From Neural Networks to Emotional Networks: A Systematic Review of EEG-Based Emotion Recognition in Cognitive Neuroscience and Real-World Applications

Brain Sciences, Год журнала: 2025, Номер 15(3), С. 220 - 220

Опубликована: Фев. 20, 2025

Background/Objectives: This systematic review presents how neural and emotional networks are integrated into EEG-based emotion recognition, bridging the gap between cognitive neuroscience practical applications. Methods: Following PRISMA, 64 studies were reviewed that outlined latest feature extraction classification developments using deep learning models such as CNNs RNNs. Results: Indeed, findings showed multimodal approaches practical, especially combinations involving EEG with physiological signals, thus improving accuracy of classification, even surpassing 90% in some studies. Key signal processing techniques used during this process include spectral features, connectivity analysis, frontal asymmetry detection, which helped enhance performance recognition. Despite these advances, challenges remain more significant real-time processing, where a trade-off computational efficiency limits implementation. High cost is prohibitive to use real-world applications, therefore indicating need for development application optimization techniques. Aside from this, obstacles inconsistency labeling emotions, variation experimental protocols, non-standardized datasets regarding generalizability recognition systems. Discussion: These developing adaptive, algorithms, integrating other inputs like facial expressions sensors, standardized protocols elicitation classification. Further, related ethical issues respect privacy, data security, machine model biases be much proclaimed responsibly apply research on emotions areas healthcare, human–computer interaction, marketing. Conclusions: provides critical insight suggestions further field toward robust, scalable, applications by consolidating current methodologies identifying their key limitations.

Язык: Английский

Spreading New Light on Attention Restoration Theory: An Environmental Posner Paradigm

Brain Sciences, Год журнала: 2025, Номер 15(6), С. 578 - 578

Опубликована: Май 27, 2025

Background/Objectives: Environmental psychology has long investigated how exposure to natural versus urban environments influences cognitive processes, particularly attention. According Attention Restoration Theory (ART), scenes promote involuntary attention and facilitate recovery from mental fatigue. In this study, we used a modified Posner cueing paradigm assess backgrounds affect both exogenous (involuntary) endogenous (voluntary) To capture behavioral neural responses, the study collected reaction times (RTs) as measure of task performance, alongside electrophysiological data (event-related potentials, ERPs: P1, N1, P2, N2, P3) explore underlying attentional processes. Methods: Participants completed visuospatial in which visual cues anticipated appearance target stimulus, while background images depicting either or remained visible throughout. was assessed under valid (cue correctly predicts location) invalid misleads conditions. Results: The overall findings align with existing literature: RTs were shorter trials compared ones. No main facilitation effect observed. However, participants showed slower backgrounds, may support ART by suggesting that restoration could lead responses certain scenarios. Electrophysiological reinforced these results, revealing an increased N2 amplitude condition. Conclusions: Despite some limitations, provides novel insights into human–nature interactions, offering fresh perspective on complex relationship between environment cognition.

Язык: Английский