This study investigated the impact of problematic mobile phone use(PMPU)on emotion recognition.The PMPU levels of 150 participants were measured using the standardized SAS-SV scale.Based on the SAS-SV cutoff scores,pa...This study investigated the impact of problematic mobile phone use(PMPU)on emotion recognition.The PMPU levels of 150 participants were measured using the standardized SAS-SV scale.Based on the SAS-SV cutoff scores,participants were divided into PMPU and Control groups.These participants completed two emotion recognition experiments involving facial emotion stimuli that had been manipulated to varying emotional intensities using Morph software.Experiment 1(n=75)assessed differences in facial emotion detection accuracy.Experiment 2(n=75),based on signal detection theory,examined differences in hit and false alarm rates across emotional expressions.The results showed that PMPU users demonstrated higher recognition accuracy rates for disgust faces but lower accuracy for happy faces.This indicates a tendency among PMPU users to prioritize specific negative emotions and may have impaired perception of positive emotions.Practically,incorporating diverse emotional stimuli into PMPU intervention may help alleviate the negative emotional focus bias associated with excessive mobile devices use.展开更多
Although distinctive neural and physiological states are suggested to underlie the six basic emotions,basic emotions are often indistinguishable from functional magnetic resonance imaging(f MRI)voxelwise activation(VA...Although distinctive neural and physiological states are suggested to underlie the six basic emotions,basic emotions are often indistinguishable from functional magnetic resonance imaging(f MRI)voxelwise activation(VA)patterns.Here,we hypothesize that functional connectivity(FC)patterns across brain regions may contain emotion-representation information beyond VA patterns.We collected whole-brain f MRI data while human participants viewed pictures of faces expressing one of the six basic emotions(i.e.,anger,disgust,fear,happiness,sadness,and surprise)or showing neutral expressions.We obtained FC patterns for each emotion across brain regions over the whole brain and applied multivariate pattern decoding to decode emotions in the FC pattern representation space.Our results showed that the whole-brain FC patterns successfully classified not only the six basic emotions from neutral expressions but also each basic emotion from other emotions.An emotion-representation network for each basic emotion that spanned beyond the classical brain regions for emotion processing was identified.Finally,we demonstrated that within the same brain regions,FC-based decoding consistently performed better than VA-based decoding.Taken together,our findings revealed that FC patterns contained emotional information and advocated for paying further attention to the contribution of FCs to emotion processing.展开更多
基金supported by the National Social Science Fund of China(Grant Number:20BSH134).
文摘This study investigated the impact of problematic mobile phone use(PMPU)on emotion recognition.The PMPU levels of 150 participants were measured using the standardized SAS-SV scale.Based on the SAS-SV cutoff scores,participants were divided into PMPU and Control groups.These participants completed two emotion recognition experiments involving facial emotion stimuli that had been manipulated to varying emotional intensities using Morph software.Experiment 1(n=75)assessed differences in facial emotion detection accuracy.Experiment 2(n=75),based on signal detection theory,examined differences in hit and false alarm rates across emotional expressions.The results showed that PMPU users demonstrated higher recognition accuracy rates for disgust faces but lower accuracy for happy faces.This indicates a tendency among PMPU users to prioritize specific negative emotions and may have impaired perception of positive emotions.Practically,incorporating diverse emotional stimuli into PMPU intervention may help alleviate the negative emotional focus bias associated with excessive mobile devices use.
基金supported by the National Natural Science Foundation of China(31930053)the National Science and Technology Innovation 2030 Major Program(2022ZD0204802)+2 种基金Beijing Academy of Artificial Intelligence(BAAI)Project funded by China Postdoctoral Science Foundation(2022M710210)the Fundamental Research Funds for the Central Universities(2021FZZX001-06)。
文摘Although distinctive neural and physiological states are suggested to underlie the six basic emotions,basic emotions are often indistinguishable from functional magnetic resonance imaging(f MRI)voxelwise activation(VA)patterns.Here,we hypothesize that functional connectivity(FC)patterns across brain regions may contain emotion-representation information beyond VA patterns.We collected whole-brain f MRI data while human participants viewed pictures of faces expressing one of the six basic emotions(i.e.,anger,disgust,fear,happiness,sadness,and surprise)or showing neutral expressions.We obtained FC patterns for each emotion across brain regions over the whole brain and applied multivariate pattern decoding to decode emotions in the FC pattern representation space.Our results showed that the whole-brain FC patterns successfully classified not only the six basic emotions from neutral expressions but also each basic emotion from other emotions.An emotion-representation network for each basic emotion that spanned beyond the classical brain regions for emotion processing was identified.Finally,we demonstrated that within the same brain regions,FC-based decoding consistently performed better than VA-based decoding.Taken together,our findings revealed that FC patterns contained emotional information and advocated for paying further attention to the contribution of FCs to emotion processing.
