Aberrant affective neural processing and negative emotional bias are trait-marks of major depression disorders (MDDs). However, most research on biased emotional perception in depression has only focused on unimodal experimental stimuli, the neural basis of potentially biased emotional processing of multimodal inputs remains unclear. Here, we addressed this issue by implementing an audiovisual emotional task during functional MRI scanning sessions with 37 patients with MDD and 37 gender-, age-and education-matched healthy controls. Participants were asked to distinguish laughing and crying sounds while being exposed to faces with different emotional valences as background. We combined general linear model and psychophysiological interaction analyses to identify abnormal local functional activity and integrative processes during audiovisual emotional processing in MDD patients. At the local neural level, MDD patients showed increased bias activity in the ventromedial prefrontal cortex (vmPFC) while listening to negative auditory stimuli and concurrently processing visual facial expressions, along with decreased dorsolateral prefrontal cortex (dlPFC) activity in both the positive and negative visual facial conditions. At the network level, MDD exhibited significantly decreased connectivity in areas involved in automatic emotional processes and voluntary control systems during perception of negative stimuli, including the vmPFC, dlPFC, insula, as well as the subcortical regions of posterior cingulate cortex and striatum. These findings support a multimodal emotion dysregulation hypothesis for MDD by demonstrating that negative bias effects may be facilitated by the excessive ventral bottom-up negative emotional influences along with incapability in dorsal prefrontal top-down control system.

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Introduction: Schizophrenia is a mental disease with a profound impact on human health. Patients with schizophrenia have poor oral hygiene, increasing their risk of systemic diseases, such as respiratory infections, and declining their quality of life. Therefore, this study aims to assess the oral health status of inpatients with schizophrenia, analyze its related factors, and thus provide scientific evidence for further exploration of corresponding control strategies.Methods: A total of 425 inpatients older than 50 years with a diagnosis of schizophrenia from two psychiatric hospitals (mean age 58.49 ± 5.72 years) were enrolled. The demographic data of the patients were checked on admission. Two independent dentists examined caries, missing teeth, and fillings. Mini-Mental State Examination (MMSE) and Global Deterioration Scale were performed as cognitive tests. Positive and Negative Syndrome Scale and Repeatable Battery for the Assessment of Neuropsychological Status rating scale were used to determine their mental status.Results: The average decayed, missing, and filled teeth index was 12.99 ± 8.86. Linear regression analysis showed that the decayed, missing, and filled teeth index had a significantly positive relationship with age (p < 0.001) and smoking (p < 0.001) and a negative relationship with MMSE (p = 0.029). The missing teeth index had a positive relationship with age (p < 0.001), smoking (p < 0.001), and Global Deterioration Scale (p = 0.014) and a negative relationship with MMSE (p = 0.004).Conclusion: The oral health of elderly patients with schizophrenia is poor, which may be related to the cognitive level of patients and affect their quality of life. The focus should be provided to the oral care of patients with schizophrenia, and investment in their specialized oral treatment should be increased.

Objective:To reveal the possible routine of brain network dynamic alterations in patients with mesial temporal lobe epilepsy (mTLE) and to establish a predicted model of seizure recurrence during interictal periods.Methods: Seventy-nine unilateral mTLE patients with hippocampal sclerosis and 97 healthy controls from two centers were retrospectively enrolled. Dynamic brain configuration analyses were performed with resting-state functional magnetic resonance imaging (MRI) data to quantify the functional stability over time and the dynamic interactions between brain regions. Relationships between seizure frequency and ipsilateral hippocampal module allegiance were evaluated using a machine learning predictive model. Results:Compared to the healthy controls, patients with mTLE displayed an overall higher dynamic network, switching mainly in the epileptogenic regions (false discovery rate [FDR] corrected p-FDR < .05). Moreover, the dynamic network configuration in mTLE was characterized by decreased recruitment (intra-network communication), and increased integration (inter-network communication) among hippocampal systems and large-scale higher-order brain networks (p-FDR < .05). We further found that the dynamic interactions between the hippocampal system and the default-mode network (DMN) or control networks exhibited an opposite distribution pattern (p-FDR < .05). Strikingly, we showed that there was a robust association between predicted seizure frequency based on | 2243 LI et al.