Research

@article{nardi2026isolating,

title = {Isolating error-based and reward-based learning in a real-world task via gradual perturbations in embodied VR},

author = {Federico Nardi and Aaruni Arora and A Aldo Faisal and Shlomi Haar},

doi = {https://doi.org/10.1016/j.isci.2026.117523},

year  = {2026},

date = {2026-09-15},

urldate = {2026-01-01},

journal = {iScience},

volume = {29},

number = {10},

publisher = {Elsevier},

abstract = {Error-based and reward-based mechanisms act together in real-world motor learning. Laboratory tasks separate them by manipulating feedback, but we previously showed that in a real-world task the correction of a large error is rewarding in itself, and engages reward-based learning even without a reward signal. Here, we asked whether they separate when errors are kept small. We used embodied virtual reality of pool billiards, in which the visual scene is aligned with a physical table, and rotated the cue ball’s seen trajectory gradually while haptics and proprioception stayed unchanged. Thirty-two participants played two sessions, learning the same rotation with error-only feedback in one and reward-only feedback in the other. Their exploration after failed shots and their post-movement beta rebound over the motor cortex differed between sessions. Gradual perturbations can therefore isolate the two mechanisms in a real-world task, and open a way to target them in rehabilitation and skill training.

},

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pubstate = {published},

tppubtype = {article}

}

@article{cheng2026resting,

title = {Resting-State 40 Hz EEG Activity Before and After Single-Session Non-Flickering 40 Hz Light Stimulation in Cognitively Normal Older Adults: An Uncontrolled Pilot Study},

author = {Chia-Hsiung Cheng and Hsinjie Lu},

doi = {https://doi.org/10.3390/brainsci16090976},

year  = {2026},

date = {2026-09-15},

urldate = {2026-01-01},

journal = {Brain Sciences},

volume = {16},

number = {9},

pages = {976},

publisher = {MDPI},

abstract = {Background: Forty-hertz sensory stimulation has emerged as a potential approach for modulating neural activity relevant to Alzheimer’s disease. However, electrophysiological changes following non-flickering 40 Hz light stimulation in older adults remain unclear. This study investigated whether a single-session intervention of non-flickering 40 Hz light stimulation would be associated with increased resting-state 40 Hz oscillations in cognitively normal older adults. Methods: In this uncontrolled single-arm pilot study, 16 cognitively normal older adults underwent a 60 min session of non-flickering 40 Hz light stimulation. Resting-state EEG was recorded immediately before and after stimulation. Relative power within 38–42 Hz was analyzed across six predefined scalp regions and the whole-brain measure using one-tailed Wilcoxon signed-rank tests with Benjamini–Hochberg false discovery rate (FDR) correction. Exploratory real-time EEG recordings during stimulation were available in 10 participants. Results: After FDR correction, resting-state 38–42 Hz relative power was higher post-stimulation in the central (FDR = 0.045, effect size = 0.555) and right temporal (FDR = 0.014, effect size = 0.724) regions. In the absolute-power sensitivity analysis, only the right temporal increase remained significant after FDR correction (FDR = 0.042). Exploratory during-stimulation analysis showed a nominally increased 38–42 Hz signal-to-noise ratio in the right temporal region (p = 0.026). One participant reported very mild fatigue; no other adverse responses were reported. Conclusions: This pilot study suggests regional increases in resting-state 38–42 Hz activity after non-flickering 40 Hz light stimulation, with additional absolute-power support for the right temporal finding. These findings remain preliminary given the uncontrolled design and small sample.},

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}

@article{hsu2026hikikomori,

title = {Hikikomori symptoms, depressive symptoms, and frontal beta activity in young adult males with gaming disorder},

author = {Tien-Wei Hsu and Ching-Hung Lin and Takahiro A Kato and Masaru Tateno and Ju-Yu Yen and Chih-Hsing Hung and Chih-Hung Ko},

doi = {https://doi.org/10.1016/j.psychres.2026.117454},

year  = {2026},

date = {2026-09-07},

urldate = {2026-01-01},

journal = {Psychiatry Research},

pages = {117454},

publisher = {Elsevier},

abstract = {Gaming disorder (GD) is a clinically heterogeneous condition that frequently co-occurs with hikikomori symptoms, depressive symptoms, and reduced resilience. The interrelationships between psychological characteristics and resting-state electroencephalography (EEG) features were investigated. In this cross-sectional study, 59 males with GD and corresponding age-matched healthy controls were recruited. The diagnoses were made through face-to-face psychiatric interviews. The participants completed the Hikikomori Questionnaire-25 (HQ-25), Center for Epidemiologic Studies Depression Scale, and 14-Item Resilience Scale. Resting-state EEG (eyes closed) was recorded for 5 min. In the GD group, subgroup analyses were performed according to high (≧42-points) and low (<42-points) HQ-25 symptom levels. Group comparisons, hierarchical logistic regressions, and correlation analyses were performed. In the hierarchical logistic regression analysis, depressive and total hikikomori symptoms were independently associated with GD, whereas resilience was not. When HQ-25 was decomposed into subscales, only the physical isolation subscale was independently associated with GD. In the GD group, participants with high hikikomori symptoms were more depressed and had lower resilience than those with low hikikomori symptoms. No significant differences in resting EEG were observed between the GD and control groups. Within the GD group, the high-hikikomori subgroup showed nominally higher frontal beta activity at Fz, F3, and F4; however, these differences were attenuated and no longer statistically significant after adjustment for depressive symptoms. Frontal beta power was positively correlated with depressive symptoms and hikikomori severity, whereas F4 beta power was associated with clinical severity. These findings suggest that depressive symptoms and isolation-related social withdrawal are important clinical dimensions in GD, while frontal beta activity may reflect overlapping depressive and social withdrawal-related burden rather than a hikikomori-specific biomarker.

},

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pubstate = {published},

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@article{kim2026dynamics,

title = {The dynamics of beliefs in social decision-making: insights from intra-and inter-brain neural networks},

author = {Heegyu Kim and Gyewon Jeon and Sangwon Lee and Sung Chan Jun and Jae-Yoon Jung and Chang S Nam},

doi = {https://doi.org/10.1038/s41598-026-58455-5},

year  = {2026},

date = {2026-08-21},

urldate = {2026-01-01},

journal = {Scientific Reports},

publisher = {Nature Publishing Group UK London},

abstract = {Social beliefs are internalized expectations about others’ behaviors and intentions within social systems, shaping how individuals interpret, predict, and respond to interpersonal events. This study aims to examine how the dynamics of social beliefs influence neural activity and inter-brain synchrony within group interactions. To quantitatively assess relational changes, we implemented an iterated 3-player Prisoner’s Dilemma game paradigm, allowing for the observation of group-level behavioral patterns across repeated cooperation and defection scenarios. Participants were repeatedly exposed to cooperative and non-cooperative interactions, during which we observed neurophysiological responses associated with beliefs formation and change. Event-Related Potential analysis was used to assess individual cognitive responses to beliefs shifts, with P300 and N100 components reflecting sensitivity to social feedback. Additionally, intra-brain network analysis revealed changes centered around the parietal region, indicating altered social relationship representations at the individual level. At the group level, inter-brain synchrony significantly declined following beliefs changes, reflecting a disruption in shared intentionality and coordination. These findings suggest that violations of social expectations may induce cognitive instability and reduce neural synchrony in group decision-making contexts, offering new insights into the neural mechanisms underlying dynamic social cognition.



},

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@article{leuthardt2026home,

title = {At-Home BCI Rehabilitation Therapy for Chronic Upper Extremity Deficit After Stroke (BCI-REHAB): A Randomized Trial},

author = {Eric C Leuthardt and Seth J Wilk and Lauren Souders and Kelly B Carr and Robert Coker and Gregory E Wilding and Dorothee Zuleger and Benjamin T Acland and Alexandre R Carter},

doi = {https://doi.org/10.1161/SVIN.126.002345},

year  = {2026},

date = {2026-08-13},

urldate = {2026-01-01},

journal = {Stroke: Vascular and Interventional Neurology},

pages = {10–1161},

publisher = {Lippincott Williams & Wilkins Hagerstown, MD},

abstract = {BACKGROUND:

At-home stroke rehabilitation methods have strong potential to supplement limited clinical resources, but realizing that potential for survivors in the chronic phase of recovery requires developing and validating more effective options than the home exercise programs typically used today. BCI-REHAB (At-Home BCI Rehabilitation Therapy for Chronic Upper Extremity Deficit After Stroke) compared an at-home brain-computer interface (BCI) therapy system (IpsiHand System) versus an at-home exercise program for improving upper extremity function in patients with chronic hemiparetic stroke.

METHODS:

Participants aged 18 to 85 years with a history of stroke ≥6 months before enrollment and right or left upper extremity paresis or plegia were screened and randomly assigned to either an at-home exercise program or to a BCI electroencephalogram system coupled to a range-of-motion assist handpiece. Participants completed 12 weeks of at-home therapy (5 sessions per week). The primary outcome was the change in the Upper Extremity Fugl-Meyer Assessment from baseline to 12 weeks.

RESULTS:

Overall, 109 participants were assessed for eligibility; 85 met the inclusion criteria and were randomized (43 intervention, 42 control). Of the 42 control participants, n=17 declined to participate further due to dissatisfaction with study arm assignment. A total of 62 participants were analyzed for the primary outcome (37 intervention, 25 control). The primary outcome (mean change) was significantly higher in the BCI group (6.0 [95% CI, 3.9–8.1]; P<0.0001) versus the control group (1.5 [95% CI, −0.1 to 3.1]; P=0.07), with an estimated treatment difference of 4.5 ([95% CI, 1.9–7.1]; P=0.0007). Participants who received the BCI intervention showed an estimated response rate of 55.5% (95% CI, 33.7%–77.2%), compared with 9.6% (95% CI, −2.9% to 22.1%) in the control group. This corresponds to an absolute increase in response of 45.8% ([95% CI, 20.9%–70.8%]; P=0.0003), yielding a number needed to treat of 2.2.

CONCLUSIONS:

At-home BCI therapy provides clinically meaningful improvement in upper extremity function for chronic stroke survivors compared with standard at-home exercise programs.},

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pubstate = {published},

tppubtype = {article}

}

@article{li2026stmae,

title = {STMAE-Few: A Spatial-Temporal Masked Autoencoder for Few-channel EEG-based Emotion Recognition},

author = {Ming Li and Junjun Pan and Dai Ju and Wanqing Wu and Aimin Hao and Yong-Jin Liu and Yang Gao},

doi = {https://doi.org/10.1109/TAFFC.2026.3719828},

year  = {2026},

date = {2026-08-04},

urldate = {2026-01-01},

journal = {IEEE Transactions on Affective Computing},

publisher = {IEEE},

abstract = {Conventional EEG-based supervised emotion recognition typically requires large manually annotated multi-channel EEG data. The susceptibility of EEG to noise can lead to corruption of certain channels, making it challenging for emotion recognition from few available channels (denoted as few-channel in this paper). Masked Autoencoder (MAE) can learn highly generalizable representations by reconstructing the original signals from the visible subset of channels. However, most studies do not consider temporal masking, and random spatial masking overlooks the brain's inherent structure, impeding reconstruction efficacy. In this paper, we propose a novel pre-training framework, STMAE-Few, based on a spatial-temporal masked autoencoder, which introduces spatial-temporal masking strategies at both the EEG channel and frame levels to extract robust feature representations and enhance the performance of few-channel emotion recognition in real-world scenarios. Inspired by neuroscience, our approach integrates region and region-selection spatial masking strategies and introduces true position encoding during pre-training to capture richer spatial information. Extensive experimental results on SEED, SEED-IV, and SEED-V datasets demonstrate that our pre-training framework can effectively capture the temporal dynamics and spatial correlations within and between different brain regions.

},

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pubstate = {published},

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@article{kim2026reproducible,

title = {A reproducible EEG hyperscanning dataset for triadic social decision-making during an iterated 3-player Prisoner’s Dilemma},

author = {H Kim and SC Jun and CS Nam},

doi = {https://doi.org/10.1016/j.dib.2026.113064},

year  = {2026},

date = {2026-07-10},

urldate = {2026-01-01},

journal = {Data in Brief},

pages = {113064},

publisher = {Elsevier},

abstract = {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.},

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}