Institute of Psychology, Chinese Academy of Sciences
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Anterior Cingulate Cortex Glutamate Levels and Sensory Integration Are Associated in Individuals With Social Anhedonia: A Comparison Between 3T and 7T MRS
No full textDeficits in schizophrenia are linked to abnormalities in the glutamate (Glu) system, which are believed to result in neurological soft signs (NSS) and negative symptoms. This study investigated the relationship between Glu levels of the anterior cingulate cortex (ACC) and NSS, particularly sensory integration, in individuals with high and low levels of social anhedonia using 3 Tesla (T) and 7T Magnetic Resonance Spectroscopy (MRS). We recruited 16 participants with high social anhedonia and 18 with low social anhedonia and correlated their NSS scores with ACC Glu levels. While spectral quality metrics differed between field strengths, with 7T showing better spectral resolution and metabolite quantification reliability, both 3T and 7T data showed consistent correlation patterns. Our findings demonstrated that higher ACC Glu levels were associated with poorer sensory integration in high levels of social anhedonia across both field strengths, supported by both Pearson and Spearman rank correlations. Notably, the opposite pattern of association was found in people with low levels of social anhedonia at 7T. The Glu systems may be the common mechanisms for negative symptoms and NSS, highlighting its potential as a therapeutic target
Electrophysiological Signatures of Visual Sensations Elicited by Direct Electrical Stimulation
No full textDirect electrical stimulation of the human cortex can produce subjective visual sensations, yet these sensations are unstable. The underlying mechanisms may stem from differences in electrophysiological activity within the distributed network outside the stimulated site. To address this problem, we recruited 69 patients who experienced visual sensations during invasive electrical stimulation while intracranial electroencephalography (iEEG) data were recorded. We found significantly flattened power spectral slopes in distributed regions involving different brain networks and decreased integrated information during elicited visual sensations compared with the non-sensation condition. Further analysis based on minimum information partitions revealed that the reconfigured network interactions primarily involved the inferior frontal cortex, posterior superior temporal sulcus, and temporoparietal junction. The flattened power spectral slope in the inferior frontal gyrus was also correlated with integrated information. Taken together, this study indicates that the altered electrophysiological signatures provide insights into the neural mechanisms underlying subjective visual sensations
Short-term visual adaptation to body shape induces sustained aftereffect on body size estimation
No full textVisual adaptation to thin or large bodies was found to shift the subjective body normality towards the adapting body shape. Here we investigated the persistency of such adaptation effect by tracking the timecourse of decay of short-term body size adaptation in young healthy Chinese women. Participants adapted to contracted or expanded body images of unfamiliar female volunteers with a top-up paradigm. Their subjective point of normal body size (PNS) was measured before, immediately after and 10/20/30 min after adaptation. The results showed that about 12 min of adaptation to contracted or expanded body stimuli could shift participants' estimations of body normality towards the adapting body shape, with the effect sustaining for more than 30 min after the end of adaptation. In addition, by fitting the timecourse of decay of adaptation with the exponential, power or logarithmic functions, we found that the recovery of body size adaptation effect could be best described with the logarithmic models. These findings indicated that short-term exposure to distorted body shapes of other people could lead to a lingering bias on body size estimation
A comparison of the persuasiveness of human and ChatGPT generated pro-vaccine messages for HPV
No full textIntroduction Public health messaging is crucial for promoting beneficial health outcomes, and the latest advancements in artificial intelligence offer new opportunities in this field. This study aimed to evaluate the effectiveness of ChatGPT-4 in generating pro-vaccine messages on different topics for Human Papillomavirus (HPV) vaccination.Methods In this study (N = 60), we examined the persuasive effect of pro-vaccine messages generated by GPT-4 and humans, which were constructed based on 17 factors impacting HPV vaccination. Paired-samples t-tests were used to compare the persuasiveness of these messages.Results GPT-generated messages were reported as more persuasive than human-generated messages on some influencing factors (e.g., untoward effect, stigmatized perception). Human-generated messages performed better on the message regarding convenience of vaccination.Discussion This study provides evidence for the viability of ChatGPT, in generating persuasive pro-vaccine messages to influence people's vaccine attitudes. It is indicated that the feasibility and efficiency of using AI for public health communication
The Relationship Between Co-rumination and Depressive Symptoms: A Systematic Review and Meta-Analysis
No full textNumerous studies have explored the link between co-rumination and depressive symptoms, but a consensus remains elusive. This study proposes a dual-pathway model to explain this relationship through a "positive path" (adaptive response) and a "negative path" (distress response). It also conducts a meta-analysis to evaluate the exact association between co-rumination and depressive symptoms in children, adolescents, and young adults. A total of 66 studies (27,794 participants) were included in the meta-analysis. In this study, the main effect test revealed a significant positive correlation between co-rumination and depressive symptoms (n = 70; r = 0.128; 95% CI = 0.106 to 0.150). Moreover, age was found to be a significant moderator. Specifically, the association between co-rumination and depressive symptoms was weaker in adolescents compared to undergraduates and adults. In addition, measure of co-rumination was identified as an important moderator, showing marginal significance. The association was stronger when using the original Co-Rumination Questionnaire compared to other versions and code methods. Finally, the relationship between co-rumination and depressive symptoms was not moderated by gender, measure of depressive symptoms, publication year, study quality, or simple size. The current study reveals the positive association between co-rumination and depressive symptoms while highlighting both the positive and negative trade-offs of co-rumination
Micro-expression recognition using dual-view self-supervised contrastive learning with intensity perception
No full textMicro-expressions, as indicators of true emotions, have significant applications in medical care and public safety. These expressions are characterized by their short duration, low intensity, and localized occurrence. These characteristics lead to the small sample problem in micro-expressions, making feature learning challenging and limiting the improvement of recognition performance. To address this issue, we propose a multimodal contrastive learning pre-training model based on Action Unit (AU) intensity perception. We conducted an experiment to determine the minimum threshold for recognizing facial expressions. Using this threshold, we filtered a large volume of unsupervised samples. The first stage involves unsupervised multimodal contrastive learning, where the model learns from differences in facial actions across various modalities. Subsequently, the model is trained on the micro-expression recognition task using a small amount of labeled data, overcoming the limitations of small sample sizes. Comparative experiments using the MEGC2019-CD and the multimodal dataset CAS(ME)3 datasets demonstrate the superiority of our method. Our method is available at https: //github.com/MELABIPCAS/DVSCL.git
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.</p
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.</p
Duration of untreated psychosis and cognitive function in first-episode antipsychotic-na?ve schizophrenia: Evidence from auditory P300
No full textObjective: The relationship between the duration of untreated psychosis (DUP) and cognitive function in schizophrenia (SZ) patients remains debated, with no empirical evidence from event-related potential (ERP) studies supporting their association. This study aims to investigate the relationship between DUP and cognitive functions, as well as psychiatric symptoms, in first-episode antipsychotic-na & iuml;ve SZ (FEAN-SZ) patients using ERP. Methods: The study included 321 Chinese FEAN-SZ patients and 146 healthy controls. The DUP and sociodemographic characteristics of all participants were collected, and psychiatric symptoms were assessed using the Positive and Negative Syndrome Scale. The P300 (P3) components, including P3a, P3b and N100, were recorded from all participants using auditory oddball paradigm. Results: 25.5 % of patients did not receive timely treatment for over four years, and those with lower educational levels or more severe negative symptoms had longer DUP (p = 0.027, p = 0.020). Compared to healthy controls, FEAN-SZ patients exhibited longer latencies and lower amplitudes in the P3 components (all p(s) = 48 months) (all p(s) 48 months group (beta = -0.228, p = 0.040). Multiple linear regression analysis indicated that the latency and amplitude of P3a were independently associated with DUP (B = 0.124, p < 0.001; B = -1.161, p = 0.012). Conclusions: SZ patients who have a longer DUP exhibit more severe P3 deficits, and the P3 components may be indicative of different psychiatric symptom severity in DUPs of different lengths, as well as the P3a component may serve as an electrophysiologic marker to assess the length of DUP
Right inferior frontal cortex and preSMA in response inhibition: An investigation based on PTC model
No full textResponse inhibition is an essential component of cognitive function. A large body of literature has used neuroimaging data to uncover the neural architecture that regulates inhibitory control in general and movement cancelation. The presupplementary motor area (preSMA) and the right inferior frontal cortex (rIFC) are the key nodes in the inhibitory control network. However, how these two regions contribute to response inhibition remains controversial. Based on the Pause-then-Cancel Model (PTC), this study employed functional magnetic resonance imaging (fMRI) to investigate the functional specificity of two regions in the stopping process. The Go/ No-Go task (GNGT) and the Stop Signal Task (SST) were administered to the same group of participants. We used the GNGT to dissociate the pause process and both the GNGT and the SST to investigate the inhibition mechanism. Imaging data revealed that response inhibition produced by both tasks activated the preSMA and rIFC. Furthermore, an across-participants analysis showed that increased activation in the rIFC was associated with a delay in the go response in the GNGT. In contrast, increased activation in the preSMA was associated with good inhibition efficiency via the striatum in both GNGT and SST. These behavioral and imaging findings support the PTC model of the role of rIFC and preSMA, that the former is involved in a pause process to delay motor responses, whereas the preSMA is involved in the stopping of motor responses
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