Validating a new methodology for optical probe design and image registration in fNIRS studies

Functional near-infrared spectroscopy (fNIRS) is an imaging technique that relies on the principle of shining near-infrared light through tissue to detect changes in hemodynamic activation. An important methodological issue encountered is the creation of optimized probe geometry for fNIRS recordings. Here, across three experiments, we describe and validate a processing pipeline designed to create an optimized, yet scalable probe geometry based on selected regions of interest (ROIs) from the functional magnetic resonance imaging (fMRI) literature. In experiment 1, we created a probe geometry optimized to record changes in activation from target ROIs important for visual working memory. Positions of the sources and detectors of the probe geometry on an adult head were digitized using a motion sensor and projected onto a generic adult atlas and a segmented head obtained from the subject's MRI scan. In experiment 2, the same probe geometry was scaled down to fit a child's head and later digitized and projected onto the generic adult atlas and a segmented volume obtained from the child's MRI scan. Using visualization tools and by quantifying the amount of intersection between target ROIs and channels, we show that out of 21 ROIs, 17 and 19 ROIs intersected with fNIRS channels from the adult and child probe geometries, respectively. Further, both the adult atlas and adult subject-specific MRI approaches yielded similar results and can be used interchangeably. However, results suggest that segmented heads obtained from MRI scans be used for registering children's data. Finally, in experiment 3, we further validated our processing pipeline by creating a different probe geometry designed to record from target ROIs involved in language and motor processing

Characterizing reproducibility of cerebral hemodynamic responses when applying short-channel regression in functional near-infrared spectroscopy

Significance: Functional near-infrared spectroscopy (fNIRS) enables the measurement of brain activity noninvasively. Optical neuroimaging with fNIRS has been shown to be reproducible on the group level and hence is an excellent research tool, but the reproducibility on the single-subject level is still insufficient, challenging the use for clinical applications. Aim: We investigated the effect of short-channel regression (SCR) as an approach to obtain fNIRS measurements with higher reproducibility on a single-subject level. SCR simultaneously considers contributions from long- and short-separation channels and removes confounding physiological changes through the regression of the short-separation channel information. Approach: We performed a test-retest study with a hand grasping task in 15 healthy subjects using a wearable fNIRS device, optoHIVE. Relevant brain regions were localized with transcranial magnetic stimulation to ensure correct placement of the optodes. Reproducibility was assessed by intraclass correlation, correlation analysis, mixed effects modeling, and classification accuracy of the hand grasping task. Further, we characterized the influence of SCR on reproducibility. Results: We found a high reproducibility of fNIRS measurements on a single-subject level ( and correlation ). SCR increased the reproducibility from 0.64 to 0.81 ( ) but did not affect classification (85% overall accuracy). Significant intersubject variability in the reproducibility was observed and was explained by Mayer wave oscillations and low raw signal strength. The raw signal-to-noise ratio (threshold at 40 dB) allowed for distinguishing between persons with weak and strong activations. Conclusions: We report, for the first time, that fNIRS measurements are reproducible on a single-subject level using our optoHIVE fNIRS system and that SCR improves reproducibility. In addition, we give a benchmark to easily assess the ability of a subject to elicit sufficiently strong hemodynamic responses. With these insights, we pave the way for the reliable use of fNIRS neuroimaging in single subjects for neuroscientific research and clinical applications

Characterizing reproducibility of cerebral hemodynamic responses when applying short-channel regression in functional near-infrared spectroscopy.

Significance: Functional near-infrared spectroscopy (fNIRS) enables the measurement of brain activity noninvasively. Optical neuroimaging with fNIRS has been shown to be reproducible on the group level and hence is an excellent research tool, but the reproducibility on the single-subject level is still insufficient, challenging the use for clinical applications. Aim: We investigated the effect of short-channel regression (SCR) as an approach to obtain fNIRS measurements with higher reproducibility on a single-subject level. SCR simultaneously considers contributions from long- and short-separation channels and removes confounding physiological changes through the regression of the short-separation channel information. Approach: We performed a test-retest study with a hand grasping task in 15 healthy subjects using a wearable fNIRS device, optoHIVE. Relevant brain regions were localized with transcranial magnetic stimulation to ensure correct placement of the optodes. Reproducibility was assessed by intraclass correlation, correlation analysis, mixed effects modeling, and classification accuracy of the hand grasping task. Further, we characterized the influence of SCR on reproducibility. Results: We found a high reproducibility of fNIRS measurements on a single-subject level ( and correlation ). SCR increased the reproducibility from 0.64 to 0.81 ( ) but did not affect classification (85% overall accuracy). Significant intersubject variability in the reproducibility was observed and was explained by Mayer wave oscillations and low raw signal strength. The raw signal-to-noise ratio (threshold at 40 dB) allowed for distinguishing between persons with weak and strong activations. Conclusions: We report, for the first time, that fNIRS measurements are reproducible on a single-subject level using our optoHIVE fNIRS system and that SCR improves reproducibility. In addition, we give a benchmark to easily assess the ability of a subject to elicit sufficiently strong hemodynamic responses. With these insights, we pave the way for the reliable use of fNIRS neuroimaging in single subjects for neuroscientific research and clinical applications

Array Designer: automated optimized array design for functional near-infrared spectroscopy

The position of each source and detector "optode" on the scalp, and their relative separations, determines the sensitivity of each functional near-infrared spectroscopy (fNIRS) channel to the underlying cortex. As a result, selecting appropriate scalp locations for the available sources and detectors is critical to every fNIRS experiment. At present, it is standard practice for the user to undertake this task manually; to select what they believe are the best locations on the scalp to place their optodes so as to sample a given cortical region-of-interest (ROI). This process is difficult, time-consuming, and highly subjective. Here, we propose a tool, Array Designer, that is able to automatically design optimized fNIRS arrays given a user-defined ROI and certain features of the available fNIRS device. Critically, the Array Designer methodology is generalizable and will be applicable to almost any subject population or fNIRS device. We describe and validate the algorithmic methodology that underpins Array Designer by running multiple simulations of array design problems in a realistic anatomical model. We believe that Array Designer has the potential to end the need for manual array design, and in doing so save researchers time, improve fNIRS data quality, and promote standardization across the field

Motor learning induced neuroplasticity in minimally invasive surgery

Technical skills in surgery have become more complex and challenging to acquire since the introduction of technological aids, particularly in the arena of Minimally Invasive Surgery. Additional challenges posed by reforms to surgical careers and increased public scrutiny, have propelled identification of methods to assess and acquire MIS technical skills. Although validated objective assessments have been developed to assess motor skills requisite for MIS, they poorly understand the development of expertise. Motor skills learning, is indirectly observable, an internal process leading to relative permanent changes in the central nervous system. Advances in functional neuroimaging permit direct interrogation of evolving patterns of brain function associated with motor learning due to the property of neuroplasticity and has been used on surgeons to identify the neural correlates for technical skills acquisition and the impact of new technology. However significant gaps exist in understanding neuroplasticity underlying learning complex bimanual MIS skills. In this thesis the available evidence on applying functional neuroimaging towards assessment and enhancing operative performance in the field of surgery has been synthesized. The purpose of this thesis was to evaluate frontal lobe neuroplasticity associated with learning a complex bimanual MIS skill using functional near-infrared spectroscopy an indirect neuroimaging technique. Laparoscopic suturing and knot-tying a technically challenging bimanual skill is selected to demonstrate learning related reorganisation of cortical behaviour within the frontal lobe by shifts in activation from the prefrontal cortex (PFC) subserving attention to primary and secondary motor centres (premotor cortex, supplementary motor area and primary motor cortex) in which motor sequences are encoded and executed. In the cross-sectional study, participants of varying expertise demonstrate frontal lobe neuroplasticity commensurate with motor learning. The longitudinal study involves tracking evolution in cortical behaviour of novices in response to receipt of eight hours distributed training over a fortnight. Despite novices achieving expert like performance and stabilisation on the technical task, this study demonstrates that novices displayed persistent PFC activity. This study establishes for complex bimanual tasks, that improvements in technical performance do not accompany a reduced reliance in attention to support performance. Finally, least-squares support vector machine is used to classify expertise based on frontal lobe functional connectivity. Findings of this thesis demonstrate the value of interrogating cortical behaviour towards assessing MIS skills development and credentialing.Open Acces

A multimodal approach to investigate brain reorganization after spinal cord injury using functional magnetic resonance imaging and functional near-infrared spectroscopy

Traumatic Spinal Cord Injury (SCI) results in structural and functional neurological changes at both the brain and the level of the spinal cord. Anatomical studies indicate decreased grey matter volume in sensorimotor and non-sensorimotor regions of the cortex following SCI; whereas, neurophysiological findings mostly report altered functional activity in the sensorimotor nodes of the cortex, subcortex, and cerebellum. Therefore, it is currently unknown whether tissue atrophy observed in non-motor related areas has any concomitant functional consequences. Furthermore, the neural underpinnings of adaptive neuroplasticity after SCI is not well-defined in the current literature. Hence, this dissertation is a pioneer study investigating the structural and functional changes in the whole brain after SCI, with particular focus on subcortical regions, using a multimodal approach employing magnetic resonance imaging (MRI), resting-state functional MRI (fMRI) and functional near-infrared spectroscopy (fNIRS), that may take best advantage of each of these three tools. MRI scans from 23 healthy controls (HC) and 36 individuals with complete SCI within two years of injury were used to demonstrate that both injury level and duration since injury are important factors contributing to recovery. Specifically, cervical level injury when compared to thoracolumbar level injury exhibits a greater loss of cortical grey matter volume in the orbitofrontal cortex, insula, and anterior cingulate cortex. Next, using the fMRI scans of the same participants during a resting-state scan, the intrinsic functional connectivity of the mediodorsal, pulvinar and ventrolateral nuclei of the thalamus to the regions of salient network and the fronto-parietal network is observed to be dynamic and altered in the SCI group. Lastly, a continuous-wave fNIRS is used to reliably measure brain function in individuals with SCI during both dynamic and static tasks while accounting for cerebrovascular reactivity. Five min of resting-state data and 26 min of motor data including finger tapping, finger tapping imagery and ankle tapping were acquired to identify the spatial activation pattern unique to each of the movement type. A breath-hold paradigm is also used to quantify cerebrovascular reactivity as a means to calibrate task activity from neurovascular constraints. Sixteen HC were scanned at two separate visits to determine the sensitivity and test-retest reliability of fNIRS data from the sensorimotor cortex. Following validation, the same procedure was repeated in 13 individuals with paraplegia resulting from SCI and 13 HC to quantify alterations in the cortical activity of the motor cortex and cerebrovascular reactivity between the two groups. Results indicate that SCI group exhibit altered cerebrovascular reactivity with greater delay in response and greater pre-stimulus undershoot. As hypothesized, the hemodynamic response to ankle movement resulted in only a small change in oxyhemoglobin concentration in the sensorimotor cortex of SCI group when compared to HC. The application of fNIRS to assess cortical reorganization following SCI is unique and expands our understanding of the neurophysiology after SCI. It paves the groundwork for extending the implementation of fNIRS to rehabilitation research and other clinical populations with vascular dysfunction. This dissertation is one of the first studies to comprehensively examine both the structural and functional alterations of the brain in humans with complete SCI and opens promising avenues for SCI research using fNIRS modality

fNIRS Measurement of Cortical Activity in Younger and Older Adults During Gait and Dual-Task Assignment

Functional Near-Infrared Spectroscopy (fNIRS) is a non-invasive brain imaging technique which measures brain activity via local changes in blood hemoglobin concentration. Since brain activity decreases as a function of age, it is expected that aging adults will demonstrate less hemodynamic changes and therefore, indicate less cortical activation compared to younger adults. To test the stated relationships, this study involves using the Near Infra-Red Optimal Tomography (NIROT) workflow with Maximum Entropy on the Mean (MEM), using personalized fNIRS and local 3D reconstruction to assess the hemodynamic response elicited during simultaneous walking and arithmetic tasks in healthy young and older adults. Personalized fNIRS consisted of following the Optimal Montage algorithm, which maximizes the positions of fNIRS sensors to increase sensitivity to two targeted brain regions: the Inferior Frontal Gyrus (IFG) and Middle Frontal Gyrus (MFG) which are both involved in performing mental arithmetic and shown to demonstrate compensatory behaviors in single task (mental arithmetic only) when compared to dual task (walking while performing mental arithmetic). Single and dual tasks were considered for five younger adults and two older adults. Subject-specific optimal montages were calculated to ensure maximum light sensitivity to the target ROI and sufficient spatial overlap between sensors, allowing local 3D reconstruction of [HbO] and [HbR] response along the underlying cortical surface. Single task consisted of a block design arithmetic task (Serial-Sevens: sequential subtraction. For dual task, the same arithmetic task was performed, while participants were walking on a treadmill. NIRSTORM software package was used for channel space analysis of fNIRS signal, motion correction, modified Beer Lambert Law and block averaging. Reconstruction in 3D using Maximum Entropy on the Mean (MEM) was calculated using the same number of trials for each subject. In addition to answering questions encompassing brain activity as a function of age and balancing a cognitive task during gait, the study provided data for investigating trends around motion artifacts and testing the effectiveness of an accelerometer during simultaneous gait and fNIRS acquisitions. Due to restrictions during the Covid-19 pandemic, this study serves as a proof of concept and methods in improving the quality of data

Detection of Human Vigilance State During Locomotion Using Wearable FNIRS

Human vigilance is a cognitive function that requires sustained attention toward change in the environment. Human vigilance detection is a widely investigated topic which can be accomplished by various approaches. Most studies have focused on stationary vigilance detection due to the high effect of interference such as motion artifacts which are prominent in common movements such as walking. Functional Near-Infrared Spectroscopy is a preferred modality in vigilance detection due to the safe nature, the low cost and ease of implementation. fNIRS is not immune to motion artifact interference, and therefore human vigilance detection performance would be severely degraded when studied during locomotion. Properly treating and removing walking-induced motion artifacts from the contaminated signals is crucial to ensure accurate vigilance detection. This study compared the vigilance level detection during both stationary and walking states and confirmed that the performance of vigilance level detection during walking is significantly deteriorated (with a