Scott C. Bunce

Optical brain monitoring for operator training and mental workload assessment

An accurate measure of mental workload in human operators is a critical element of monitoring and adaptive aiding systems that are designed to improve the efficiency and safety of human-machine systems during critical tasks. Functional near infrared (fNIR) spectroscopy is a field-deployable non-invasive optical brain monitoring technology that provides a measure of cerebral hemodynamics within the prefrontal cortex in response to sensory, motor, or cognitive activation. In this paper, we provide evidence from two studies that fNIR can be used in ecologically valid environments to assess the: 1) mental workload of operators performing standardized (n-back) and complex cognitive tasks (air traffic control--ATC), and 2) development of expertise during practice of complex cognitive and visuomotor tasks (piloting unmanned air vehicles--UAV). Results indicate that fNIR measures are sensitive to mental task load and practice level, and provide evidence of the fNIR deployment in the field for its ability to monitor hemodynamic changes that are associated with relative cognitive workload changes of operators. The methods reported here provide guidance for the development of strategic requirements necessary for the design of complex human-machine interface systems and assist with assessments of human operator performance criteria.

Event-related brain potentials differentiate positive and negative mood adjectives during both supraliminal and subliminal visual processing

This experiment provides brain event-related potential (ERP) evidence for differential processing of visually presented pleasant and unpleasant affectively valent words (mood adjectives) for both supraliminal (40 ms) and subliminal (unmasked, 1 ms) stimulus durations. Unpleasant words elicited a more positive amplitude than pleasant words in both durations. ERP components (P1, N1, P2, P3, and a late positive potential; LP) were measured at six electrode sites (F3, F4, P3, P4, CzPz, Oz). ERPs to subliminal stimuli demonstrated differences between pleasant and unpleasant words in the left hemisphere across all measured components. Supraliminal processing showed similar differences in the left hemisphere for early components (P1 and N1), but bilateral differences for late components (P3 and LP). Activity in the P2 time window was associated with the divergence between supraliminal and subliminal affective responses. Implications for the study of affect and consciousness are discussed.

Functional Near Infrared Spectroscopy (fNIRS): An Emerging Neuroimaging Technology with Important Applications for the Study of Brain Disorders

Functional near-infrared spectroscopy (fNIRS) is an emerging functional neuroimaging technology offering a relatively non-invasive, safe, portable, and low-cost method of indirect and direct monitoring of brain activity. Most exciting is its potential to allow more ecologically valid investigations that can translate laboratory work into more realistic everyday settings and clinical environments. Our aim is to acquaint clinicians and researchers with the unique and beneficial characteristics of fNIRS by reviewing its relative merits and limitations vis-à-vis other brain-imaging technologies such as functional magnetic resonance imaging (fMRI). We review cross-validation work between fMRI and fNIRS, and discuss possible reservations about its deployment in clinical research and practice. Finally, because there is no comprehensive review of applications of fNIRS to brain disorders, we also review findings from the few studies utilizing fNIRS to investigate neurocognitive processes associated with neurological (Alzheimers disease, Parkinsons disease, epilepsy, traumatic brain injury) and psychiatric disorders (schizophrenia, mood disorders, anxiety disorders).

Functional near-infrared spectroscopy

The purpose of the this article is to describe an emerging neuroimaging technology, functional near-infrared spectroscopy (fNIRs), which has several attributes that make it possible to conduct neuroimaging studies of the cortex in clinical offices and under more realistic, ecologically valid parameters. fNIRs use near-infrared light to measure changes in the concentration of oxygenated and deoxygenated hemoglobin in the cortex. Although fNIR imaging is limited to the outer cortex, it provides neuroimaging that is safe, portable, and very affordable relative to other neuroimaging technologies. It is also relatively robust to movement artifacts and can readily be integrated with other technologies such as EEG

Functional Optical Brain Imaging Using Near-Infrared During Cognitive Tasks

A symbiotic relation between the operator and the operational environment can be realized by an advanced computing platform designed to understand and adapt to the cognitive and the physiological state of the user, especially during sensitive and cognitively demanding operations. The success of such a complex system depends not only on the efficacy of the individual components, but also on the efficient and appropriate integration of its parts. Because near infrared technology allows the design of portable, safe, affordable, and negligibly intrusive monitoring systems, the functional near infrared (fNIR) monitoring of brain hemodynamics can be of value in this type of complex system, particularly in helping to understand the cognitive and emotional state of the user during mentally demanding operations. This article presents the deployment and statistical analysis of fNIR spectroscopy for the purpose of cognitive state assessment while the user performs a complex task. This article is based on data collected during the Augmented Cognition-Technical Integration Experiment session. The experimental protocol for this session used a complex task, resembling a video game, called the Warship Commander Task (WCT). The WCT was designed to approximate naval air warfare management. Task difficulty and task load were manipulated by changing the following: (a) the number of airplanes that had to be managed at a given time, (b) the number of unknown (vs. known) airplane identities, and (c) the presence or absence of an auditory memory task. The fNIR data analysis explored the following: (a) the relations among cognitive workload, the participants performance, and changes in blood oxygenation levels of the dorsolateral prefrontal cortex; and (b) the effect of divided attention as manipulated by the secondary component of the WCT (the auditory task). The primary hypothesis was that blood oxygenation in the prefrontal cortex, as assessed by fNIR, would rise with increasing task load and would demonstrate a positive correlation with performance measures. The results indicated that the rate of change in blood oxygenation was significantly sensitive to task load changes and correlated fairly well with performance variables.

Motion artifact cancellation in NIR spectroscopy using Wiener filtering

We present a Wiener filtering based algorithm for the elimination of motion artifacts present in Near Infrared (NIR) spectroscopy measurements. Until now, adaptive filtering was the only technique used in the noise cancellation in NIR studies. The results in this preliminary study revealed that the proposed method gives better estimates than the classical adaptive filtering approach without the need for additional sensor measurements. Moreover, this novel technique has the potential to filter out motion artifacts in functional near infrared (fNIR) signals, too.

Functional brain imaging using near-infrared technology

0739-5175/07/

Motion artifact cancellation in NIR spectroscopy using discrete Kalman filtering.

25.00©2007IEEE I n the last decade, functional near-infrared spectroscopy (fNIR) has been introduced as a new neuroimaging modality with which to conduct functional brain imaging studies [1]–[24]. fNIR technology uses specific wavelengths of light, irradiated through the scalp, to enable the noninvasive measurement of changes in the relative ratios of deoxygenated hemoglobin (deoxy-Hb) and oxygenated hemoglobin (oxy-Hb) during brain activity. This technology allows the design of portable, safe, affordable, noninvasive, and minimally intrusive monitoring systems. These qualities make fNIR suitable for the study of hemodynamic changes due to cognitive and emotional brain activity under many working and educational conditions, as well as in the field. Functional imaging is typically conducted in an effort to understand the activity in a given brain region in terms of its relationship to a particular behavioral state or its interactions with inputs from another region’s activity. The program of research in cognitive neuroscience conducted by our optical brain imaging group has utilized the current-generation fNIR system to investigate brain activity, primarily in the dorsolateral and inferior frontal cortex [20]–[24]. To date, the fNIR studies of cognition and emotion have focused on functions associated with Brodman’s areas BA9, BA10, BA46, BA45, BA47, and BA44. Recent positron emission tomography (PET) and functional magnetic resonance (fMRI) studies have shown that these areas play a critical role in sustained attention, both the short-term storage and the executive process components of working memory, episodic memory, problem solving, response inhibition, and the perception of smell (for a recent review, see [25] and [26]). In addition, word recognition and the storage of verbal materials activate Broca’s area and left hemisphere supplementary and premotor areas [25], [27], [28]. To date, studies utilizing fNIR have shown results consistent with fMRI and PET findings for working memory and sustained attention [21]–[23]. In this article, we will describe the working principles of fNIR and how the hemodynamic signals are extracted from the raw fNIR measurements using the modified Beer-Lambert Law. We will also introduce the fNIR system that we have developed and used in our studies. Current results from the augmented cognition research conducted in our laboratory are also presented, and the merits of optical imaging in augmented cognition are summarized. Working Principles Typically, an optical apparatus consists of a light source by which the tissue is radiated and a light detector that receives light after it has interacted with the tissue. Photons that enter tissue undergo two different types of interaction, namely absorption (loss of energy to the medium) and scattering [4], [5], [19]. Most biological tissues are relatively transparent to light in the near-infrared range between 700 to 900 nm, which is usually called the “optical window.” This is mainly due to the fact that within this optical window, the absorbance of the main constituents in the human tissue (i.e., water, oxy-Hb, and deoxy-Hb) is small, allowing the light to penetrate the tissue (see Figure 1). Among the main absorbers (chromophores) in the tissue, oxyand deoxy-Hb are strongly linked to tissue oxygenation and metabolism. Fortunately, in the optical window, the absorption spectra of oxyand deoxy-Hb remain significantly different than each other, allowing spectroscopic separation of these compounds to be possible using only a few sample wavelengths. fNIR technology employs specified wavelengths of light within the optical window. Once the photons are introduced into the human head, they are either scattered by extraand intracellular boundaries of different layers of the head (skin, skull, cerebrospinal fluid, brain, etc.) or absorbed mainly by oxyand deoxy-Hb. A photodetector placed a certain distance away from the light source can collect the photons that are not absorbed and those that traveled along the “banana shaped path” between the source and detector due to scattering [9], [29] as shown Figure 2. In functional optical brain imaging studies, the attenuation (reduction in the amount of photons detected by the photodetectors) due to scattering is assumed to be constant since the amount of scatterers within different layers of the head does not change due to cognitive activity. The change in the attenuation measured as a result of cognitive activity is hence due to the changes in absorption resulting from the variation in the concentrations of oxyand deoxy-Hb in the brain tissue. This relationship is not surprising, since cerebral hemodynamic changes are related to functional brain activity through a mechanism that is called neurovascular coupling [8], [30]. In fact, this physiological relationship and the ability of fNIR Functional Brain Imaging Using Near-Infrared Technology

Registering fNIR Data to Brain Surface Image using MRI templates

BackgroundAs a continuation of our earlier work, we present in this study a Kalman filtering based algorithm for the elimination of motion artifacts present in Near Infrared spectroscopy (NIR) measurements. Functional NIR measurements suffer from head motion especially in real world applications where movement cannot be restricted such as studies involving pilots, children, etc. Since head movement can cause fluctuations unrelated to metabolic changes in the blood due to the cognitive activity, removal of these artifacts from NIR signal is necessary for reliable assessment of cognitive activity in the brain for real life applications.MethodsPreviously, we had worked on adaptive and Wiener filtering for the cancellation of motion artifacts in NIR studies. Using the same NIR data set we have collected in our previous work where different speed motion artifacts were induced on the NIR measurements we compared the results of the newly proposed Kalman filtering approach with the results of previously studied adaptive and Wiener filtering methods in terms of gains in signal to noise ratio. Here, comparisons are based on paired t-tests where data from eleven subjects are used.ResultsThe preliminary results in this current study revealed that the proposed Kalman filtering method provides better estimates in terms of the gain in signal to noise ratio than the classical adaptive filtering approach without the need for additional sensor measurements and results comparable to Wiener filtering but better suitable for real-time applications.ConclusionsThis paper presented a novel approach based on Kalman filtering for motion artifact removal in NIR recordings. The proposed approach provides a suitable solution to the motion artifact removal problem in NIR studies by combining the advantages of the existing adaptive and Wiener filtering methods in one algorithm which allows efficient real time application with no requirement on additional sensor measurements.

Further evidence for unconscious learning: preliminary support for the conditioning of facial EMG to subliminal stimuli.

Functional near-infrared spectroscopy (fNIR) measures changes in the relative levels of oxygenated and deoxygenated hemoglobin and has increasingly been used to assess neural functioning in the brain. In addition to the ongoing technological developments, investigators have also been conducting studies on functional mapping and refinement of data analytic strategies in order to better understand the relationship between the fNIR signal and brain activity. However, since fNIR is a relatively new functional brain imaging modality as compared to positron emission tomography (PET) and functional magnetic resonance imaging (fMRI), it still lacks brain-mapping tools designed to allow researchers and clinicians to easily interact with their data. The aim of this study is to develop a registration technique for the fNIR measurements using anatomical landmarks and structural magnetic resonance imaging (MRI) templates in order to visualize the brain activation when and where it happens. The proposed registration technique utilizes chain-code algorithm and depicts activations over respective locations based on sensor geometry. Furthermore, registered data locations have been used to create spatiotemporal visualization of fNIR measurements