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Articles by Banu Onaral in JoVE

 

Using MazeSuite and Functional Near Infrared Spectroscopy to Study Learning in Spatial Navigation


JoVE 3443 10/08/2011

1School of Biomedical Engineering, Science and Health Systems, Drexel University, 2College of Nursing and Health Professions, Drexel University

MazeSuite is a complete toolset to prepare, present and analyze navigational and spatial experiments. Functional near-infrared spectroscopy (fNIR) is an optical brain imaging technique that enables noninvasive and portable monitoring of cerebral blood oxygenation changes. This paper summarizes collective use of MazeSuite and fNIR within a cognitive processing learning paradigm.

Other articles by Banu Onaral on PubMed

Safety Assessment of Near Infrared Light Emitting Diodes for Diffuse Optical Measurements

Near infrared (NIR) light has been used widely to monitor important hemodynamic parameters in tissue non-invasively. Pulse oximetry, near infrared spectroscopy, and diffuse optical tomography are examples of such NIR light-based applications. These and other similar applications employ either lasers or light emitting diodes (LED) as the source of the NIR light. Although the hazards of laser sources have been addressed in regulations, the risk of LED sources in such applications is still unknown.

Functional Near-infrared Neuroimaging

Functional near-infrared (fNIR) spectroscopy is a wearable neuroimaging device that enables the continuous, non-invasive, and portable monitoring of changes in blood oxygen and blood volume related to human brain function. Over the last three years, studies in the laboratory and under field conditions have established the positive correlation between a participant's performance and oxygenation responses as a function of task load. Our findings indicate that fNIR can effectively monitor attention and working memory in real-life situations. These experimental outcomes compare favorably with functional magnetic resonance imaging (fMRI) studies, and in particular, with the blood oxygenation level dependent (BOLD) signal. The capacity to monitor brain hemodynamics with a wearable device holds promise for the use of fNIR in the creation of a symbiotic relationship between the user and his/her everyday environment. Moreover, under operational conditions, the fNIR system is amenable to integration with other established physiological and neurobehavioral measures, including EEG, eye tracking, pupil reflex, heart rate variability, respiration and electrodermal activity.

Use of a Light Emitting Diode (LED) Array for Bilirubin Phototransformation

The Effect of Auditory Stimulation Upon Cerebral Blood Oxygenation in Infants: Measurements by Light Emitting Diode (LED) Near Infrared Spectroscopy

This study assessed the feasibility of neonatal cerebral oxygen monitoring by near-infrared light spectroscopy (NIRS) using a light emitting diode (LED) based system. We aimed to measure the changes in cerebral oxygen saturation, as regional oxygen saturation and tissue oxygenation index, in response to auditory stimuli. Documenting changes in oxygenation in response to such stimuli will help validate the usefulness of LED-NIRS as a tool in the study of cerebral oxygen saturation in neonates.

A Portable Near Infrared Spectroscopy System for Bedside Monitoring of Newborn Brain

Newborns with critical health conditions are monitored in neonatal intensive care units (NICU). In NICU, one of the most important problems that they face is the risk of brain injury. There is a need for continuous monitoring of newborn's brain function to prevent any potential brain injury. This type of monitoring should not interfere with intensive care of the newborn. Therefore, it should be non-invasive and portable.

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 Near-infrared Neuroimaging

Functional near-infrared spectroscopy (fNIR) is a neroimaging modality that enables continuous, noninvasive, and portable monitoring of changes in blood oxygenation and blood volume related to human brain function. Over the last decade, studies in the laboratory have established that fNIR spectroscopy provides a veridical measure of oxygenation and blood flow in the brain. Our recent findings indicate that fNIR can effectively monitor cognitive tasks such as attention, working memory, target categorization, and problem solving. These experimental outcomes compare favorably with functional magnetic resonance imaging (fMRI) studies, and in particular, with the blood oxygenation level dependent signal. Since fNIR can be implemented in the form of a wearable and minimally intrusive device, it has the capacity to monitor brain activity under real life conditions and in everyday environments. Moreover, the fNIR system is amenable to integration with other established physiological and neurobehavioral measures, including electroencephalogram, eye tracking, pupil reflex, heart rate variability, respiration, and electrodermal activity.

Functional Near-infrared Spectroscopy

Wavelet Analysis for EEG Feature Extraction in Deception Detection

Deception detection has important clinical and legal implications. However, the reliability of methods for the discrimination between truthful and deceptive responses is still limited. Efforts to improve reliability have examined measures of central nervous system function such as EEG. However, EEG analyses based on either time- or frequency-domain parameters have had mixed results. Because EEG is a nonstationary signal, the use of joint time-frequency features may yield more reliable results for detecting deception. The goal of this study was to investigate the feasibility of deception detection based on EEG features extracted through wavelet transformation. EEG was recorded from 4 electrode sites (F3, F4, F7, F8) during a modified version of the Guilty Knowledge Test (GKT) in 5 subjects. Wavelet analysis revealed significant differences between deceptive and truthful responses. These differences were detected in features whose frequency range roughly corresponds to the EEG beta rhythm and within a time window which coincides with the P300 component. These preliminary results indicate that joint time-frequency EEG features extracted through wavelet analysis may provide a more reliable method for detecting deception than standard ERPs.

Registering FNIR Data to Brain Surface Image Using MRI Templates

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.

Time-domain Analysis of EEG During Guilty Knowledge Test: Investigation of Epoch Extraction Criteria

The study of electroencephalography (EEG) for deception detection has long been regarded as an alternative to the standard polygraphy, whose main shortcoming is its unacceptably low level of reliability. Most of the EEG deception research has focused on the amplitude and topography of P300. However, the characteristics of the P300 component are tightly connected to the experimental design and hence countermeasures are easily available for P300-based deception detection. The goal of this study is to evaluate different epoching criteria for the extraction of EEG features that are most suitable for the discrimination between truthful and deceptive responses. In order to reach this aim, a modified version of the Guilty Knowledge Test was used where EEG recordings were obtained from four frontal electrodes and two midline electrodes. In none of the electrodes the P300 component differed between deceptive and truthful responses. Differences have instead been revealed through the extraction of response-locked epochs and analysis of area under the curve.

Functional Brain Imaging Using Near-infrared Technology

Maze Suite 1.0: a Complete Set of Tools to Prepare, Present, and Analyze Navigational and Spatial Cognitive Neuroscience Experiments

Maze Suite is a complete set of tools that enables researchers to perform spatial and navigational behavioral experiments within interactive, easy-to-create, and extendable (e.g., multiple rooms) 3-D virtual environments. Maze Suite can be used to design and edit adapted 3-D environments, as well as to track subjects' behavioral performance. Maze Suite consists of three main applications: an editing program for constructing maze environments (MazeMaker), a visualization/rendering module (MazeWalker), and an analysis and mapping tool (MazeViewer). Each of these tools is run and used from a graphical user interface, thus making editing, execution, and analysis user friendly. MazeMaker is a .NET architecture application that can easily be used to create new 3-D environments and to edit objects (e.g., geometric shapes, pictures, landscapes, etc.) or add them to the environment effortlessly. In addition, Maze Suite has the capability of sending signal-out pulses to physiological recording devices, using standard computer ports. Maze Suite, with all three applications, is a unique and complete toolset for researchers who want to easily and rapidly deploy interactive 3-D environments.

The Impact of Ablated Cortex on the Validity and Interpretation of the FNIRS Signal

Functional near infrared spectroscopy (fNIRS) is a safe and portable brain imaging modality that monitors changes in the hemodynamic activity at the cortical level. Although still in its emerging stage, fNIRS has recently gained increasing acknowledgements of its strengths and suitability for many clinical applications. The fast evolution and growth of fNIRS applications has been made possible mainly by studies that substantiate the general validity of the fNIRS measures. Such studies investigate both the fNIRS construct, by cross-validating it with fMRI, and the repeatability of fNIRS measures.Nonetheless, cases exist that would pose a challenge forfNIRS measures of cortical activation. In particular, violations of the assumptions made on the optical properties of the sampled tissue would affect some variables included in the modified Beer-Lambert law (mBBL), which allows conversion of the changes in measured light intensity into changes in the oxyhemoglobin and deoxyhemoglobin concentrations. These violations would therefore reflect on the fNIRS readings and on the way data are interpreted. The aim of this paper is to present an example of such challenging situations. The case presented is a subject whose left frontal lobe cortex has been partially ablated following a subdural hematoma. fNIRS measures were recorded during a verbal fluency task, known to be associated to functioning of the left frontal lobe. We examine the outcome of fNIRS, contextualizing it in the framework of the mBLL and its assumptions.

Array Lead Zirconate Titanate/glass Piezoelectric Microcantilevers for Real-time Detection of Bacillus Anthracis with 10 Spores/ml Sensitivity and 1/1000 Selectivity in Bacterial Mixtures

An array of three identical piezoelectric microcantilever sensors (PEMSs) consisting of a lead zirconate titanate layer bonded to a glass layer was fabricated and examined for simultaneous, in situ, real-time, all-electrical detection of Bacillus anthracis (BA) spores in an aqueous suspension using the first longitudinal extension mode of resonance. With anti-BA antibody immobilized on the sensor surfaces all three PEMS exhibited identical BA detection resonance frequency shifts at all tested concentrations, 10-10(7) spores/ml with a standard deviation of less than 10%. The detection concentration limit of 10 spores/ml was about two orders of magnitude lower than would be permitted by flexural peaks. In blinded-sample testing, the array PEMS detected BA in three samples containing BA: (1) 3.3x10(3) spores/ml, (2) a mixture of 3.3x10(3) spores/ml and 3.3x10(5) S. aureus (SA) and P. aeruginosa (PA) per ml, and (3) a mixture of 3.3x10(3) spores/ml with 3.3x10(6) SA+PA/ml. There was no response to a sample containing only 3.3x10(6) SA+PA/ml. These results illustrate the sensitivity, specificity, reusability, and reliability of array PEMS for in situ, real-time detection of BA spores.

Medial Prefrontal Cortex Hyperactivation During Social Exclusion in Borderline Personality Disorder

Frontal systems dysfunction and abandonment fears represent central features of borderline personality disorder (BPD). BPD subjects (n=10) and matched non-psychiatric comparison subjects (n=10) completed a social-cognitive task with two confederates instructed to either include or exclude subjects from a circumscribed interaction. Evoked cerebral blood oxygenation in frontal cortex was measured using 16-channel functional near infrared spectroscopy. BPD subjects showed left medial prefrontal cortex hyperactivation during social exclusion suggesting potential dysfunction of frontolimbic circuitry.

Motion Artifact Cancellation in NIR Spectroscopy Using Discrete Kalman Filtering

As 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.

Sliding-window Motion Artifact Rejection for Functional Near-Infrared Spectroscopy

Functional Near-Infrared Spectroscopy (fNIR) is an optical brain monitoring technology that tracks changes in hemodynamic responses within the cortex. fNIR uses specific wavelengths of light, introduced at 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 that can be used to measure brain activity in natural environments, ambulatory and field conditions. However, for such applications fNIR signals can get prone to noise due to motion of the head. Improving signal quality and reducing noise, can be especially challenging for real time applications. Here, we study motion artifact related noise especially due to poor and changing sensor coupling. We have developed a simple and iterative method that can be used to automate the preprocessing of data to identify segments with such noise for exclusion and this method is also suitable for real time applications.

FNIRS Study of Walking and Walking While Talking in Young and Old Individuals

Evidence suggests that gait is influenced by higher order cognitive and cortical control mechanisms. However, less is known about the functional correlates of cortical control of gait.

A Methodology for Validating Artifact Removal Techniques for FNIRS

fNIRS recordings are increasingly utilized to monitor brain activity in both clinical and connected health settings. These optical recordings provide a convenient measurement of cerebral hemodynamic changes which can be linked to motor and cognitive performance. Such measurements are of clinical utility in a broad range of conditions ranging from dementia to movement rehabilitation therapy. For such applications fNIRS is increasingly deployed outside the clinic for patient monitoring in the home. However, such a measurement environment is poorly controlled and motion, in particular, is a major source of artifacts in the signal, leading to poor signal quality for subsequent clinical interpretation. Artifact removal techniques are increasingly being employed with an aim of reducing the effect of the noise in the desired signal. Currently no methodology is available to accurately determine the efficacy of a given artifact removal technique due to the lack of a true reference for the uncontaminated signal. In this paper we propose a novel methodology for fNIRS data collection allowing for effective validation of artifact removal techniques. This methodology describes the use of two fNIRS channels in close proximity allowing them to sample the same measurement location; allowing for the introducing of motion artifact to only one channel while having the other free of contamination. Through use of this methodology, for each motion artifact epoch, a true reference for the uncontaminated signal becomes available for use in the development and performance evaluation of signal processing strategies. The advantage of the described methodology is demonstrated using a simple artifact removal technique with an accelerometer based reference.

An Optical Brain Computer Interface for Environmental Control

A brain computer interface (BCI) is a system that translates neurophysiological signals detected from the brain to supply input to a computer or to control a device. Volitional control of neural activity and its real-time detection through neuroimaging modalities are key constituents of BCI systems. The purpose of this study was to develop and test a new BCI design that utilizes intention-related cognitive activity within the dorsolateral prefrontal cortex using functional near infrared (fNIR) spectroscopy. fNIR is a noninvasive, safe, portable and affordable optical technique with which to monitor hemodynamic changes, in the brain's cerebral cortex. Because of its portability and ease of use, fNIR is amenable to deployment in ecologically valid natural working environments. We integrated a control paradigm in a computerized 3D virtual environment to augment interactivity. Ten healthy participants volunteered for a two day study in which they navigated a virtual environment with keyboard inputs, but were required to use the fNIR-BCI for interaction with virtual objects. Results showed that participants consistently utilized the fNIR-BCI with an overall success rate of 84% and volitionally increased their cerebral oxygenation level to trigger actions within the virtual environment.

Frontal Lobe Role in Simple Arithmetic Calculations: An FNIR Study

This study aimed to affirm the use of functional near-infrared spectroscopy (fNIR) in examining frontal lobe role during automatic (i.e., requires retrieval from long-term memory) and method-based (i.e., requires calculation) arithmetic processing. Adult university students (math difficulties [MD] and control) performed simple arithmetic calculations while monitored using an fNIR system designed to image regions within the frontal cortices. Addition and subtraction problems presented on a computer screen belonged to one of three categories: triples "under 10" (e.g., 2+3=?, 5-3=?), triples that "break 10" (e.g., 5+8=?, 13-5=?), or triples "including 10" (e.g., 10+7=?, 17-10=?). fNIR recordings indicated significant interactions between type of triple, operation, and group over left frontal lobe, and between type of triple and group over right frontal lobe. Within-group differences among controls were found in the "break 10" triples with higher DeOxyHb level recorded during subtraction processing. Between-group differences were found in the "break 10" and "including 10" triples for subtraction with higher levels of DeOxyHb recorded among controls. Results imply that among adults frontal lobe is still involved during simple mathematical processing and fNIR recordings can differentiate its role in adults of varying mathematical ability.

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.

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