@article{peters2025rsvp,

title = {RSVP Keyboard with Inquiry Preview: mixed performance and user experience with an adaptive, multimodal typing interface combining EEG and switch input},

author = {Betts Peters and Basak Celik and Dylan Gaines and Deirdre Galvin-McLaughlin and Tales Imbiriba and Michelle Kinsella and Daniel Klee and Matthew Lawhead and Tab Memmott and Niklas Smedemark-Margulies and others},

doi = {10.1088/1741-2552/ada8e0},

year  = {2025},

date = {2025-01-10},

urldate = {2025-01-01},

journal = {Journal of Neural Engineering},

abstract = {Objective. The RSVP Keyboard is a non-implantable, event-related potential-based brain-computer interface (BCI) system designed to support communication access for people with severe speech and physical impairments. Here we introduce Inquiry Preview, a new RSVP Keyboard interface incorporating switch input for users with some voluntary motor function, and describe its effects on typing performance and other outcomes. Approach. Four individuals with disabilities participated in the collaborative design of possible switch input applications for the RSVP Keyboard, leading to the development of Inquiry Preview and a method of fusing switch input with language model and electroencephalography (EEG) evidence for typing. Twenty-four participants without disabilities and one potential end user with incomplete locked-in syndrome took part in two experiments investigating the effects of Inquiry Preview and two modes of switch input on typing accuracy and speed during a copy-spelling task. Main results. For participants without disabilities, Inquiry Preview and switch input tended to worsen typing performance compared to the standard RSVP Keyboard condition, with more consistent effects across participants for speed than for accuracy. However, there was considerable variability, with some participants demonstrating improved typing performance and better user experience with Inquiry Preview and switch input. Typing performance for the potential end user was comparable to that of participants without disabilities. He typed most quickly and accurately with Inquiry Preview and switch input and gave favorable user experience ratings to those conditions, but preferred standard RSVP Keyboard. Significance. Inquiry Preview is a novel multimodal interface for the RSVP Keyboard BCI, incorporating switch input as an additional control signal. Typing performance and user experience and preference varied widely across participants, reinforcing the need for flexible, customizable BCI systems that can adapt to individual users. ClinicalTrials.gov Identifier: NCT04468919.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{al2024brain,

title = {Brain Functional Connectivity During Stroop Task and CSF Amyloid/tau in Cognitively Healthy Individuals},

author = {Abdulhakim Al-Ezzi and Natalie Astraea and J Yu and Xiaomeng Wu and Alfred N Fonteh and Yafa Minazad and Robert A Kloner and Xianghong Arakaki},

doi = {https://doi.org/10.1002/alz.090859},

year  = {2025},

date = {2025-01-09},

urldate = {2024-01-09},

journal = {Alzheimer's & Dementia},

volume = {20},

pages = {e090859},

publisher = {Wiley Online Library},

abstract = {Background

At the pre-clinical stages of Alzheimer’s disease (AD) development, the accumulation of amyloid-β (Aβ) and tau induces neural toxicity, synaptic dysfunction, and excitation/inhibition instability of neural network activity, leading to cognitive decline. However, the effects of Aβ/tau accumulation on electroencephalography (EEG) functional connectivity (FC) in cognitively healthy (CH) individuals during a cognitive challenge have not been elucidated. Therefore, the main objective of this work is to evaluate the association between Aβ/tau level and brain FC during a cognitive challenge in CH individuals.



Method

Established EEG data was recorded using a 21-EEG sensor headset (Wearable Sensing, DSI-24) during a cognitive challenge (Stroop interference test). Amyloid-β and total-tau proteins were measured from cerebrospinal fluid (CSF) using electrochemiluminescence. We assessed FC at sensor level using Partial Directed Coherence (PDC) from EEG data of CH participants including 22 normal CSF Aβ/tau ratio (CH-NAT) and 24 pathological CSF Aβ/tau (CH-PAT). For each trial type (congruent or incongruent) in the Stroop task and each of 19 sensors, linear regression was used to estimate the difference in mean FC between CH-NAT and CH-PAT, while controlling for age, gender, and years of education. The Benjamini–Hochberg procedure was used to control the false discovery rate below q = .1.



Result

Compared with CH-NATs, CH-PATs exhibit higher causal connectivity at specific sensors which each had an estimated local effect size index Cohen’s f2 >0.15, and putatively represent brain regions including medial prefrontal cortex (Fz, Fp1, and F8), central cortex (Cz and C4), and posterior cingulate cortex (Pz). For each of the same sensors, the estimated difference between CH-NAT and CH-PAT had an adjusted P value below .1.



Conclusion

These findings suggest a potential association between the CSF Aβ42/tau pathology and differences between individuals in brain connectivity during a cognitive challenge. These differences may involve compensatory mechanisms as the brain adapts to the amyloid/tau pathology. These results provide potential insights into the neurobiological implications of varying CSF amyloid/tau on brain networks. The areas with estimated medium-to-large effect sizes are favorable to doing a study with a lower significance level to confirm the findings.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{tanveer18multimodal,

title = {Multimodal Consumer Choice Prediction Using EEG Signals and Eye Tracking},

author = {Aimen Tanveer and Syed Muhammad Usman and Shehzad Khalid and Ali Shariq Imran and Muhammad Zubair},

doi = {https://doi.org/10.3389/fncom.2024.1516440},

year  = {2025},

date = {2025-01-07},

journal = {Frontiers in Computational Neuroscience},

volume = {18},

pages = {1516440},

publisher = {Frontiers},

abstract = {Marketing plays a vital role in the success of a business, driving customer engagement, brand recognition, and revenue growth. Neuromarketing adds depth to this by employing insights into consumer behavior through brain activity and emotional responses to create more effective marketing strategies. Electroencephalogram (EEG) has typically been utilized by researchers for neuromarketing, whereas Eye Tracking (ET) has remained unexplored. To address this gap, we propose a novel multimodal approach to predict consumer choices by integrating EEG and ET data. Noise from EEG signals is mitigated using a bandpass filter, Artifact Subspace Reconstruction (ASR), and Fast Orthogonal Regression for Classification and Estimation (FORCE). Class imbalance is handled by employing the Synthetic Minority Over-sampling Technique (SMOTE). Handcrafted features, including statistical and wavelet features, and automated features from Convolutional Neural Network and Long Short-Term Memory (CNN-LSTM), have been extracted and concatenated to generate a feature space representation. For ET data, preprocessing involved interpolation, gaze plots, and SMOTE, followed by feature extraction using LeNet-5 and handcrafted features like fixations and saccades. Multimodal feature space representation was generated by performing feature-level fusion for EEG and ET, which was later fed into a meta-learner-based ensemble classifier with three base classifiers, including Random Forest, Extended Gradient Boosting, and Gradient Boosting, and Random Forest as the meta-classifier, to perform classification between buy vs. not buy. The performance of the proposed approach is evaluated using a variety of performance metrics, including accuracy, precision, recall, and F1 score. Our model demonstrated superior performance compared to competitors by achieving 84.01% accuracy in predicting consumer choices and 83% precision in identifying positive consumer preferences.



},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{godfrey2024investigation,

title = {An investigation of acute Physiological and Psychological Moderators of Psychedelic-induced Personality Change among Healthy Volunteers},

author = {Kate Godfrey and Brandon Weiss and Xinhu Zhang and Meg Spriggs and Joseph Peill and Taylor Lyons and Robin Carhart-Harris and David Erritzoe},

doi = {https://doi.org/10.1016/j.nsa.2024.104092},

year  = {2024},

date = {2024-12-02},

urldate = {2024-01-01},

journal = {Neuroscience Applied},

pages = {104092},

publisher = {Elsevier},

abstract = {This study investigated the effects of a single high-dose of psilocybin on personality traits in psychedelic-naïve healthy volunteers. These data originate from a larger within-subjects fixed-order design trial, where a single high dose of psilocybin (25mg) was administered in a psychologically supportive setting and was compared against a (one-month) prior, 1mg ‘placebo’ dose. Personality shifts were assessed by the Big Five Inventory and the Big Five Aspect Scale, while the Altered States of Consciousness questionnaire (5D-ASC) and the Psychological Insight Scale gauged the acute psychological effects of the substance. Electroencephalography provided neurophysiological insights, specifically examining alpha power and Lempel-Ziv complexity (LZc). Results indicated significant reductions in neuroticism one month after 25mg psilocybin administration, a finding consistent with prior studies. Reductions in neuroticism were moderated by the subjective meaningfulness of the psychedelic experience, as well as by the dread of ego dissolution subscale of the 5D-ASC, suggesting a relationship between acute drug effects and enduring personality alterations. Thus, this study substantiates the role of acute psychedelic states in catalysing lasting personality transformations in a generally beneficial direction, with broader implications for therapeutic applications and understanding of personality dynamics.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{busch2024monitoring,

title = {Monitoring Cortical and Neuromuscular Activity: Six-month Insights into Knee Joint Position Sense Following ACL Reconstruction},

author = {Aglaja Busch and Lorena RR Gianotti and Frank Mayer and Heiner Baur},

doi = {https://doi.org/10.26603/001c.124840},

year  = {2024},

date = {2024-11-02},

urldate = {2024-01-01},

journal = {International Journal of Sports Physical Therapy},

volume = {19},

number = {11},

pages = {1290},

abstract = {Background

Changes in cortical activation patterns after rupture of the anterior cruciate ligament (ACL) have been described. However, evidence of these consequences in the early stages following the incident and through longitudinal monitoring is scarce. Further insights could prove valuable in informing evidence-based rehabilitation practices.



Purpose

To analyze the angular accuracy, neuromuscular, and cortical activity during a knee joint position sense (JPS) test over the initial six months following ACL reconstruction. Study design: Cohort Study



Methods

Twenty participants with ACL reconstruction performed a JPS test with both limbs. The measurement time points were approximately 1.5, 3-4 and 6 months after surgery, while 20 healthy controls were examined on a single occasion. The active JPS test was performed seated with a target angle of 50° for two blocks of continuous angular reproduction (three minutes per block). The reproduced angles were recorded simultaneously by an electrogoniometer. Neuromuscular activity of the quadriceps muscles during extension to the target angle was measured with surface electromyography. Spectral power for theta, alpha-2, beta-1 and beta-2 frequency bands were determined from electroencephalographic recordings. Linear mixed models were performed with group (ACL or controls), the measurement time point, and respective limb as fixed effect and each grouping per subject combination as random effect with random intercept.



Results

Significantly higher beta-2 power over the frontal region of interest was observed at the first measurement time point in the non-involved limb of the ACL group in comparison to the control group (p = 0.03). Despite individual variation, no other statistically significant differences were identified for JPS error, neuromuscular, or other cortical activity.



Conclusion

Variation in cortical activity between the ACL and control group were present, which is consistent with published results in later stages of rehabilitation. Both indicate the importance of a neuromuscular and neurocognitive focus in the rehabilitation.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{gwon2024motor,

title = {Motor task-to-task transfer learning for motor imagery brain-computer interfaces},

author = {Daeun Gwon and Minkyu Ahn},

doi = {https://doi.org/10.1016/j.neuroimage.2024.120906},

year  = {2024},

date = {2024-10-28},

urldate = {2024-01-01},

journal = {NeuroImage},

pages = {120906},

publisher = {Elsevier},

abstract = {Motor imagery (MI) is one of the popular control paradigms in the non-invasive brain-computer interface (BCI) field. MI-BCI generally requires users to conduct the imagination of movement (e.g., left or right hand) to collect training data for generating a classification model during the calibration phase. However, this calibration phase is generally time-consuming and tedious, as users conduct the imagination of hand movement several times without being given feedback for an extended period. This obstacle makes MI-BCI non user-friendly and hinders its use. On the other hand, motor execution (ME) and motor observation (MO) are relatively easier tasks, yield lower fatigue than MI, and share similar neural mechanisms to MI. However, few studies have integrated these three tasks into BCIs. In this study, we propose a new task-to-task transfer learning approach of 3-motor tasks (ME, MO, and MI) for building a better user-friendly MI-BCI. For this study, 28 subjects participated in 3-motor tasks experiment, and electroencephalography (EEG) was acquired. User opinions regarding the 3-motor tasks were also collected through questionnaire survey. The 3-motor tasks showed a power decrease in the alpha rhythm, known as event-related desynchronization, but with slight differences in the temporal patterns. In the classification analysis, the cross-validated accuracy (within-task) was 67.05 % for ME, 65.93 % for MI, and 73.16 % for MO on average. Consistently with the results, the subjects scored MI (3.16) as the most difficult task compared with MO (1.42) and ME (1.41), with p < 0.05. In the analysis of task-to-task transfer learning, where training and testing are performed using different task datasets, the ME–trained model yielded an accuracy of 65.93 % (MI test), which is statistically similar to the within-task accuracy (p > 0.05). The MO–trained model achieved an accuracy of 60.82 % (MI test). On the other hand, combining two datasets yielded interesting results. ME and 50 % of the MI–trained model (50-shot) classified MI with a 69.21 % accuracy, which outperformed the within-task accuracy (p < 0.05), and MO and 50 % of the MI–trained model showed an accuracy of 66.75 %. Of the low performers with a within-task accuracy of 70 % or less, 90 % (n = 21) of the subjects improved in training with ME, and 76.2 % (n = 16) improved in training with MO on the MI test at 50-shot. These results demonstrate that task-to-task transfer learning is possible and could be a promising approach to building a user-friendly training protocol in MI-BCI.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{harel2024task,

title = {Task-guided attention increases non-linearity of steady-state visually evoked potentials},

author = {Asaf Harel and Oren Shriki},

doi = {https://doi.org/10.1088/1741-2552/ad8032},

year  = {2024},

date = {2024-09-26},

urldate = {2024-01-01},

journal = {Journal of Neural Engineering},

abstract = {Attention is a multifaceted cognitive process, with nonlinear dynamics playing a crucial role. In this study, we investigated the involvement of nonlinear processes in top-down visual attention by employing a contrast-modulated sequence of letters and numerals, encircled by a consistently flickering white square on a black background - a setup that generated steady-state visually evoked potentials. Nonlinear processes are recognized for eliciting and modulating the harmonics of constant frequencies. We examined the fundamental and harmonic frequencies of each stimulus to evaluate the underlying nonlinear dynamics during stimulus processing. In line with prior research, our findings indicate that the power spectrum density of EEG responses is influenced by both task presence and stimulus contrast. By utilizing the Rhythmic Entrainment Source Separation (RESS) technique, we discovered that actively searching for a target within a letter stream heightened the amplitude of the fundamental frequency and harmonics related to the background flickering stimulus. While the fundamental frequency amplitude remained unaffected by stimulus contrast, a lower contrast led to an increase in the second harmonic's amplitude. We assessed the relationship between the contrast response function and the nonlinear-based harmonic responses. Our findings contribute to a more nuanced understanding of the nonlinear processes impacting top-down visual attention while also providing insights into optimizing brain-computer interfaces.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{cha2024effect,

title = {Effect of Electroencephalography-based Motor Imagery Neurofeedback on Mu Suppression During Motor Attempt in Patients with Stroke},

author = {Seungwoo Cha and Kyoung Tae Kim and Won Kee Chang and Nam-Jong Paik and Ji Soo Choi and Hyunmi Lim and Won-Seok Kim and Jeonghun Ku},

doi = {https://doi.org/10.21203/rs.3.rs-5106561/v1},

year  = {2024},

date = {2024-09-26},

urldate = {2024-01-01},

journal = {Journal of NeuroEngineering and Rehabilitation },

abstract = {Objective

The primary aims of this study were to explore the neurophysiological effects of motor imagery neurofeedback using electroencephalography (EEG), specifically focusing on mu suppression during serial motor attempts and assessing its potential benefits in patients with subacute stroke.



Methods

A total of 15 patients with hemiplegia following subacute ischemic stroke were prospectively enrolled in this randomized cross-over study. This study comprised two experiments: neurofeedback and sham. Each experiment included four blocks: three blocks of resting, grasp, resting, and intervention, followed by one block of resting and grasp. During the resting sessions, the participants fixated on a white cross on a black background for 2 minutes without moving their upper extremities. In the grasp sessions, the participants were instructed to grasp and release their paretic hand at a frequency of about 1 Hz for 3 minutes while fixating on the same white cross. During the intervention sessions, neurofeedback involved presenting a punching image with the affected upper limb corresponding to the mu suppression induced by imagined movement, while the sham involved mu suppression of other randomly selected participants 3 minutes. EEG data were recorded during the experiment, and data from C3/C4 and P3/P4 were used for analyses to compare the degree of mu suppression between the neurofeedback and sham conditions.



Results

Significant mu suppression was observed in the bilateral motor and parietal cortices during the neurofeedback intervention compared with the sham condition across serial sessions (p < 0.001). Following neurofeedback, the real grasping sessions showed progressive strengthening of mu suppression in the ipsilesional motor cortex and bilateral parietal cortices compared to those following sham (p < 0.05), an effect not observed in the contralesional motor cortex.



Conclusion

Motor imagery neurofeedback significantly enhances mu suppression in the ipsilesional motor and bilateral parietal cortices during motor attempts in patients with subacute stroke. These findings suggest that motor imagery neurofeedback could serve as a promising adjunctive therapy to enhance motor-related cortical activity and support motor rehabilitation in patients with stroke.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}