Micro-Expression Recognition Based on Nodal Efficiency in the EEG Functional Networks.

Micro-expression recognition based on ima- ges has made some progress, yet limitations persist. For instance, image-based recognition of micro-expressions is affected by factors such as ambient light, changes in head posture, and facial occlusion. The high temporal resolution of electroencephalogram (EEG) technology can record brain activity associated with micro-expressions and identify them objectively from a neurophysiological standpoint. Accordingly, this study introduces a novel method for recognizing micro-expressions using node efficiency features of brain networks derived from EEG signals. We designed a real-time Supervision and Emotional Expression Suppression (SEES) experimental paradigm to collect video and EEG data reflecting micro- and macro-expression states from 70 participants experiencing positive emotions. By constructing functional brain networks based on graph theory, we analyzed the network efficiencies at both macro- and micro-levels. The participants exhibited lower connection density, global efficiency, and nodal efficiency in the alpha, beta, and gamma networks during micro-expressions compared to macro-expressions. We then selected the optimal subset of nodal efficiency features using a random forest algorithm and applied them to various classifiers, including Support Vector Machine (SVM), Gradient-Boosted Decision Tree (GBDT), Logistic Regression (LR), Random Forest (RF), and eXtreme Gradient Boosting (XGBoost). These classifiers achieved promising accuracy in micro-expression recognition, with SVM exhibiting the highest accuracy of 92.6% when 15 channels were selected. This study provides a new neuroscientific indicator for recognizing micro-expressions based on EEG signals, thereby broadening the potential applications for micro-expression recognition.

Spermidine ameliorates the neuronal aging by improving the mitochondrial function in vitro.

Changes in mitochondrial structure and function are the initial factors of cell aging. Spermidine has an antiaging effect, but its effect on neuronal aging and mitochondrial mechanisms is unclear. In this study, mouse neuroblastoma (N2a) cells were treated with d­galactose (d­Gal) to establish cell aging to investigate the antiaging effect and mechanisms of spermidine. Changes in the cell cycle and ß-galactosidase activity were analyzed to evaluate the extent of cell aging. Stabilities of mitochondrial mRNA and mitochondrial membrane potential (MMP) were evaluated in the process of cell aging under different treatments. The mitochondrial function was also evaluated using the Seahorse Metabolic Analysis System combined with ATP production. The unfolded protein response (UPR) of the N2a cells was analyzed under different treatments. Results showed that spermidine pretreatment could delay the cell aging and could maintain the mitochondrial stability during d­Gal treatment. Spermidine increased the proportion of cells in the S phase and maintained the MMP. The oxygen utilization and ATP production in the N2a cells were reduced by d­Gal treatment but were partially rescued by the spermidine pretreatment. Spermidine ameliorated the N2a cell aging by promoting the autophagy and inhibiting the apoptosis except the UPR. These results showed that spermidine could ameliorate the N2a cell aging by maintaining the mitochondrial mRNA transcription, MMP and oxygen utilization during the d­Gal treatment.