NIRS-EEG joint imaging during transcranial direct current stimulation: Online parameter estimation with an autoregressive model

Sood, Mehak; Besson, Pierre; Muthalib, Makii; Jindal, Utkarsh; Perrey, Stéphane; Dutta, Anirban; Hayashibe, Mitsuhiro

doi:10.1016/j.jneumeth.2016.09.008

Cited by 51 publications

(110 citation statements)

References 45 publications

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“…Thus, multimodal measures of corticospinal, corticocortical, cortico-thalamic and cortico-sub-cortical excitability, depending on the area of stimulation, are highly recommended to help to clarify whether there is an effect of tDCS and through which mechanisms it could impact on performance. Monitoring tDCS neuromodulatory effects can be measured using electroencephalography (EEG) in conjunction with near-infrared spectroscopy (NIRS) [91]. Simultaneous use of one or two neuroimaging modalities can reveal bi-directional or uni-directional information flow patterns between the SMC, PMC and DLPFC brain regions, the three core regions of the cortical sensorimotor network for movement control.…”

Section: Tdcs For Improving Muscle Strength In Isometric Exercisementioning

confidence: 99%

Effect of transcranial direct current stimulation on exercise performance: A systematic review and meta-analysis

et al. 2019

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Section: Tdcs For Improving Muscle Strength In Isometric Exercisementioning

confidence: 99%

Effect of transcranial direct current stimulation on exercise performance: A systematic review and meta-analysis

et al. 2019

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“…A lot of research has been carried out in this area for stroke patients. The most recent work in this context has used EEG–NIRS joint imaging for the measurement of the brain recovery of stroke patients after tDCS stimulation (Das et al, 2016; Guhathakurta and Dutta, 2016; Sood et al, 2016). …”

Section: Applicationsmentioning

confidence: 99%

Hybrid Brain–Computer Interface Techniques for Improved Classification Accuracy and Increased Number of Commands: A Review

2017

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In this article, non-invasive hybrid brain–computer interface (hBCI) technologies for improving classification accuracy and increasing the number of commands are reviewed. Hybridization combining more than two modalities is a new trend in brain imaging and prosthesis control. Electroencephalography (EEG), due to its easy use and fast temporal resolution, is most widely utilized in combination with other brain/non-brain signal acquisition modalities, for instance, functional near infrared spectroscopy (fNIRS), electromyography (EMG), electrooculography (EOG), and eye tracker. Three main purposes of hybridization are to increase the number of control commands, improve classification accuracy and reduce the signal detection time. Currently, such combinations of EEG + fNIRS and EEG + EOG are most commonly employed. Four principal components (i.e., hardware, paradigm, classifiers, and features) relevant to accuracy improvement are discussed. In the case of brain signals, motor imagination/movement tasks are combined with cognitive tasks to increase active brain–computer interface (BCI) accuracy. Active and reactive tasks sometimes are combined: motor imagination with steady-state evoked visual potentials (SSVEP) and motor imagination with P300. In the case of reactive tasks, SSVEP is most widely combined with P300 to increase the number of commands. Passive BCIs, however, are rare. After discussing the hardware and strategies involved in the development of hBCI, the second part examines the approaches used to increase the number of control commands and to enhance classification accuracy. The future prospects and the extension of hBCI in real-time applications for daily life scenarios are provided.

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“…Neuroimaging methods can be used to provide information about the brain-tissue effects of the tDCS electric fields when measured in a resting-state during (15)(16)(17)(18)(19)(20)(21)(22) and/or after (23-25) neurostimulation. Hemodynamic-based neuroimaging methods, such as positron emission tomography (PET), functional magnetic resonance imaging (fMRI), and functional near-infrared spectroscopy (fNIRS), detect cerebral hemodynamic changes based on neurovascular coupling mechanisms (26,27).…”

Section: Introductionmentioning

confidence: 99%

“…fNIRS being a noninvasive and portable optical neuroimaging technique is ideal for in vivo monitoring of brain hemodynamics during and/or after tDCS in naturalistic settings (4,13,(20)(21)(22)25,(32)(33)(34)(35). Moreover, since fNIRS uses optically based measurements of light intensity, electrically induced artifacts do not influence it.…”

Section: Introductionmentioning

confidence: 99%

Focal Hemodynamic Responses in the Stimulated Hemisphere During High-Definition Transcranial Direct Current Stimulation

Muthalib

Besson

Rothwell

et al. 2018

Neuromodulation: Technology at the Neural Interface

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Objective: High-definition tDCS (HD-tDCS) using a 4x1 electrode montage has been previously shown to constrain the electric field within the spatial extent of the electrodes. The aim of this study was to determine if functional near-infrared spectroscopy (fNIRS) neuroimaging can be used to determine a hemodynamic correlate of this 4x1 HD-tDCS electric field on the brain. Materials and Methods:In a 3 session cross-over study design, 13 healthy males received sham (2mA, 30s) and real (HD-tDCS-1 and HD-tDCS-2, 2mA, 10min) anodal HD-tDCS targeting the left M1 via a 4x1 electrode montage (anode C3, 4 return electrodes 3.5cm from anode). fNIRS was used to measure changes in brain hemodynamics (oxygenated hemoglobin integral-O2Hbint) during each 10min session from 2 regions of interest (ROIs) in the stimulated left hemisphere that corresponded to "within" (Lin) and "outside" (Lout) the spatial extent of the 4x1 electrode montage, and 2 corresponding ROIs (Rin and Rout) in the right hemisphere. Results:The ANOVA showed that both real anodal HD-tDCS compared to sham induced a significantly greater O2Hbint in the Lin than Lout ROIs of the stimulated left hemisphere; while there were no significant differences between the real and sham sessions for the right hemisphere ROIs. Intra-class correlation coefficients for the 2 real HD-tDCS sessions showed "fair to good" reproducibility for Lin (0.54) and Lout (0.52) ROIs. Conclusion:The greater O2Hbint "within" than "outside" the spatial extent of the 4x1 electrode montage represents a hemodynamic correlate of the electrical field distribution, and thus provides a prospective reliable method to determine the dose of stimulation that is necessary to optimize HD-tDCS parameters in various applications.

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NIRS-EEG joint imaging during transcranial direct current stimulation: Online parameter estimation with an autoregressive model

Abstract: Our new online ARX model based tracking method allows continuous assessment of the transient coupling between the electrophysiological (EEG) and the hemodynamic (NIRS) signals representing resting-state spontaneous brain activation during anodal tDCS.

Cited by 51 publications

References 45 publications

Effect of transcranial direct current stimulation on exercise performance: A systematic review and meta-analysis

Effect of transcranial direct current stimulation on exercise performance: A systematic review and meta-analysis

Hybrid Brain–Computer Interface Techniques for Improved Classification Accuracy and Increased Number of Commands: A Review

Focal Hemodynamic Responses in the Stimulated Hemisphere During High-Definition Transcranial Direct Current Stimulation

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