Single-trial neurodynamics reveal N400 and P600 coupling in language comprehension.

IF 3.1 3区 工程技术 Q2 NEUROSCIENCES
Cognitive Neurodynamics Pub Date : 2024-12-01 Epub Date: 2023-06-20 DOI:10.1007/s11571-023-09983-7
Christoph Aurnhammer, Matthew W Crocker, Harm Brouwer
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Abstract

Theories of the electrophysiology of language comprehension are mostly informed by event-related potential effects observed between condition averages. We here argue that a dissociation between competing effect-level explanations of event-related potentials can be achieved by turning to predictions and analyses at the single-trial level. Specifically, we examine the single-trial dynamics in event-related potential data that exhibited a biphasic N400-P600 effect pattern. A group of multi-stream models can explain biphasic effects by positing that each individual trial should induce either an N400 increase or a P600 increase, but not both. An alternative, single-stream account, Retrieval-Integration theory, explicitly predicts that N400 amplitude and P600 amplitude should be correlated at the single-trial level. In order to investigate the single-trial dynamics of the N400 and the P600, we apply a regression-based technique in which we quantify the extent to which N400 amplitudes are predictive of the electroencephalogram in the P600 time window. Our findings suggest that, indeed, N400 amplitudes and P600 amplitudes are inversely correlated within-trial and, hence, the N400 effect and the P600 effect in biphasic data are driven by the same trials. Critically, we demonstrate that this finding also extends to data which exhibited only monophasic effects between conditions. In sum, the observation that the N400 is inversely correlated with the P600 on a by-trial basis supports a single stream view, such as Retrieval-Integration theory, and is difficult to reconcile with the processing mechanisms proposed by multi-stream models.

Abstract Image

单试验神经动力学揭示语言理解中N400和P600的耦合
语言理解的电生理学理论主要是根据在条件平均之间观察到的与事件相关的潜在效应。我们在此认为,事件相关电位的相互竞争的效应水平解释之间的分离可以通过转向单试验水平的预测和分析来实现。具体来说,我们在事件相关电位数据中检查了单试验动态,显示了双相N400-P600效应模式。一组多流模型可以解释双相效应,假设每个单独的试验应该引起N400增加或P600增加,但不是两者都增加。另一种选择,单流解释,检索-整合理论,明确预测N400振幅和P600振幅应该在单次试验水平上相关。为了研究N400和P600的单次试验动态,我们应用了一种基于回归的技术,在该技术中,我们量化了N400振幅对P600时间窗内脑电图的预测程度。我们的研究结果表明,N400振幅和P600振幅确实在试验中呈负相关,因此,双相数据中的N400效应和P600效应是由相同的试验驱动的。关键的是,我们证明,这一发现也延伸到数据,只显示条件之间的单相效应。总之,N400与P600呈负相关的观察结果支持单一流观点,如检索-整合理论,难以与多流模型提出的处理机制相一致。
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来源期刊
Cognitive Neurodynamics
Cognitive Neurodynamics 医学-神经科学
CiteScore
6.90
自引率
18.90%
发文量
140
审稿时长
12 months
期刊介绍: Cognitive Neurodynamics provides a unique forum of communication and cooperation for scientists and engineers working in the field of cognitive neurodynamics, intelligent science and applications, bridging the gap between theory and application, without any preference for pure theoretical, experimental or computational models. The emphasis is to publish original models of cognitive neurodynamics, novel computational theories and experimental results. In particular, intelligent science inspired by cognitive neuroscience and neurodynamics is also very welcome. The scope of Cognitive Neurodynamics covers cognitive neuroscience, neural computation based on dynamics, computer science, intelligent science as well as their interdisciplinary applications in the natural and engineering sciences. Papers that are appropriate for non-specialist readers are encouraged. 1. There is no page limit for manuscripts submitted to Cognitive Neurodynamics. Research papers should clearly represent an important advance of especially broad interest to researchers and technologists in neuroscience, biophysics, BCI, neural computer and intelligent robotics. 2. Cognitive Neurodynamics also welcomes brief communications: short papers reporting results that are of genuinely broad interest but that for one reason and another do not make a sufficiently complete story to justify a full article publication. Brief Communications should consist of approximately four manuscript pages. 3. Cognitive Neurodynamics publishes review articles in which a specific field is reviewed through an exhaustive literature survey. There are no restrictions on the number of pages. Review articles are usually invited, but submitted reviews will also be considered.
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