ArticleFrontiers in human neuroscience2019
Challenge for Affective Brain-Computer Interfaces: Non-stationary Spatio-spectral EEG Oscillations of Emotional Responses.
Article in Frontiers in human neuroscience, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Bridging Neural Topology and Affective Computing: Graph Attention for EEG Emotion Recognition.Journal of medical systems · 2026Review
- Closed-loop EEG-based neurofeedback and brain-computer interface interventions for mental health: a review.Frontiers in neuroscience · 2026Review
- Tackling the possibility of extracting a brain digital fingerprint based on personal hobbies predilection.Frontiers in neuroscience · 2025Article
- Brain connectivity dynamics during listening to music and potential impact on task performance.Cognitive neurodynamics · 2024Article
- Impact of negative links on the structural balance of brain functional network during emotion processing.Scientific reports · 2023Article
- Comparison of event-related modulation index and traditional methods for evaluating phase-amplitude coupling using simulated brain signals.Biological cybernetics · 2022Article
- Multi-source joint domain adaptation for cross-subject and cross-session emotion recognition from electroencephalography.Frontiers in human neuroscience · 2022Article
- Not All Electrode Channels Are Needed: Knowledge Transfer From Only Stimulated Brain Regions for EEG Emotion Recognition.Frontiers in neuroscience · 2022Article
- Brain-Computer Interface: Advancement and Challenges.Sensors (Basel, Switzerland) · 2021Review
- Objective assessment of impulse control disorder in patients with Parkinson's disease using a low-cost LEGO-like EEG headset: a feasibility study.Journal of neuroengineering and rehabilitation · 2021Article
- Recurrent neural network-based acute concussion classifier using raw resting state EEG data.Scientific reports · 2021Article
- EEGs Vary Less Between Lab and Home Locations Than They Do Between People.Frontiers in computational neuroscience · 2021Article
- A Review on Signal Processing Approaches to Reduce Calibration Time in EEG-Based Brain-Computer Interface.Frontiers in neuroscience · 2021Review
- Independent Components of EEG Activity Correlating with Emotional State.Brain sciences · 2020Article
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2 authors.
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Abstract
Electroencephalogram (EEG)-based affective brain-computer interfaces (aBCIs) have been attracting ever-growing interest and research resources. Whereas most previous neuroscience studies have focused on single-day/-session recording and sensor-level analysis, less effort has been invested in assessing the fundamental nature of non-stationary EEG oscillations underlying emotional responses across days and individuals. This work thus aimed to use a data-driven blind source separation method, i.e., independent component analysis (ICA), to derive emotion-relevant spatio-spectral EEG source oscillations and assess the extent of non-stationarity. To this end, this work conducted an 8-day music-listening experiment (i.e., roughly interspaced over 2 months) and recorded whole-scalp 30-ch EEG data from 10 subjects. Given the large size of the data (i.e., from 80 sessions), results indicated that EEG non-stationarity was clearly revealed in the numbers and locations of brain sources of interest as well as their spectral modulation to the emotional responses. Less than half of subjects (two to four) showed the same relatively day-stationary (source reproducibility >6 days) spatio-spectral tendency towards one of the binary valence and arousal states. This work substantially advances the previous work by exploiting intra- and inter-individual EEG variability in an ecological multiday scenario. Such EEG non-stationarity may inevitably present a great challenge for the development of an accurate, robust, and generalized emotion-classification model.
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