Objective:To investigate the moderating role of emotional expressivity in the relationship between test anxiety and working memory capacity (WMC).Methods:Totally 332 college students were selected.The Test Anxiety Inventory (TAI),Emotional Expressivity Inventory (EEI) and Arithmetic Operation-Word Memory Span Task (OSPAN) were used to measure the severity of test anxiety,working memory capacity,and degree of emotional expressivity,respectively.Results:TAI scores were negatively correlated with WMC scores (r =-0.36,P ＜0.01).Emotional expressivity had a moderating effect between scores of test anxiety and WMC (β =0.19,P ＜0.01).Test anxiety score negatively predicted WMC score in students with low emotional expressivity (β =-0.74,P ＜ 0.01),whereas it couldn't predict WMC in those with high emotional expressivity (β =-0.07,P ＞0.05).Conclusion:It suggests that higher emotional expressivity could buffer the negative effect of test anxiety on working memory capacity.

As an important component of the event related potential (ERP), late positive potential (LPP) is an ideal component for studying emotion regulation. This study was focused on processing and analysing the LPP component of the emotional cognitive reappraisal electroencephalogram (EEG) signal. Firstly, we used independent component analysis (ICA) algorithm to remove electrooculogram, electromyogram and some other artifacts based on 16 subjects' EEG data by using EGI 64-channal EEG acquisition system. Secondly, we processed feature extraction of the EEG signal at Pz electrode by using one versus the rest common spatial patterns (OVR-CSP) algorithm. Finally, the extracted LPP component was analysed both in time domain and spatial domain. The results indicated that (1) From the perspective of amplitude comparison, the LPP amplitude, which was induced by cognitive reappraisal, was much higher than the amplitude under the condition of watching neural stimuli, but lower than the amplitude under condition of watching negative stimuli; (2) from the perspective of time process, the difference between cognitive reappraisal and watching after processing with OVR-CSP algorithm was in the process of range between 0.3 s and 1.5 s; but the difference between cognitive reappraisal and watching after processing with averaging method was during the process between 0.3 s and 1.25 s. The results suggested that OVR-CSP algorithm could not only accurately extract the LPP component with fewer trials compared with averaging method so that it provided a better method for the follow-up study of cognitive reappraisal strategy, but also provide neurophysiological basis for cognitive reappraisal in emotional regulation.
Algorithms ; Artifacts ; Cognition ; Electroencephalography ; Electromyography ; Emotions ; Evoked Potentials ; Humans

The robust extracting of evoked potential (EP) has become a vexed question in the process of electroencephalogram owing to the faint signal-to-noise ratio of EP. This paper presents the single trial of EP in time, transform and space field. Several methods such as adaptive filter, wavelet transform, principal component analysis (PCA) and independent component analysis (ICA) have been applied to the process of EP.
Algorithms ; Brain ; physiology ; Electroencephalography ; methods ; Evoked Potentials ; Humans ; Principal Component Analysis ; Signal Processing, Computer-Assisted