Is Cortical Activation During Walking Different Between Parkinson’s Disease Motor Subtypes? DOI
Diego Orcioli‐Silva, Rodrigo Vitório, Victor Spiandor Beretta

et al.

The Journals of Gerontology Series A, Journal Year: 2020, Volume and Issue: 76(4), P. 561 - 567

Published: July 16, 2020

Abstract Parkinson’s disease (PD) is often classified into tremor dominant (TD) and postural instability gait disorder (PIGD) subtypes. Degeneration of subcortical/cortical pathways different between PD subtypes, which leads to differences in motor behavior. However, the influence subtype on cortical activity during walking remains poorly understood. Therefore, we aimed investigate subtypes unobstructed obstacle avoidance. Seventeen PIGD 19 TD patients performed avoidance conditions. Brain was measured using a mobile functional near-infrared spectroscopy–electroencephalography (EEG) systems, parameters were analyzed an electronic carpet. Concentrations oxygenated hemoglobin (HbO2) prefrontal cortex (PFC) EEG absolute power from alpha, beta, gamma bands FCz, Cz, CPz, Oz channels calculated. These correspond supplementary area, primary cortex, posterior parietal visual respectively. Postural presented higher PFC than patients, regardless condition. Tremor reduced beta Cz channel compared walking. Both decreased alpha FCz CPz channels. In conclusion, need recruit additional cognitive resources for changes activation brain areas related motor/sensorimotor order maintain balance control avoidance, being that further area (Cz channel) avoid obstacles.

Language: Английский

Neural mechanisms distinguishing two types of cooperative problem-solving approaches: An fNIRS hyperscanning study DOI Creative Commons
Mingming Zhang, Zijun Yin, Xue Zhang

et al.

NeuroImage, Journal Year: 2024, Volume and Issue: 291, P. 120587 - 120587

Published: March 26, 2024

Collaborative cooperation (CC) and division of labor (DLC) are two prevalent forms cooperative problem-solving approaches in daily life. Despite extensive research on the neural mechanisms underlying approaches, a notable gap exists between processes that support CC DLC. The present study utilized functional near-infrared spectroscopy (fNIRS) hyperscanning technique along with classic tangram puzzle task to investigate engaged by both friends stranger dyads during versus key findings this were as follows: (1) Dyads exhibited superior behavioral performance DLC than task. bolstered intra-brain connectivity inter-brain synchrony (IBS) regions linked mirror neuron system (MNS), spatial perception (SP) cognitive control. (2) Friend showed stronger IBS brain associated MNS dyads. (3) Perspective-taking predicted not only dyads' but also their SP Taken together, these elucidate divergent connection patterns approaches. This provides novel insights into various neurocognitive flexible coordination strategies real-world contexts.

Language: Английский

Citations

8
Convolutional Neural Network for Hybrid fNIRS-EEG Mental Workload Classification DOI

Marjan Saadati,

Jill Nelson, Hasan Ayaz

et al.

Advances in intelligent systems and computing, Journal Year: 2019, Volume and Issue: unknown, P. 221 - 232

Published: June 11, 2019

Language: Английский

Citations

49
Development of a ternary hybrid fNIRS-EEG brain–computer interface based on imagined speech DOI
Alborz Rezazadeh Sereshkeh, Rozhin Yousefi, Andrew Wong

et al.

Brain-Computer Interfaces, Journal Year: 2019, Volume and Issue: 6(4), P. 128 - 140

Published: Oct. 2, 2019

There is increasing interest in developing intuitive brain-computer interfaces (BCIs) to differentiate mental tasks such as imagined speech. Both electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) have been used for this purpose. However, the classification accuracy number of commands BCIs limited. The use multi-modal address these issues has proposed some common BCI tasks, but not Here, we propose a multi-class hybrid fNIRS-EEG based on Eleven participants performed multiple iterations three tasks: mentally repeating 'yes' or 'no' 15 s an equivalent duration unconstrained rest. We achieved average ternary 70.45 ± 19.19% which significantly better than that attained with each modality alone (p < 0.05). Our findings suggest concurrent measurements EEG fNIRS can improve

Language: Английский

Citations

45
A review on functional near-infrared spectroscopy and application in stroke rehabilitation DOI Creative Commons
Congcong Huo, Gongcheng Xu, Wenhao Li

et al.

Medicine in Novel Technology and Devices, Journal Year: 2021, Volume and Issue: 11, P. 100064 - 100064

Published: March 1, 2021

Functional near-infrared spectroscopy (fNIRS) has gained great interest as a noninvasive modality to study the changes in cerebral hemodynamics related brain activity. The unique and beneficial characteristics of fNIRS allow ecologically effective investigations all ages conditions more realistic clinical environments. In this review, we provide comprehensive description basics, analytical method developments applications stroke rehabilitation. We first review various new methods for time-series processing functional analysis data. Then, fNIRS-based application research rehabilitation highlight exciting based on fNIRS. Finally, discuss possible technical limitations implementation suggestions from different aspects practical application.

Language: Английский

Citations

39
Evidence of Neurovascular Un-Coupling in Mild Alzheimer’s Disease through Multimodal EEG-fNIRS and Multivariate Analysis of Resting-State Data DOI Creative Commons
Antonio Maria Chiarelli, David Perpetuini, Pierpaolo Croce

et al.

Biomedicines, Journal Year: 2021, Volume and Issue: 9(4), P. 337 - 337

Published: March 26, 2021

Alzheimer’s disease (AD) is associated with modifications in cerebral blood perfusion and autoregulation. Hence, neurovascular coupling (NC) alteration could become a biomarker of the disease. NC might be assessed clinical settings through multimodal electroencephalography (EEG) functional near-infrared spectroscopy (fNIRS). Multimodal EEG-fNIRS was recorded at rest an ambulatory setting to assess evaluate sensitivity specificity methodology AD. Global evaluated general linear model (GLM) framework by regressing whole-head EEG power envelopes three frequency bands (theta, alpha beta) average fNIRS oxy- deoxy-hemoglobin concentration changes frontal prefrontal cortices. lower AD compared healthy controls (HC) significant differences linkage theta deoxy-hemoglobin, respectively (p = 0.028 p 0.020). Importantly, standalone metrics did not highlight between HC. Furthermore, multivariate data-driven analysis two hemoglobin species delivered cross-validated classification performance HC Area Under Curve, AUC 0.905 2.17 × 10−5). The findings demonstrate that may indeed represent powerful ecological tool for evaluation early identification

Language: Английский

Citations

33
Motor Imagery Decoding Enhancement Based on Hybrid EEG-fNIRS Signals DOI Creative Commons

Tao Xu,

Zhengkang Zhou,

Yuliang Yang

et al.

IEEE Access, Journal Year: 2023, Volume and Issue: 11, P. 65277 - 65288

Published: Jan. 1, 2023

This study explores the combination of electroencephalogram (EEG) and functional near-infrared spectroscopy (fNIRS) to enhance decoding performance motor imagery (MI) tasks for brain-computer interface (BCI). The experiment involved measuring 64 channels EEG signals 20 fNIRS simultaneously during a task left-right hand MI. By combining these two types signals, aimed understand how feature fusion affected classification accuracy were filtered into three bands (θ: 4-7 Hz, α: 8-13 β: 14-30 Hz), while 0.02-0.08 Hz improve signal quality subsequent analysis. common spatial patterns (CSP) algorithm was utilized extract features from both signals. allowed researchers create fused with that could then be processed using principal component analysis (PCA). Finally, data fed support vector machine (SVM) classifier, which improved mean rate MI 92.25%. comparing accuracies obtained unfused segments discovered fusing significantly by 5%-10%. Furthermore, analyzing activated brain regions showed auxiliary cortex These results demonstrate hybrid strategy can stability fault tolerance in BCI systems, making them valuable practical applications.

Language: Английский

Citations

15
Incorporating EEG and fNIRS Patterns to Evaluate Cortical Excitability and MI-BCI Performance During Motor Training DOI Creative Commons
Zhongpeng Wang, Yang Lu, Yijie Zhou

et al.

IEEE Transactions on Neural Systems and Rehabilitation Engineering, Journal Year: 2023, Volume and Issue: 31, P. 2872 - 2882

Published: Jan. 1, 2023

As electroencephalography (EEG) is nonlinear and nonstationary in nature, an imperative challenge for brain-computer interfaces (BCIs) to construct a robust classifier that can survive long time monitor the brain state stably. To this end, research aims improve BCI performance by incorporation of electroencephalographic cerebral hemodynamic patterns. A motor imagery (MI)-BCI based visual-haptic neurofeedback training (NFT) experiment was designed with sixteen participants. EEG functional near infrared spectroscopy (fNIRS) signals were simultaneously recorded before after transient NFT. Cortical activation significantly improved repeated continuous NFT through time-frequency topological analysis. calibration strategy, weighted EEG-fNIRS patterns (WENP), proposed, which elementary classifiers constructed using both fNIRS information then integrated into strong their independent accuracy-based weight assessment. The results revealed on integrating superior only (~10% ~18% improvement respectively), reaching ~89% mean classification accuracy. WENP strategy effectively MI-BCI could also be used other paradigms. These findings validate our proposed methods are feasible promising optimizing conventional clinical rehabilitation.

Language: Английский

Citations

13
A Combined EEG-fNIRS Study Investigating Mechanisms Underlying the Association between Aerobic Fitness and Inhibitory Control in Young Adults DOI
Sebastian Ludyga, Martin Mücke, Flora Colledge

et al.

Neuroscience, Journal Year: 2019, Volume and Issue: 419, P. 23 - 33

Published: Sept. 2, 2019

Language: Английский

Citations

42
Complexity of Frontal Cortex fNIRS Can Support Alzheimer Disease Diagnosis in Memory and Visuo-Spatial Tests DOI Creative Commons
David Perpetuini, Antonio Maria Chiarelli, Daniela Cardone

et al.

Entropy, Journal Year: 2019, Volume and Issue: 21(1), P. 26 - 26

Published: Jan. 1, 2019

Decline in visuo-spatial skills and memory failures are considered symptoms of Alzheimer's Disease (AD) they can be assessed at early stages employing clinical tests. However, performance a single test is generally not indicative AD. Functional neuroimaging, such as functional Near Infrared Spectroscopy (fNIRS), may employed during these tests an ecological setting to support diagnosis. Indeed, neuroimaging should alter practice allowing free doctor-patient interaction. block-designed paradigms, necessary for standard analysis, require adaptation. Novel signal analysis procedures (e.g., complexity evaluation) useful establish brain signals differences without altering experimental conditions. In this study, we estimated fNIRS (through Sample Entropy metric) frontal cortex AD controls three that assess short-term-memory abilities (Clock Drawing Test, Digit Span Corsi Block Tapping Test). A channel-based the revealed AD-induced changes. Importantly, multivariate provided good specificity sensitivity This outcome was compared cognitive performances were predictive only one test. Our results demonstrated capabilities metric

Language: Английский

Citations

39
BCI Monitor Enhances Electroencephalographic and Cerebral Hemodynamic Activations During Motor Training DOI
Zhongpeng Wang, Yijie Zhou, Long Chen

et al.

IEEE Transactions on Neural Systems and Rehabilitation Engineering, Journal Year: 2019, Volume and Issue: 27(4), P. 780 - 787

Published: March 7, 2019

Motor imagery-based brain-computer interface (MI-BCI) controlling functional electrical stimulation (FES) is promising for disabled patients to restore their motor functions. However, it remains unclear how much the BCI part can contribute coupling between brain and muscle. Specifically, whether enhance cerebral activation training? Here, we investigate electroencephalographic hemodynamic responses MI-BCI-FES training MI-FES training, respectively. Twelve healthy subjects were recruited in study when concurrent electroencephalography (EEG) near-infrared spectroscopy (fNIRS) recorded. Compared with conditions, could induce significantly stronger event-related desynchronization (ERD) blood oxygen response, which demonstrates that indeed plays a role closed-loop training. Therefore, this paper verifies feasibility of using train functions manner.

Language: Английский

Citations

39