scholarly journals Deconvolution of hemodynamic responses along the cortical surface using personalized functional near infrared spectroscopy

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
A Machado ◽  
Z Cai ◽  
T Vincent ◽  
G Pellegrino ◽  
J-M Lina ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Temporal Dynamics ◽  
Optical Tomography ◽  
Cortical Surface ◽  
Functional Near Infrared Spectroscopy ◽  
Large Variability ◽  
Deconvolution Analysis ◽  
Concentration Changes

AbstractIn functional near infrared spectroscopy (fNIRS), deconvolution analysis of oxy and deoxy-hemoglobin concentration changes allows estimating specific hemodynamic response functions (HRF) elicited by neuronal activity, taking advantage of the fNIRS excellent temporal resolution. Diffuse optical tomography (DOT) is also becoming the new standard reconstruction procedure as it is more accurate than the modified Beer Lambert law approach at the sensor level. The objective of this study was to assess the relevance of HRF deconvolution after DOT constrained along the cortical surface. We used local personalized fNIRS montages which consists in optimizing the position of fNIRS optodes to ensure maximal sensitivity to subject specific target brain regions. We carefully evaluated the accuracy of deconvolution when applied after DOT, using realistic simulations involving several HRF models at different signal to noise ratio (SNR) levels and on real data related to motor and visual tasks in healthy subjects and from spontaneous pathological activity in one patient with epilepsy. We demonstrated that DOT followed by deconvolution was able to accurately recover a large variability of HRFs over a large range of SNRs. We found good performances of deconvolution analysis for SNR levels usually encountered in our applications and we were able to reconstruct accurately the temporal dynamics of HRFs in real conditions.

scholarly journals Imaging System Based on Silicon Photomultipliers and Light Emitting Diodes for Functional Near-Infrared Spectroscopy

2020 ◽  
Vol 10 (3) ◽  
pp. 1068 ◽  
Author(s):  
Giovanni Maira ◽  
Antonio M. Chiarelli ◽  
Stefano Brafa ◽  
Sebania Libertino ◽  
Giorgio Fallica ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Human Brain ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Light Emitting Diodes ◽  
Optical Tomography ◽  
System Optimization ◽  
Infrared Light ◽  
Functional Near Infrared Spectroscopy ◽  
Light Emitting

We built a fiber-less prototype of an optical system with 156 channels each one consisting of an optode made of a silicon photomultiplier (SiPM) and a pair of light emitting diodes (LEDs) operating at 700 nm and 830 nm. The system uses functional near-infrared spectroscopy (fNIRS) and diffuse optical tomography (DOT) imaging of the cortical activity of the human brain at frequencies above 1 Hz. In this paper, we discuss testing and system optimization performed through measurements on a multi-layered optical phantom with mechanically movable parts that simulate near-infrared light scattering inhomogeneities. The baseline optical characteristics of the phantom are carefully characterized and compared to those of human tissues. Here we discuss several technical aspects of the system development, such as LED light output drift and its possible compensation, SiPM linearity, corrections of channel signal differences, and signal-to-noise ratio (SNR). We implement an imaging algorithm that investigates large phantom regions. Thanks to the use of SiPMs, very large source-to-detector distances are acquired with a high SNR and 2 Hz time resolution. The overall results demonstrate the high potentialities of a system based on SiPMs for fNIRS/DOT human brain imaging applications.

Algorithm Establishment with Model Experiment for Continuous-Wave Functional Near-Infrared Spectroscopy

2011 ◽  
Vol 138-139 ◽  
pp. 553-559
Author(s):  
Ting Li ◽  
Zhi Li Zhang ◽  
Yi Zheng
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Model Experiment ◽  
Near Infrared ◽  
Continuous Wave ◽  
Valsalva Maneuver ◽  
Hemoglobin Concentration ◽  
Functional Near Infrared Spectroscopy ◽  
Concentration Changes

Although functional near-infrared spectroscopy (fNIRS) has been developing as a useful tool for monitoring functional brain activity since the early 1990s, the quantification of hemoglobin concentration changes is still controversial and there are few detailed reports especially for continuous-wave (CW) instruments. By means of a two-layer model experiment mimicking hemodynamic changes in brain and mathematical analysis based on the modified Beer-Lambert law, we established an algorithm for a CW functional near-infrared spectroscopy (CW-fNIRS). The accuracy of this algorithm was validated both in comparison with direct measurements on brain tissue model and in vivo measurement upon human valsalva maneuver. This described method can also be utilized for other CW-fNIRS instruments to establish measuring algorithm.

scholarly journals Measuring speaker-listener neural coupling with functional near infrared spectroscopy

2016 ◽  
Author(s):  
Yichuan Liu ◽  
Elise A. Piazza ◽  
Erez Simony ◽  
Patricia A. Shewokis ◽  
Banu Onaral ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Brain Activity ◽  
Hemoglobin Concentration ◽  
Verbal Communication ◽  
Story Comprehension ◽  
Speech Comprehension ◽  
Functional Near Infrared Spectroscopy ◽  
Concentration Changes

AbstractThe present study investigates brain-to-brain coupling, defined as inter-subject correlations in the hemodynamic response, during natural verbal communication. We used functional near-infrared spectroscopy (fNIRS) to record brain activity of speakers telling stories and listeners comprehending audio recordings of these stories. Listeners’ brain activity was correlated with speakers’ with a delay. This between-brain correlation disappeared when verbal communication failed. We further compared the fNIRS and functional Magnetic Resonance Imaging (fMRI) recordings of listeners comprehending the same story and found a relationship between the fNIRS oxygenated-hemoglobin concentration changes and the fMRI BOLD in brain areas associated with speech comprehension. This correlation between fNIRS and fMRI was only present when data from the same story were compared between the two modalities and vanished when data from different stories were compared; this cross-modality consistency further highlights the reliability of the spatiotemporal brain activation pattern as a measure of story comprehension. Our findings suggest that fNIRS is a powerful tool for investigating brain-to-brain coupling during verbal communication. As fNIRS sensors are relatively low-cost and can even be built into wireless, portable, battery-operated systems, these results highlight the potential of broad utilization of this approach in everyday settings for augmenting communication and interaction.

scholarly journals DISCRIMINATION OF MENTAL WORKLOAD LEVELS IN HUMAN SUBJECTS WITH FUNCTIONAL NEAR-INFRARED SPECTROSCOPY

2008 ◽  
Vol 01 (02) ◽  
pp. 227-237 ◽  
Author(s):  
ANGELO SASSAROLI ◽  
FENG ZHENG ◽  
LEANNE M. HIRSHFIELD ◽  
AUDREY GIROUARD ◽  
ERIN TREACY SOLOVEY ◽  
...  
Keyword(s):  
Working Memory ◽  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Nearest Neighbor ◽  
Mental Workload ◽  
Human Subjects ◽  
Success Rates ◽  
Functional Near Infrared Spectroscopy ◽  
Concentration Changes

We have applied functional near-infrared spectroscopy (fNIRS) to the human forehead to distinguish different levels of mental workload on the basis of hemodynamic changes occurring in the prefrontal cortex. We report data on 3 subjects from a protocol involving 3 mental workload levels based on to working memory tasks. To quantify the potential of fNIRS for mental workload discrimination, we have applied a 3-nearest neighbor classification algorithm based on the amplitude of oxyhemoglobin ( HbO 2) and deoxyhemoglobin ( HbR ) concentration changes associated with the working memory tasks. We have found classification success rates in the range of 44–72%, which are significantly higher than the corresponding chance level (for random data) of 19.1%. This work shows the potential of fNIRS for mental workload classification, especially when more parameters (rather than just the amplitude of concentration changes used here) and more sophisticated classification algorithms (rather than the simple 3-nearest neighbor algorithm used here) are considered and optimized for this application.

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.

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