Technical NoteNormative database of judgment of complexity task with functional near infrared spectroscopy—Application for TBI
Highlights
► Normative database of activation for the judgment of complexity task. ► Functional Near infrared spectroscopy images registered with MRI anatomical image. ► Activation in the prefrontal cortex which is consistent with previous fMRI results. ► Quick and easy detection of activation of frontal lobe in group study, creation of group data and look their variability.
Introduction
Traumatic brain injury (TBI) is a major public health problem, affecting almost 1.6 million people in the United States annually (Maas et al., 2008). TBI is also prevalent in the military population (Rish et al., 1983), ranging in severity from mild, closed TBI to penetrating head injuries (PHI) from low-velocity metallic shrapnel. The prefrontal cortex is particularly vulnerable to TBI and injuries there lead to impaired executive function which is a major source of disability and social displacement, even in patients who recover well in other spheres (Hanna-Pladdy, 2007, Salazar et al., 1995, Schwab et al., 1993). Functional neuroimaging, particularly functional magnetic resonance imaging (fMRI), which provides a local measure of Blood Oxygenation Level Dependent (BOLD) signal during behavior, is widely used to investigate cognitive processes and has been proposed as a means of evaluating deficits due to TBI and guiding rehabilitation (Dubroff and Newberg, 2008, Hillary et al., 2002, Laatsch, 2007, Ptito et al., 2007, Wishart et al., 2002). However, fMRI is relatively expensive, requires specialized, permanently sited, facilities and specialized personnel; these are often unavailable in the acute setting.
Functional near infrared spectroscopy (fNIRS) is an established technique to noninvasively measure local hemodynamic changes in brain areas near the head surface. Multi-channel fNIRS systems can produce maps of brain activation during cognitive, perceptual, and motor tasks (Benaron et al., 2000, Boas et al., 2004, Villringer and Chance, 1997) and may have utility for imaging brain activation in neurological disease or after TBI. The technique takes advantage of the fact that biological tissues are relatively transparent to light in the near-infrared (700–1000 nm) range (Ferrari et al., 2004). Light sources, usually lasers, are applied to the scalp and surrounding detectors (optodes), a few centimeters away, detect the light as it scatters and diffuses through the underlying tissues. The system detects changes in the absorption spectrum of the tissue corresponding to local changes in oxyhemoglobin (HbO) and deoxyhemoglobin (HbR) concentrations related to regional brain activity. The blood flow response to brain activation shows the same overshoot in HbR. This is familiar to fMRI users who use the BOLD contrast in the same way (Boas et al., 2003, Boas et al., 2004). fNIRS has the additional advantage of directly measuring HbO, HbR, and total hemoglobin concentration.
Though fMRI is useful in the diagnosis and development of treatment strategies for TBI, facilities with fMRI capability are not always readily available during the acute stage of head injury thus necessitating development of alternative approaches to functional imaging. fNIRS, with its simple and inexpensive apparatus, may represent a substitute for the current functional imaging “gold standard”, fMRI, where appropriate paradigms have been established and cross-validated. However, unlike fMRI which can provide registered functional and anatomical images, fNIRS images require registration with individual data or a standard anatomical system for interpretation and analysis. This requires co-registration with anatomical images and the need to develop simple, reproducible techniques for image construction. Several techniques have been developed to co-register functional images from fNIRS with structural images into a common space. However, this registration depends on the ability to reliably localize the optodes on the scalp. One technique is to use probabilistically locations on a pre-existing neurological atlas (Ayaz et al., 2006, Okamoto and Dan, 2005, Okamoto et al., 2004, Okamoto et al., 2009) for positioning the light sources and the detectors needed to acquire an fNIRS image. However, optode position is difficult to estimate without instrumentation, and errors can lead to unreliable fNIRS measurement (Kleinschmidt et al., 1996). Another solution is to acquire a structural head image including the locations of the optodes (Cui et al., 2010). However, this method does not allow positioning of optodes over specific brain areas or consistent optode positioning for repeated experiments. Additionally, the anatomical and functional images have to be acquired within a short time frame and the structural imaging device may have limited availability.
Co-registering physical points (optode coordinates) with two- or three-dimensional images (anatomical images) can be done with 3-D digitization and stereotaxic systems. The challenge consists in finding the appropriate registration algorithm. The alignment between the structural image (MRI generally) and the point surface measurement is done using landmark points (reference points easily identifiable), surface fitting alignment (surface of the scalp), or a combination of the two (Whalen et al., 2008). Such methods are commonly used for transcranial magnetic stimulation (TMS) and give good localization (Sparing et al., 2008). Frameless stereotaxy has the advantage of being able to co-register optode coordinates and the subject's MRI, thereby allowing group analysis by registering group data in the same space and avoiding the need for anatomical scanning with the optodes in place.
Here, we replicated an fMRI study, using a simple fNIRS technique combined with frameless stereotaxy and a novel angular method to localize scalp activations. The goal was to quantitatively compare the locations of the activations detected with the two techniques and a preliminary estimate of individual topographical variation in the fNIRS measurements. This latter goal, in particular, is relevant to developing a clinical test. We adapted a cognitive activation paradigm (Krueger et al., 2009), which produced robust anterior frontal activation on fMRI, to the fNIRS environment.
Section snippets
Participants
Twenty healthy native English speakers (10 females and 10 males; aged (mean ± s.d.) 28.3 ± 5.7 years) participated in the experiment. None of the participants had a history of medical, psychiatric, or neurological disorder; no participant was taking neuroactive medications. Written informed consent was obtained and the study was approved by the Brain Institutional Review Board of the National Institutes of Health, Bethesda, MD, USA.
Experimental design
We chose an event-related paradigm previously shown to produce
Results
For each source/detector pair of a single subject, the Complexity condition was contrasted with the Font condition and normalized to the subject's maximum intensity value from the 16 source/detector pairs for that condition. Fig. 2 shows the normalized contrasted HRF (HbO and HbR) for 20 subjects for the source/detector pair with the maximum activation intensity.
Activation maps were created for each subject from the 16 integrated HRFs. Each pixel of the activation map corresponds to one
Discussion
The prefrontal cortex is particularly vulnerable in TBI and physiological markers of brain function are mostly important for diagnosis in mild injury and prognosis across the severity spectrum. Physiological surrogates for behavioral outcomes are also needed for therapeutic trials. This is the first step in developing a simple method to evaluate the linkage of prefrontal cortex cognitive activity to hemodynamic response. In this experiment, we successfully used a cognitive task that had
Acknowledgments
We thank Dr. Jordan Grafman for his valuable suggestions and comments on this project. We also acknowledge the funding of the intramural program of the Eunice Kennedy Shriver National Institute of Child Health and Human Development, the National Institute of Neurological Disorders and Stroke and Center for Neuroscience and Regenerative Medicine.
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