Bundled-Optode Method in Functional Near-Infrared Spectroscopy

Nguyen, Hoang-Dung; Hong, Keum–Shik; Shin, Yong‐Il

doi:10.1371/journal.pone.0165146

Cited by 62 publications

(36 citation statements)

References 71 publications

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“…To further confirm whether the channels showing initial dips were really active or not, the tvalues were computed by using the MATLAB function, robustfit [39,45,58]. This function compares the averaged HbO of each channel with the designed HR and returns the t-and pvalues.…”

Section: Resultsmentioning

confidence: 99%

Detection and classification of three-class initial dips from prefrontal cortex

Zafar

Hong

2016

Biomed. Opt. Express

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112

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In this paper, the use of initial dips using functional near-infrared spectroscopy (fNIRS) for brain-computer interface (BCI) is investigated. Features and window sizes for detecting initial dips are also discussed. Three mental tasks including mental arithmetic, mental counting, and puzzle solving are performed in obtaining fNIRS signals from the prefrontal cortex. Vector-based phase analysis method combined with a threshold circle, as a decision criterion, are used to detect the initial dips. Eight healthy subjects participate in experiment. Linear discriminant analysis is used as a classifier. To classify initial dips, five features (signal mean, peak value, signal slope, skewness, and kurtosis) of oxy-hemoglobin (HbO) and four different window sizes (0~1, 0~1.5, 0~2, and 0~2.5 sec) are examined. It is shown that a combination of signal mean and peak value and a time period of 0~2.5 sec provide the best average classification accuracy of 57.5% for three classes. To further validate the result, three-class classification using the conventional hemodynamic response (HR) is also performed, in which two features (signal mean and signal slope) and 2~7 sec window size have yielded the average classification accuracy of 65.9%. This reveals that fNIRS-based BCI using initial dip detection can reduce the command generation time from 7 sec to 2.5 sec while the classification accuracy is a bit sacrificed from 65.9% to 57.5% for three mental tasks. Further improvement can be made by using deoxy hemoglobin signals in coping with the slow HR problem.

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Section: Resultsmentioning

confidence: 99%

Detection and classification of three-class initial dips from prefrontal cortex

Zafar

Hong

2016

Biomed. Opt. Express

Self Cite

112

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“…Recent developments in the acquisition, processing, and 3-D representation of fNIRS signals allow for the presentation of hemodynamic signals that can be compared easily with those acquired using more traditional fMRI methods. 43,44 EEG-fNIRS experiments are well-suited to acquire electrocortical and hemodynamic signals related to faces.…”

Section: Introductionmentioning

confidence: 99%

Co-localization of theta-band activity and hemodynamic responses during face perception: simultaneous electroencephalography and functional near-infrared spectroscopy recordings

et al. 2019

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Face-specific neural processes in the human brain have been localized to multiple anatomical structures and associated with diverse and dynamic social functions. The question of how various face-related systems and functions may be bound together remains an active area of investigation. We hypothesize that face processing may be associated with specific frequency band oscillations that serve to integrate distributed face processing systems. Using a multimodal imaging approach, including electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS), simultaneous signals were acquired during face and object picture viewing. As expected for face processing, hemodynamic activity in the right occipital face area (OFA) increased during face viewing compared to object viewing, and in a subset of participants, the expected N170 EEG response was observed for faces. Based on recently reported associations between the theta band and visual processing, we hypothesized that increased hemodynamic activity in a face processing area would also be associated with greater theta-band activity originating in the same area. Consistent with our hypothesis, theta-band oscillations were also localized to the right OFA for faces, whereas alpha-and beta-band oscillations were not. Together, these findings suggest that theta-band oscillations originating in the OFA may be part of the distributed face-specific processing mechanism.

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“…Figure 3 depicts, in the form of a t-map, the spatial distribution together with the expected HR induced by a given stimulus (i.e., RGB-color stimulus). [63][64][65] However, as the signal strength in the target brain area cannot be revealed on a t-map, and the temporal magnitude of the HR must also be taken into account.…”

Section: Discussionmentioning

confidence: 99%

Detection of primary RGB colors projected on a screen using fNIRS

Liu

Hong

2017

J. Innov. Opt. Health Sci.

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In this study, functional near-infrared spectroscopy (fNIRS) is utilized to measure the hemodynamic responses (HRs) in the visual cortex of 14 subjects (aged 22-34 years) viewing the primary red, green, and blue (RGB) colors displayed on a white screen by a beam projector. The spatiotemporal characteristics of their oxygenated and deoxygenated hemoglobins (HbO and HbR) in the visual cortex are measured using a 15-source and 15-detector optode con¯guration. To see whether the activation maps upon RGB-color stimuli can be distinguished or not, the t-values of individual channels are averaged over 14 subjects. To¯nd the best combination of two features for classi¯cation, the HRs of activated channels are averaged over nine trials. The HbO mean, peak, slope, skewness and kurtosis values during 2-7 s window for a given 10 s stimulation period are analyzed. Finally, the linear discriminant analysis (LDA) for classifying three classes is applied. Individually, the best classi¯cation accuracy obtained with slope-skewness features was 74.07% (Subject 1), whereas the best overall over 14 subjects was 55.29% with peak-skewness combination. Noting that the chance level of 3-class classi¯cation is 33.33%, it can be said that RGB colors can be distinguished. The overall results reveal that fNIRS can be used for monitoring purposes of the HR patterns in the human visual cortex.

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Bundled-Optode Method in Functional Near-Infrared Spectroscopy

Cited by 62 publications

References 71 publications

Detection and classification of three-class initial dips from prefrontal cortex

Detection and classification of three-class initial dips from prefrontal cortex

Co-localization of theta-band activity and hemodynamic responses during face perception: simultaneous electroencephalography and functional near-infrared spectroscopy recordings

Detection of primary RGB colors projected on a screen using fNIRS

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