Normative database of judgment of complexity task with functional near infrared spectroscopy--application for TBI

Tomographic Task-Related Functional Near-Infrared Spectroscopy in Acute Sport-Related Concussion: An Observational Case Study

Making decisions regarding return-to-play after sport-related concussion (SRC) based on resolution of symptoms alone can expose contact-sport athletes to further injury before their recovery is complete. Task-related functional near-infrared spectroscopy (fNIRS) could be used to scan for abnormalities in the brain activation patterns of SRC athletes and help clinicians to manage their return-to-play. This study aims to show a proof of concept of mapping brain activation, using tomographic task-related fNIRS, as part of the clinical assessment of acute SRC patients. A high-density frequency-domain optical device was used to scan 2 SRC patients, within 72 h from injury, during the execution of 3 neurocognitive tests used in clinical practice. The optical data were resolved into a tomographic reconstruction of the brain functional activation pattern, using diffuse optical tomography. Moreover, brain activity was inferred using single-subject statistical analyses. The advantages and limitations of the introduction of this optical technique into the clinical assessment of acute SRC patients are discussed.

On fractality of functional near-infrared spectroscopy signals: analysis and applications

Significance: The human brain is a highly complex system with nonlinear, dynamic behavior. A majority of brain imaging studies employing functional near-infrared spectroscopy (fNIRS), however, have considered only the spatial domain and have ignored the temporal properties of fNIRS recordings. Methods capable of revealing nonlinearities in fNIRS recordings can provide new insights about how the brain functions. Aim: The temporal characteristics of fNIRS signals are explored by comprehensively investigating their fractal properties. Approach: Fractality of fNIRS signals is analyzed using scaled windowed variance (SWV), as well as using visibility graph (VG), a method which converts a given time series into a graph. Additionally, the fractality of fNIRS signals obtained under resting-state and task-based conditions is compared, and the application of fractality in differentiating brain states is demonstrated for the first time via various classification approaches. Results: Results from SWV analysis show the existence of high fractality in fNIRS recordings. It is shown that differences in the temporal characteristics of fNIRS signals related to task-based and resting-state conditions can be revealed via the VGs constructed for each case. Conclusions: fNIRS recordings, regardless of the experimental conditions, exhibit high fractality. Furthermore, VG-based metrics can be employed to differentiate rest and task-execution brain states.

Neurodevelopmental Outcomes Associated with Prefrontal Cortical Deoxygenation in Children with Fetal Alcohol Spectrum Disorders

Relationships between neurodevelopmental functioning and hemodynamic changes in the prefrontal cortex (PFC) were contrasted between children with prenatal alcohol exposure (PAE) and children who differed relative to their history of PAE and the presence of other neurodevelopmental impairment. For all groups, deoxygenated hemoglobin (HBR) levels in the medial PFC area were negatively related to externalizing problems and levels in the medial and right lateral PFC were positively related to errors on a cognitive inhibition task. Hemodynamic changes in the medial and right lateral PFC of children with PAE demonstrated stronger relationships to aspects of executive functioning relative to contrast groups.

Effects of Performance and Task Duration on Mental Workload during Working Memory Task

N-back is a working memory (WM) task to study mental workload on the prefrontal cortex (PFC). We assume that the subject’s performance and changes in mental workload over time depends on the length of the experiment. The performance of the participant can change positively due to the participant’s learning process or negatively because of objective mental fatigue and/or sleepiness. In this pilot study, we examined the PFC activation of 23 healthy subjects while they performed an N-back task with two different levels of task difficulty (2-, and 3-back). The hemodynamic responses were analyzed along with the behavioral data (correct answers). A comparison was done between the hemodynamic activation and behavioral data between the two different task levels and between the beginning and end of the 3-back task. Our results show that there is a significant difference between the two task levels, which is due to the difference in task complication. In addition, a significant difference was seen between the beginning and end of the 3-back task in both behavioral data and hemodynamics due to the subject’s learning process throughout the experiment.

The Use of Functional Near-Infrared Spectroscopy to Differentiate Alcohol-Related Neurodevelopmental Impairment

Oxygenated (HBO) and deoxygenated hemoglobin (HBR) levels in the prefrontal cortex (PFC) were measured using functional near-infrared spectroscopy (fNIRS) to determine if PFC activity during a cognitive inhibition task distinguishes children with prenatal alcohol exposure (PAE, n = 26) from both typically developing controls (n = 19) and a contrast group of children with other neurobehavioral problems (n = 14). Despite showing evidence of increased PFC activity in the non-inhibitory condition relative to controls, children in the PAE group displayed reduced PFC HBO and increased HBR relative to both other groups in the inhibitory condition, suggesting reduced PFC activity but increased oxygen consumption without sufficient oxygen replacement.

Exploring the role of task performance and learning style on prefrontal hemodynamics during a working memory task

Existing literature outlines the quality and location of activation in the prefrontal cortex (PFC) during working memory (WM) tasks. However, the effects of individual differences on the underlying neural process of WM tasks are still unclear. In this functional near infrared spectroscopy study, we administered a visual and auditory n-back task to examine activation in the PFC while considering the influences of task performance, and preferred learning strategy (VARK score). While controlling for age, results indicated that high performance (HP) subjects (accuracy > 90%) showed task dependent lower activation compared to normal performance subjects in PFC region Specifically HP groups showed lower activation in left dorsolateral PFC (DLPFC) region during performance of auditory task whereas during visual task they showed lower activation in the right DLPFC. After accounting for learning style, we found a correlation between visual and aural VARK score and level of activation in the PFC. Subjects with higher visual VARK scores displayed lower activation during auditory task in left DLPFC, while those with higher visual scores exhibited higher activation during visual task in bilateral DLPFC. During performance of auditory task, HP subjects had higher visual VARK scores compared to NP subjects indicating an effect of learning style on the task performance and activation. The results of this study show that learning style and task performance can influence PFC activation, with applications toward neurological implications of learning style and populations with deficits in auditory or visual processing.

Prefrontal cortical responses in children with prenatal alcohol-related neurodevelopmental impairment: A functional near-infrared spectroscopy study

OBJECTIVE

Disruption in the neural activation of the prefrontal cortex (PFC) in modulating arousal was explored in children with heavy prenatal alcohol exposure (PAE), who have known neurobehavioral impairment.

METHODS

During a task that elicits frustration, functional near-infrared spectroscopy (fNIRS) was used to measure PFC activation, specifically levels of oxygenated (HBO) and deoxygenated (HBR) hemoglobin, in children with PAE (n=18) relative to typically developing Controls (n=12) and a Clinical Contrast group with other neurodevelopmental or behavioral problems (n=14).

RESULTS

Children with PAE had less activation during conditions with positive emotional arousal, as indicated by lower levels of HBO in the medial areas of the PFC and higher levels of HBR in all areas of the PFC sampled relative to both other groups. Children in the Control group demonstrated greater differentiation of PFC activity than did children with PAE. Children in the Clinical Contrast group demonstrated the greatest differences in PFC activity between valences of task conditions.

CONCLUSIONS

Specific patterns of PFC activation differentiated children with PAE from typically developing children and children with other clinical problems.

SIGNIFICANCE

FNIRS assessments of PFC activity provide new insights regarding the mechanisms of commonly seen neurobehavioral dysfunction in children with PAE.

Cortical activity changes as related to oral irritation-an fNIRS study

We present the first investigation of how the cortical regions of the brain respond to the sensations related to oral irritation, using functional near-infrared spectroscopy (fNIRS). fNIRS is used to record irritant-induced activities in the prefrontal and somatosensory regions of nine healthy individuals. Two types of solutions, irritant-free and soft tissue-irritant-contained, are adopted as the stimuli for the control and task experiments, respectively. Our findings reveal that both somatosensory and prefrontal regions show activity as a result of oral irritation. Furthermore, using moving window analysis, we identify the time interval during which the largest number of channels (indicative of high involvement of cortical regions) show irritant-induced activity. Our results indicate that fNIRS can be used to study brain activities related to oral irritation.

Prefrontal Activation During Executive Tasks Emerges Over Early Childhood: Evidence From Functional Near Infrared Spectroscopy

Functional Near Infrared Spectroscopy (fNIRS) is a brain imaging technique that is well-suited for use in young children, making it particularly useful for investigating the neural bases of the development of executive functions. In the present study, children (ages 4-10) underwent fNIRS while completing response inhibition and working memory tasks. While both tasks were associated with increases in oxyhemoglobin and decreases in deoxyhemoglobin, we found that strength of activation increased with age and with improvements in task performance. These findings support the relation between emerging executive functions and maturation of the prefrontal cortex.

Prefrontal Hemodynamics in Toddlers at Rest: A Pilot Study of Developmental Variability

Functional near infrared spectroscopy (fNIRS) is a non-invasive functional neuroimaging modality. Although, it is amenable to use in infants and young children, there is a lack of fNIRS research within the toddler age range. In this study, we used fNIRS to measure cerebral hemodynamics in the prefrontal cortex (PFC) in 18-36 months old toddlers (n = 29) as part of a longitudinal study that enrolled typically-developing toddlers as well as those "at risk" for language and other delays based on presence of early language delays. In these toddlers, we explored two hemodynamic response indices during periods of rest during which time audiovisual children's programming was presented. First, we investigate Lateralization Index, based on differences in oxy-hemoglobin saturation from left and right prefrontal cortex. Then, we measure oxygenation variability (OV) index, based on variability in oxygen saturation at frequencies attributed to cerebral autoregulation. Preliminary findings show that lower cognitive (including language) abilities are associated with fNIRS measures of both lower OV index and more extreme Lateralization index values. These preliminary findings show the feasibility of using fNIRS in toddlers, including those at risk for developmental delay, and lay the groundwork for future studies.

A machine learning approach to identify functional biomarkers in human prefrontal cortex for individuals with traumatic brain injury using functional near-infrared spectroscopy

BACKGROUND

We have explored the potential prefrontal hemodynamic biomarkers to characterize subjects with Traumatic Brain Injury (TBI) by employing the multivariate machine learning approach and introducing a novel task-related hemodynamic response detection followed by a heuristic search for optimum set of hemodynamic features. To achieve this goal, the hemodynamic response from a group of 31 healthy controls and 30 chronic TBI subjects were recorded as they performed a complexity task.

METHODS

To determine the optimum hemodynamic features, we considered 11 features and their combinations in characterizing TBI subjects. We investigated the significance of the features by utilizing a machine learning classification algorithm to score all the possible combinations of features according to their predictive power.

RESULTS AND CONCLUSIONS

The identified optimum feature elements resulted in classification accuracy, sensitivity, and specificity of 85%, 85%, and 84%, respectively. Classification improvement was achieved for TBI subject classification through feature combination. It signified the major advantage of the multivariate analysis over the commonly used univariate analysis suggesting that the features that are individually irrelevant in characterizing the data may become relevant when used in combination. We also conducted a spatio-temporal classification to identify regions within the prefrontal cortex (PFC) that contribute in distinguishing between TBI and healthy subjects. As expected, Brodmann areas (BA) 10 within the PFC were isolated as the region that healthy subjects (unlike subjects with TBI), showed major hemodynamic activity in response to the High Complexity task. Overall, our results indicate that identified temporal and spatio-temporal features from PFC's hemodynamic activity are promising biomarkers in classifying subjects with TBI.

A Review of the Effectiveness of Neuroimaging Modalities for the Detection of Traumatic Brain Injury

The incidence of traumatic brain injury (TBI) in the United States was 3.5 million cases in 2009, according to the Centers for Disease Control and Prevention. It is a contributing factor in 30.5% of injury-related deaths among civilians. Additionally, since 2000, more than 260,000 service members were diagnosed with TBI, with the vast majority classified as mild or concussive (76%). The objective assessment of TBI via imaging is a critical research gap, both in the military and civilian communities. In 2011, the Department of Defense (DoD) prepared a congressional report summarizing the effectiveness of seven neuroimaging modalities (computed tomography [CT], magnetic resonance imaging [MRI], transcranial Doppler [TCD], positron emission tomography, single photon emission computed tomography, electrophysiologic techniques [magnetoencephalography and electroencephalography], and functional near-infrared spectroscopy) to assess the spectrum of TBI from concussion to coma. For this report, neuroimaging experts identified the most relevant peer-reviewed publications and assessed the quality of the literature for each of these imaging technique in the clinical and research settings. Although CT, MRI, and TCD were determined to be the most useful modalities in the clinical setting, no single imaging modality proved sufficient for all patients due to the heterogeneity of TBI. All imaging modalities reviewed demonstrated the potential to emerge as part of future clinical care. This paper describes and updates the results of the DoD report and also expands on the use of angiography in patients with TBI.

Effect of mechanical optical clearing on near-infrared spectroscopy

Near-infrared Spectroscopy (NIRS) is a broadly utilized technology with many emerging applications including clinical diagnostics, sports medicine, and functional neuroimaging, to name a few. For functional brain imaging NIR light is delivered at multiple wavelengths through the scalp and skull to the brain to enable spatial oximetry measurements. Dynamic changes in brain oxygenation are highly correlated with neural stimulation, activation, and function. Unfortunately, NIRS is currently limited by its low spatial resolution, shallow penetration depth, and, perhaps most importantly, signal corruption due to light interactions with superficial non-target tissues such as scalp and skull. In response to these issues, we have combined the non-invasive and rapidly reversible method of mechanical tissue optical clearing (MOC) with a commercially available NIRS system. MOC utilizes a compressive loading force on tissue, causing the lateral displacement of blood and water, while simultaneously thinning the tissue. A MOC-NIRS Breath Hold Test displayed a ∼3.5-fold decrease in the time-averaged standard deviation between channels, consequentially promoting greater channel agreement. A Skin Pinch Test was implemented to negate brain and muscle activity from affecting the recorded signal. These results displayed a 2.5-3.0 fold increase in raw signal amplitude. Existing NIRS instrumentation has been further integrated within a custom helmet device to provide a uniform force distribution across the NIRS sensor array. These results showed a gradual decrease in time-averaged standard deviation among channels with an increase in applied pressure. Through these experiments, and the development of the MOC-NIRS helmet device, MOC appears to provide enhancement of NIRS technology beyond its current limitations.

Relative brain signature: a population-based feature extraction procedure to identify functional biomarkers in the brain of alcoholics

BACKGROUND

A novel feature extraction technique, Relative-Brain-Signature (RBS), which characterizes subjects' relationship to populations with distinctive neuronal activity, is presented. The proposed method transforms a set of Electroencephalography's (EEG) time series in high dimensional space to a space of fewer dimensions by projecting time series onto orthogonal subspaces.

METHODS

We apply our technique to an EEG data set of 77 abstinent alcoholics and 43 control subjects. To characterize subjects' relationship to the alcoholic and control populations, one RBS vector with respect to the alcoholic and one with respect to the control population is constructed. We used the extracted RBS vectors to identify functional biomarkers over the brain of alcoholics. To achieve this goal, the classification algorithm was used to categorize subjects into alcoholics and controls, which resulted in 78% accuracy.

RESULTS AND CONCLUSIONS

Using the results of the classification, regions with distinctive functionality in alcoholic subjects are detected. These affected regions, with respect to their spatial extent, are frontal, anterior frontal, centro-parietal, parieto-occiptal, and occipital lobes. The distribution of these regions over the scalp indicates that the impact of the alcohol in the cerebral cortex of the alcoholics is spatially diffuse. Our finding suggests that these regions engage more of the right hemisphere relative to the left hemisphere of the alcoholics' brain.

Prefrontal cortex hemodynamics and age: a pilot study using functional near infrared spectroscopy in children

Cerebral hemodynamics reflect cognitive processes and underlying physiological processes, both of which are captured by functional near infrared spectroscopy (fNIRS). Here, we introduce a novel parameter of Oxygenation Variability directly obtained from fNIRS data —the OV Index—and we demonstrate its use in children. fNIRS data were collected from 17 children (ages 4–8 years), while they performed a standard Go/No-Go task. Data were analyzed using two frequency bands—the first attributed to cerebral autoregulation (CA) (<0.1 Hz) and the second to respiration (0.2–0.3 Hz). Results indicate differences in variability of oscillations of oxygen saturation (SO₂) between the two different bands. These pilot data reveal a dynamic relationship between chronological age and OV index in CA associated frequency of <0.1 Hz. Specifically, OV index increased with age between 4 and 6 years. In addition, there was much higher variability in frequencies associated with CA than for respiration across subjects. These findings provide preliminary evidence for the utility of the OV index and are the first to describe the relationship between cerebral autoregulation and age in children using fNIRS methodology.

Atlas-based head modeling and spatial normalization for high-density diffuse optical tomography: in vivo validation against fMRI

Diffuse optical imaging (DOI) is increasingly becoming a valuable neuroimaging tool when fMRI is precluded. Recent developments in high-density diffuse optical tomography (HD-DOT) overcome previous limitations of sparse DOI systems, providing improved image quality and brain specificity. These improvements in instrumentation prompt the need for advancements in both i) realistic forward light modeling for accurate HD-DOT image reconstruction, and ii) spatial normalization for voxel-wise comparisons across subjects. Individualized forward light models derived from subject-specific anatomical images provide the optimal inverse solutions, but such modeling may not be feasible in all situations. In the absence of subject-specific anatomical images, atlas-based head models registered to the subject's head using cranial fiducials provide an alternative solution. In addition, a standard atlas is attractive because it defines a common coordinate space in which to compare results across subjects. The question therefore arises as to whether atlas-based forward light modeling ensures adequate HD-DOT image quality at the individual and group level. Herein, we demonstrate the feasibility of using atlas-based forward light modeling and spatial normalization methods. Both techniques are validated using subject-matched HD-DOT and fMRI data sets for visual evoked responses measured in five healthy adult subjects. HD-DOT reconstructions obtained with the registered atlas anatomy (i.e. atlas DOT) had an average localization error of 2.7mm relative to reconstructions obtained with the subject-specific anatomical images (i.e. subject-MRI DOT), and 6.6mm relative to fMRI data. At the group level, the localization error of atlas DOT reconstruction was 4.2mm relative to subject-MRI DOT reconstruction, and 6.1mm relative to fMRI. These results show that atlas-based image reconstruction provides a viable approach to individual head modeling for HD-DOT when anatomical imaging is not available.