs over time and (ii) slow antiphase oscillations in the perceptual impact of external sensory information versus internal predictions that are provided by perceptual history. We propose that between-mode fluctuations generate unambiguous error signals that enable optimal inference in volatile environments.
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来源期刊
PLoS Biology
PLoS Biology 生物-生化与分子生物学
CiteScore
14.40
自引率
2.00%
发文量
359
审稿时长
3 months
期刊介绍: PLOS Biology is an open-access, peer-reviewed general biology journal published by PLOS, a nonprofit organization of scientists and physicians dedicated to making the world's scientific and medical literature freely accessible. The journal publishes new articles online weekly, with issues compiled and published monthly. ISSN Numbers: eISSN: 1545-7885 ISSN: 1544-9173
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