fMRI-based validation of continuous-wave fNIRS of supplementary motor area activation during motor execution and motor imagery

Wearable fNIRS platform for dense sampling and precision functional neuroimaging

Precision mental health aims to improve care by tailoring interventions based on individual neurobiological features. Functional near-infrared spectroscopy (fNIRS) is a cost-effective and portable alternative to traditional neuroimaging, making it a promising tool for this purpose. This study evaluates a self-administered, wearable fNIRS platform designed for precision mental health applications, focusing on its reliability and specificity in capturing individualized functional connectivity patterns. The platform incorporates a wireless, portable multichannel fNIRS device, augmented reality guidance for reproducible device placement, and a cloud-based system for remote data access. In this proof-of-concept study, eight adults completed ten dense-sampled sessions involving cognitive tasks and resting-state measurements. Results demonstrated high test-retest reliability and within-participant consistency in functional connectivity and activation patterns. These findings support the platform's feasibility for individualized functional mapping. Future research with larger and more diverse cohorts, including clinical populations, is necessary to explore its potential for disorder-specific applications.

Age-specific neural responses to SMA and M1 stimulation during implicit motor sequence learning: Insights from a concurrent tDCS-fNIRS approach

Implicit Motor Sequence Learning (IMSL) is critical for automating motor skills, yet it declines with age, impacting independence and quality of life. This study investigated the age-specific roles of the primary motor cortex (M1) and supplementary motor area (SMA) in IMSL using a novel concurrent transcranial direct current stimulation (tDCS) and functional near-infrared spectroscopy (fNIRS) approach. Twenty younger adults (21-32 years old [M = 24.3 ± 3.26]) and twenty older adults (60-76 years old [M = 67.5 ± 4.88]) performed a Serial Reaction Time Task (SRTT) in three cross-over, counterbalanced sessions with anodal tDCS targeting: i) SMALeft, ii) M1Left, or iii) sham stimulation during task. Neural activity and connectivity were measured pre-, during-, and post-stimulation using a 20-channel fNIRS, covering prefrontal, premotor, and motor regions. Results revealed significant age-related differences in SRTT performance, with older adults consistently performing poorer despite practice-driven improvements in both groups. While tDCS did not enhance motor learning behaviourally, distinct neural effects emerged, demonstrating age-specific modulation. In older adults, M1 stimulation elicited task- dependent, asymmetric O2Hb changes in the premotor area (PMA): decreased PMARight activity during sequence blocks and increased activity during random blocks, with opposite patterns in PMALeft. SMA stimulation normalised weak PMALeft-prefrontal connectivity in older adults, whereas younger adults showed strengthened connectivity between PMARight- PFCRight and PFCLeft-PFCRight, reflecting its role in spatial integration and motor planning. These findings advance the understanding of IMSL-related neuroplasticity, highlighting the importance of optimising tDCS protocols to support motor learning in ageing population.

Effects and mechanisms of synchronous virtual reality action observation and electrical stimulation on upper extremity motor function and activities of daily living in patients with stroke: a protocol for a randomized controlled trial

Background

Existing rehabilitation techniques are not satisfactory in improving motor function after stroke, resulting in heavy social burdens. With discovery of mirror neuron system (MNS), action observation (AO) has become a promising strategy to promote motor learning in rehabilitation. Based on MNS theory and virtual reality (VR) technology, we designed an innovative rehabilitative approach: synchronous 360° VR video AO (VRAO) and neuromuscular electrical stimulation (NMES). We hypothesized that VRAO+NMES could enhance MNS activation, thus to improve upper limb motor function and activities of daily living in stroke survivors.

Methods

To explore the efficacy and mechanism of VRAO+NMES, we designed this single center, evaluator blinded, prospective, two arm parallel group randomized controlled trial with 1:1 allocation ratio. The experiment group will receive VRAO+NMES, while the control group will receive VR landscape observation combined with NMES. The Fugl-Meyer Assessment for Upper Extremity is the primary outcome of this study, Brunstrom Recovery Stages for Upper Extremity, Manual Muscle Test, Range of Motion, Modified Barthel Index, and Functional Independence Measure are the secondary outcomes. In addition, functional near-infrared spectroscopy (fNIRS) and surface electromyography (sEMG) will be used to evaluate the activation of MNS brain regions and related muscles, respectively.

Discussion

Applying VR in AO therapy (AOT) has become popular, another study direction to improve AOT is to combine it with peripheral stimulations simultaneously. Due to its full immersive characteristic and multi-sensory input, 360° videos based VRAO+NMES could improve the motivation and engagement level of participants. In addition, fNIRS and sEMG test results may act as good biomarkers to predict rehabilitation outcomes, helping select suitable candidates for this new intervention.

Conclusion

The results of this study will provide evidence for the feasibility and potential clinical efficacy of VRAO+NMES in stroke rehabilitation, thus to promote the clinical applicability and generalize its use in hospital, community, and home rehabilitation settings.

Clinical trial registration

https://www.chictr.org.cn/showproj.html?proj=178276, Identifier [ChiCTR2200063552].

The Effect of Perceived Groove in Music on Effective Brain Connectivity during Cycling: An fNIRS Study

INTRODUCTION

Perceived groove, a complex and integrated musical characteristic, is considered a core factor in inducing synchronization between movement and music. This study aimed to use functional near-infrared spectroscopy to explore the effective connectivity (EC) changes among brain regions during cycling activities under different perceived groove conditions.

METHODS

In a randomized crossover design, 18 university students performed 3-min cycling tasks under high (HG) and low (LG) perceived groove music conditions. Revolutions per minute, coefficient of variation of pedaling cadence, and sensorimotor coupling index were measured. Granger causality analyses were performed on the functional near-infrared spectroscopy data from the cycling task to obtain EC matrices at the brain region and channel (Ch) levels.

RESULTS

The revolution per minute was significantly higher, and coefficient of variation of pedaling cadence and sensorimotor coupling index were significantly lower in HG than in LG. The EC values of the Brodmann area (BA) 8→the left prefrontal cortex (lPFC), the superior portion of BA 6 (BA 6_Sup)→lPFC, and BA 1-3→lPFC were significantly higher in HG than in LG. Channel analyses indicated that the EC values of Ch 14→Ch 9, Ch 41→Ch 9, Ch 14→Ch 10, Ch 41→Ch 10, Ch 31→Ch 10, and Ch 35→Ch 23 were significantly higher in HG than in LG. Correlation analysis revealed that the EC values of the channels included in BA 6_Sup→lPFC were significantly correlated with cycling performance metrics.

CONCLUSIONS

The EC changes from BA 6_Sup to lPFC may play a critical role in the process through which perceived groove affects the synchronization of cycling to music.

Applications and advances of combined fMRI-fNIRs techniques in brain functional research

Understanding the intricate functions of the human brain requires multimodal approaches that integrate complementary neuroimaging techniques. This review systematically examines the integration of functional magnetic resonance imaging (fMRI) and functional near-infrared spectroscopy (fNIRs) in brain functional research, addressing their synergistic potential, methodological advancements, clinical and neuroscientific applications, and persistent challenges. We conducted a comprehensive literature review of 63 studies (from PubMed and Web of Science up to September 2024) using keyword combinations such as fMRI, fNIRs, and multimodal imaging. Our analysis reveals three key findings: (1) Methodological Synergy: Combining fMRI's high spatial resolution with fNIRs's superior temporal resolution and portability enables robust spatiotemporal mapping of neural activity, validated across motor, cognitive, and clinical tasks. Additionally, this study examines experimental paradigms and data processing techniques essential for effective multimodal neuroimaging. (2) Applications: The review categorizes integration methodologies into synchronous and asynchronous detection modes, highlighting their respective applications in spatial localization, validation of efficacy, and mechanism discovery. Synchronous and asynchronous integration modes have advanced research in neurological disorders (e.g., stroke, Alzheimer's), social cognition, and neuroplasticity, while novel hyperscanning paradigms extend applications to naturalistic, interactive settings. (3) Challenges: Hardware incompatibilities (e.g., electromagnetic interference in MRI environments), experimental limitations (e.g., restricted motion paradigms), and data fusion complexities hinder widespread adoption. The future direction emphasizes hardware innovation (such as fNIR probe compatible with MRI), standardized protocol and data integration driven by machine learning, etc. to solve the depth limitation of fNIR and infer subcortical activities. This synthesis underscores the transformative potential of fMRI-fNIRs integration in bridging spatial and temporal gaps in neuroimaging, while enhancing diagnostic and therapeutic strategies and paving the way for future innovations in brain research.

Method for Using Functional Near-Infrared Spectroscopy (fNIRS) to Explore Music-Induced Brain Activation in Orchestral Musicians in Concert

The act of performing music may induce a specific state of mind, musicians potentially becoming immersed and detached from the rest of the world. May this be measured? Does this state of mind change based on repetition? In collaboration with Stavanger Symphony Orchestra (SSO), we developed protocols to investigate ongoing changes in the brain activation of a first violinist and a second violinist in real time during seven sequential, public concerts using functional near-infrared spectroscopy (fNIRS). Using wireless fNIRS systems (Brite MKII) from Artinis, we measured ongoing hemodynamic changes and projected the brain activation to the audience through the software OxySoft 3.5.15.2. We subsequently developed protocols for further analyses through the Matlab toolboxes Brainstorm and Homer2/Homer3. Our developed protocols demonstrate how one may use "functional dissection" to imply how the state of mind of musicians may alter while performing their art. We focused on a subset of cortical regions in the right hemisphere, but the current study demonstrates how fNIRS may be used to shed light on brain dynamics related to producing art in ecological and natural contexts on a general level, neither restricted to the use of musical instrument nor art form.

Deciphering brain activation during wrist movements: comparative fMRI and fNIRS analysis of active, passive, and imagery states

Understanding the complex activation patterns of brain regions during motor tasks is crucial. Integrated functional magnetic resonance imaging (fMRI) and functional near-infrared spectroscopy (fNIRS) offers advanced insights into how brain activity fluctuates with motor activities. This study explores neuronal activation patterns in the cerebral cortex during active, passive, and imagined wrist movements using these functional imaging techniques. Data were collected from 10 right-handed volunteers performing a motor task using fMRI and fNIRS. fMRI utilized a 3T scanner and a 20-channel head coil, while fNIRS recorded data with a 48-channel device at 765 nm and 855 nm. Analysis focused on key motor and sensory cortices using NIRS-SPM and SPM12, applying a significance threshold of p < 0.05 and a minimum cluster size of 10 voxels for group analysis. Super-threshold voxels were identified with FWE thresholding in SPM12. For activation map extraction we focused on the primary motor cortex, primary somatosensory cortex, somatosensory association cortex, premotor cortex, and supplementary motor cortex. Both fMRI and fNIRS detected activation in the primary motor cortex (M1). The primary somatosensory cortex was found to influence movement direction coding, with smaller activation sizes for upward movements. Combining fNIRS with fMRI provided clearer differentiation of brain activation patterns for wrist movements in various directions and conditions (p < 0.05). This study highlights variations in left motor cortex activity across different movement states. fNIRS proved effective in detecting brain function and showed strong correlation with fMRI results, suggesting it as a viable alternative for those unable to undergo fMRI.

From lab to life: challenges and perspectives of fNIRS for haemodynamic-based neurofeedback in real-world environments

Neurofeedback allows individuals to monitor and self-regulate their brain activity, potentially improving human brain function. Beyond the traditional electrophysiological approach using primarily electroencephalography, brain haemodynamics measured with functional magnetic resonance imaging (fMRI) and more recently, functional near-infrared spectroscopy (fNIRS) have been used (haemodynamic-based neurofeedback), particularly to improve the spatial specificity of neurofeedback. Over recent years, especially fNIRS has attracted great attention because it offers several advantages over fMRI such as increased user accessibility, cost-effectiveness and mobility-the latter being the most distinct feature of fNIRS. The next logical step would be to transfer haemodynamic-based neurofeedback protocols that have already been proven and validated by fMRI to mobile fNIRS. However, this undertaking is not always easy, especially since fNIRS novices may miss important fNIRS-specific methodological challenges. This review is aimed at researchers from different fields who seek to exploit the unique capabilities of fNIRS for neurofeedback. It carefully addresses fNIRS-specific challenges and offers suggestions for possible solutions. If the challenges raised are addressed and further developed, fNIRS could emerge as a useful neurofeedback technique with its own unique application potential-the targeted training of brain activity in real-world environments, thereby significantly expanding the scope and scalability of haemodynamic-based neurofeedback applications.This article is part of the theme issue 'Neurofeedback: new territories and neurocognitive mechanisms of endogenous neuromodulation'.

NiReject: toward automated bad channel detection in functional near-infrared spectroscopy

Significance

The increasing sample sizes and channel densities in functional near-infrared spectroscopy (fNIRS) necessitate precise and scalable identification of signals that do not permit reliable analysis to exclude them. Despite the relevance of detecting these "bad channels," little is known about the behavior of fNIRS detection methods, and the potential of unsupervised and semi-supervised machine learning remains unexplored.

Aim

We developed three novel machine learning-based detectors, unsupervised, semi-supervised, and hybrid NiReject, and compared them with existing approaches.

Approach

We conducted a systematic literature search and demonstrated the influence of bad channel detection. Based on 29,924 signals from two independently rated datasets and a simulated scenario space of diverse phenomena, we evaluated the NiReject models, six of the most established detection methods in fNIRS, and 11 prominent methods from other domains.

Results

Although the results indicated that a lack of proper detection can strongly bias findings, detection methods were reported in only 32% of the included studies. Semi-supervised models, specifically semi-supervised NiReject, outperformed both established thresholding-based and unsupervised detectors. Hybrid NiReject, utilizing a human feedback loop, addressed the practical challenges of semi-supervised methods while maintaining precise detection and low rating effort.

Conclusions

This work contributes toward more automated and reliable fNIRS signal quality control by comprehensively evaluating existing and introducing novel machine learning-based techniques and outlining practical considerations for bad channel detection.

Lights on music cognition: A systematic and critical review of fNIRS applications and future perspectives

Research investigating the neural processes related to music perception and production constitutes a well-established field within the cognitive neurosciences. While most neuroimaging tools have limitations in studying the complexity of musical experiences, functional Near-Infrared Spectroscopy (fNIRS) represents a promising, relatively new tool for studying music processes in both laboratory and ecological settings, which is also suitable for both typical and pathological populations across development. Here we systematically review fNIRS studies on music cognition, highlighting prospects and potentialities. We also include an overview of fNIRS basic theory, together with a brief comparison to characteristics of other neuroimaging tools. Fifty-nine studies meeting inclusion criteria (i.e., using fNIRS with music as the primary stimulus) are presented across five thematic sections. Critical discussion of methodology leads us to propose guidelines of good practices aiming for robust signal analyses and reproducibility. A continuously updated world map is proposed, including basic information from studies meeting the inclusion criteria. It provides an organized, accessible, and updatable reference database, which could serve as a catalyst for future collaborations within the community. In conclusion, fNIRS shows potential for investigating cognitive processes in music, particularly in ecological contexts and with special populations, aligning with current research priorities in music cognition.

Functional near-infrared spectroscopy: A novel tool for detecting consciousness after acute severe brain injury

Recent advancements in functional neuroimaging have demonstrated that some unresponsive patients in the intensive care unit retain a level of consciousness that is inconsistent with their behavioral diagnosis of awareness. Functional near-infrared spectroscopy (fNIRS) is a portable optical neuroimaging method that can be used to measure neural activity with good temporal and spatial resolution. However, the reliability of fNIRS for detecting the neural correlates of consciousness remains to be established. In a series of studies, we evaluated whether fNIRS can record sensory, perceptual, and command-driven neural processing in healthy participants and in behaviorally nonresponsive patients. At the individual healthy subject level, we demonstrate that fNIRS can detect commonly studied resting state networks, sensorimotor processing, speech-specific auditory processing, and volitional command-driven brain activity to a motor imagery task. We then tested fNIRS with three acutely brain injured patients and found that one could willfully modulate their brain activity when instructed to imagine playing a game of tennis-providing evidence of preserved consciousness despite no observable behavioral signs of awareness. The successful application of fNIRS for detecting preserved awareness among behaviorally nonresponsive patients highlights its potential as a valuable tool for uncovering hidden cognitive states in critical care settings.

Optimizing spatial specificity and signal quality in fNIRS: an overview of potential challenges and possible options for improving the reliability of real-time applications

The optical brain imaging method functional near-infrared spectroscopy (fNIRS) is a promising tool for real-time applications such as neurofeedback and brain-computer interfaces. Its combination of spatial specificity and mobility makes it particularly attractive for clinical use, both at the bedside and in patients' homes. Despite these advantages, optimizing fNIRS for real-time use requires careful attention to two key aspects: ensuring good spatial specificity and maintaining high signal quality. While fNIRS detects superficial cortical brain regions, consistently and reliably targeting specific regions of interest can be challenging, particularly in studies that require repeated measurements. Variations in cap placement coupled with limited anatomical information may further reduce this accuracy. Furthermore, it is important to maintain good signal quality in real-time contexts to ensure that they reflect the true underlying brain activity. However, fNIRS signals are susceptible to contamination by cerebral and extracerebral systemic noise as well as motion artifacts. Insufficient real-time preprocessing can therefore cause the system to run on noise instead of brain activity. The aim of this review article is to help advance the progress of fNIRS-based real-time applications. It highlights the potential challenges in improving spatial specificity and signal quality, discusses possible options to overcome these challenges, and addresses further considerations relevant to real-time applications. By addressing these topics, the article aims to help improve the planning and execution of future real-time studies, thereby increasing their reliability and repeatability.

Spatial correspondence of cortical activity measured with whole head fNIRS and fMRI: Toward clinical use within subject

Functional near infrared spectroscopy (fNIRS) and functional magnetic resonance imaging (fMRI) both measure the hemodynamic response, and so both imaging modalities are expected to have a strong correspondence in regions of cortex adjacent to the scalp. To assess whether fNIRS can be used clinically in a manner similar to fMRI, 22 healthy adult participants underwent same-day fMRI and whole-head fNIRS testing while they performed separate motor (finger tapping) and visual (flashing checkerboard) tasks. Analyses were conducted within and across subjects for each imaging approach, and regions of significant task-related activity were compared on the cortical surface. The spatial correspondence between fNIRS and fMRI detection of task-related activity was good in terms of true positive rate, with fNIRS overlap of up to 68 % of the fMRI for analyses across subjects (group analysis) and an average overlap of up to 47.25 % for individual analyses within subject. At the group level, the positive predictive value of fNIRS was 51 % relative to fMRI. The positive predictive value for within subject analyses was lower (41.5 %), reflecting the presence of significant fNIRS activity in regions without significant fMRI activity. This could reflect task-correlated sources of physiologic noise and/or differences in the sensitivity of fNIRS and fMRI measures to changes in separate (vs. combined) measures of oxy and de-oxyhemoglobin. The results suggest whole-head fNIRS as a noninvasive imaging modality with promising clinical utility for the functional assessment of brain activity in superficial regions of cortex physically adjacent to the skull.

Reliability Evaluation for Continuous-Wave Functional Near-Infrared Spectroscopy Systems: Comprehensive Testing from Bench Characterization to Human Test

In recent years, biomedical optics technology has developed rapidly. The current widespread use of biomedical optics was made possible by the invention of optical instruments. The advantages of being non-invasive, portable, effective, low cost, and less susceptible to system noise have led to the rapid development of functional near-infrared spectroscopy (fNIRS) technology for hemodynamics detection, especially in the field of functional brain imaging. At the same time, laboratories and companies have developed various fNIRS-based systems. The safety, stability, and efficacy of fNIRS systems are key performance indicators. However, there is still a lack of comprehensive and systematic evaluation methods for fNIRS instruments. This study uses the fNIRS system developed in our laboratory as the test object. The test method established in this study includes system validation and performance testing to comprehensively assess fNIRS systems' reliability. These methods feature low cost and high practicality. Based on this study, existing or newly developed systems can be comprehensively and easily evaluated in the laboratory or workspace.

Exploring protocol development: Implementing systematic contextual memory to enhance real-time fMRI neurofeedback

Objective

The goal of this study was to explore the development and implementation of a protocol for real-time fMRI neurofeedback (rtfMRI-nf) and to assess the potential for enhancing the selective brain activation using stimuli from Virtual Reality (VR). In this study we focused on two specific brain regions, supplementary motor area (SMA) and right inferior frontal gyrus (rIFG). Publications by other study groups have suggested impaired function in these specific brain regions in patients with the diagnoses Attention Deficit Hyperactivity Disorder (ADHD) and Tourette's Syndrome (TS). This study explored the development of a protocol to investigate if attention and contextual memory may be used to systematically strengthen the procedure of rtfMRI-nf.

Methods

We used open-science software and platforms for rtfMRI-nf and for developing a simulated repetition of the rtfMRI-nf brain training in VR. We conducted seven exploratory tests in which we updated the protocol at each step. During rtfMRI-nf, MRI images are analyzed live while a person is undergoing an MRI scan, and the results are simultaneously shown to the person in the MRI-scanner. By focusing the analysis on specific regions of the brain, this procedure can be used to help the person strengthen conscious control of these regions. The VR simulation of the same experience involved a walk through the hospital toward the MRI scanner where the training sessions were conducted, as well as a subsequent simulated repetition of the MRI training. The VR simulation was a 2D projection of the experience.The seven exploratory tests involved 19 volunteers. Through this exploration, methods for aiming within the brain (e.g. masks/algorithms for coordinate-system control) and calculations for the analyses (e.g. calculations based on connectivity versus activity) were updated by the project team throughout the project. The final procedure involved three initial rounds of rtfMRI-nf for learning brain strategies. Then, the volunteers were provided with VR headsets and given instructions for one week of use. Afterward, a new session with three rounds of rtfMRI-nf was conducted.

Results

Through our exploration of the indirect effect parameters - brain region activity (directed oxygenated blood flow), connectivity (degree of correlated activity in different regions), and neurofeedback score - the volunteers tended to increase activity in the reinforced brain regions through our seven tests. Updates of procedures and analyses were always conducted between pilots, and never within. The VR simulated repetition was tested in pilot 7, but the role of the VR contribution in this setting is unclear due to underpowered testing.

Conclusion

This proof-of-concept protocol implies how rtfMRI-nf may be used to selectively train two brain regions (SMA and rIFG). The method may likely be adapted to train any given region in the brain, but readers are advised to update and adapt the procedure to experimental needs.

Prefrontal cortex activity of active motion, cyclic electrical muscle stimulation, assisted motion, and imagery of wrist extension in stroke using fNIRS

OBJECTIVES

This study aimed to determine whether the prefrontal cortex (PFC) was activated during four training approaches for wrist extension in patients with stroke, including active motion, cyclic electrical muscle stimulation (EMS), assisted motion, and motor imagery (MI).

MATERIALS AND METHODS

We conducted a cross-sectional study involving 16 patients with stroke, and adopted functional near-infrared spectroscopy (fNIRS) to observe PFC activity during four treatment paradigms. The beta value of 53 channels in fNIRS under each paradigm, compared to the baseline, was evaluated using single sample t-test. The one-way analysis of variance with post hoc analysis was employed to compare the difference of significantly activated channels among four treatment paradigms.

RESULTS

This study revealed that the active motion (t values ranging from 2.399 to 4.368, p values <0.05), as well as MI of wrist extension (t values ranging from 2.161 to 4.378, p values <0.05), significantly increased HBO concentration across the entire PFC. The cyclic EMS enhanced the activation of Broca's area and frontal pole (FP) (t values ranging from -2.540 to 2.303, p values <0.05). The assisted motion induced significant activation in Broca's area, dorsolateral prefrontal cortex, and FP (t values ranging from -2.226 to 3.056, p values <0.05). The difference in ΔHBO among the four tasks was seen in Broca's area, FP, and frontal eye field.

CONCLUSIONS

Active wrist extension and MI activate most PFC areas, whereas assisted motion and single-use of cyclic EMS have limited effectiveness for PFC activation in stroke patients.

Surface-based integration approach for fNIRS-fMRI reliability assessment

INTRODUCTION

Studies integrating functional near-infrared spectroscopy (fNIRS) with functional MRI (fMRI) employ heterogeneous methods in defining common regions of interest in which similarities are assessed. Therefore, spatial agreement and temporal correlation may not be reproducible across studies. In the present work, we address this issue by proposing a novel method for integration and analysis of fNIRS and fMRI over the cortical surface.

MATERIALS AND METHODS

Eighteen healthy volunteers (age mean±SD 30.55 ± 4.7, 7 males) performed a motor task during non-simultaneous fMRI and fNIRS acquisitions. First, fNIRS and fMRI data were integrated by projecting subject- and group-level source maps over the cortical surface mesh to define anatomically constrained functional ROIs (acfROI). Next, spatial agreement and temporal correlation were quantified as Dice Coefficient (DC) and Pearson's correlation coefficient between fNIRS-fMRI in the acfROIs.

RESULTS

Subject-level results revealed moderate to substantial spatial agreement (DC range 0.43 - 0.64), confirmed at the group-level only for blood oxygenation level-dependent (BOLD) signal vs. HbO2 (0.44 - 0.69), while lack of agreement was found for BOLD vs. HbR in some instances (0.05 - 0.49). Subject-level temporal correlation was moderate to strong (0.79 - 0.85 for BOLD vs. HbO2 and -0.62 to -0.72 for BOLD vs. HbR), while an overall strong correlation was found for group-level results (0.95 - 0.98 for BOLD vs. HbO2 and -0.91 to -0.94 for BOLD vs. HbR).

CONCLUSION

The proposed method directly compares fNIRS and fMRI by projecting individual source maps to the cortical surface. Our results indicate spatial and temporal correspondence between fNIRS and fMRI, and promotes the use of fNIRS when more ecological acquision settings are required, such as longitudinal monitoring of brain activity before and after rehabilitation.

Measuring acute effects of subanesthetic ketamine on cerebrovascular hemodynamics in humans using TD-fNIRS

Quantifying neural activity in natural conditions (i.e. conditions comparable to the standard clinical patient experience) during the administration of psychedelics may further our scientific understanding of the effects and mechanisms of action. This data may facilitate the discovery of novel biomarkers enabling more personalized treatments and improved patient outcomes. In this single-blind, placebo-controlled study with a non-randomized design, we use time-domain functional near-infrared spectroscopy (TD-fNIRS) to measure acute brain dynamics after intramuscular subanesthetic ketamine (0.75 mg/kg) and placebo (saline) administration in healthy participants (n = 15, 8 females, 7 males, age 32.4 ± 7.5 years) in a clinical setting. We found that the ketamine administration caused an altered state of consciousness and changes in systemic physiology (e.g. increase in pulse rate and electrodermal activity). Furthermore, ketamine led to a brain-wide reduction in the fractional amplitude of low frequency fluctuations, and a decrease in the global brain connectivity of the prefrontal region. Lastly, we provide preliminary evidence that a combination of neural and physiological metrics may serve as predictors of subjective mystical experiences and reductions in depressive symptomatology. Overall, our study demonstrated the successful application of fNIRS neuroimaging to study the physiological effects of the psychoactive substance ketamine in humans, and can be regarded as an important step toward larger scale clinical fNIRS studies that can quantify the impact of psychedelics on the brain in standard clinical settings.

Using preregistration as a tool for transparent fNIRS study design

Significance

The expansion of functional near-infrared spectroscopy (fNIRS) methodology and analysis tools gives rise to various design and analytical decisions that 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 is 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 on the design and analysis steps involved in fNIRS studies and to 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 (CW) 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 CW, 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.

Functional Near-Infrared Spectroscopy as a Personalized Digital Healthcare Tool for Brain Monitoring

The sustained growth of digital healthcare in the field of neurology relies on portable and cost-effective brain monitoring tools that can accurately monitor brain function in real time. Functional near-infrared spectroscopy (fNIRS) is one such tool that has become popular among researchers and clinicians as a practical alternative to functional magnetic resonance imaging, and as a complementary tool to modalities such as electroencephalography. This review covers the contribution of fNIRS to the personalized goals of digital healthcare in neurology by identifying two major trends that drive current fNIRS research. The first major trend is multimodal monitoring using fNIRS, which allows clinicians to access more data that will help them to understand the interconnection between the cerebral hemodynamics and other physiological phenomena in patients. This allows clinicians to make an overall assessment of physical health to obtain a more-detailed and individualized diagnosis. The second major trend is that fNIRS research is being conducted with naturalistic experimental paradigms that involve multisensory stimulation in familiar settings. Cerebral monitoring of multisensory stimulation during dynamic activities or within virtual reality helps to understand the complex brain activities that occur in everyday life. Finally, the scope of future fNIRS studies is discussed to facilitate more-accurate assessments of brain activation and the wider clinical acceptance of fNIRS as a medical device for digital healthcare.

Stroke-Related Alterations in the Brain's Functional Connectivity Response Associated with Upper Limb Multi-Joint Linkage Movement

Stroke is one of the primary causes of motor disorders, which can seriously affect the patient's quality of life. However, the assessment of the upper limb affected by stroke is commonly based on scales, and the characteristics of brain reorganization induced by limb movement are not clear. Thus, this study aimed to investigate stroke-related cortical reorganization based on functional near infrared spectroscopy (fNIRS) during upper limb multi-joint linkage movement with reference to the Fugl-Meyer Assessment of the upper extremities (FMA-UE). In total, 15 stroke patients and 15 healthy subjects participated in this study. The functional connectivity (FC) between channels and the regions of interest (ROI) was calculated by Pearson's correlation coefficient. The results showed that compared with the control group, the FC between the prefrontal cortex and the motor cortex was significantly increased in the resting state and the affected upper limb's multi-joint linkage movements, while the FC between the motor cortex was significantly decreased during the unaffected upper limb's multi-joint linkage movements. Moreover, the significantly increased ROI FC in the resting state showed a significantly positive correlation with FMA-UE in stroke patients (p < 0.05). This study highlights a new biomarker for evaluating the function of movement in stroke patients and provides guidance for rehabilitation training.

Multimodal assessment of the spatial correspondence between fNIRS and fMRI hemodynamic responses in motor tasks

Functional near-infrared spectroscopy (fNIRS) provides a cost-efficient and portable alternative to functional magnetic resonance imaging (fMRI) for assessing cortical activity changes based on hemodynamic signals. The spatial and temporal underpinnings of the fMRI blood-oxygen-level-dependent (BOLD) signal and corresponding fNIRS concentration of oxygenated (HbO), deoxygenated (HbR), and total hemoglobin (HbT) measurements are still not completely clear. We aim to analyze the spatial correspondence between these hemodynamic signals, in motor-network regions. To this end, we acquired asynchronous fMRI and fNIRS recordings from 9 healthy participants while performing motor imagery and execution. Using this multimodal approach, we investigated the ability to identify motor-related activation clusters in fMRI data using subject-specific fNIRS-based cortical signals as predictors of interest. Group-level activation was found in fMRI data modeled from corresponding fNIRS measurements, with significant peak activation found overlapping the individually-defined primary and premotor motor cortices, for all chromophores. No statistically significant differences were observed in multimodal spatial correspondence between HbO, HbR, and HbT, for both tasks. This suggests the possibility of translating neuronal information from fMRI into an fNIRS motor-coverage setup with high spatial correspondence using both oxy and deoxyhemoglobin data, with the inherent benefits of translating fMRI paradigms to fNIRS in cognitive and clinical neuroscience.

Performance comparison of systemic activity correction in functional near-infrared spectroscopy for methods with and without short distance channels

Significance: Functional near-infrared spectroscopy (fNIRS) is a promising tool for neurofeedback (NFB) or brain-computer interfaces (BCIs). However, fNIRS signals are typically highly contaminated by systemic activity (SA) artifacts, and, if not properly corrected, NFB or BCIs run the risk of being based on noise instead of brain activity. This risk can likely be reduced by correcting for SA, in particular when short-distance channels (SDCs) are available. Literature comparing correction methods with and without SDCs is still sparse, specifically comparisons considering single trials are lacking. Aim: This study aimed at comparing the performance of SA correction methods with and without SDCs. Approach: Semisimulated and real motor task data of healthy older adults were used. Correction methods without SDCs included a simple and a more advanced spatial filter. Correction methods with SDCs included a regression approach considering only the closest SDC and two GLM-based methods, one including all eight SDCs and one using only two a priori selected SDCs as regressors. All methods were compared with data uncorrected for SA and correction performance was assessed with quality measures quantifying signal improvement and spatial specificity at single trial level. Results: All correction methods were found to improve signal quality and enhance spatial specificity as compared with the uncorrected data. Methods with SDCs usually outperformed methods without SDCs. Correction methods without SDCs tended to overcorrect the data. However, the exact pattern of results and the degree of differences observable between correction methods varied between semisimulated and real data, and also between quality measures. Conclusions: Overall, results confirmed that both Δ [ HbO ] and Δ [ HbR ] are affected by SA and that correction methods with SDCs outperform methods without SDCs. Nonetheless, improvements in signal quality can also be achieved without SDCs and should therefore be given priority over not correcting for SA.

Functional quantification of oral motor cortex at rest and during tasks using activity phase ratio: A zero-setting vector functional near-infrared spectroscopy study

Oral frailty associated with oral hypokinesia may cause dementia. Functional near-infrared spectroscopy (fNIRS) can be used while the participants are in seating position with few restrictions. Thus, it is useful for assessing brain function, particularly oral motor activity. However, methods for identifying oral motor cortex (OMC) activation via the scalp have not been established. The current study aimed to detect OMC activation, an indicator of activity phase ratio (APR), which reflects increased oxygen consumption (0 &lt; [deoxyhemoglobin (ΔDeoxyHb) or 0 &lt; {[ΔDeoxyHb- oxyhemoglobin (ΔOxyHb)/√2]}, via fNIRS to accurately identify local brain activity. The APR, calculated via zero-set vector analysis, is a novel index for quantifying brain function both temporally and spatially at rest and during tasks. In total, 14 healthy participants performed bite tasks for 3 s per side for 10 times while in the sitting position. Then, time-series data on concentration changes in ΔOxyHb and ΔDeoxyHb were obtained via fNIRS. The anatomical location of the OMC was determined using a pooled data set of three-dimensional magnetic resonance images collected in advance from 40 healthy adults. In the zero-set vector analysis, the average change in ΔOxyHb and ΔDeoxyHb concentrations was utilized to calculate the APR percentage in 140 trials. The significant regions (z-score of ≥2.0) of the APR and ΔOxyHb in the task were compared. During the bite task, the APR significantly increased within the estimated OMC region (56–84 mm lateral to Cz and 4–20 mm anterior to Cz) in both the right and left hemispheres. By contrast, the ΔOxyHb concentrations increased on the bite side alone beyond the OMC region. The mean APR at rest for 2 s before the task showed 59.5%–62.2% in the left and right OMCs. The average APR for 3 s during the task showed 75.3% for the left OMC and 75.7% for the right OMC during the left bite task, and 65.9% for the left OMC and 80.9% for the right OMC during the right bite task. Interestingly, the average increase in APR for the left and right OMCs for the left bite task and the right bite task was 13.9% and 13.7%, respectively, showing almost a close match. The time course of the APR was more limited to the bite task segment than that of ΔOxyHb or ΔDexyHb concentration, and it increased in the OMC. Hence, the APR can quantitatively monitor both the resting and active states of the OMC in the left and right hemispheres. Using the zero-set vector-based fNIRS, the APR can be a valid indicator of oral motor function and bite force.