Institute of Psychology, Chinese Academy of Sciences
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What is the optimal display range? Exploring the impacts of area and shape on in-vehicle head-up display efficiency
No full textIn-vehicle Head-Up Displays (HUDs) are expected to incorporate more information in the future, necessitating deeper understandings of design properties that can enhance display safety and efficiency. However, the optimal display characteristics-particularly in terms of area and shape-remain inadequately understood. This study investigated these two factors by manipulating horizontal and vertical Field of View (FOV) angles within a simulated in-vehicle HUD. Thirty-one participants participated in this laboratory-based study they completed a digit matching task while driving within a driving simulator. The accuracy and response time of the task served as indicators for efficiency. The standard deviation of lateral position (SDLP) was employed to assess area and shape's impacts on driving performance, alongside subjective ease-of-use evaluations. Results indicated that an increase in horizontal FOV angle significantly delay response times and reduce ease-of-use ratings. We also observed significant effects of area and shape on response time and ratings; specifically, participants responded faster in smaller display area conditions, which were also rated as the easiest to use. Accuracy, however, was largely unaffected by size and shape. Importantly, most manipulations did not interfere with driving performance, except for the area 500 condition, wherein landscape shape was associated with better lane-keeping performance. Our findings provide valuable insights for the design of in-vehicle HUDs.</p
The Impact of Adverse Childhood Experiences on the Development of Adolescent Risk-Taking: The Mediating Effect of Self-Control and Moderating Effect of Genetic Variations
No full textRisk-taking is a concerning yet prevalent issue during adolescence and can be life-threatening. Examining its etiological sources and evolving pathways helps inform strategies to mitigate adolescents' risk-taking behavior. Studies have found that unfavorable environmental factors, such as adverse childhood experiences (ACEs), are associated with momentary levels of risk-taking in adolescents, but little is known about whether ACEs shape the developmental trajectory of risk-taking. Even less research has investigated the underlying mechanisms. Drawing on the self-regulation theory, this study examined the associations between ACEs and the developmental trajectory of adolescent risk-taking. Moreover, it also explored self-control as a mediator and genetic variations as a moderator from a "gene x environment" approach. Participants were 564 Chinese adolescents (48.40% males, Mage = 14.20 years, SD = 1.52). Adolescents reported their ACEs and self-control at T1 and risk-taking three times, with a six-month interval between each time point. Adolescents' saliva was collected at T1 for genetic extraction, and polygenetic index was created based on the gene-by-environment interaction between SNPs and ACEs for self-control via the leave-one-out machine learning approach. Findings of latent growth modeling revealed that adolescents' risk-taking decreased over time. ACEs were directly and indirectly through self-control associated with high initial levels of, and a rapid decrease in, risk-taking, especially for those with a higher polygenetic index compared to those with a lower polygenetic index. Theoretically, these results suggest a tripartite model of adolescent risk-taking, such that risk-taking is the combined function of adverse experiences in early years, low self-control, and carriage of sensitive genes. Practically, intervention strategies should reduce childhood adversities, build up self-control, and consider the potential impacts of genetic plasticity
A Comparative Study of Form-sound Integration between School-aged Children and Adults: The Mutual Influence of Visual Form and Phonetic Information
No full text本研究采用词汇判断任务，探究了学龄儿童与成人在形音整合中，字形与字音加工的相互影响的差异。结果表明:(1)字音影响字形加工方面，不一致字音干扰了儿童的字形加工，一致字音促进了成人的字形加工;(2)字形影响字音加工方面，一致字形促进了儿童和成人的字音加工，且对成人字音加工的促进作用更大，不一致字形干扰了儿童和成人的字音加工。本研究从字音影响字形加工和字形影响字音加工两个角度出发，揭示了学龄儿童与成人形音整合能力的差异。</p
Preoperative resting-state electrophysiological signals predict acute but not chronic postoperative pain
No full textBackgroundThe prevalence of postoperative pain is notably high among the elderly population, which poses significant challenges for their postoperative recovery. In this study, we aimed to identify preoperative predictors for acute and chronic postoperative pain in patients undergoing lumbar spinal surgery through a longitudinal investigation.MethodsWe recruited 75 patients (mean age 68.29 +/- 5.60 years) and collected their resting-state electroencephalography (EEG) data two hours before the surgery. The aperiodic and periodic signal components were extracted from the resting-state EEG using the Fitting Oscillations and One-Over-F algorithm. We also collected the preoperative pain ratings, demographic information and the Hospital Anxiety and Depression Scale from all patients. The postoperative pain ratings were collected ten times from Day 1 to Week 12 after surgery.ResultsWe observed a high incidence of postoperative acute and chronic pain among older patients. Preoperative pain and peak alpha frequency in resting-state EEG were the primary predictors of acute postoperative pain. Although age is a significant predictor of chronic postoperative pain, its predictive performance is poor.ConclusionsOverall, our study provides valuable insights into the complex pattern of preoperative EEG features, preoperative pain and age in predicting postoperative pain at different stages. Our findings highlight the significance of exploring preoperative features to identify patients who are at a higher risk of developing severe postoperative pain, which can aid in the development of more personalized and effective pain management strategies.SignificanceThe heightened occurrence of postoperative pain among the elderly presents formidable obstacles to their recuperation. This study delves into identifying preoperative factors influencing acute and chronic postoperative pain. Our findings indicate that preoperative pain and peak alpha frequency are crucial predictors of acute postoperative pain. However, the predictive performance for chronic postoperative pain is limited, although age was a significant predictor of chronic postoperative pain. These insights contribute to the identification of patients at elevated risk for severe acute and chronic postoperative pain, offering valuable guidance for pre-surgical risk assessment.</p
The primacy of taxonomic semantic organization over thematic semantic organization during picture naming
No full textDifferent organizational structures have been argued to underlie semantic knowledge about concepts; taxonomic organization, based on shared features, and thematic organization based on co-occurrence in common scenes and scenarios. The goal of the current study is to examine which of the two organizational systems are more engaged in the semantic context of a picture naming task. To address this question, we examined the representational structure underlying the semantic space in different picture naming tasks by applying representational similarity analysis (RSA) to electroencephalography (EEG) datasets. In a series of experiments, EEG signals were collected while participants named pictures under different semantic contexts. Study 1 reanalyzes existing data from semantic contexts directing attention to taxonomic organization and semantic contexts that are not biased towards either taxonomic or thematic organization. In Study 2 we keep the stimuli the same and vary semantic contexts to draw attention to either taxonomic or thematic organization. The RSA approach allows us to examine the pairwise similarity in scalp-recorded amplitude patterns at each time point following the onset of the picture and relate it to theoretical taxonomic and thematic measures derived from computational models of semantics. Across all tasks, the similarity structure of scalp-recorded neural activity correlated better with taxonomic than thematic measures, in time windows associated with semantic processing. Most strikingly, we found that the scalp-recorded patterns of neural activity between taxonomically related items were more similar to each other than the scalp-recorded patterns of neural activity for thematically related or unrelated items, even in tasks that makes thematic information more salient. These results suggest that the principle semantic organization of these concepts during picture naming is taxonomic, at least in the context of picture naming
A deep learning method for contactless emotion recognition from ballistocardiogram
No full textEmotion recognition is a major research point in the field of affective computing. Existing research on the application of physiological signals to emotion recognition mainly focuses on the processing of contact signals. However, there are issues with contact signal acquisition equipment, such as limited portability and poor user compliance, which make it difficult to promote its use. To explore a new method for emotion recognition based on contactless ballistocardiogram (BCG), we proposed a SE-CNN model with a multi-class focal loss function. To construct the dataset, we used audio-visual stimuli to evoke the subjects' emotions and collected data on the subjects' three discrete emotions, positive, neutral, and negative, through our established BCG signal acquisition system based on a piezoelectric ceramics sensor. Root mean square filter and thresholding were used to detect and eliminate motion artifacts of BCG signals. We did two kinds of preprocessing on BCG signals: wavelet transform and bandpass filtering, to explore the effect of different components of BCG on emotion recognition. Subsequently, we verified the model's performance and cross-time working ability through traditional K-Fold and our proposed K-Session cross-validation methods. The results showed that the band-pass filtering method was more beneficial to the current classification task. Under K-Fold cross-validation, the model's accuracy, precision, and recall were 97.21%, 97.00%, and 97.11%. Under K-Session cross-validation, the model's accuracy, precision, and recall were 94.66%, 93.92%, and 94.86%, respectively, all of which were better than the classification effect of synchronous ECG. The reliability of BCG in contactless emotion recognition was proved
Dark brain energy: Toward an integrative model of spontaneous slow oscillations
No full textNeural oscillations facilitate the functioning of the human brain in spatial and temporal dimensions at various frequencies. These oscillations feature a universal frequency architecture that is governed by brain anatomy, ensuring frequency specificity remains invariant across different measurement techniques. Initial magnetic resonance imaging (MRI) methodology constrained functional MRI (fMRI) investigations to a singular frequency range, thereby neglecting the frequency characteristics inherent in blood oxygen level-dependent oscillations. With advancements in MRI technology, it has become feasible to decode intricate brain activities via multi-band frequency analysis (MBFA). During the past decade, the utilization of MBFA in fMRI studies has surged, unveiling frequency-dependent characteristics of spontaneous slow oscillations (SSOs) believed to base dark energy in the brain. There remains a dearth of conclusive insights and hypotheses pertaining to the properties and functionalities of SSOs in distinct bands. We surveyed the SSO MBFA studies during the past 15 years to delineate the attributes of SSOs and enlighten their correlated functions. We further proposed a model to elucidate the hierarchical organization of multi-band SSOs by integrating their function, aimed at bridging theoretical gaps and guiding future MBFA research endeavors
Expectation violations signal goals in novel human communication
No full textCommunication, often grounded in shared expectations, faces challenges when a Sender and Receiver lack a common linguistic background. Our study explores how people instinctively turn to the fundamental principles of the physical world to overcome such barriers. Specifically, through an experimental game in which Senders convey messages via trajectories, we investigate how they develop novel strategies without relying on common linguistic cues. We build a computational model based on the principle of expectancy violations and a set of common universal priors derived from movement kinetics. The model replicates participant-designed messages with high accuracy and shows how its core variable-surprise-predicts the Receiver's physiological and neuronal responses in brain areas processing expectation violations. This work highlights the adaptability of human communication, showing how surprise can be a powerful tool in forming new communicative strategies without relying on common language
Neuronal mechanisms of nociceptive-evoked gamma-band oscillations in rodents
No full textGamma-band oscillations (GBOs) in the primary somatosensory cortex (S1) play key roles in nociceptive processing. Yet, one crucial question remains unaddressed: what neuronal mechanisms underlie nociceptiveevoked GBOs? Here, we addressed this question using a range of somatosensory stimuli (nociceptive and non-nociceptive), neural recording techniques (electroencephalography in humans and silicon probes and calcium imaging in rodents), and optogenetics (alone or simultaneously with electrophysiology in mice). We found that (1) GBOs encoded pain intensity independent of stimulus intensity in humans, (2) GBOs in S1 encoded pain intensity and were triggered by spiking of S1 interneurons, (3) parvalbumin (PV)-positive interneurons preferentially tracked pain intensity, and critically, (4) PV S1 interneurons causally modulated GBOs and pain-related behaviors for both thermal and mechanical pain. These findings provide causal evidence that nociceptive-evoked GBOs preferentially encoding pain intensity are generated by PV interneurons in S1, thereby laying a solid foundation for developing GBO-based targeted pain therapies.</p
Semantic and Phonological Prediction in Language Comprehension: Pretarget Attraction Toward Semantic and Phonological Competitors in a Mouse Tracking Task
No full textRecent evidence increasingly suggests that comprehenders are capable of generating probabilistic predictions about forthcoming linguistic inputs during language comprehension. However, it remains debated whether language comprehenders predict low-level word forms and whether they always make predictions. In this study, we investigated semantic and phonological prediction in high- and low-constraining sentence contexts, utilizing the mouse-tracking paradigm to trace mouse movement trajectories. Mandarin Chinese speakers listened to high- and low-constraining sentences which resulted in high and low predictability for the critical target words. While listening, participants viewed a visual display featuring two objects: one corresponding to the critical target word (the target object) and the other being either semantically related, phonologically related, or unrelated to the target word. Participants were instructed to click on the target object. The analysis of mouse movement trajectories revealed two key findings: (1) In both high- and low-constraining contexts, there was a spatial attraction of the cursor toward semantic competitors, notably occurring before the target word was heard; (2) there are indications that phonological pretarget attraction effects were observed primarily in high-constraining contexts. These findings suggest that the constraints of sentences have the potential to modulate the representational contents of linguistic prediction during language comprehension. Methodologically, the mouse-tracking paradigm presents a promising tool for further exploration of linguistic prediction
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