Institute of Psychology, Chinese Academy of Sciences
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Behavioral theta oscillations in cross-modal stimulus conflict and response conflict processing
No full textTheta振荡与认知控制密切相关。以往研究发现theta振荡参与跨通道刺激冲突与反应冲突的加工,然而,theta振荡与跨通道刺激冲突和反应冲突程度之间的关系目前仍不清楚。本研究采用视听Stroop任务,结合具有高时间分辨率的行为采样方法对该问题进行探究。结果表明大脑对任务相关通道刺激的加工节律受任务无关通道刺激的影响。当任务无关刺激与任务相关刺激相同或冲突时,大脑对任务相关刺激的加工节律为theta;当任务无关刺激为中性刺激时,大脑则以alpha节律加工任务相关刺激。此外,研究发现,在听觉任务中,反应冲突幅度在视听刺激呈现时间间隔(StimulusOnsetAsynchrony,SOA)上表现出theta振荡;在视觉任务中,刺激冲突幅度在SOA上表现出theta振荡。当前结果表明冲突加工在行为上表现出节律性,揭示了theta振荡与冲突幅度之间的关系,将注意的节律性理论扩展到认知控制的冲突加工领域。</p
Advances in Mental Time Travel Research in Adolescent Depression: A Narrative Review
No full textAdolescent depression is a serious public health issue affecting the mental health and quality of life of adolescents worldwide. Mental time travel (MTT), an individual's capacity to recall the past or look to the future, plays an important role in emotion regulation and mental health. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a systematic literature search was conducted. Due to considerable heterogeneity among the included studies, a narrative synthesis approach was adopted. A total of 22 articles retrieved from PubMed, Web of Science, PsycINFO, and EBSCO (up to October 31, 2024) were included to elucidate the mechanisms underlying MTT impairments and related interventions in depressed adolescents. The main findings indicated that depressed adolescents exhibit overgeneralization of autobiographical memories, impoverished future simulations, and negative bias in MTT constructs. Neuroimaging studies have revealed aberrant activation within the autobiographical memory network, hyperengagement of the self-referential network during MTT tasks, and alterations in emotion regulation circuits. Furthermore, the efficacy of cognitive therapy and memory/imagery-specific training in ameliorating temporal cognitive biases and fostering positive future expectations was demonstrated. These findings underscore the importance of examining adolescent depression through the lens of MTT, offering a promising framework for understanding its cognitive and neural mechanisms and the development of novel intervention strategies
Therapeutic Metaphors Enhance Memory Systems in Mental Health Contexts
No full textBackgroundPsychotherapeutic memory plays an important role in maintaining therapeutic effects; however, the neural mechanisms of therapeutic metaphor promoting long-term memory were still unknown.ObjectiveThis study used metaphorical micro-counseling dialog scenarios to investigate the memory effect of therapeutic metaphor and correlated neural mechanisms.MethodsAt first, 31 participants read a mental distress problem, followed by a metaphorical or a literal solution, while undergoing functional magnetic resonance imaging scanning during the encoding phase. One week later, a recognition memory test was performed outside the scanner.ResultsThe results revealed that metaphorical solutions were associated with higher insight experiences and better memory performance than literal solutions. Greater activations were observed in the multiple memory systems, including episodic (parahippocampal gyrus, hippocampus, and thalamus), emotional (amygdala), and procedural/implicit (caudate, putamen, and cerebellum), in contrast to later remembered versus later forgotten based on the gap between metaphorical and literal solutions. Insightfulness and activities of the hippocampus, caudate, and cerebellum could predict memory performance.ConclusionsThese findings indicated that multiple memory systems are involved in successful memory encoding of therapeutic metaphors; this suggested that incorporating metaphors into psychotherapy practices could lead to better retention of therapeutic information and improve clinical outcomes compared to literal psychotherapy
Advances and applications of peripheral optogenetics in animal models
No full textPeripheral optogenetics is an emerging neuromodulation technique that regulates the activity of the nervous system outside the brain through the expression of photosensitive proteins and the application of photic stimulation. This article reviews recent advances in applying optogenetics to the spinal cord and peripheral nerves, offering a comprehensive understanding of the functions and regulatory mechanisms of the peripheral nervous system through the modulation of specific neuronal activities. By showcasing novel opportunities for disease treatment, this technique opens new avenues in psychophysiological research and neural regulation therapy. Despite current challenges, such as operability, effectiveness, and selective neuron targeting, peripheral optogenetics holds significant potential for advancing neuromodulation. Continued research and technological innovations will further expand its role, offering new possibilities for understanding and treating disorders involving the peripheral nervous system
Advances and applications of peripheral optogenetics in animal models
No full textPeripheral optogenetics is an emerging neuromodulation technique that regulates the activity of the nervous system outside the brain through the expression of photosensitive proteins and the application of photic stimulation. This article reviews recent advances in applying optogenetics to the spinal cord and peripheral nerves, offering a comprehensive understanding of the functions and regulatory mechanisms of the peripheral nervous system through the modulation of specific neuronal activities. By showcasing novel opportunities for disease treatment, this technique opens new avenues in psychophysiological research and neural regulation therapy. Despite current challenges, such as operability, effectiveness, and selective neuron targeting, peripheral optogenetics holds significant potential for advancing neuromodulation. Continued research and technological innovations will further expand its role, offering new possibilities for understanding and treating disorders involving the peripheral nervous system.</p
Burnout and its relationship with depressive symptoms in primary school teachers under the "Double Reduction" policy in China
No full textBackground: The "Double Reduction" policy requires schools to reduce Chinese students' extracurricular activities and homework to lessen academic stress and improve mental well-being. However, there is limited research on primary school teachers' psychological well-being within the context of the "Double Reduction" policy. This study examined self-reported burnout levels of primary school teachers and investigated the relationship between burnout and depressive symptoms in the context of the "Double Reduction" policy in China. Methods: A cross-sectional survey recruited 3,199 primary school teachers from 15 cities across China. The teachers' burnout levels were assessed with the Maslach Burnout Inventory, and depressive symptoms were evaluated with the Patient Health Questionnaire depression scale. Results: Under the "Double Reduction" policy in China, 66.6% of the primary school teachers experience burnout. Individual and work-related characteristics were independently correlated with burnout. These factors included holding a bachelor's degree (OR = 2.244, 95% CI: 1.559-3.230, p < 0.001), being married (OR = 0.598, 95% CI: 0.443-0.807, p < 0.001), being dissatisfied with one's income (OR = 2.602, 95% CI: 2.191-3.090, p < 0.001), and having an intermediate professional title (OR = 1.351, 95% CI: 1.086-1.681, p = 0.007). The correlation coefficients between burnout subscale scores and depressive symptoms were 0.588 for emotional exhaustion, 0.585 for cynicism, and - 0.180 for professional efficacy (all p < 0.001). Conclusion: Our findings indicate that the prevalence of burnout among primary school teachers in China is exceptionally high, particularly under the "Double Reduction" policy. This situation is correlated with various psychological disorders, including depression. It is crucial to urgently implement psychological interventions for primary school teachers. Specifically, psychological assistance should be targeted at educators who are bachelor degree holders, married, dissatisfied with their income, and holders of an intermediate professional title
A cross-database micro-expression recognition framework based on meta-learning
No full textMicro-expressions are facial expressions that are revealed unconsciously when suppressing true emotions and are widely used in multiple tasks, such as deception detection. However, at present, the amount of available micro-expression data is small, and there are large differences between different databases, so it is still difficult to accurately perform cross-database micro-expression recognition, which hinders real applications of recognition. To address this issue, this article first presents a meta-learning framework suitable for cross-database micro-expression recognition named Meta-CDMERF, which is trained by combining multiple micro-expression databases. Then, a residual feature-wise linear (RFL) module is proposed to generate more feature distributions and adaptively choose representative features during multi micro-expression database training, thereby reducing the feature distance between samples of the same type in different databases. Next, a new loss function is designed, which combines the cross-entropy loss function with an interclass loss function. Specifically, the inter-class loss is based on the mean value of similar features from the support set and aims to increase the distance between samples of different categories, thereby capturing subtle changes in micro-expression images. Finally, the unweighted average recall (UAR) and unweighted F1 score (UF1) values of the proposed method on the CASME II database are 62.64% and 60.00%, respectively, reaching state-of-the-art performance.</p
Temporal-Noise-Aware Neural Networks for Suicidal Ideation Prediction Using Physiological Data
No full textThe robust generalization of deep learning models in the presence of inherent noise remains a significant challenge, especially when labels are ambiguous due to their subjective nature and noise is indiscernible in natural settings. In this article, we address a specific and important scenario of monitoring suicidal ideation (SI), where time-series data, such as galvanic skin response (GSR) and photoplethysmography (PPG), are susceptible to such noise. Current methods predominantly focus on image and text data or address artificially introduced noise, neglecting the complexities of natural noise in time-series analysis. To tackle this, we introduce a novel neural network model tailored for analyzing noisy physiological time-series data, named DBN_ConvNet, which integrates advanced encoding techniques with confidence learning training to enhance prediction performance. Another main contribution of our work is the collection of a specialized dataset of GSR and PPG signals derived from real-world environments for SI prediction. By employing this dataset, our DBN_ConvNet achieves a prediction accuracy of 76.67% and an F1 score of 0.74 in a binary classification task, outperforming state-of-the-art methods. Furthermore, comprehensive evaluations have been conducted on three other well-known public datasets with artificially introduced noise to test the DBN_ConvNet's capabilities rigorously. These tests consistently demonstrated DBN_ConvNet's superior performance by achieving an improvement of more than 10% in both accuracy and F1 score compared to the baseline methods
Neural representation of sensorimotor features in language-motor areas during auditory and visual perception
No full textSpeech processing involves a complex interplay between sensory and motor systems in the brain, essential for early language development. Recent studies have extended this sensory-motor interaction to visual word processing, emphasizing the connection between reading and handwriting during literacy acquisition. Here we show how language-motor areas encode motoric and sensory features of language stimuli during auditory and visual perception, using functional magnetic resonance imaging (fMRI) combined with representational similarity analysis. Chinese-speaking adults completed tasks involving the perception of spoken syllables and written characters, alongside syllable articulation and finger writing tasks to localize speech-motor and writing-motor areas. We found that both language-motor and sensory areas generally encode production-related motoric features across modalities, indicating cooperative interactions between motor and sensory systems. Notably, sensory encoding within sensorimotor areas was observed during auditory speech perception, but not in visual character perception. These findings underscore the dual encoding capacities of language-motor areas, revealing both shared and distinct neural representation patterns across modalities, which may be linked to innate sensory-motor mechanisms and modality-specific processing demands. Our results shed light on the sensorimotor integration mechanisms underlying language perception, highlighting the importance of a cross-modality perspective
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