Institute of Psychology, Chinese Academy of Sciences
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Relationships between clinical symptoms, cognitive functioning, and TMS-evoked potential features in patients with major depressive disorder
No full textBackground: Cognitive impairment is a common clinical symptom of patients with major depressive disorder (MDD). Transcranial magnetic stimulation-evoked potentials (TEPs) detect cortical excitability and connectivity and provide potential biomarkers for MDD patients and their cognitive impairment. This study aimed to investigate the interrelationships between clinical symptoms, cognitive function, and electrophysiological marker TEPs in patients with MDD. Methods: A total of 117 participants were recruited, including 59 MDD patients and 58 healthy controls. Clinical symptoms were assessed by the Hamilton Depression Rating Scale and Hamilton Anxiety Rating Scale, and cognitive functioning was assessed by the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). TEPs were recorded by transcranial magnetic stimulation combined with electroencephalography (TMS-EEG). Results: MDD patients exhibited lower RBANS total (P < 0.001), immediate memory (P = 0.001), language (P = 0.003), attention (P < 0.001), and delayed memory (P = 0.008) scores than HCs. Patients with MDD had larger amplitudes for N100 (P = 0.040) and N280 (P = 0.037), compared to HCs. Correlation analysis indicated significant correlations between the following RBANS scores and TEPs: language and N45 amplitude (r = 0.222, P = 0.024), language and P60 amplitude (r = 0.278, P = 0.004), attention and P180 amplitude (r = 0.213, P = 0.030), RBANS total score and P30 amplitude (r = 0.198, P = 0.044), visuospatial/constructional index and N100 amplitude (r = -0.272, P = 0.005). Conclusion: The results of this study indicate that cortical dysfunction and cognitive impairment are present in patients with MDD and that there is a strong correlation between them, suggesting that TEPs detected by the TMS-EEG may be used as a biomarker for MDD patients and their cognitive impairment
Longitudinal associations between metalinguistic awareness, executive functions, and Chinese character reading: A network analysis
No full textUsing behavioral network analysis, the present study aimed to examine the relation between various cognitive-linguistic skills and Chinese character reading in children from preschool to primary school. A cohort of 172 Chinese children (41.3% female; Mage = 5.74 +/- 0.32 years) were followed from the end of kindergarten (T1) to first grade (T2) and end of Grade 3 (T3), and were assessed on cognitive-linguistic skills (i.e., orthographic awareness, morphological awareness, rapid automatized naming, and phonological awareness), executive functions, and character reading. Behavioral network analysis showed that the association between orthographic awareness and Chinese character reading was significant at T1 and T2 but faded by T3. Morphological awareness displayed no significant correlation with Chinese character reading at T1 and T2, while this correlation strengthened at T3. Rapid automatized naming consistently demonstrated a significant correlation with Chinese character reading across all three time points. In contrast, phonological awareness, inhibitory control, and working memory failed to exhibit a significant correlation with Chinese character reading at all three time points. The findings shed light on the unique and evolving roles of metalinguistic skills in shaping Chinese character reading during this developmental stage
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
Protective effects of maternal mindfulness on social withdrawal in young children
No full text目的:探讨母亲正念对幼儿社交退缩行为的保护作用,以及正念养育、亲子关系和幼儿趋避气质在其间可能的中介作用和调节作用。方法:选取幼儿母亲605人,采用正念注意觉知量表(MAAS)、儿童社会偏好量表(CSPS)、正念养育量表(IM-P)、亲子关系量表(CPRS)、儿童气质问卷(PTQ)分别对母亲正念、社交退缩、正念养育、亲子关系、趋避气质进行评估。结果:幼儿CSPS得分与MAAS、IM-P、CPRS和PTQ得分均呈负相关(r=-0.65～-0.16,均P<0.01);IM-P和CPRS得分在MAAS与CSPS得分之间起链式中介作用(β=-0.05,P<0.01),CPRS得分在MAAS与CSPS得分之间起部分中介作用(β=-0.04,P<0.01);PTQ得分在MAAS和IM-P得分的关系中起调节作用(β=0.11,P<0.01)。结论:母亲正念不仅直接作用于社交退缩,还通过正念养育、亲子关系间接作用于社交退缩,趋避气质可调节母亲正念与正念养育之间的关系。</p
Identifying and Validating Neuroanatomical Subtypes of Patients with Major Depressive Disorder by Semi-Supervised Machine Learning
No full textBackground: Major depressive disorder (MDD) is a complex psychiatric disorder characterized by diverse clinical profiles and variable treatment responses. Parsing the neuroanatomical heterogeneity among patients with MDD holds great promise for improving the predictive accuracy for treatment outcome and developing more effective treatments.
Methods: We utilized a semi-supervised machine learning method called heterogeneity through discriminative analysis (HYDRA) to delineate patterns of neuroanatomical heterogeneity characterized by fractional anisotropy (FA) from 48 fiber tracts within a discovery dataset (130 patients with MDD and 128 healthy controls [HCs]). Among of these patients, 92 MDD patients underwent an 8-week antidepressant treatment. We further investigated the generalizability of these identified subtypes in an independent dataset comprising 84 patients.
Results: Two stable subtypes of patients with MDD were identified. The Atypical MDD subtype was defined by widespread increases in FA compared to the Typical MDD subtype and HCs. The Typical subtype was characterized by more severe depressive symptoms, an earlier age of onset, decreased FA, and decreased resting-state functional connectivity compared to the Atypical MDD subtype. Furthermore, differentiating these subtypes improved the accuracy of prediction of remission following antidepressant treatment. The independent dataset validated the existence of these two subtypes.
Conclusions: Our study reveals two distinct subtypes of patients with MDD based on neuroanatomical heterogeneity, with one subtype showing more severe depressive symptoms, severe brain structural and functional connectivity abnormalities, and improved accuracy in prognosis prediction. These findings underscore the potential of biotyping for precision medicine in MDD, offering promise for personalized approaches to treatment and care.</p
Gendered Artificial Intelligence in Marketing: Behavioral and Neural Insights Into Product Recommendations
No full textMarketing research consistently demonstrates that gender stereotypes influence the effectiveness of product recommendations. When artificial intelligence (AI) agents are designed with gendered features to enhance anthropomorphism, a follow-up question is whether these agents' recommendations are also shaped by gender stereotypes. To investigate this, the current study employed a shopping task featuring product recommendations (utilitarian vs. hedonic), using both behavioral measures (purchase likelihood, personal interest, and tip amount) and event-related potential components (P1, N1, P2, N2, P3, and late positive potential) to capture explicit and implicit responses to products recommended by male and female humans, virtual assistants, or robots. The findings revealed that gender stereotypes influenced responses at both levels but in distinct ways. Behaviorally, participants consistently favored female recommenders across all conditions. Additionally, female recommenders received more tips than males for hedonic products in the virtual assistant condition and utilitarian products in the robot condition. Implicitly, the N1 and N2 components reflected a classic gender stereotype from prior research: utilitarian products recommended by male humans elicited greater attention and received more inhibition control. We propose that task design and cultural factors may have contributed to the observed discrepancies between explicit (consumer behaviors) and implicit responses. These findings provide insights for mitigating the impact of gender difference when designing the anthropomorphic appearance of AI agents, which would help the development of more effective marketing strategies
Association between fasting blood glucose and psychotic symptoms in Chinese patients with first-episode drug-na?ve major depressive disorder
No full textIntroductionPsychotic depression (PD) is a highly debilitating disorder characterized by hallucinations and/or delusions accompanied by depression. A variety of neurotransmitters, hormones and corresponding receptors in the endocrine system are involved in the onset and progression of depression, and fasting blood glucose (FBG) can be an important indicator for monitoring the stability of the endocrine system. The aim of this study was to investigate the relationship between FBG and PD in a Chinese population with first-episode drug-na & iuml;ve (FEDN) major depressive disorder (MDD). MethodsIn this study, 1718 outpatient individuals diagnosed with first-episode drug-na & iuml;ve major depressive disorder (FEDN MDD) were included. The association between PD and FBG levels was identified through multivariable binary logistic regression analysis. To investigate potential non-linear relationships, a two-piecewise linear regression model was utilized. Additionally, interaction and stratified analyses were performed based on gender, educational background, marital status, presence of comorbid anxiety, and history of suicide attempt. ResultsMultivariate logistic regression analysis showed that FBG was positively associated with the risk of PD in FEDN MDD patients (OR = 1.68, 95% CI: 1.31 to 2.13; P < 0.05). Smoothed plots showed a non-linear relationship between FBG and PD, while the inflection point of FBG was calculated using a two-segmented logistic regression model to be 6.23 mmol/L. On the right side of the inflection point, the probability of PD increased substantially by 278% (OR = 3.78, 95% CI: 1.75 to 8.18, p < 0.001), while no significant association was observed on the left side of the inflection point (OR = 1.06, 95% CI: 0.73 to 1.52, p = 0.772). ConclusionsOur investigation revealed a nonlinear relationship between FBG and PD in patients with FEDN MDD, thereby informing more effective intervention strategies for managing psychotic symptoms in individuals with depression
Brain Activation and Aberrant Effective Connectivity in the Mentalizing Network of Preadolescent Children at Familial High Risk of Schizophrenia or Bipolar Disorder
No full textBACKGROUND: Schizophrenia and bipolar disorder are characterized by social cognitive impairments, and recent research has identified alterations of the social brain. However, it is unknown whether familial high risk (FHR) of these disorders is associated with neurobiological alterations already present in childhood. METHODS: As part of the Danish High Risk and Resilience Study-VIA 11, we examined children at FHR of schizophrenia (n = 121, 50% female) or bipolar disorder (n = 75, 47% female) and population-based control children (PBCs) (n = 128, 48% female). Using functional magnetic resonance imaging and dynamic causal modeling, we investigated brain activation and effective connectivity during the social cognition paradigm from the Human Connectome Project. RESULTS: We found similar activation of the mentalizing network across groups, including visual area V5, the dorsomedial prefrontal cortex, and the posterior superior temporal sulcus (pSTS). Nonetheless, both FHR groups showed aberrant brain connectivity in the form of increased feedforward connectivity from left V5 to pSTS compared with PBCs. Children at FHR of schizophrenia had reduced intrinsic connectivity in bilateral V5 compared with PBCs, whereas children at FHR of bipolar disorder showed increased reciprocal connectivity between the left dorsomedial prefrontal cortex and the pSTS, increased intrinsic connectivity in the right pSTS, and reduced feedforward connectivity from the right pSTS to the dorsomedial prefrontal cortex compared with PBCs. CONCLUSIONS: Our results provide first-time evidence of aberrant brain connectivity in the mentalizing network of children at FHR of schizophrenia or FHR of bipolar disorder. Longitudinal research is warranted to clarify whether aberrant brain connectivity during mentalizing constitutes an endophenotype associated with the development of a mental disorder later in life.</p
Nonacademic predictors of China medical licensing examination
No full textBackgroundNational Medical Licensing Examination (NMLE) is the entrance exam for medical practice in China, and its general medical knowledge test (GMKT) evaluates abilities of medical students to comprehensively apply medical knowledge to clinical practice. This study aimed to identify nonacademic predictors of GMKT performance, which would benefit medical schools in designing appropriate strategies and techniques to facilitate the transition from medical students to qualified medical practitioners.MethodsIn 1202 medical students, we conducted the deletion-substitution-addition (DSA) and structural equation model (SEM) analyses to identify nonacademic predictors of GMKT performance from 98 candidate variables including early life events, physical conditions, psychological and personality assessments, cognitive abilities, and socioeconomic conditions. The candidate variables were assessed using psychometrically or cognitively validated and accepted instruments.ResultsWe identified seven nonacademic predictors for GMKT performance. Body mass index (BMI) and working memory reaction time showed direct negative effects on GMKT performance. Psychological and personality features (conscientiousness, state anxiety, and openness to experience) indirectly affected GMKT performance via BMI, while socioeconomic conditions (father's education and mother's occupation) indirectly affected GMKT performance by influencing psychological and personality features and further BMI.ConclusionThe identified nonacademic predictors for GMKT performance and their pathways may be useful for improving medical education by strengthening favorable and weakening, rectifying, or compensating unfavorable factors that are modifiable
Nonacademic predictors of China medical licensing examination
No full textBackgroundNational Medical Licensing Examination (NMLE) is the entrance exam for medical practice in China, and its general medical knowledge test (GMKT) evaluates abilities of medical students to comprehensively apply medical knowledge to clinical practice. This study aimed to identify nonacademic predictors of GMKT performance, which would benefit medical schools in designing appropriate strategies and techniques to facilitate the transition from medical students to qualified medical practitioners.MethodsIn 1202 medical students, we conducted the deletion-substitution-addition (DSA) and structural equation model (SEM) analyses to identify nonacademic predictors of GMKT performance from 98 candidate variables including early life events, physical conditions, psychological and personality assessments, cognitive abilities, and socioeconomic conditions. The candidate variables were assessed using psychometrically or cognitively validated and accepted instruments.ResultsWe identified seven nonacademic predictors for GMKT performance. Body mass index (BMI) and working memory reaction time showed direct negative effects on GMKT performance. Psychological and personality features (conscientiousness, state anxiety, and openness to experience) indirectly affected GMKT performance via BMI, while socioeconomic conditions (father's education and mother's occupation) indirectly affected GMKT performance by influencing psychological and personality features and further BMI.ConclusionThe identified nonacademic predictors for GMKT performance and their pathways may be useful for improving medical education by strengthening favorable and weakening, rectifying, or compensating unfavorable factors that are modifiable.</p
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