Accurate Image-guided (Re)Placement of NIRS Probes

Wu, Shin-Ting; Silva, José Angel Iván Rubianes; Novi, Sérgio L.; Souza, Nicolas Gabriel S.R. de; Forero, Edwin Johan; Mesquita, Rickson C.

doi:10.1016/j.cmpb.2020.105844

Cited by 15 publications

(22 citation statements)

References 48 publications

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“…This could lead to variability in cap placement across participants, thus affecting the sensitivity of the probes to underlying brain areas Abdalmalak et al (2020) . A more sophisticated approach using a real-time neuronavigation system could decrease the variability in cap placement and increase the average correlation within each brain network, further strengthening our results ( Novi et al, 2020a ; Wu et al, 2021 ).…”

Section: Discussionsupporting

confidence: 82%

Effects of Systemic Physiology on Mapping Resting-State Networks Using Functional Near-Infrared Spectroscopy

et al. 2022

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Resting-state functional connectivity (rsFC) has gained popularity mainly due to its simplicity and potential for providing insights into various brain disorders. In this vein, functional near-infrared spectroscopy (fNIRS) is an attractive choice due to its portability, flexibility, and low cost, allowing for bedside imaging of brain function. While promising, fNIRS suffers from non-neural signal contaminations (i.e., systemic physiological noise), which can increase correlation across fNIRS channels, leading to spurious rsFC networks. In the present work, we hypothesized that additional measurements with short channels, heart rate, mean arterial pressure, and end-tidal CO2 could provide a better understanding of the effects of systemic physiology on fNIRS-based resting-state networks. To test our hypothesis, we acquired 12 min of resting-state data from 10 healthy participants. Unlike previous studies, we investigated the efficacy of different pre-processing approaches in extracting resting-state networks. Our results are in agreement with previous studies and reinforce the fact that systemic physiology can overestimate rsFC. We expanded on previous work by showing that removal of systemic physiology decreases intra- and inter-subject variability, increasing the ability to detect neural changes in rsFC across groups and over longitudinal studies. Our results show that by removing systemic physiology, fNIRS can reproduce resting-state networks often reported with functional magnetic resonance imaging (fMRI). Finally, the present work details the effects of systemic physiology and outlines how to remove (or at least ameliorate) their contributions to fNIRS signals acquired at rest.

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Section: Discussionsupporting

confidence: 82%

Effects of Systemic Physiology on Mapping Resting-State Networks Using Functional Near-Infrared Spectroscopy

et al. 2022

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“…Although the high fNIRS variability is often attributed to low SNR, motion artifacts, and physiological noise, 127 – 132 recent works have shown that the lack of spatial information plays an important role in the observed fNIRS variability, particularly in low-density probes. 132 , 133 Variability in probe placement across subjects or sessions increases the fNIRS variance and reduces statistical power in data analysis. In some cases, marginal changes that are deemed statistically significant may merely reflect heterogeneity from underlying anatomy rather than brain functional changes.…”

Section: Data Analysis and Algorithmsmentioning

confidence: 99%

“… 138 Another powerful alternative approach employs real-time neuronavigation software to guide the optode positioning. 132 , 133 , 139 With real-time feedback, one can precisely position the optodes on the subject’s head and guarantee the NIRS optodes are on the target ROI before any measurement is taken, thus reducing variability due to spatial imprecisions. When applied to a longitudinal study, this approach doubled the intra-subject reproducibility and increased the fNIRS sensitivity to detect hemodynamic changes during a motor task ( Fig.…”

Section: Data Analysis and Algorithmsmentioning

confidence: 99%

Optical imaging and spectroscopy for the study of the human brain: status report

et al. 2022

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. This report is the second part of a comprehensive two-part series aimed at reviewing an extensive and diverse toolkit of novel methods to explore brain health and function. While the first report focused on neurophotonic tools mostly applicable to animal studies, here, we highlight optical spectroscopy and imaging methods relevant to noninvasive human brain studies. We outline current state-of-the-art technologies and software advances, explore the most recent impact of these technologies on neuroscience and clinical applications, identify the areas where innovation is needed, and provide an outlook for the future directions.

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“…The most accurate optode array design results from individual anatomical information in combination with individual 3-dimensional optode coordinates that are obtained by digitization or neuronavigation tools [78][79][80] . The precision of this procedure can be further improved by incorporating functional MRI data of the same participant or based on a probabilistic approach 78 .…”

Section: Optode Array Design and Optode Placementmentioning

confidence: 99%

Using preregistration as a tool for transparent fNIRS study design

Schroeder¹,

Artemenko²,

Kosie

et al. 2022

Preprint

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Significance: The expansion of fNIRS methodology and analysis tools give rise to various design and analytical decisions researchers have to make. Several recent efforts have developed guidelines for preprocessing, analyzing, and reporting practices. For the planning stage of fNIRS studies, similar guidance would be desirable. Study preregistration helps researchers to transparently document study protocols before conducting the study - including materials, methods and analyses - and thus others to verify, understand, and reproduce a study. Preregistration can thus serve as a useful tool for transparent, careful and comprehensive fNIRS study design. Aim: We aim to create a guide about the design and analysis steps involved in fNIRS studies and provide a preregistration template specified for fNIRS studies.Approach: The presented preregistration guide has a strong focus on fNIRS specific requirements, and the associated template provides examples based on continuous-wave fNIRS studies conducted in humans. These can, however, be extended to other types of fNIRS studies. Results: On a step-by-step basis, we walk the fNIRS user through key methodological and analysis-related aspects central to a comprehensive fNIRS study design. These include items specific to the design of continuous-wave, task-based fNIRS studies, but also sections that are of general importance, including an in-depth elaboration on sample size planning. Conclusions: Our guide introduces these open science tools to the fNIRS community, providing researchers with an overview of key design aspects and specification recommendations for comprehensive study planning. As such it can be used as a template to preregister fNIRS studies or merely as a tool for transparent fNIRS study design.

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Accurate Image-guided (Re)Placement of NIRS Probes

Cited by 15 publications

References 48 publications

Effects of Systemic Physiology on Mapping Resting-State Networks Using Functional Near-Infrared Spectroscopy

Effects of Systemic Physiology on Mapping Resting-State Networks Using Functional Near-Infrared Spectroscopy

Optical imaging and spectroscopy for the study of the human brain: status report

Using preregistration as a tool for transparent fNIRS study design

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