Integration of Spatial Information Increases Reproducibility in Functional Near-Infrared Spectroscopy

Habituation of Brain Activity with Repetition in Color and Picture-Word Stroop Tests

As a widely used mental task for functional near-infrared spectroscopy (fNIRS), the original color-word Stroop task has the advantage of being difficult to habituate, but also the disadvantage of being difficult to understand, especially for children. While the introduction of derived Stroop tasks offers highly promising countermeasures, changes in brain activity during these tests have not been well tested. We investigated the degree of habituation between the original and a derived Stroop task by measuring brain activity to obtain a better fNIRS task design. Fourteen healthy adults participated in the study, and a 10-channel fNIRS device was used. A picture-word Stroop task with lower linguistic conflict than the original was conducted. The original and derived Stroop tests were repeated four times in a 1-week interval. We found that the original Stroop test did not show any significant changes in brain activity with repeated measures; however, brain activity decreased during the derived test. The differences in habituation between the original and derived tests may be due to the differences in the strength of the linguistic conflict. Our findings also highlight the need to consider the effects of habituation when using derived Stroop tasks in repeated measures.

Subject-specific information enhances spatial accuracy of high-density diffuse optical tomography

Functional near-infrared spectroscopy (fNIRS) is a widely used imaging method for mapping brain activation based on cerebral hemodynamics. The accurate quantification of cortical activation using fNIRS data is highly dependent on the ability to correctly localize the positions of light sources and photodetectors on the scalp surface. Variations in head size and shape across participants greatly impact the precise locations of these optodes and consequently, the regions of the cortical surface being reached. Such variations can therefore influence the conclusions drawn in NIRS studies that attempt to explore specific cortical regions. In order to preserve the spatial identity of each NIRS channel, subject-specific differences in NIRS array registration must be considered. Using high-density diffuse optical tomography (HD-DOT), we have demonstrated the inter-subject variability of the same HD-DOT array applied to ten participants recorded in the resting state. We have also compared three-dimensional image reconstruction results obtained using subject-specific positioning information to those obtained using generic optode locations. To mitigate the error introduced by using generic information for all participants, photogrammetry was used to identify specific optode locations per-participant. The present work demonstrates the large variation between subjects in terms of which cortical parcels are sampled by equivalent channels in the HD-DOT array. In particular, motor cortex recordings suffered from the largest optode localization errors, with a median localization error of 27.4 mm between generic and subject-specific optodes, leading to large differences in parcel sensitivity. These results illustrate the importance of collecting subject-specific optode locations for all wearable NIRS experiments, in order to perform accurate group-level analysis using cortical parcellation.

Mobile fNIRS for exploring inter-brain synchrony across generations and time

While still relatively rare, longitudinal hyperscanning studies are exceptionally valuable for documenting changes in inter-brain synchrony, which may in turn underpin how behaviors develop and evolve in social settings. The generalizability and ecological validity of this experimental approach hinges on the selected imaging technique being mobile-a requirement met by functional near-infrared spectroscopy (fNIRS). fNIRS has most frequently been used to examine the development of inter-brain synchrony and behavior in child-parent dyads. In this position paper, we contend that dedicating attention to longitudinal and intergenerational hyperscanning stands to benefit the fields of social and cognitive neuroscience more broadly. We argue that this approach is particularly relevant for understanding the neural mechanisms underpinning intergenerational social dynamics, and potentially for benchmarking progress in psychological and social interventions, many of which are situated in intergenerational contexts. In line with our position, we highlight areas of intergenerational research that stand to be enhanced by longitudinal hyperscanning with mobile devices, describe challenges that may arise from measuring across generations in the real world, and offer potential solutions.

Neuroimaging evidence of visual-vestibular interaction accounting for perceptual mislocalization induced by head rotation

Significance

A fleeting flash aligned vertically with an object remaining stationary in the head-centered space would be perceived as lagging behind the object during the observer's horizontal head rotation. This perceptual mislocalization is an illusion named head-rotation-induced flash-lag effect (hFLE). While many studies have investigated the neural mechanism of the classical visual FLE, the hFLE has been hardly investigated.

Aim

We measured the cortical activity corresponding to the hFLE on participants experiencing passive head rotations using functional near-infrared spectroscopy.

Approach

Participants were asked to judge the relative position of a flash to a fixed reference while being horizontally rotated or staying static in a swivel chair. Meanwhile, functional near-infrared spectroscopy signals were recorded in temporal-parietal areas. The flash duration was manipulated to provide control conditions.

Results

Brain activity specific to the hFLE was found around the right middle/inferior temporal gyri, and bilateral supramarginal gyri and superior temporal gyri areas. The activation was positively correlated with the rotation velocity of the participant around the supramarginal gyrus and negatively related to the hFLE intensity around the middle temporal gyrus.

Conclusions

These results suggest that the mechanism underlying the hFLE involves multiple aspects of visual-vestibular interactions including the processing of multisensory conflicts mediated by the temporoparietal junction and the modulation of vestibular signals on object position perception in the human middle temporal complex.

Between-sessions test-retest reliability of prefrontal cortical activity during usual walking in patients with Parkinson's Disease: A fNIRS study

BACKGROUND

Examining between-sessions test-retest reliability of functional near-infrared spectroscopy (fNIRS) data is crucial to better interpret rehabilitation-related changes in the hemodynamic response.

RESEARCH QUESTION

This study investigated test-retest reliability of prefrontal activity during usual walking in 14 patients with Parkinson's Disease with a fixed retest intervals of five weeks.

METHODS

Fourteen patients performed usual walking in two sessions (T0 and T1). Relative changes in cortical activity (oxy and deoxyhemoglobin: ∆HbO₂ and ∆HbR, respectively) in the dorsolateral prefrontal cortex (DLPFC) using fNIRS system and gait performance were measured. Test-retest reliability of mean ∆HbO₂ for the total DLPFC and for each hemisphere were measured using paired t-test, intraclass correlation coefficient (ICC), and Bland-Altman plots with 95% agreement. Pearson correlations between cortical activity and gait performance were also performed.

RESULTS

Moderate reliability was found for ∆HbO₂ in the total DLPFC (mean difference of ∆HbO₂ between T1 and T0 = -0.005 µmol, p = 0.93; ICC average = 0.72). However, test-retest reliability of ∆HbO₂ was poorer when considering each hemisphere.

SIGNIFICANCE

Findings suggest that fNIRS may be used as a reliable tool for rehabilitation studies in patients with PD. Test-retest reliability of fNIRS data between 2 sessions during walking tasks should be interpreted respectively of gait performance.

fNIRS is sensitive to leg activity in the primary motor cortex after systemic artifact correction

BACKGROUND

functional near-infrared spectroscopy (fNIRS) is an increasingly popular tool to study cortical activity during movement and gait that requires further validation. This study aimed to assess (1) whether fNIRS can detect the difficult-to-measure leg area of the primary motor cortex (M1) and distinguish it from the hand area; and (2) whether fNIRS can differentiate between automatic (i.e., not requiring one's attention) and non-automatic movement processes. Special attention was attributed to systemic artifacts (i.e., changes in blood pressure, heart rate, breathing) which were assessed and corrected by short channels, i.e., fNIRS channels which are mainly sensitive to superficial scalp hemodynamics.

METHODS

Twenty-three seated, healthy participants tapped four fingers on a keyboard or tapped the right foot on four squares on the floor in a specific order given by a 12-digit sequence (e.g., 434141243212). Two different sequences were executed: a beforehand learned (i.e., automatic) version and a newly learned (i.e., non-automatic) version. A 36-channel fNIRS device including 12 short channels covered multiple motor-related cortical areas including M1. The fNIRS data were analyzed with a general linear model (GLM). Correlation between the expected functional hemodynamic responses (i.e. task regressor) and the short channels (i.e. nuisance regressors), necessitated performing a separate short channel regression instead of integrating them in the GLM.

RESULTS

Consistent with the M1 somatotopy, we found significant HbO increases of very large effect size in the lateral M1 channels during finger tapping (Cohen's d = 1.35, p<0.001) and significant HbO increases of moderate effect size in the medial M1 channels during foot tapping (Cohen's d = 0.8, p<0.05). The cortical activity differences between automatic and non-automatic tasks were not significantly different. Importantly, leg movements produced large systemic fluctuations, which were adequately removed by the use of all available short channels.

DISCUSSION

Our results indicate that fNIRS is sensitive to leg activity in M1, though the sensitivity is lower than for finger activity and requires rigorous correction for systemic fluctuations. We furthermore highlight that systemic artifacts may result in an unreliable GLM analysis when short channels show signals that are similar to the expected hemodynamic responses.

Laterality Index Calculations in a Control Study of Functional Near Infrared Spectroscopy

Hemispheric dominance has been used to understand the influence of central and peripheral neural damage on the motor function of individuals with stroke, cerebral palsy, and limb loss. It has been well established that greater activation occurs in the contralateral hemisphere to the side of the body used to perform the task. However, there is currently a large variability in calculation procedures for brain laterality when using functional near-infrared spectroscopy (fNIRS) as a non-invasive neuroimaging tool. In this study, we used fNIRS to measure brain activity over the left and right sensorimotor cortices while participants (n = 20, healthy and uninjured) performed left and right-hand movement tasks. Then, we analyzed the fNIRS data using two different processing pipelines (block averaging or general linear model [GLM]), two different criteria of processing for negative values (include all beta values or include only positive beta values), and three different laterality index (LI) formulas. The LI values produced using the block averaging analysis indicated an expected contralateral dominance with some instances of bilateral dominance, which agreed with the expected contralateral activation. However, the inclusion criteria nor the LI formulas altered the outcome. The LI values produced using the GLM analysis displayed a robust left hemisphere dominance regardless of the hand performing the task, which disagreed with the expected contralateral activation but did provide instances of correctly identifying brain laterality. In conclusion, both analysis pipelines were able to correctly determine brain laterality, but processes to account for negative beta values were recommended especially when utilizing the GLM analysis to determine brain laterality.

Revealing the spatiotemporal requirements for accurate subject identification with resting-state functional connectivity: a simultaneous fNIRS-fMRI study

SIGNIFICANCE

Brain fingerprinting refers to identifying participants based on their functional patterns. Despite its success with functional magnetic resonance imaging (fMRI), brain fingerprinting with functional near-infrared spectroscopy (fNIRS) still lacks adequate validation.

AIM

We investigated how fNIRS-specific acquisition features (limited spatial information and nonneural contributions) influence resting-state functional connectivity (rsFC) patterns at the intra-subject level and, therefore, brain fingerprinting.

APPROACH

We performed multiple simultaneous fNIRS and fMRI measurements in 29 healthy participants at rest. Data were preprocessed following the best practices, including the removal of motion artifacts and global physiology. The rsFC maps were extracted with the Pearson correlation coefficient. Brain fingerprinting was tested with pairwise metrics and a simple linear classifier.

RESULTS

Our results show that average classification accuracy with fNIRS ranges from 75% to 98%, depending on the number of runs and brain regions used for classification. Under the right conditions, brain fingerprinting with fNIRS is close to the 99.9% accuracy found with fMRI. Overall, the classification accuracy is more impacted by the number of runs and the spatial coverage than the choice of the classification algorithm.

CONCLUSIONS

This work provides evidence that brain fingerprinting with fNIRS is robust and reliable for extracting unique individual features at the intra-subject level once relevant spatiotemporal constraints are correctly employed.

Hierarchical Bayesian modeling of the relationship between task-related hemodynamic responses and cortical excitability

Investigating the relationship between task-related hemodynamic responses and cortical excitability is challenging because it requires simultaneous measurement of hemodynamic responses while applying noninvasive brain stimulation. Moreover, cortical excitability and task-related hemodynamic responses are both associated with inter-/intra-subject variability. To reliably assess such a relationship, we applied hierarchical Bayesian modeling. This study involved 16 healthy subjects who underwent simultaneous Paired Associative Stimulation (PAS10, PAS25, Sham) while monitoring brain activity using functional Near-Infrared Spectroscopy (fNIRS), targeting the primary motor cortex (M1). Cortical excitability was measured by Motor Evoked Potentials (MEPs), and the motor task-related hemodynamic responses were measured using fNIRS 3D reconstructions. We constructed three models to investigate: (1) PAS effects on the M1 excitability, (2) PAS effects on fNIRS hemodynamic responses to a finger tapping task, and (3) the correlation between PAS effects on M1 excitability and PAS effects on task-related hemodynamic responses. Significant increase in cortical excitability was found following PAS25, whereas a small reduction of the cortical excitability was shown after PAS10 and a subtle increase occurred after sham. Both HbO and HbR absolute amplitudes increased after PAS25 and decreased after PAS10. The probability of the positive correlation between modulation of cortical excitability and hemodynamic activity was 0.77 for HbO and 0.79 for HbR. We demonstrated that PAS stimulation modulates task-related cortical hemodynamic responses in addition to M1 excitability. Moreover, the positive correlation between PAS modulations of excitability and hemodynamics brought insight into understanding the fundamental properties of cortical function and cortical excitability.

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

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.

Neural Activity during Audiovisual Speech Processing: Protocol for a Functional Neuroimaging Study (Preprint)

Background

Functional near-infrared spectroscopy (fNIRS) studies have demonstrated associations between hearing outcomes after cochlear implantation and plastic brain changes. However, inconsistent results make it difficult to draw conclusions. A major problem is that many variables need to be controlled. To gain further understanding, a careful preparation and planning of such a functional neuroimaging task is key.

Objective

Using fNIRS, our main objective is to develop a well-controlled audiovisual speech comprehension task to study brain activation in individuals with normal hearing and hearing impairment (including cochlear implant users). The task should be deductible from clinically established tests, induce maximal cortical activation, use optimal coverage of relevant brain regions, and be reproducible by other research groups.

Methods

The protocol will consist of a 5-minute resting state and 2 stimulation periods that are 12 minutes each. During the stimulation periods, 13-second video recordings of the clinically established Oldenburg Sentence Test (OLSA) will be presented. Stimuli will be presented in 4 different modalities: (1) speech in quiet, (2) speech in noise, (3) visual only (ie, lipreading), and (4) audiovisual speech. Each stimulus type will be repeated 10 times in a counterbalanced block design. Interactive question windows will monitor speech comprehension during the task. After the measurement, we will perform a 3D scan to digitize optode positions and verify the covered anatomical locations.

Results

This paper reports the study protocol. Enrollment for the study started in August 2021. We expect to publish our first results by the end of 2022.

Conclusions

The proposed audiovisual speech comprehension task will help elucidate neural correlates to speech understanding. The comprehensive study will have the potential to provide additional information beyond the conventional clinical standards about the underlying plastic brain changes of a hearing-impaired person. It will facilitate more precise indication criteria for cochlear implantation and better planning of rehabilitation.

International Registered Report Identifier (IRRID)

DERR1-10.2196/38407

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

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.

Diffuse optical reconstructions of functional near infrared spectroscopy data using maximum entropy on the mean

Functional near-infrared spectroscopy (fNIRS) measures the hemoglobin concentration changes associated with neuronal activity. Diffuse optical tomography (DOT) consists of reconstructing the optical density changes measured from scalp channels to the oxy-/deoxy-hemoglobin concentration changes within the cortical regions. In the present study, we adapted a nonlinear source localization method developed and validated in the context of Electro- and Magneto-Encephalography (EEG/MEG): the Maximum Entropy on the Mean (MEM), to solve the inverse problem of DOT reconstruction. We first introduced depth weighting strategy within the MEM framework for DOT reconstruction to avoid biasing the reconstruction results of DOT towards superficial regions. We also proposed a new initialization of the MEM model improving the temporal accuracy of the original MEM framework. To evaluate MEM performance and compare with widely used depth weighted Minimum Norm Estimate (MNE) inverse solution, we applied a realistic simulation scheme which contained 4000 simulations generated by 250 different seeds at different locations and 4 spatial extents ranging from 3 to 40\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\text {cm}^2$$\end{document}cm2 along the cortical surface. Our results showed that overall MEM provided more accurate DOT reconstructions than MNE. Moreover, we found that MEM was remained particularly robust in low signal-to-noise ratio (SNR) conditions. The proposed method was further illustrated by comparing to functional Magnetic Resonance Imaging (fMRI) activation maps, on real data involving finger tapping tasks with two different montages. The results showed that MEM provided more accurate HbO and HbR reconstructions in spatial agreement with the main fMRI cluster, when compared to MNE.

Evaluation of a personalized functional near infra-red optical tomography workflow using maximum entropy on the mean

In the present study, we proposed and evaluated a workflow of personalized near infra-red optical tomography (NIROT) using functional near-infrared spectroscopy (fNIRS) for spatiotemporal imaging of cortical hemodynamic fluctuations. The proposed workflow from fNIRS data acquisition to local 3D reconstruction consists of: (a) the personalized optimal montage maximizing fNIRS channel sensitivity to a predefined targeted brain region; (b) the optimized fNIRS data acquisition involving installation of optodes and digitalization of their positions using a neuronavigation system; and (c) the 3D local reconstruction using maximum entropy on the mean (MEM) to accurately estimate the location and spatial extent of fNIRS hemodynamic fluctuations along the cortical surface. The workflow was evaluated on finger-tapping fNIRS data acquired from 10 healthy subjects for whom we estimated the reconstructed NIROT spatiotemporal images and compared with functional magnetic resonance imaging (fMRI) results from the same individuals. Using the fMRI activation maps as our reference, we quantitatively compared the performance of two NIROT approaches, the MEM framework and the conventional minimum norm estimation (MNE) method. Quantitative comparisons were performed at both single subject and group-level. Overall, our results suggested that MEM provided better spatial accuracy than MNE, while both methods offered similar temporal accuracy when reconstructing oxygenated (HbO) and deoxygenated hemoglobin (HbR) concentration changes evoked by finger-tapping. Our proposed complete workflow was made available in the brainstorm fNIRS processing plugin-NIRSTORM, thus providing the opportunity for other researchers to further apply it to other tasks and on larger populations.

Hearing brain evaluated using near-infrared spectroscopy in congenital toxoplasmosis

Congenital toxoplasmosis (CT) is a known cause of hearing loss directly caused by Toxoplasma gondii. Hearing loss might result from sensory, neural, or sensorineural lesions. Early treated infants rarely develop hearing loss, but retinochoroidal lesions, intracranial calcifications and hydrocephalus are common. In this study, we aimed to evaluate the brain evoked hemodynamic responses of CT and healthy infants during four auditory stimuli: mother infant directed speech, researcher infant directed speech, mother reading and researcher recorded. Children underwent Transitionally Evoked Otoacoustic Emission Auditory Testing and Automated Brainstem Auditory Response tests with normal auditory results, but with a tendency for greater latencies in the CT group compared to the control group. We assessed brain hemodynamics with functional near-infrared spectroscopy (fNIRS) measurements from 61 infants, and we present fNIRS results as frequency maps of activation and deactivation for each stimulus. By evaluating infants in the three first months of life, we observed an individual heterogeneous brain activation pattern in response to all auditory stimuli for both groups. Each channel was activated or deactivated in less than 30% of children for all stimuli. There is a need of prospective studies to evaluate if the neurologic or auditory changes course with compromise of children outcomes.

Data Processing in Functional Near-Infrared Spectroscopy (fNIRS) Motor Control Research

FNIRS pre-processing and processing methodologies are very important-how a researcher chooses to process their data can change the outcome of an experiment. The purpose of this review is to provide a guide on fNIRS pre-processing and processing techniques pertinent to the field of human motor control research. One hundred and twenty-three articles were selected from the motor control field and were examined on the basis of their fNIRS pre-processing and processing methodologies. Information was gathered about the most frequently used techniques in the field, which included frequency cutoff filters, wavelet filters, smoothing filters, and the general linear model (GLM). We discuss the methodologies of and considerations for these frequently used techniques, as well as those for some alternative techniques. Additionally, general considerations for processing are discussed.

Neural Basis of Scale Errors in Young Children

In this study, we examined whether 2-and 3-year-old children exhibited activation in the dorsolateral and ventrolateral prefrontal regions while engaging in a tool-based scale error task as measured by near-infrared spectroscopy. Results revealed no significant differences in the prefrontal activation between children who produced scale errors and those who did not. However, we found significant activations of the prefrontal region during scale error sessions compared to free play sessions. Our results do not deny that the activation of prefrontal regions may, at least in part, be associated with children's scale error.