Weiyong Xu

Emotional events evoke changing neural and bodily responses, but how these responses relate to overall emotional evaluations and how brain and body responses correspond over time remain unclear. Ninety-two participants viewed 25 silent emotional videos, each approximately one minute long, and rated valence and arousal after each video. We recorded brain activity using magnetoencephalography alongside cardiac, electrodermal, respiratory and facial-muscle activity. Representational similarity analysis (RSA) compared source-resolved cortical spectral patterns and peripheral response patterns with participants' valence and arousal ratings, adjusting each affective dimension for the other. Across whole videos, valence similarity corresponded to beta-band power patterns predominantly in left sensorimotor and frontotemporal cortex and to facial-muscle responses. Arousal similarity corresponded to alpha-band power patterns in the right frontoparietal cortex and to phasic electrodermal activity. The neural associations persisted after adjustment for visual and semantic similarities between the videos. Windowed neural correspondence with retrospective valence was significant from around 10 s onwards, with both neural and facial-muscle associations strengthening towards the end of the videos, whereas no significant windowed arousal associations were detected throughout viewing. We further applied dynamic RSA to compare neural and physiological response patterns across videos at different temporal lags. Correspondence exceeded a temporally decoupled reference for facial muscles, heart rate and electrodermal activity, but not respiration rate. On average, corrugator activity preceded corresponding neural patterns by about 1 s, zygomaticus activity occurred at approximately the same time, and heart-rate and electrodermal activity followed about 1.7 s and 4.5 s later, respectively. Together, these findings link overall affective evaluations to complementary neural and peripheral response geometries and reveal signal-specific temporal profiles of ongoing brain-body correspondence.

Flexible behavior requires the ability to maintain current goals while adapting to changing demands. Task-set representations provide a mechanism for sustaining goal-relevant information, yet whether they remain stable or dynamically reconfigured remains unclear. Using magnetoencephalography (MEG) and multivariate pattern analysis, we examined the temporal dynamics of task-set representations during working-memory performance with object-based and feature-based task contexts established before stimulus presentation. Task-set information was reliably decodable before stimulus onset and throughout encoding in broadband MEG activity and alpha-band power. Temporal generalization revealed broader cross-temporal decoding during preparation, consistent with stable representations, whereas encoding-related decoding was more time-specific. Together, these findings show that task-set representations persist across cognitive stages while their neural expression adapts dynamically to ongoing processing demands. These results suggest that sustained maintenance and flexible adaptation reflect complementary temporal modes through which cognitive control supports goal-directed behavior.

Icons, as simplified visual symbols, play a key role in visual communication, yet little neuroimaging research has addressed how icons are represented in the brain. We investigated how concreteness and attractiveness modulate the spatiotemporal dynamics of icon processing in a 2 × 2 factorial design in 35 adults using magnetoencephalography. Source-level event-related field (ERF) analysis and representational similarity analysis (RSA) were used to characterize neural responses, with partial RSA isolating each feature’s unique contribution after controlling for low-level visual similarity. ERF results showed that concreteness exerted a robust and sustained influence on neural dynamics, with concrete icons eliciting stronger responses than abstract ones from 90 to 1,000 ms, emerging in bilateral occipital cortices and extending to occipitotemporal, temporal, and parietal regions. RSA confirmed concreteness as a representational dimension across processing stages. Attractiveness showed an early but transient effect in occipital and ventral occipitotemporal regions (80 to 130 ms), though this did not survive RSA after controlling for low-level visual property models. A concreteness × attractiveness interaction modulated early occipital and later parietal processing (100 to 185 ms), indicating these features do not operate independently. Our results reveal that semantic content outweighs esthetic appeal in shaping the neural representation of icons.

Automaticity in decoding print is crucial for fluent reading. This process relies on associative memories between letters and speech sounds (LSS) that are overlearned through years of reading practice. While previous neuroimaging studies have identified neural correlates of LSS integration across different stages of reading development, the specific neural signatures underlying automatic LSS integration remain unclear. In the present study, we aimed to isolate neural components specifically associated with automatic LSS integration in literate adults. To this end, we developed an artificial script training paradigm in which adult native Finnish speakers were taught to associate unfamiliar foreign letters with familiar Finnish speech sounds. Using magnetoencephalography (MEG), we directly compared the audiovisual processing of newly learned and overlearned LSS associations within the same task, one day after training. Event-related fields (ERFs) and multivariate decoding revealed largely shared neural circuits of audiovisual integration for both types of LSS associations, as evidenced by multisensory interaction and congruency effects. Interestingly, the processing of congruent overlearned audiovisual associations uniquely recruited brain activity in the left medial parietal cortex during the 235–475 ms time window. Furthermore, temporal generalization analysis of the congruency effects revealed that while both newly learned and overlearned audiovisual associations engaged common neural mechanisms, the newly learned associations were processed systematically more slowly by a few hundred milliseconds. Our study identified the spatiotemporal neural signatures underlying automatized LSS processing, offering insights into neural markers that may help identify levels of reading proficiency.

Previous brain research on phonetic learning of foreign speech sounds has focused on learning outcomes, mostly neglecting the dynamical neural changes during learning. In the present study, Finnish-speaking participants listened passively to a repeated presentation of vowel /a/ with infrequent changes in Mandarin tone for 2 h per day for 4 consecutive days while their brain activity was recorded using electroencephalography. While our previous study has reported the brain activity changes from test recordings conducted before and after the sound exposure, we here analyzed the data recorded during the exposure. We investigated learning dynamics across daily exposure sessions using event-related potentials and multivariate pattern analysis and within sessions using a sliding average across trials. Both mismatch negativity and P3a—markers of change detection and preattentive attention shifts—exhibited learning-related changes in both the event-related potential analysis and multivariate pattern analysis. Changes in multivariate pattern analysis were evident after the first 2-h training session, while event-related potential–based effects emerged later. During the daily exposure sessions, the mismatch negativity amplitude gradually decreased over the first 3 d, whereas the P3a amplitude exhibited an opposite trend, showing a significant increase, and only on day 1. These findings demonstrate dynamic neural changes driven by passive exposure and pave the way for investigating learning processes across multiple levels of analysis, including event-related potential, single-trial dynamics, and machine learning–based methods.

Automaticity in decoding print is crucial for fluent reading. This process relies on associative memories between letters and speech sounds (LSS) that are overlearned through years of reading practice. While previous neuroimaging studies have identified neural correlates of LSS integration across different stages of reading development, the specific neural signatures underlying automatic LSS integration remain unclear. In the present study, we aimed to isolate neural components specifically associated with automatic LSS integration in literate adults. To this end, we developed an artificial script training paradigm in which adult native Finnish speakers were taught to associate unfamiliar foreign letters with familiar Finnish speech sounds. Using magnetoencephalography (MEG), we directly compared the audiovisual processing of newly learned and overlearned LSS associations within the same task, one day after training. Event-related fields (ERFs) and multivariate decoding revealed largely shared neural circuits of audiovisual integration for both types of LSS associations, as evidenced by multisensory interaction and congruency effects. Interestingly, the processing of congruent overlearned audiovisual associations uniquely recruited brain activity in the left parietal cortex during the 235-475 ms time window. Furthermore, temporal generalization analysis of the congruency effects revealed that while both newly learned and overlearned audiovisual associations engaged common neural mechanisms, the newly learned associations were processed systematically more slowly by a few hundred milliseconds. Our study identified the spatiotemporal neural signatures underlying automatized LSS processing, offering insights into neural markers that may help identify levels of reading proficiency.

The ability to accurately assess one’s own memory performance during learning is essential for adaptive behavior, but the brain mechanisms underlying this metamemory function are not well understood. We investigated the neural correlates of memory accuracy and retrospective memory confidence in a face–name associative learning task using magnetoencephalography in healthy young adults (n = 32). We found that high retrospective confidence was associated with stronger occipital event-related fields during encoding and widespread event-related fields during retrieval compared to low confidence. On the other hand, memory accuracy was linked to medial temporal activities during both encoding and retrieval, but only in low-confidence trials. A decrease in oscillatory power at alpha/beta bands in the parietal regions during retrieval was associated with higher memory confidence. In addition, representational similarity analysis at the single-trial level revealed distributed but differentiable neural activities associated with memory accuracy and confidence during both encoding and retrieval. In summary, our study unveiled distinct neural activity patterns related to memory confidence and accuracy during associative learning and underscored the crucial role of parietal regions in metamemory.

We trained healthy elderly individuals in trace eyeblink conditioning, either at inspiration-systole or at expiration-diastole. Those who learned exhibited more conditioned responses when trained at expiration-diastole rather than inspiration-systole. However, there was no difference between the experimental groups in the proportion of individuals who learned or did not learn.

Visual working memory (VWM) is a temporary storage system capable of retaining information that can be accessed and manipulated by higher cognitive processes, thereby facilitating a wide range of cognitive functions. Electroencephalography (EEG) is used to understand the neural correlates of VWM with high temporal precision, and one commonly used EEG measure is an event-related potential called the contralateral delay activity (CDA). In a landmark study by Vogel and Machizawa (2004), the authors found that the CDA amplitude increases with the number of items stored in VWM and plateaus around three to four items, which is thought to represent the typical adult working memory capacity. Critically, this study also showed that the increase in CDA amplitude between two-item and four-item arrays correlated with individual subjects’ VWM performance. Although these results have been supported by subsequent studies, a recent study suggested that the number of subjects used in experiments investigating the CDA may not be sufficient to detect differences in set size and to provide a reliable account of the relationship between behaviorally measured VWM capacity and the CDA amplitude. To address this, the current study, as part of the #EEGManyLabs project, aims to conduct a multi-site replication of Vogel and Machizawa's (2004) seminal study on a large sample of participants, with a pre-registered analysis plan. Through this, our goal is to contribute to deepening our understanding of the neural correlates of visual working memory.

We report, for the first time, that the rhythms of breathing and the beating of the heart have a phase combination that is indicative of a neural state beneficial for cognition. This suggests that bodily rhythms not only modulate cognition but that this phenomenon can also be noninvasively harnessed to improve learning in humans.