2026 |
Kim, H; Jun, SC; Nam, CS A reproducible EEG hyperscanning dataset for triadic social decision-making during an iterated 3-player Prisoner’s Dilemma Journal Article In: Data in Brief, pp. 113064, 2026. Abstract | Links | Tags: DSI-24, Hyperscanning @article{kim2026reproducible,This data article describes an open EEG hyperscanning dataset acquired during an iterated 3-player Prisoner’s Dilemma (PD) task, designed to support reproducible research on triadic social decision-making. EEG was recorded simultaneously from three participants per group (11 groups; 33 subjects) using synchronized acquisition, with decision-locked and feedback-locked epochs provided for 40 task trials per subject and three 60-s resting-state runs per group. The released MATLAB files contain stacked 57-channel EEG arrays (19 channels × 3 subjects) sampled at 300 Hz, with explicit epoch definitions for decision (−1000 to 4000 ms) and feedback (−1000 to 2000 ms) periods, as well as trial-wise behavioral choice labels (1=cooperate, 2=defect) enabling reconstruction of dyad- and triad-level outcomes. Questionnaire metadata (personal information and pre/mid/post state measures) Yare also provided as supplementary spreadsheets. To facilitate reuse and benchmarking, we release Python code that reproduces the preprocessing pipeline (average reference, FIR filtering, ICA + ICLabel for task EEG), ERP summaries, and inter-brain synchrony measures (PLV and coherence) with window-matched resting baselines and cluster-permutation statistics. The dataset is intended for method development and benchmarking in ERP analysis, inter-brain synchrony estimation, and modeling of dynamic group interaction states in triadic games. |
Fincham, Jon M; Betts, Shawn; Anderson, John R Combining EEG signals from the 2 members of a team to improve event identification Journal Article In: NeuroImage: Reports, vol. 6, no. 2, pp. 100356, 2026. Abstract | Links | Tags: Comparisons, DSI-24, Hyperscanning @article{fincham2026combining,We examined the potential of combining EEG signals from multiple individuals to identify critical events in a team task. In this study two subjects played a video game in which they had complementary roles, one player serving as a Bait to distract 5 enemy fortress and the other serving as a Shooter to destroy the fortress. Twenty-one pairs of subjects were analyzed. Critical events, destruction of the fortress and deaths of each player, evoked distinguishable P300-like responses from both players. Fortress kills could be best identified by combining the two EEG signals, while deaths could be best identified by focusing on the response of the player who died. Hidden semi-Markov models (HSMMs) achieved good identification of the events by combining information about the temporal distribution of these critical events with the conditional probability of the EEG activity. These findings indicate that we can track and improve by adaptively merging or selecting the signals from different team members. |
2025 |
Kim, Heegyu; Jun, Sung Chan; Nam, Chang S Neural Dynamics of Group Interaction in the Iterate Multi-player Prisoner’s Dilemma Game: Multilayer Network Approach Proceedings Article In: International Conference on Human-Computer Interaction, pp. 18–31, Springer 2025. Abstract | Links | Tags: DSI-24, Hyperscanning @inproceedings{kim2025neural,Understanding social interaction from various human behaviors is a complex task. Hyperscanning research tackles this challenge by delving into behavioral mechanisms through a neuroscience lens. While traditional studies focus on inter-brain synchrony in paired functional brain networks, they often lack methods for measuring interactions at the group level. In this study, we propose a multilayer network approach to estimate group brain synchrony and gain deeper insights into the brain’s intricate organization. By utilizing the Prisoner’s Dilemma Game, our goal is to find group interaction processes through distinct behaviors such as cooperation and defection. Thus, the inter-brain synchrony along with differences in network connectivity and structural properties within the functional group network were statistically analyzed between cooperation and defection. |
2024 |
Georgiadis, Kostas; Nikolopoulos, Spiros; Kalaganis, Fotis P; Kompatsiaris, Ioannis; Laskaris, Nikos A Assessing video advertising engagement via Nonlinear Intersubject Correlation Analysis of EEG and eye tracking dynamics Miscellaneous 2024. Abstract | Links | Tags: DSI-24, Eye-Tracking, Hyperscanning, Neuromarketing @misc{georgiadisassessing,A novel framework for assessing engagement through video commercials is presented. Deviating from the current approaches, here we cast the problem as nonlinear intersubject correlation analysis and pursue the collective (i.e. across-participants) treatment of EEG signals and eye-tracking measurements. Regarding brain dynamics, two well-known descriptors, namely spatial covariance and phase locking value, undergo transcription to their ‘hyperscanning’ equivalents. Regarding eye-related measurements, individual paths and pupillometric measurements are summarized at population level. Using data from a recording paradigm, where each participant independently watched a cartoon video interrupted by a commercial clip, we show that our approach can provide signatures of engagement to the content being delivered and reconstruct the level of appreciation of the potential consumers. |
2026 |
Kim, H; Jun, SC; Nam, CS A reproducible EEG hyperscanning dataset for triadic social decision-making during an iterated 3-player Prisoner’s Dilemma Journal Article In: Data in Brief, pp. 113064, 2026. @article{kim2026reproducible,This data article describes an open EEG hyperscanning dataset acquired during an iterated 3-player Prisoner’s Dilemma (PD) task, designed to support reproducible research on triadic social decision-making. EEG was recorded simultaneously from three participants per group (11 groups; 33 subjects) using synchronized acquisition, with decision-locked and feedback-locked epochs provided for 40 task trials per subject and three 60-s resting-state runs per group. The released MATLAB files contain stacked 57-channel EEG arrays (19 channels × 3 subjects) sampled at 300 Hz, with explicit epoch definitions for decision (−1000 to 4000 ms) and feedback (−1000 to 2000 ms) periods, as well as trial-wise behavioral choice labels (1=cooperate, 2=defect) enabling reconstruction of dyad- and triad-level outcomes. Questionnaire metadata (personal information and pre/mid/post state measures) Yare also provided as supplementary spreadsheets. To facilitate reuse and benchmarking, we release Python code that reproduces the preprocessing pipeline (average reference, FIR filtering, ICA + ICLabel for task EEG), ERP summaries, and inter-brain synchrony measures (PLV and coherence) with window-matched resting baselines and cluster-permutation statistics. The dataset is intended for method development and benchmarking in ERP analysis, inter-brain synchrony estimation, and modeling of dynamic group interaction states in triadic games. |
Fincham, Jon M; Betts, Shawn; Anderson, John R Combining EEG signals from the 2 members of a team to improve event identification Journal Article In: NeuroImage: Reports, vol. 6, no. 2, pp. 100356, 2026. @article{fincham2026combining,We examined the potential of combining EEG signals from multiple individuals to identify critical events in a team task. In this study two subjects played a video game in which they had complementary roles, one player serving as a Bait to distract 5 enemy fortress and the other serving as a Shooter to destroy the fortress. Twenty-one pairs of subjects were analyzed. Critical events, destruction of the fortress and deaths of each player, evoked distinguishable P300-like responses from both players. Fortress kills could be best identified by combining the two EEG signals, while deaths could be best identified by focusing on the response of the player who died. Hidden semi-Markov models (HSMMs) achieved good identification of the events by combining information about the temporal distribution of these critical events with the conditional probability of the EEG activity. These findings indicate that we can track and improve by adaptively merging or selecting the signals from different team members. |
2025 |
Kim, Heegyu; Jun, Sung Chan; Nam, Chang S Neural Dynamics of Group Interaction in the Iterate Multi-player Prisoner’s Dilemma Game: Multilayer Network Approach Proceedings Article In: International Conference on Human-Computer Interaction, pp. 18–31, Springer 2025. @inproceedings{kim2025neural,Understanding social interaction from various human behaviors is a complex task. Hyperscanning research tackles this challenge by delving into behavioral mechanisms through a neuroscience lens. While traditional studies focus on inter-brain synchrony in paired functional brain networks, they often lack methods for measuring interactions at the group level. In this study, we propose a multilayer network approach to estimate group brain synchrony and gain deeper insights into the brain’s intricate organization. By utilizing the Prisoner’s Dilemma Game, our goal is to find group interaction processes through distinct behaviors such as cooperation and defection. Thus, the inter-brain synchrony along with differences in network connectivity and structural properties within the functional group network were statistically analyzed between cooperation and defection. |
2024 |
Georgiadis, Kostas; Nikolopoulos, Spiros; Kalaganis, Fotis P; Kompatsiaris, Ioannis; Laskaris, Nikos A Assessing video advertising engagement via Nonlinear Intersubject Correlation Analysis of EEG and eye tracking dynamics Miscellaneous 2024. @misc{georgiadisassessing,A novel framework for assessing engagement through video commercials is presented. Deviating from the current approaches, here we cast the problem as nonlinear intersubject correlation analysis and pursue the collective (i.e. across-participants) treatment of EEG signals and eye-tracking measurements. Regarding brain dynamics, two well-known descriptors, namely spatial covariance and phase locking value, undergo transcription to their ‘hyperscanning’ equivalents. Regarding eye-related measurements, individual paths and pupillometric measurements are summarized at population level. Using data from a recording paradigm, where each participant independently watched a cartoon video interrupted by a commercial clip, we show that our approach can provide signatures of engagement to the content being delivered and reconstruct the level of appreciation of the potential consumers. |
