What MEG can reveal about inference making: the case of if...then sentences

Examining the role and neural electrophysiological mechanisms of adjective cues in size judgment

Numerous influential theories have attempted to elucidate the relationship between language and thought. The debate persists on whether language and thought are distinct entities or if language is deeply embedded in individual cognitive processes. This study employs adjective cues combined with a mental imagery size judgment task as an experimental paradigm, utilizing neurophysiological techniques to preliminarily explore the role of adjectives in size judgment tasks and their underlying neurophysiological mechanisms. Findings reveal that performance is best when adjectives are congruent with the size of the object, with EEG microstate results indicating strong activity in Class A, related to language networks under this condition. Additionally, when adjectives conflict with object size, the discovery of the Ni component suggests that individuals monitor and inhibit the conflict between adjectives and object size, leading to decreased task performance in this condition. Moreover, when object size is ambiguous, individuals' size judgments do not benefit significantly from clear adjective cues. Event-related potentials and EEG microstate results suggest that under this condition, top-down cognitive resources are recruited more extensively. In conclusion, language plays a more crucial role in simpler judgment tasks; as tasks become more complex, judgment processes engage a greater number of distributed brain regions to collaborate, while the language system remains active. This study provides initial cognitive neuroscience evidence for understanding the relationship between language and simple forms of thought, offering preliminary insights for future investigations into the connection between language and thought.

BCI learning induces core-periphery reorganization in M/EEG multiplex brain networks

Brain-computer interfaces (BCIs) constitute a promising tool for communication and control. However, mastering non-invasive closed-loop systems remains a learned skill that is difficult to develop for a non-negligible proportion of users. The involved learning process induces neural changes associated with a brain network reorganization that remains poorly understood. To address this inter-subject variability, we adopted a multilayer approach to integrate brain network properties from electroencephalographic (EEG) and magnetoencephalographic (MEG) data resulting from a four-session BCI training program followed by a group of healthy subjects. Our method gives access to the contribution of each layer to multilayer network that tends to be equal with time. We show that regardless the chosen modality, a progressive increase in the integration of somatosensory areas in the α band was paralleled by a decrease of the integration of visual processing and working memory areas in the β band. Notably, only brain network properties in multilayer network correlated with future BCI scores in the α2 band: positively in somatosensory and decision-making related areas and negatively in associative areas. Our findings cast new light on neural processes underlying BCI training. Integrating multimodal brain network properties provides new information that correlates with behavioral performance and could be considered as a potential marker of BCI learning.

P300 and positive slow waves reveal the plausibility in inductive reasoning

Category-based induction is an advanced cognitive function that is based on our category-level knowledge. Previous findings have recognized the distance effect in category-based induction: Inductive strength is affected by the hierarchical distance between the premises and conclusions. However, the neural mechanisms underlying this effect require elucidation. In the present study, we investigated the neural mechanisms of the distance effect by using EEG technology and a new experimental paradigm-category-based induction. In this paradigm, we used three hierarchical levels of categories-the subordinate category, the basic category, the superordinate category-and an irrelevant category. We further used these categories to create four types of trial that varied in the hierarchical distance between the premise and the conclusion: the subordinate-basic, the basic-superordinate, the subordinate-superordinate, and the irrelevant-superordinate trials. In each trial, participants judged the probability that the conclusion category had the same property as the premise category. Our behavioral results revealed that people responded more slowly in the irrelevant-superordinate trials than in the basic-superordinate and the subordinate-basic trials. Our ERP results showed that the irrelevant-superordinate trials elicited smaller P300 (250-500 ms) amplitudes than did the subordinate-basic and the basic-superordinate trials. In addition, the subordinate-superordinate trials elicited smaller P300 and PSW (700-998 ms) amplitudes than did the subordinate-basic and the basic-superordinate combinations. These findings indicate that the amplitudes of P300 and PSW may reflect the distance effect in inductive reasoning: The further the premise-conclusion hierarchical distance, the lower the inductive strength, and thus the smaller the P300 and PSW amplitudes.