Extremely negative emotion interferes with cognition: Evidence from ERPs and time-varying brain network

被引:12
作者
Yang, Kai [1 ]
Zeng, Ying [1 ]
Tong, Li [1 ]
Hu, Yidong [1 ]
Zhang, Rongkai [1 ]
Li, Zhongrui [1 ]
Yan, Bin [1 ]
机构
[1] PLA Strategy Support Force Informat Engn Univ, Zhengzhou 450001, Peoples R China
基金
中国国家自然科学基金;
关键词
Emotion; Cognition; Stroop; ERP; Time-varying Brain Networks; INHIBITION; DEPRESSION; COMPONENT; MODULATION; ATTENTION; CONFLICT; WORDS; N400; BIAS;
D O I
10.1016/j.jneumeth.2023.109922
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
In recent years, the relationship between emotion and cognition was a hot topic. However, it remains unclear which specific emotions can significantly interfere with cognition and how they do so. In this study, we designed a novel Affective Stroop experiment paradigm to investigate these issues. The extremely negative (EN), moderately negative (MN), moderately positive (MP), extremely positive (EP) and neutral pictures were displayed before Stroop tasks. The behavioral results revealed that EN emotion significantly interfered with cognitive performance compared to other types of emotions, with a significant increase in reaction time under the EN emotion condition (P < 0.05). Furthermore, the dynamic brain mechanisms were analyzed from both Event-Related Potential (ERP) and time-varying brain network perspectives. Results showed that EN emotion evoked larger N2, P3, and LPP amplitudes in the frontal, parietal, and occipital brain regions. In contrast, the Stroop task under EN condition led to smaller N2, P3, and LPP amplitudes compared to neutral condition. This indicates that EN emotion was prioritized and consumed more cognitive resources relative to neutral emotion. During the P3 and LPP stages, we observed enhanced bottom-up connections between the parietal and frontal regions while the processing of EN emotion. Additionally, there were stronger top-down cognitive control connections from the frontal to the occipital regions while processing the Stroop task under EN condition. These findings consistently suggest that EN emotion interferes with cognition by consuming more cognitive resources, and the brain needs to enhance cognitive control to support Stroop task execution.
引用
收藏
页数:10
相关论文
共 68 条
[51]   Making sense of brain network data [J].
Sporns, Olaf .
NATURE METHODS, 2013, 10 (06) :491-493
[52]   The effects of acute stress on attentional networks and working memory in females [J].
Stone, Caleb ;
Ney, Luke ;
Felmingham, Kim ;
Nichols, David ;
Matthews, Allison .
PHYSIOLOGY & BEHAVIOR, 2021, 242
[53]   Increasing Cognitive Load Reduces Interference from Masked Appetitive and Aversive but Not Neutral Stimuli [J].
Uher, Rudolf ;
Brooks, Samantha J. ;
Bartholdy, Savani ;
Tchanturia, Kate ;
Campbell, Iain C. .
PLOS ONE, 2014, 9 (04)
[54]  
Urushadze M, 2017, ALLIED ACAD, V1, P20
[55]   Positive emotion broadens attention focus through decreased position-specific spatial encoding in early visual cortex: Evidence from ERPs [J].
Vanlessen, Naomi ;
Rossi, Valentina ;
De Raedt, Rudi ;
Pourtois, Gilles .
COGNITIVE AFFECTIVE & BEHAVIORAL NEUROSCIENCE, 2013, 13 (01) :60-79
[56]   Effects of attention and emotion on face processing in the human brain: An event-related fMRI study [J].
Vuilleumier, P ;
Armony, JL ;
Driver, J ;
Dolan, RJ .
NEURON, 2001, 30 (03) :829-841
[57]   The Effects of Low and High Levels of Sadness on Scope of Attention: An ERP Study [J].
Wang, Hailu ;
Chen, Ying ;
Zhang, Qin .
FRONTIERS IN PSYCHOLOGY, 2018, 9
[58]   Cognitive reappraisal and acceptance: An experimental comparison of two emotion regulation strategies [J].
Wolgast, Martin ;
Lundh, Lars-Gunnar ;
Viborg, Gardar .
BEHAVIOUR RESEARCH AND THERAPY, 2011, 49 (12) :858-866
[59]   Time-varying whole-brain functional network connectivity coupled to task engagement [J].
Xie, Hua ;
Gonzalez-Castillo, Javier ;
Handwerker, Daniel A. ;
Bandettini, Peter A. ;
Calhoun, Vince D. ;
Chen, Gang ;
Damaraju, Eswar ;
Liu, Xiangyu ;
Mitra, Sunanda .
NETWORK NEUROSCIENCE, 2018, 3 (01) :49-66
[60]   High Gamma Band EEG Closely Related to Emotion: Evidence From Functional Network [J].
Yang, Kai ;
Tong, Li ;
Shu, Jun ;
Zhuang, Ning ;
Yan, Bin ;
Zeng, Ying .
FRONTIERS IN HUMAN NEUROSCIENCE, 2020, 14