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Attentional sampling resolves competition along the visual hierarchy. 注意抽样解决了视觉层次上的竞争。
IF 17.2 1区 心理学 Q1 BEHAVIORAL SCIENCES Pub Date : 2026-02-01 Epub Date: 2025-07-08 DOI: 10.1016/j.tics.2025.06.004
Daniele Re, Flor Kusnir, Ayelet N Landau

Navigating the environment involves engaging with multiple objects, each activating specific neuronal populations. When objects appear together, these populations compete. Classical attention theories suggest that selection involves biasing one population over another. Recent research shows that perception fluctuates over time at ~8 Hz for single-object attention and 4 Hz for two-object attention, possibly because of the division of the 8-Hz rhythm between competing objects. This opinion surveys these fluctuations, coined 'attentional sampling,' across the visual hierarchy. We propose that sampling is a selection mechanism that negotiates neuronal competition. It manifests as early as eye channels and extends to complex features higher in the visual hierarchy. We discuss the cognitive significance of this mechanism and its potential neuronal implementation.

在环境中导航需要与多个物体接触,每个物体都会激活特定的神经元群。当物体一起出现时,这些种群就会竞争。经典的注意力理论认为,选择涉及到一个群体对另一个群体的偏见。最近的研究表明,随着时间的推移,单物体注意力的感知波动为~8赫兹,双物体注意力的感知波动为4赫兹,这可能是因为8赫兹的节奏在竞争物体之间的分裂。这个观点调查了这些波动,创造了“注意力抽样”,跨越视觉层次。我们认为采样是一种调节神经元竞争的选择机制。它早在眼通道就表现出来,并扩展到视觉层次更高的复杂特征。我们讨论了这一机制的认知意义及其潜在的神经元实现。
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引用次数: 0
Language learning as ontogenetic adaptation 语言学习作为个体发生适应
IF 19.9 1区 心理学 Q1 BEHAVIORAL SCIENCES Pub Date : 2026-01-30 DOI: 10.1016/j.tics.2025.12.005
Manuel Bohn, Marisa Casillas
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引用次数: 0
A dysfunctional hub model of voice–reward integration in autism 自闭症中语音奖励整合的功能失调中枢模型
IF 19.9 1区 心理学 Q1 BEHAVIORAL SCIENCES Pub Date : 2026-01-26 DOI: 10.1016/j.tics.2025.12.006
Daniel A. Abrams, Simon Leipold, Daniel L. Bowling
Children with autism often struggle to tune in to voices, missing important cues for social connection and language learning. What underlies this diminished engagement? Neuroimaging evidence implicates disrupted connectivity between voice-selective temporal regions and brain networks supporting reward, salience, and social cognition, leading to a new neural model of vocal insensitivity in autism.
患有自闭症的儿童往往难以适应各种声音,错过了社会联系和语言学习的重要线索。是什么导致了这种参与度的下降?神经影像学证据暗示语音选择颞区和支持奖励、显著性和社会认知的大脑网络之间的连接中断,导致自闭症中声音不敏感的新神经模型。
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引用次数: 0
A unifying taxonomy of dyadic emotional processes 二元情感过程的统一分类
IF 19.9 1区 心理学 Q1 BEHAVIORAL SCIENCES Pub Date : 2026-01-22 DOI: 10.1016/j.tics.2025.12.008
Martine W.F.T. Verhees, Batja Mesquita, Eva Ceulemans, Joeri Hofmans, Lesley Verhofstadt, Peter Kuppens
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引用次数: 0
Neurocomputational mechanisms of adaptive mentalization in humans 人类适应性心智化的神经计算机制
IF 19.9 1区 心理学 Q1 BEHAVIORAL SCIENCES Pub Date : 2026-01-21 DOI: 10.1016/j.tics.2025.11.009
Toan Nong, Jun Feng, Jean-Claude Dreher
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引用次数: 0
Emotion may indirectly link rendering and social reasoning 情感可能间接地将渲染与社会推理联系起来
IF 19.9 1区 心理学 Q1 BEHAVIORAL SCIENCES Pub Date : 2026-01-21 DOI: 10.1016/j.tics.2025.12.009
Halely Balaban, Tomer D. Ullman
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引用次数: 0
Rendering aphantasia into the social realm 使幻觉进入社会领域
IF 19.9 1区 心理学 Q1 BEHAVIORAL SCIENCES Pub Date : 2026-01-20 DOI: 10.1016/j.tics.2025.11.014
Adam Zeman, Bérengère Digard, Francesca Happé, Brian Levine, Merlin Monzel
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引用次数: 0
No free lunch with the binding problem. 没有免费的午餐和绑定问题。
IF 17.2 1区 心理学 Q1 BEHAVIORAL SCIENCES Pub Date : 2026-01-15 DOI: 10.1016/j.tics.2025.12.002
Giacomo Aldegheri, Roland W Fleming
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引用次数: 0
Moving intentions from brains to machines. 将意图从大脑转移到机器。
IF 17.2 1区 心理学 Q1 BEHAVIORAL SCIENCES Pub Date : 2026-01-14 DOI: 10.1016/j.tics.2025.12.003
Christian Beste, Heleen A Slagter, Christian Herff, Yukiyasu Kamitani, Sabrina Coninx, Richard van Wezel, Christian Frings

Brain-computer interface (BCI) research has achieved remarkable technical progress but remains limited in scope, typically relying on motor and visual cortex signals in limited patient populations. We propose a paradigm shift in BCI design rooted in ideomotor theory, which conceptualizes voluntary action as driven by internally represented sensory outcomes. This underused framework offers a principled basis for next-generation BCIs that align closely with the brain's natural intentional and action-planning architecture. We suggest a more intuitive, generalizable, and scalable path by reorienting BCIs around the 'what for' of action-user goals and anticipated effects. This shift is timely and feasible, enabled by advances in neural recording and artificial intelligence-based decoding of sensory representations. It may help resolve challenges of usability and generalizability in BCI design.

脑机接口(BCI)的研究已经取得了显著的技术进步,但范围仍然有限,通常依赖于有限患者群体的运动和视觉皮层信号。我们提出了一种基于观念运动理论的BCI设计范式转变,该理论将自愿行为概念化为由内部表征的感觉结果驱动。这个未被充分利用的框架为下一代脑机接口提供了一个原则性的基础,这些脑机接口与大脑的自然意图和行动计划架构密切相关。我们建议采用一种更直观、更通用、更可扩展的路径,即围绕行动用户目标和预期效果的“目的”重新定位bci。由于神经记录和基于人工智能的感官表征解码技术的进步,这种转变是及时和可行的。它可能有助于解决BCI设计中的可用性和通用性挑战。
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引用次数: 0
Advisory Board and Contents 咨询委员会及内容
IF 19.9 1区 心理学 Q1 BEHAVIORAL SCIENCES Pub Date : 2026-01-06 DOI: 10.1016/s1364-6613(25)00363-8
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引用次数: 0
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Trends in Cognitive Sciences
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