Optimizing real-time fNIRS in BCI and neurofeedback: A comprehensive overview of strategies to improve reliability, spatial specificity, and signal quality DOI Open Access
Franziska Klein

Published: Sept. 14, 2023

The optical brain imaging method functional near-infrared spectroscopy (fNIRS) is a promising tool for real-time applications such as neurofeedback and brain-computer interfaces. Its combination of spatial specificity mobility makes it particularly attractive clinical use, both at the bedside in patients’ homes. Despite these advantages, optimizing fNIRS use requires careful attention to two key aspects: ensuring good maintaining high signal quality. While detects superficial cortical regions, consistently reliably targeting specific regions interest can be challenging, studies that require repeated measurements. Variations cap placement coupled with limited anatomical information may further reduce this accuracy. Furthermore, important tomaintain quality contexts ensure they reflect true underlying activity. However, signals are susceptible contamination by cerebral extracerebral systemic noise well motion artifacts. Insuffcient preprocessing therefore cause system run on instead aim review article help advance progress fNIRS-based applications. It highlights potential challenges improving quality, discusses possible options overcome challenges, addresses considerations relevant By addressing topics, aims improve planning execution future studies, thereby increasing their reliability repeatability.

Language: Английский

Advancements in Epilepsy Classification: Current Trends and Future Directions DOI Creative Commons

Rajani Rai B,

Karunakara Rai B,

Moore As

et al.

MethodsX, Journal Year: 2025, Volume and Issue: unknown, P. 103257 - 103257

Published: March 1, 2025

Language: Английский

Citations

0
Neuroscientific Evidence in Legal Proceedings DOI
K. Jayasankara Reddy

Published: Jan. 1, 2025

Language: Английский

Citations

0
The Virtual Parkinsonian patient DOI Creative Commons
Marianna Angiolelli, Damien Depannemaecker,

Hasnae Agouram

et al.

npj Systems Biology and Applications, Journal Year: 2025, Volume and Issue: 11(1)

Published: April 26, 2025

This study investigates the influence of pharmacological nigrostriatal dopaminergic stimulation on entire brain by analyzing EEG and deep electrodes, placed near subthalamic nuclei, from 10 Parkinsonian patients before (OFF) after (ON) L-Dopa administration. We characterize large-scale dynamics as spatio-temporal spreading aperiodic bursts. then simulate effects utilizing a novel neural-mass model that includes local dopamine concentration. Whole-brain are simulated for different tones, generating predictions expected dynamics, to be compared with empirical electrode data. To this end, we invert infer most likely tone data, correctly identifying higher Dopaminergic in ON-state, lower OFF-state, each patient. In conclusion, successfully integrating anatomical functional knowledge into physiological predictions, using solid ground truth validate our findings.

Language: Английский

Citations

0
Garden of forking paths in ERP research – Effects of varying pre‐processing and analysis steps in an N400 experiment DOI
Аnđela Šoškić, Suzy J Styles, Emily S. Kappenman

et al.

Psychophysiology, Journal Year: 2024, Volume and Issue: 61(10)

Published: July 3, 2024

This study tackles the Garden of Forking Paths, as a challenge for replicability and reproducibility ERP studies. Here, we applied multiverse analysis to sample N400 dataset, donated by an independent research team. We analyzed this dataset using 14 pipelines selected showcase full range methodological variability found in literature systematic review approach. The were compared depth looking into statistical test outcomes, descriptive statistics, effect size, data quality, power. In way provide worked example how analytic flexibility can impact results fields with high dimensionality such ERP, when standard null-hypothesis significance testing. Out decisions that varied, high-pass filter cut-off, artifact removal method, baseline duration, reference, measurement latency locations, amplitude measure (peak vs. mean) all shown affect at least some outcome measures. Low-pass filtering was only step which did not notably influence any these shows even seemingly minor procedural deviations conclusions study. demonstrate power both identifying most reliable effects given study, providing insights consequences decisions.

Language: Английский

Citations

3
Garden of forking paths in ERP research – effects of varying pre-processing and analysis steps in an N400 experiment DOI Open Access
Аnđela Šoškić, Suzy J Styles, Emily S. Kappenman

et al.

Published: March 16, 2022

This paper tackles the Garden of Forking Paths (Gelman & Loken, 2013), as a challenge for replicability and reproducibility ERP studies. Here, we applied multiverse analysis to sample N400 dataset, donated by an independent research team. We analysed this dataset using 14 pipelines selected showcase full range methodological variability found in literature systematic review approach (Šoškić et al., 2022). The were compared depth looking into statistical test outcomes, descriptive statistics, effect size, data quality, power. In way provide worked example how analytic flexibility can impact results fields with high dimensionality such ERP, when standard null-hypothesis significance testing. Out decisions that varied, high-pass filter cut-off, artifact removal method, baseline duration, reference, measurement latency locations, amplitude measure (peak vs. mean) all shown affect at least some study outcome measures. Low-pass filtering was only step which did not notably influence any these shows even seemingly minor procedural deviations conclusions study. demonstrate power both identifying most reliable effects given study, providing insights consequences decisions.

Language: Английский

Citations

15
A Novel OpenBCI Framework for EEG-Based Neurophysiological Experiments DOI Creative Commons

Yeison Nolberto Cardona-Álvarez,

Andrés Marino Álvarez-Meza, David Cárdenas‐Peña

et al.

Sensors, Journal Year: 2023, Volume and Issue: 23(7), P. 3763 - 3763

Published: April 6, 2023

An Open Brain-Computer Interface (OpenBCI) provides unparalleled freedom and flexibility through open-source hardware firmware at a low-cost implementation. It exploits robust platforms powerful software development kits to create customized drivers with advanced capabilities. Still, several restrictions may significantly reduce the performance of OpenBCI. These limitations include need for more effective communication between computers peripheral devices fast settings under specific protocols neurophysiological data. This paper describes flexible scalable OpenBCI framework electroencephalographic (EEG) data experiments using Cyton acquisition board updated maximize benefits ADS1299 platforms. The handles distributed computing tasks supports multiple sampling rates, protocols, free electrode placement, single marker synchronization. As result, system delivers real-time feedback controlled execution EEG-based clinical implementing steps neural recording, decoding, stimulation, analysis. In addition, incorporates automatic background configuration user-friendly widgets stimuli delivery. Motor imagery tests closed-loop BCI designed enable streaming within required latency jitter ranges. Therefore, presented offers promising solution tailored processing.

Language: Английский

Citations

7
Tuning Minimum-Norm regularization parameters for optimal MEG connectivity estimation DOI Creative Commons
Elisabetta Vallarino,

Ana Sofia Hincapié,

Karim Jerbi

et al.

NeuroImage, Journal Year: 2023, Volume and Issue: 281, P. 120356 - 120356

Published: Sept. 11, 2023

The accurate characterization of cortical functional connectivity from Magnetoencephalography (MEG) data remains a challenging problem due to the subjective nature analysis, which requires several decisions at each step analysis pipeline, such as choice source estimation algorithm, metric and parcellation, name but few. Recent studies have emphasized importance selecting regularization parameter in minimum norm estimates with caution, variations its value can result significant differences estimates. In particular, amount that is optimal for MEG actually be suboptimal coherence-based analysis. this study, we expand upon previous work by examining broader range commonly used metrics, including imaginary part coherence, corrected Phase Locking Value, weighted Lag Index, within larger more realistic simulation scenario. Our results show best estimate achieved using 1 or 2 orders magnitude smaller than one yields estimation. This remarkable difference may imply assessing source-space minimum-norm benefited less regularization, helped reduce false positives. Importantly, provide code offering research community valuable open tool informed selections when space analyses.

Language: Английский

Citations

6
Selecting methods for a modular EEG pre-processing pipeline: An objective comparison DOI Creative Commons
Stefania Coelli, Alessandra Calcagno,

Chiara Maria Cassani

et al.

Biomedical Signal Processing and Control, Journal Year: 2023, Volume and Issue: 90, P. 105830 - 105830

Published: Dec. 14, 2023

Electroencephalography (EEG) to study brain functions has become fundamental in many research settings across very different protocols. Indeed, a plethora of processing methods have been developed, for both data preparation (pre-processing) and analysis. While an effect the pre-processing on signal is admitted accepted, there increasing effort better understand which extent such influence may affect analysis results, be best practices correct pre-processing. Pre-processing procedures include steps, each them induce modifications affecting results. Thus, we analyze methodologies at step propose quantitative parameters choice preferable strategy. We illustrate how method selection quality EEG Action Observation Motor Imagery protocol, using indices. analyzed strategies early-stage preparation; two independent component (ICA) algorithms (SOBI Extended Infomax) used artifact removal; four re-reference approaches (Common averaged reference-CAR, robust-CAR, reference electrode standardization technique – REST, interpolation RESIT). The effects pipelines were also evaluated through computation event-related spectral perturbation (ERSP) sensorimotor rhythm. Results showed that segmentation significantly affects cleaning procedure, while comparable results are obtained ICA approaches. Finally, similar topographical representations after application CAR, RESIT re-referencing approaches, where rCAR most ERSP pattern.

Language: Английский

Citations

5
Complexity of STG signals and linguistic rhythm: a methodological study for EEG data DOI
Silvana Silva Pereira, Ege Ekin Özer, Núria Sebastián‐Gallés

et al.

Cerebral Cortex, Journal Year: 2024, Volume and Issue: unknown

Published: Jan. 17, 2024

Abstract The superior temporal and the Heschl’s gyri of human brain play a fundamental role in speech processing. Neurons synchronize their activity to amplitude envelope signal extract acoustic linguistic features, process known as neural tracking/entrainment. Electroencephalography has been extensively used language-related research due its high resolution reduced cost, but it does not allow for precise source localization. Motivated by lack unified methodology interpretation reconstructed signals, we propose method based on modularity complexity. procedure was tested data from an experiment which investigated impact native language tracking rhythms two groups: English natives Spanish natives. In experiment, found no effect rhythm. Here, compare projected signals auditory areas both hemispheres different conditions using nonparametric permutation tests, modularity, dynamical complexity measure. We increasing values decreased regularity stimuli, giving us possibility conclude that languages with less complex are easier track cortex.

Language: Английский

Citations

1
Exploring the disruptions of the neurophysiological organization in Alzheimer’s disease: An integrative approach DOI Creative Commons
Víctor Gutiérrez-de Pablo, Jesús Poza, Aarón Maturana-Candelas

et al.

Computer Methods and Programs in Biomedicine, Journal Year: 2024, Volume and Issue: 250, P. 108197 - 108197

Published: April 24, 2024

Alzheimer's disease (AD) is a neurological disorder that impairs brain functions associated with cognition, memory, and behavior. Noninvasive neurophysiological techniques like magnetoencephalography (MEG) electroencephalography (EEG) have shown promise in reflecting changes related to AD. These are usually assessed at two levels: local activation (spectral, nonlinear, dynamic properties) global synchronization (functional connectivity, frequency-dependent network, multiplex network organization characteristics). Nonetheless, the understanding of formed by existing relationships between these levels, henceforth named organization, remains unexplored. This work aims assess alterations AD causes resting-state organization.

Language: Английский

Citations

1