@article{nyffenegger2025cortical,

title = {Cortical activity during the first 4 months after anterior cruciate ligament reconstruction while performing an active knee joint position sense test: A pilot study},

author = {Daniela Nyffenegger and Heiner Baur and Philipp Henle and Aglaja Busch},

doi = {https://doi.org/10.1016/j.knee.2025.04.017},

year  = {2025},

date = {2025-05-07},

urldate = {2025-01-01},

journal = {The Knee},

volume = {55},

pages = {168–178},

publisher = {Elsevier},

abstract = {Background

Anterior cruciate ligament (ACL) rupture is thought to alter the way in which the brain receives and processes information, affecting body movements. Although alterations in brain activity after ACL rupture have been described, these are limited to time points more than 6 months after rupture. Therefore, this pilot study aims to investigate cortical activity during an active knee joint position sense (JPS) test within the first 4 months after ACL reconstruction.



Methods

Twelve participants with ACL reconstruction (nine males; age 25.3 ± 6.4 years; height 173.6 ± 8.0 cm; mass 71.1 ± 9.1 kg) and 12 matched healthy controls (nine males; age 28.8 ± 9.7 years; height 174.5 ± 9.7 cm; mass 72.7 ± 12.7 kg) performed an active knee JPS test in an open kinetic chain with a starting angle of 90° knee flexion and a target angle of 50°. Absolute angular error was measured with an electrogoniometer. Cortical activity was simultaneously recorded with dry electroencephalography. Participants with ACL reconstruction were measured at 5–8 weeks postoperative (M1) and 12–16 weeks postoperative (M2), the control group once. Power spectra for the frequencies, theta (4.75–6.75 Hz), alpha-1 (7.0–9.5 Hz) and alpha-2 (9.75–12.5 Hz) for frontal, central and parietal regions of interest were calculated.



Results

Participants with ACL reconstruction exhibited significantly higher central theta power during JPS testing with their uninvolved leg at M1 compared with M2 (adjusted P = 0.01; rank epsilon squared = 0.39). No other comparisons yielded statistically significant differences.



Conclusions

The results cautiously support current evidence on cortical alterations following ACL reconstruction. A larger sample size and more measurement time points may provide further insight into possible alterations in the early postoperative period.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{carter2025eeg,

title = {EEG Functional Connectivity, Heartrate Synchrony, and Eye Movements Reveal Distinct Components within Narrative Engagement and Immersion},

author = {Felix Carter and Iain D Gilchrist and Danae Stanton-Fraser},

doi = {https://doi.org/10.1162/jocn_a_02338},

year  = {2025},

date = {2025-04-28},

urldate = {2025-01-01},

journal = {Journal of Cognitive Neuroscience},

pages = {1–22},

publisher = {MIT Press 255 Main Street, 9th Floor, Cambridge, Massachusetts 02142, USA~…},

abstract = {Storytelling is a fundamental and universal human behavior, representing a vehicle for cultural information exchange throughout human history. In the present day, consumption of narrative audiovisual media is one of the most common recreational activities worldwide. Despite the importance and ubiquity of storytelling, relatively little is known about the neurocognitive mechanisms by which narrative media capture and sustain our attention. In this study, 40 participants watched 10 short clips from television shows of various genres while electroencephalography, eye tracking, heart rate, and self-report data were recorded. Self-reported immersion and three of the four components of narrative engagement that we examined—attentional focus, emotional engagement, and narrative presence—were associated with interindividual synchrony in heart rate and gaze behavior, but were associated with relatively distinct patterns of neural activity (electroencephalography power amplitude and functional connectivity). Narrative understanding, on the other hand, was not associated with heart rate or gaze synchrony. Furthermore, structural equation modeling revealed directionally opposing relationships between overall alpha-band connectivity and narrative presence on the one hand (positive), and narrative understanding (negative) on the other. These results suggest narrative understanding may be associated with a different set of neurocognitive processes to the other dimensions of narrative engagement. These findings point toward a bifurcated model of narrative engagement and raise interesting theoretical questions about the role of narrative comprehension in this process.



},

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pubstate = {published},

tppubtype = {article}

}

@article{lim2025effects,

title = {Effects of Augmented Reality (AR) Mirror Therapy Combined with Peripheral Electrical},

author = {Hyunmi Lim and Jeonghun Ku},

url = {https://books.google.com/books?hl=en&lr=&id=fx1TEQAAQBAJ&oi=fnd&pg=PA100&dq=Effects+of+Augmented+Reality+(AR)+Mirror+Therapy+Combined+with+Peripheral+Electrical&ots=jIWVkp4Jhf&sig=9Y7R_WCksKg36QGoCge2JwgHwTU#v=onepage&q=Effects%20of%20Augmented%20Reality%20(AR)%20Mirror%20Therapy%20Combined%20with%20Peripheral%20Electrical&f=false},

year  = {2025},

date = {2025-04-05},

urldate = {2025-01-01},

journal = {Emerging Therapies in Neurorehabilitation III: Proceedings of the 10/11/12th Summer School on Neurorehabilitation (SSNR), held in 2022, 2023, 2024, in Baiona, Spain},

volume = {34},

pages = {100},

publisher = {Springer Nature},

abstract = {Abstract. In this study, we investigated the effects of an augmented reality (AR)- based mirror therapy program that combines peripheral electrical stimulation (PES) with mirror visual feedback (MVF) on brain activity. The program was tested on three healthy adults in their 20s. The results showed that the combined feedback of MVF and PES was effective in enhancing motor learning-related brain activity in the mirror-reflected hand. Further research will investigate the effects of different AR feedback factors on brain activity, which will aid in developing optimal rehabilitation protocols. These findings could be applied to rehabilitation therapy for stroke patients, potentially improving the effectiveness of their treatment.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{wang2025study,

title = {Study on cognitive impairment evaluation based on photoelectric neural information},

author = {Zehua Wang and Ye Zhang and Ning Ma and Huiting Qiao and Meiyun Xia and Deyu Li},

doi = {https://doi.org/10.1177/25424823251325537},

year  = {2025},

date = {2025-03-21},

urldate = {2025-01-01},

journal = {Journal of Alzheimer's Disease Reports},

volume = {9},

pages = {25424823251325537},

publisher = {SAGE Publications Sage UK: London, England},

abstract = {Background

Whether there is a cognitive load-dependent brain activation pattern in the pre-Alzheimer's disease phase is unknown. Multimodal system provides a powerful technical tool.

Objective

We evaluated brain activity patterns under different cognitive loads in patients with mild cognitive impairment.

Methods

Functional near-infrared spectroscopy signals and electroencephalography signals were acquired from the mild cognitive impairment group (MCI, n = 20) and the healthy control group (HC, n = 24) under four cognitive loads. We analyzed the respective brain activity features and performed correlation analyses.

Results

(1) During the encoding phase, both the left occipital (pcond = 0.05, pgroup < 0.01) and left temporal (pcond = 0.02, pgroup = 0.03) skewness condition effects and between-group effects were significant. (2) As the cognitive load increased, the clustering coefficients and local efficiencies were significantly lower for the HC group. (3) The left occipital and left temporal activation skewness in the MCI group were significantly correlated with left occipital electrical features, whereas the left occipital activation intensity and skewness were significantly correlated with left occipital electrical features in HC group.

Conclusions

The pattern of brain activity in MCI depends on cognitive load. Left occipital and left temporal may be important brain regions for evaluating MCI and need to be focused on in the future.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{gupta2025frequency,

title = {Frequency dependence of cortical somatosensory evoked response to peripheral nerve stimulation with controlled afferent excitation},

author = {Disha Gupta and Jodi Ann Brangaccio and Helia Mojtabavi and Jonathan S Carp and Jonathan R Wolpaw and N Jeremy Hill},

doi = {10.1088/1741-2552/adc204},

year  = {2025},

date = {2025-03-18},

urldate = {2025-01-01},

journal = {Journal of Neural Engineering},

abstract = {Objective: H-reflex Targeted Neuroplasticity (HrTNP) protocols comprise a promising rehabilitation approach to improve motor function after brain or spinal injury. In this operant conditioning protocol, concurrent measurement of cortical responses, such as somatosensory evoked potentials (SEPs), would be useful for examining supraspinal involvement and neuroplasticity mechanisms. To date, this potential has not been exploited. However, the stimulation parameters used in the HrTNP protocol deviate from the classically recommended settings for SEP measurements. Most notably, it demands a much longer pulse width, higher stimulation intensity, and lower frequency than traditional SEP settings. In this paper, we report SEP measurements performed within the HrTNP stimulation parameter constraints, specifically characterizing the effect of stimulation frequency.

Approach: SEPs were acquired for tibial nerve stimulation at three stimulation frequencies (0.2, 1, and 2 Hz) in 13 subjects while maintaining the afferent volley by controlling the direct soleus muscle response via the Evoked Potential Operant Conditioning System. The amplitude and latency of the short-latency P40 and mid-latency N70 SEP components were measured at the central scalp region using non-invasive electroencephalography. 

Results: As frequency rose from 0.2Hz, P40 amplitude and latency did not change. In contrast, N70 amplitude decreased significantly (39% decrease at 1 Hz, and 57% decrease at 2Hz), presumably due to gating effects. N70 latency was not affected. Across all three frequencies, N70 amplitude increased significantly with stimulation intensity and correlated with M-wave amplitude. 

Significance: We assess SEPs within an HrTNP protocol, focusing on P40 and N70, elicited with controlled afferent excitation at three stimulation frequencies. HrTNP conditioning protocols show promise for enhancing motor function after brain and spinal injuries. While SEPs offer valuable insights into supraspinal involvement, the stimulation parameters in HrTNP often differ from standard SEP measurement protocols. We address these deviations and provide recommendations for effectively integrating SEP assessments into HrTNP studies.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{rustamov2025cortical,

title = {Cortical Spectral Dynamics of Vibrotactile Frequency Processing},

author = {Nabi Rustamov and Phillip Demarest and Zhuangyu Han and Safia Mohamud and Simon Haroutounian and Eric C Leuthardt},

doi = {https://doi.org/10.21203/rs.3.rs-6043161/v1},

year  = {2025},

date = {2025-02-21},

urldate = {2025-01-01},

journal = {Scientific Reports},

abstract = {While scientific research has extensively explored how the brain integrates touch and pain signals, the cerebral processing of specific vibrotactile frequencies remains poorly understood. This gap is particularly significant given clinical evidence that vibrotactile stimulation can reduce pain in both chronic pain patients and experimental settings. Our study investigated the cortical electrophysiological correlates of peripheral vibrotactile stimulation across different frequencies in healthy volunteers, with a focus on frequency-dependent patterns of neuronal activation. While electroencephalogram (EEG) was recorded, healthy participants received vibrotactile stimulation to the left index fingertip at frequencies corresponding to established neural rhythms: delta (2 Hz), theta (6 Hz), alpha (12 Hz), beta (20 Hz), and gamma (40 Hz). We compared the EEG bandwidth activity between vibrotactile stimulation conditions relative to resting baseline. Our findings demonstrated that vibrotactile stimulation produces distinct frequency-dependent patterns of cortical activation. A key finding was that 6 Hz stimulation selectively enhanced theta power in the left prefrontal cortex - an electrophysiological signature previously linked to successful pain relief. These findings advance the understanding of the "spectrotopic" nature of vibrotactile frequency processing in the cortex and provide a mechanistic foundation for developing novel vibration-based therapies in the future.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{calvo2025deep,

title = {Deep Learning-Driven EEG Analysis for Personalized Deep Brain Stimulation Programming in Parkinson's Disease},

author = {Nicolas Calvo Peiro and Mathias Ramm Haugland and Alena Kutuzova and Cosima Graef and Aminata Bocum and Yen Foung Tai and Anastasia Borovykh and Shlomi Haar},

doi = {https://doi.org/10.1101/2025.02.11.25321886},

year  = {2025},

date = {2025-02-13},

urldate = {2025-01-01},

journal = {medRxiv},

pages = {2025–02},

publisher = {Cold Spring Harbor Laboratory Press},

abstract = {Deep Brain Stimulation (DBS) is an invasive procedure used to alleviate motor symptoms in Parkinson’s Disease (PD) patients. While brain activity can be used to optimise DBS parameters, the impact of DBS parameters on brain activity remains unclear. We aimed to identify the cortical neural response to changes in DBS parameters, which are sensitive to the effect of small changes in the stimulation parameters and could be used as neural biomarkers. We recorded in-clinic EEG data from seven hemispheres of PD patients during DBS programming sessions.



Here we developed a siamese adaptation of the EEGNet deep learning architecture and trained it to distinguish whether two short (1-sec-long) segments of brain activity were taken with the same stimulation parameters, or if either the strength or location of the stimulation had changed. 13 independent models were trained independently in each hemisphere for stimulation amplitude or contact, and all achieved high accuracy with an average of 78%. Our models are sensitive to changes in brain activity recorded at the scalp of the patients following changes as small as 0.3mA in the DBS parameters.



Next, we interpreted what our black-box AI models learned with an ablation-based explainability method, that extracts frequency bands learned by the models through a perturbation of the input’s frequency spectrum. We found that fast Narrow-Band Gamma oscillations (60-90Hz), contributed most to the models across all 7 hemispheres.



This work, using a data-driven approach, joins a recent body of evidence suggesting cortical Narrow-Band Gamma activity as the potential range for digital biomarkers for DBS optimization.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@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.



},

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tppubtype = {article}

}