Functional near-infrared spectroscopy in conjunction with electroencephalography of cerebellar transcranial direct current stimulation responses in the latent neurovascular coupling space – a chronic stroke study

2020 ◽  
Author(s):  
Zeynab Rezaee ◽  
Shashi Ranjan ◽  
Dhaval Solanki ◽  
Mahasweta Bhattacharya ◽  
MV Padma Srivastava ◽  
...  

AbstractCerebellar transcranial direct current stimulation (ctDCS) can facilitate motor learning; however, ctDCS effects have not been investigated using portable neuroimaging vis-à-vis lobular electric field strength. This is important since the subject-specific residual architecture for cerebellar interconnections with the cerebral cortex, including the prefrontal cortex (PFC) and the sensorimotor cortex (SMC), can influence the ctDCS effects on the cerebral functional activation. In this study, we investigated functional near-infrared spectroscopy (fNIRS) in conjunction with electroencephalography (EEG) to measure the changes in the brain activation at the PFC and the SMC following virtual reality (VR)-based Balance Training (VBaT), before and after ctDCS treatment in 12 hemiparetic chronic stroke survivors. Furthermore, we performed general linear modeling (GLM) that can putatively associate the lobular electric field strength due to ctDCS priming with the changes in the fNIRS-EEG measures in the chronic stroke survivors. Here, fNIRS-EEG based measures were investigated in their latent space found using canonical correlation analysis (CCA) that is postulated to capture neurovascular coupling. We found that the ctDCS electrode montage, as well as the state (pre-intervention, during intervention, post-intervention), had a significant (p<0.05) effect on the changes in the canonical scores of oxy-hemoglobin (O2Hb) signal measured with fNIRS. Also, skill acquisition during first exposure to VBaT decreased the activation (canonical score of O2Hb) of PFC of the non-lesioned hemisphere in the novices at their first exposure before the ctDCS intervention. Moreover, ctDCS intervention targeting the leg representation in the cerebellum led to a decrease in the canonical scores of O2Hb at the lesioned SMC, which is postulated to be related to the cerebellar brain inhibition. Furthermore, ctDCS electrode montage, as well as the state, had a significant (p<0.05) interaction effect on the canonical scores of log10-transformed EEG bandpower. Our current study showed the feasibility of fNIRS-EEG imaging of the ctDCS responses in the latent neurovascular coupling space that can not only be used for monitoring the dynamical changes in the brain activation associated with ctDCS-facilitated VBaT, but may also be useful in subject-specific current steering for tDCS to target the cerebral fNIRS-EEG sources to reduce inter-individual variability.

2021 ◽  
Author(s):  
Faezeh Moradi ◽  
Shima T. Moein ◽  
Issa Zakeri ◽  
Kambiz Pourrezaei

AbstractAn objective approach for odor detection is to analyze the brain activity using imaging techniques during the odor stimulation. In this study, Functional Near Infrared Spectroscopy (fNIRS) is used to record hemodynamic response from the frontal region of the brain by using a 4-channel fNIRS system. The fNIRs data is collected during the odor detection task in which the subjects were asked to press a button when they detect the given odor. Functional Data Analysis (FDA) was applied on fNIRs data to convert discrete measured samples of data to continuous smooth curves. The FDA method enables us to use the bases coefficients of fNIRS smoothed curves for features that represent the shape of the raw fNIRS signal. With the learning algorithm that we proposed, these features were used to train the support vector machine classifier. We evaluated the odor detection problem, in two binary classification cases: odorant vs. non-odorant and odorant vs. fingertapping. The model achieved a classification accuracy of 94.12% and 97.06% over the stimulus condition in the two cases, respectively. Moreover to find the actual predictors we used the extracted defined features (slope, standard deviation, and delta) to train our classifier. We achieved an average accuracy of 91.18 % on classifying odorant vs. non-odorant and an accuracy of 94.12% for odorant vs. fingertapping on the stimulus condition. The results determined that fNIRs signals of odorant and non-odorant are distinguishable without being affected by the motor activity during the experiment.These findings suggest that fNIRs measurement on the forehead could be potentially used for objective and comparably inexpensive assessment of odor detection in cases that the subjective report is unreliable.


Biosensors ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. 389
Author(s):  
Kogulan Paulmurugan ◽  
Vimalan Vijayaragavan ◽  
Sayantan Ghosh ◽  
Parasuraman Padmanabhan ◽  
Balázs Gulyás

Functional Near-Infrared Spectroscopy (fNIRS) is a wearable optical spectroscopy system originally developed for continuous and non-invasive monitoring of brain function by measuring blood oxygen concentration. Recent advancements in brain–computer interfacing allow us to control the neuron function of the brain by combining it with fNIRS to regulate cognitive function. In this review manuscript, we provide information regarding current advancement in fNIRS and how it provides advantages in developing brain–computer interfacing to enable neuron function. We also briefly discuss about how we can use this technology for further applications.


2020 ◽  
Author(s):  
Su-Hyun Lee ◽  
Hwang-Jae Lee ◽  
Youngbo Shim ◽  
Won Hyuk Chang ◽  
Byung-Ok Choi ◽  
...  

Abstract BackgroundGait dysfunction is common in post-stroke patients as a result of impairment in cerebral gait mechanism. Powered robotic exoskeletons are promising tools to maximize neural recovery by delivering repetitive walking practice.ObjectivesThe purpose of this study was to investigate the modulating effect of the Gait Enhancing and Motivating System-Hip (GEMS-H) on cortical activation during gait in patients with chronic stroke. Methods. Twenty chronic stroke patients performed treadmill walking at a self-selected speed either with assistance of GEMS-H (GEMS-H) or without assistance of GEMS-H (NoGEMS-H). Changes in oxygenated hemoglobin (oxyHb) concentration in the bilateral primary sensorimotor cortex (SMC), premotor cortices (PMC), supplemental motor areas (SMA), and prefrontal cortices (PFC) were recorded using functional near infrared spectroscopy.ResultsWalking with the GEMS-H promoted symmetrical SMC activation, with more activation in the affected hemisphere than in NoGEMS-H conditions. GEMS-H also decreased oxyHb concentration in the late phase over the ipsilesional SMC and bilateral SMA.ConclusionsThe results of the present study reveal that the GEMS-H promoted more SMC activation and a balanced activation pattern that helped to restore gait function. Less activation in the late phase over SMC and SMA during gait with GEMS-H indicates that GEMS-H reduces the cortical participation of stroke gait by producing rhythmic hip flexion and extension movement and allows a more coordinate and efficient gait patterns.Clinical trial registration: NCT03048968. Registered 09 February 2017


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