Quantitative Assessment of Image Quality of Sparse Functional Near Infrared Spectroscopy vs High-Density Diffuse Optical Tomography

Author(s):  
Tracy M. Burns-Yocum
2020 ◽  
Vol 10 (3) ◽  
pp. 1068 ◽  
Author(s):  
Giovanni Maira ◽  
Antonio M. Chiarelli ◽  
Stefano Brafa ◽  
Sebania Libertino ◽  
Giorgio Fallica ◽  
...  

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.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
A Machado ◽  
Z Cai ◽  
T Vincent ◽  
G Pellegrino ◽  
J-M Lina ◽  
...  

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.


2019 ◽  
Author(s):  
Simon Huldreich Kohl ◽  
David Marc Anton Mehler ◽  
Michael Lührs ◽  
Robert T. Thibault ◽  
Kerstin Konrad ◽  
...  

Background: The effects of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI)-neurofeedback on brain activation and behaviors have been studied extensively in the past. More recently, researchers have begun to investigate the effects of functional near-infrared spectroscopy-based neurofeedback (fNIRS-neurofeedback). FNIRS is a functional neuroimaging technique based on brain hemodynamics, which is easy to use, portable, inexpensive, and has reduced sensitivity to movement artifacts.Method: We provide the first systematic review and database of fNIRS-neurofeedback studies, synthesizing findings from 22 peer-reviewed studies (including a total of N=441 participants; 337 healthy, 104 patients). We (1) give a comprehensive overview of how fNIRS-neurofeedback training protocols were implemented, (2) review the online signal-processing methods used, (3) evaluate the quality of studies using pre-set methodological and reporting quality criteria and also present statistical sensitivity/power analyses, (4) investigate the effectiveness of fNIRS-neurofeedback in modulating brain activation, and (5) review its effectiveness in changing behavior in healthy and pathological populations. Results and discussion: (1-2) Published studies are heterogeneous (e.g., neurofeedback targets, investigated populations, applied training protocols, and methods). (3) Large randomized controlled trials are still lacking. In view of the novelty of the field, the quality of the published studies is moderate. We identified room for improvement in reporting important information and statistical power to detect realistic effects. (4) Several studies show that people can regulate hemodynamic signals from cortical brain regions with fNIRS-neurofeedback and (5) these studies indicate the feasibility of modulating motor control and prefrontal brain functioning in healthy participants and ameliorating symptoms in clinical populations (stroke, ADHD, autism, and social anxiety). However, valid conclusions about specificity or potential clinical utility are premature. Conclusion: Due to the advantages of practicability and relatively low cost, fNIRS-neurofeedback might provide a suitable and powerful alternative to EEG and fMRI neurofeedback and has great potential for clinical translation of neurofeedback. Together with more rigorous research and reporting practices, further methodological improvements may lead to a more solid understanding of fNIRS-neurofeedback. Future research will benefit from exploiting the advantages of fNIRS, which offers unique opportunities for neurofeedback research.


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