Functional near-infrared spectroscopy to probe sensorimotor region activation during electrical stimulation-evoked movement

2017 ◽  
Vol 38 (5) ◽  
pp. 816-822 ◽  
Author(s):  
Makii Muthalib ◽  
Marco Ferrari ◽  
Valentina Quaresima ◽  
Graham Kerr ◽  
Stephane Perrey
Keyword(s):  
Electrical Stimulation ◽  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Functional Near Infrared Spectroscopy ◽  
Sensorimotor Region

scholarly journals Median Nerve Electrical Stimulation–Induced Changes in Effective Connectivity in Patients With Stroke as Assessed With Functional Near-Infrared Spectroscopy

2019 ◽  
Vol 33 (12) ◽  
pp. 1008-1017 ◽  
Author(s):  
Congcong Huo ◽  
Xinglou Li ◽  
Jing Jing ◽  
Yanping Ma ◽  
Wenhao Li ◽  
...  
Keyword(s):  
Electrical Stimulation ◽  
Infrared Spectroscopy ◽  
Median Nerve ◽  
Near Infrared Spectroscopy ◽  
Resting State ◽  
Near Infrared ◽  
Cerebral Oxygenation ◽  
Effective Connectivity ◽  
Stroke Patients ◽  
Functional Near Infrared Spectroscopy

Background. The cortical plastic changes in response to median nerve electrical stimulation (MNES) in stroke patients have not been entirely illustrated. Objective. This study aimed to investigate MNES-related changes in effective connectivity (EC) within a cortical network after stroke by using functional near-infrared spectroscopy (fNIRS). Methods. The cerebral oxygenation signals in the bilateral prefrontal cortex (LPFC/RPFC), motor cortex (LMC/RMC), and occipital lobe (LOL/ROL) of 20 stroke patients with right hemiplegia were measured by fNIRS in 2 conditions: (1) resting state and (2) MNES applied to the right wrist. Coupling function together with dynamical Bayesian inference was used to assess MNES-related changes in EC among the cerebral low-frequency fluctuations. Results. Compared with the resting state, EC from LPFC and RPFC to LOL was significantly increased during the MNES state in stroke patients. Additionally, MNES triggered significantly higher coupling strengths from LMC and LOL to RPFC. The interregional main coupling direction was observed from LPFC to bilateral motor and occipital areas in responding to MNES, suggesting that MNES could promote the regulation function of ipsilesional prefrontal areas in the functional network. MNES can induce muscle twitch of the stroke-affected hand involving a decreased neural coupling of the contralesional motor area on the ipsilesional MC. Conclusions. MNES can trigger sensorimotor stimulations of the affected hand that sequentially involved functional reorganization of distant cortical areas after stroke. Investigating MNES-related changes in EC after stroke may help further our understanding of the neural mechanisms underlying MNES.

A Study of Frontal Signals in Brain Computer Interfaces: Interpretation of EEG & FNIRS

2020 ◽  
pp. 136-142
Author(s):  
S. Srilekha ◽  
B. Vanathi
Keyword(s):  
Infrared Spectroscopy ◽  
Healthy Subject ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Economic Conditions ◽  
Brain Computer Interfaces ◽  
Functional Near Infrared Spectroscopy ◽  
Computer Interfaces ◽  
Rehabilitation Devices

This paper focuses on electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) comparison to help the rehabilitation patients. Both methods have unique techniques and placement of electrodes. Usage of signals are different in application based on the economic conditions. This study helps in choosing the signal for the betterment of analysis. Ten healthy subject datasets of EEG & FNIRS are taken and applied to plot topography separately. Accuracy, Sensitivity, peaks, integral areas, etc are compared and plotted. The main advantages of this study are to prompt their necessities in the analysis of rehabilitation devices to manage their life as a typical individual.

61-LB: Use of Functional Near-Infrared Spectroscopy (fNIRS) to Assess Cognitive Effort in KATP-Related Neonatal Diabetes (KATP-NDM)

Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 61-LB
Author(s):  
LISA R. LETOURNEAU-FREIBERG ◽  
KIMBERLY L. MEIDENBAUER ◽  
ANNA M. DENSON ◽  
PERSEPHONE TIAN ◽  
KYOUNG WHAN CHOE ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Neonatal Diabetes ◽  
Cognitive Effort ◽  
Functional Near Infrared Spectroscopy

The Use of fNIRS for Unique Contributions to Social and Affective Neuroscience

2019 ◽  
Author(s):  
Shannon Burns ◽  
Matthew D. Lieberman
Keyword(s):  
Infrared Spectroscopy ◽  
Social Interaction ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Affective Neuroscience ◽  
Functional Near Infrared Spectroscopy ◽  
Psychological Experience ◽  
The World ◽  
And Behavior ◽  
Meaningful Interaction

Social and affective neuroscience studies the neurophysiological underpinnings of psychological experience and behavior as it relates to the world around us. Yet, most neuroimaging methods require the removal of participants from their rich environment and the restriction of meaningful interaction with stimuli. In this Tools of the Trade article, we explain functional near infrared spectroscopy (fNIRS) as a neuroimaging method that can address these concerns. First, we provide an overview of how fNIRS works and how it compares to other neuroimaging methods common in social and affective neuroscience. Next, we describe fNIRS research that highlights its usefulness to the field – when rich stimuli engagement or environment embedding is needed, studies of social interaction, and examples of how it can help the field become more diverse and generalizable across participant populations. Lastly, this article describes how to use fNIRS for neuroimaging research with points of advice that are particularly relevant to social and affective neuroscience studies.

The application of functional near-infrared spectroscopy in social cognitive neuroscience

2017 ◽  
Vol 25 (5) ◽  
pp. 731
Author(s):  
Peixia YE ◽  
Ruida ZHU ◽  
Honghong TANG ◽  
Xiaoqin MAI ◽  
Chao LIU
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Cognitive Neuroscience ◽  
Social Cognitive ◽  
Near Infrared ◽  
Functional Near Infrared Spectroscopy ◽  
Social Cognitive Neuroscience

Toward Neuroscience of the Everyday World (NEW) using functional near-infrared spectroscopy

2021 ◽  
Vol 18 ◽  
pp. 100272
Author(s):  
Alexander von Lühmann ◽  
Yilei Zheng ◽  
Antonio Ortega-Martinez ◽  
Swathi Kiran ◽  
David C. Somers ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Functional Near Infrared Spectroscopy ◽  
The Everyday ◽  
Everyday World

scholarly journals Classification of Prefrontal Cortex Activity Based on Functional Near-Infrared Spectroscopy Data upon Olfactory Stimulation

2021 ◽  
Vol 11 (6) ◽  
pp. 701
Author(s):  
Cheng-Hsuan Chen ◽  
Kuo-Kai Shyu ◽  
Cheng-Kai Lu ◽  
Chi-Wen Jao ◽  
Po-Lei Lee
Keyword(s):  
Prefrontal Cortex ◽  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Kernel Functions ◽  
Olfactory Stimulation ◽  
Support Vector ◽  
Hemodynamic Response Function ◽  
Functional Near Infrared Spectroscopy ◽  
Data Set

The sense of smell is one of the most important organs in humans, and olfactory imaging can detect signals in the anterior orbital frontal lobe. This study assessed olfactory stimuli using support vector machines (SVMs) with signals from functional near-infrared spectroscopy (fNIRS) data obtained from the prefrontal cortex. These data included odor stimuli and air state, which triggered the hemodynamic response function (HRF), determined from variations in oxyhemoglobin (oxyHb) and deoxyhemoglobin (deoxyHb) levels; photoplethysmography (PPG) of two wavelengths (raw optical red and near-infrared data); and the ratios of data from two optical datasets. We adopted three SVM kernel functions (i.e., linear, quadratic, and cubic) to analyze signals and compare their performance with the HRF and PPG signals. The results revealed that oxyHb yielded the most efficient single-signal data with a quadratic kernel function, and a combination of HRF and PPG signals yielded the most efficient multi-signal data with the cubic function. Our results revealed superior SVM analysis of HRFs for classifying odor and air status using fNIRS data during olfaction in humans. Furthermore, the olfactory stimulation can be accurately classified by using quadratic and cubic kernel functions in SVM, even for an individual participant data set.

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