scholarly journals Inferring deep-brain activity from cortical activity using functional near-infrared spectroscopy

2015 ◽  
Vol 6 (3) ◽  
pp. 1074 ◽  
Author(s):  
Ning Liu ◽  
Xu Cui ◽  
Daniel M. Bryant ◽  
Gary H. Glover ◽  
Allan L. Reiss
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Brain Activity ◽  
Cortical Activity ◽  
Functional Near Infrared Spectroscopy ◽  
Deep Brain

scholarly journals Functional Near-Infrared Spectroscopy for the Classification of Motor-Related Brain Activity on the Sensor-Level

Sensors ◽  
2020 ◽  
Vol 20 (8) ◽  
pp. 2362 ◽  
Author(s):  
Alexander E. Hramov ◽  
Vadim Grubov ◽  
Artem Badarin ◽  
Vladimir A. Maksimenko ◽  
Alexander N. Pisarchik
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
High Efficiency ◽  
Brain Activity ◽  
Blood Oxygenation ◽  
Hemispheric Lateralization ◽  
Motor Execution ◽  
Functional Near Infrared Spectroscopy

Sensor-level human brain activity is studied during real and imaginary motor execution using functional near-infrared spectroscopy (fNIRS). Blood oxygenation and deoxygenation spatial dynamics exhibit pronounced hemispheric lateralization when performing motor tasks with the left and right hands. This fact allowed us to reveal biomarkers of hemodynamical response of the motor cortex on the motor execution, and use them for designing a sensing method for classification of the type of movement. The recognition accuracy of real movements is close to 100%, while the classification accuracy of imaginary movements is lower but quite high (at the level of 90%). The advantage of the proposed method is its ability to classify real and imaginary movements with sufficiently high efficiency without the need for recalculating parameters. The proposed system can serve as a sensor of motor activity to be used for neurorehabilitation after severe brain injuries, including traumas and strokes.

Measurement of Train Driver’s Brain Activity by Functional Near-Infrared Spectroscopy (fNIRS)

2005 ◽  
Vol 37 (13-15) ◽  
pp. 1319-1338 ◽  
Author(s):  
Takashi Kojima ◽  
Hitoshi Tsunashima ◽  
Tomoki Shiozawa ◽  
Hiroki Takada ◽  
Takuji Sakai
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Brain Activity ◽  
Functional Near Infrared Spectroscopy

scholarly journals New Directions in Exercise Prescription: Is There a Role for Brain-Derived Parameters Obtained by Functional Near-Infrared Spectroscopy?

2020 ◽  
Vol 10 (6) ◽  
pp. 342 ◽  
Author(s):  
Fabian Herold ◽  
Thomas Gronwald ◽  
Felix Scholkmann ◽  
Hamoon Zohdi ◽  
Dominik Wyser ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Physical Exercise ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Exercise Prescription ◽  
Brain Activity ◽  
Brain Health ◽  
Functional Near Infrared Spectroscopy ◽  
Internal Load

In the literature, it is well established that regular physical exercise is a powerful strategy to promote brain health and to improve cognitive performance. However, exact knowledge about which exercise prescription would be optimal in the setting of exercise–cognition science is lacking. While there is a strong theoretical rationale for using indicators of internal load (e.g., heart rate) in exercise prescription, the most suitable parameters have yet to be determined. In this perspective article, we discuss the role of brain-derived parameters (e.g., brain activity) as valuable indicators of internal load which can be beneficial for individualizing the exercise prescription in exercise–cognition research. Therefore, we focus on the application of functional near-infrared spectroscopy (fNIRS), since this neuroimaging modality provides specific advantages, making it well suited for monitoring cortical hemodynamics as a proxy of brain activity during physical exercise.

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