Appendix D
Background Information on Functional Neuroimaging

FUNCTIONAL NEAR-INFRARED SPECTROSCOPY

Principles

It is well known that the functional state of tissue can influence its optical properties (for instance, cyanosis in hypoxia and pallor in anemia). The human brain undergoes a number of physiological changes as it responds to environmental stimuli, and these changes in electrochemical activity and blood chemistry also affect the optical properties of neuronal tissues. Functional optical imaging capitalizes on those changing optical properties in measuring neural activity. Funded by the National Institutes of Health (NIH), Jöbsis (1977) and Chance et al. (1988) conducted much of the early work on brain imaging with functional near-infrared spectroscopy (fNIRS).

Neuronal activity is fueled by glucose metabolism, and increases in neural activity result in increased consumption of glucose and oxygen from the local capillary bed. A reduction in local glucose and oxygen stimulates the brain to increase local arteriolar vasodilation, which increases local cerebral blood flow (CBF) and cerebral blood volume through a mechanism known as neurovascular coupling. Over a period of several seconds, the increased CBF carries more glucose and oxygen to the area, and the oxygen is transported by oxygenated hemoglobin in the blood. The increased oxygen transported to the area typically exceeds the local rate of neuronal oxygen use, and a result is an overabundance of cerebral blood oxygenation in the active area (Fox et al., 1988). Although the initial increase in neural activity is thought to result in a focal increase in deoxygenated hemoglobin in the capillary bed as oxygen is withdrawn from the hemoglobin for use in the metabolism of glucose, this part of the vascular



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Appendix D Background Information on Functional Neuroimaging FUNCTIONAL NEAR-INFRARED SPECTROSCOPY Principles It is well known that the functional state of tissue can influence its optical properties (for instance, cyanosis in hypoxia and pallor in anemia). The human brain undergoes a number of physiological changes as it responds to environ- mental stimuli, and these changes in electrochemical activity and blood chemistry also affect the optical properties of neuronal tissues. Functional optical imaging capitalizes on those changing optical properties in measuring neural activity. Funded by the National Institutes of Health (NIH), Jöbsis (1977) and Chance et al. (1988) conducted much of the early work on brain imaging with functional near-infrared spectroscopy (fNIRS). Neuronal activity is fueled by glucose metabolism, and increases in neural activity result in increased consumption of glucose and oxygen from the local capillary bed. A reduction in local glucose and oxygen stimulates the brain to increase local arteriolar vasodilation, which increases local cerebral blood flow (CBF) and cerebral blood volume through a mechanism known as neurovascular coupling. Over a period of several seconds, the increased CBF carries more glucose and oxygen to the area, and the oxygen is transported by oxygenated hemoglobin in the blood. The increased oxygen transported to the area typically exceeds the local rate of neuronal oxygen use, and a result is an overabundance of cerebral blood oxygenation in the active area (Fox et al., 1988). Although the initial increase in neural activity is thought to result in a focal increase in deoxygenated hemoglobin in the capillary bed as oxygen is withdrawn from the hemoglobin for use in the metabolism of glucose, this part of the vascular 

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 EMErGING COGNITIVE NEUrOSCIENCE AND rELATED TECHNOLOGIES response has been much more difficult to measure, and more controversial, than hyperoxygenation. (See Buxton, 2001 and Obrig et al., 1996, 2000a,b, for more detailed discussion of this topic.) Because oxygenated and deoxygenated hemoglobin (oxy-Hb and deoxy-Hb) have characteristic optical properties in the visible and near-infrared light range, the change in their concentrations during neurovascular coupling can be measured optically (Chance et al., 1998; Villringer and Chance, 1997). Most biological tissues are relatively transparent to light in the near-infrared range of 700-900 nm largely because water absorption is relatively low at these wavelengths. However, the chromophores oxy-Hb and deoxy-Hb absorb specific wavelengths in that range. Thus, that spectral band is often referred to as the optical window for the noninvasive assessment of brain activation (Jöbsis, 1977). Photons introduced at the scalp pass through most of the tissue and are either scattered by it or absorbed by oxy-Hb and deoxy-Hb. Because a relatively predictable quantity of photons follows a banana-shaped path back to the surface of the skin, the photons can be measured at the scalp with photodetectors (Gratton et al., 1994). Changes in the chromophore concentrations cause changes in the intensity of detected light and are quantified according to a modified Beer-Lambert law, essentially an empiri- cal description of optical attenuation in a highly scattering medium (Cope and Delpy, 1988; Cope, 1991). If absorbance changes at two (or more) wavelengths, one of which is more sensitive to oxy-Hb and another to deoxy-Hb, are measured, changes in the relative concentrations of these chromophores can be calculated. Using those principles, researchers have demonstrated that it is possible to assess brain activity through the intact skull in adult humans (Chance et al., 1993; Gratton et al., 1995; Hoshi and Tamura, 1993; Kato et al., 1993; Villringer et al., 1993). Other chromophores, including cytochrome-c oxidase, can also be assessed optically. Cytochrome-c oxidase, a marker of metabolic demands, holds the poten- tial to provide more direct information about neuronal activity than hemoglobin (Heekeren et al., 1999; Jöbsis, 1977). However, because cytochrome-c oxidase is used much less often than the hemoglobin-based measures, it will not be discussed further here (see Heekeren et al. [1999] for more detail). Typically, an fNIRS apparatus comprises a light source, which is coupled to the participant’s head via either light-emitting diodes (LEDs) or fiber-optic bundles, and a light detector that receives light after it has interacted with tissue. Light scatters after entering tissue, and a photodetector placed 2-7 cm away from the optode, an optical sensor device that optically measures a specific substance usually with the aid of a chemical transducer, can collect light after it has passed through tissue. When the distance between the source and the photodetector is set at 4 cm, the fNIRS signal is sensitive to hemodynamic changes within the top 2-3 mm of the cortex and extends 1 cm to either side perpendicular to the source- detector axis (Chance et al., 1988). Studies have shown that the gray matter of the cortex can be imaged with interoptode distances as short as 2 cm (Chance et al., 1988; Firbank et al., 1998). Several types of brain activity have been assessed

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 AppENDIX D with this technique, including motor activity, visual activation, auditory stimula- tion, and performance of cognitive tasks (e.g., Villringer and Chance, 1997). Fast Functional Near-Infrared Spectroscopy A second, more controversial method, called the event-related optical signal (EROS), capitalizes on changes in the optical properties of cell membranes that occur when a neuron “fires,” or is activated (Gratton et al., 1995). When a neuron is activated, ionic fluxes across the cell membrane (such as shifts in sodium and potassium ions) result in a change in the membrane potential. The ionic fluxes also change the magnetic and electrical fields around the neuron, which, when summed across a large number of synchronously activated neurons, constitute the signal that is assessed with electroencephalography (EEG) or magnetoencephalography (MEG). By using invasive techniques, it has been established that the optical prop- erties of neural membranes differ between the depolarized state and the resting state (Obrig and Villringer, 2003; Rector et al., 1997; Stepnoski et al., 1991) and that optical methods can be used to detect the differences. There are a number of limitations of the noninvasive use of EROS in humans. A primary disadvantage of the fast optical signal is the high signal-to-noise ratio that results from the need to image through skin, skull, and cerebrospinal fluid. Basic sensory and motor activities, such as tactile stimulation and finger-tapping, require 500-1000 trials to establish a reliable signal (Franceschini and Boas, 2004). There have been failures in attempting to replicate the results of experi- ments that reported the EROS in response to a visual stimulus in healthy adult humans (Syre et al., 2004). Final constraints are that these methods require a more expensive and cumbersome laser-based light source (as opposed to an LED- based light source), they are not portable, and there is a greater risk of inadvertent damage to the eyes than with the systems available for measuring hemodynamic responses; LED-based near-infrared sources pose very little, if any, risk to the eyes (Bozkurt and Onaral, 2004). Despite current limitations, the fast optical signal continues to be an impor- tant subject of investigation because it offers glimpses of the “holy grail” of neuroimaging: the direct measurement of neuronal activity with millisecond resolution and superior spatial resolution. The potential for implanted optodes is particularly important. Because the optical signal can be carried by fiber optics, implanted optodes would allow extremely precise localization of neural activ- ity, in addition to millisecond resolution. Proximity to the tissue would greatly reduce the amount of light power required for imaging and thus lower both the power consumption and the heat output of the optodes. Optodes used to image the cortex could be implanted just below the surface of the skull, allowing the cerebrospinal fluid to remain as a buffer and thereby avoiding the scarring that interferes with chronically implanted EEG electrodes. Fiber optics might have some of the same problems as implanted EEG electrodes for deep tissue (such

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 EMErGING COGNITIVE NEUrOSCIENCE AND rELATED TECHNOLOGIES as scar-tissue buildup), but as some of the problems yield to advancing research, fNIRS optodes could potentially be implanted for deep-tissue assessment. At least one U.S. grant has been issued to investigate the feasibility of implanted fNIRS optodes in animals. Current applications include the restoration of mobility in hemiplegic and paraplegic patients. For example, brain-computer interfaces could potentially be driven by signals in the motor cortex. The same brain-computer interfaces could potentially be used in military applications, such as weapons control (Peters et al, 2008). Overall system cost will be relatively low in a few years, and the rate- limiting factor in the near future may be the cost of surgery. Functional Near-Infrared Spectroscopy Systems A wide variety of commercial and custom-built fNIRS instruments are in use (Strangman et al., 2002). The systems differ with respect to their use and engineering, specifically among light sources, detectors, and instrument elec- tronics. Three distinct types of fNIRS implementation have been developed: time-resolved systems, frequency-domain systems, and continuous-wave (CW) spectroscopy; each has its own strengths and limitations. CW spectroscopy applies continuous or slow-pulse (up to several kilohertz) light to tissue and measures the attenuation of amplitude of the incident light (Strangman et al., 2002; Hoshi, 2003; Izzetoglu et al., 2004; Obrig and Villringer, 2003). CW systems provide somewhat less information than time-resolved or frequency-domain systems, but they have several advantages for some applications: they can be manufactured far less expensively than time-resolved and frequency-domain systems, and they can be very small, so they are practical for use in clinical and educational settings. Laser-based time-resolved or frequency-domain systems provide information on both phase and amplitude and allow more precise quantification of fNIRS signals. (For more discussion of system differences, see Boas et al., 2002; Hoshi, 2003; Izzetoglu et al., 2004; Obrig and Villringer, 2003; and Strangman et al., 2002.) Comparison of Functional Near-Infrared Spectroscopy with Other Neuroimaging Modalities Early efforts to develop neurobiological models of cognition and emotion relied on EEG or event-related potential (ERP), which are measures of physi- ological function. Those measures have several advantages for research. They are relatively inexpensive, are noninvasive, and have nearly instantaneous time reso- lution. They can be used with infants and children, as well as adults, and can be used repeatedly with no adverse effects. As a result, applications of EEG and ERP have contributed important data for developing models of cognitive and emo- tional processing. However, EEG measures are limited in their ability to provide the precise location of an electrical source. EEG does yield spatial information,

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 AppENDIX D but it must be reconstructed with probabilistic models. Although mathematical models are improving, EEG, even when applied in very-high-density fields, can provide only a relative approximation of current sources. The introduction of neuroimaging modalities, such as functional magnetic resonance imaging (fMRI) and positron-emission tomography, has made it pos- sible to examine much more precisely the anatomical location of the neural cir- cuitry underlying various mental events in humans. Many clinicians are familiar with the basic principles of fMRI and use the results of fMRI research to inform their clinical practice and research. fMRI is considered the “gold standard” for measuring functional brain activation because it offers safe, noninvasive neuro- imaging with high spatial resolution. It is therefore useful to compare fNIRS with the well-known technology of fMRI (see Gore, 2003, for a clear and more comprehensive description of the principles of fMRI). The primary measure used for fMRI is the blood-oxygen-level–dependent (BOLD) signal that accompanies neuronal activation in the brain and is secondary, for instance, to the presenta- tion of a stimulus. As previously discussed, increase in CBF to an active area exceeds the additional neuronal metabolic demand and results in a decrease in deoxy-Hb concentration in the local tissue. The magnetic susceptibility of blood containing oxy-Hb differs very little from that of water or other tissues that have low paramagnetic properties. However, deoxy-Hb is highly paramagnetic and therefore has very different magnetic properties from surrounding tissues and can act as a naturally occurring contrast agent (Pauling and Coryell, 1936). The presence of deoxygenated blood in a given area results in a less uniform magnetic field. Because the magnetic resonance signal depends on the uniformity of the magnetic field experienced by water molecules, less uniformity (that is, when more deoxy-Hb is present) results in less signal clarity and in more rapid decay of the overall signal. In contrast, as the deoxygenated blood in a given area is replaced with oxygenated blood, the local magnetic environment becomes more uniform, and the MRI signal lasts longer and is therefore stronger during image acquisition. The signal change is typically around 1 percent or less, depending on the strength of the magnetic field. Therefore, fMRI, like fNIRS, is an indi- rect measure of neuronal activity that assesses changes in the concentration of deoxy-Hb in local tissue. There is no simple relationship between the magnitude of the signal change and any single physiological measure inasmuch as the mag- nitude relies on changes in blood flow, blood volume, and local oxygen tension. There is also a delay between the time when the local neurons are activated and begin to use oxygen and the time when vasodilation occurs and allows increased blood flow and the transport of oxy-Hb to the area. The latter process, called the hemodynamic response, occurs over several seconds after the initiation of neuronal activity. The more commonly used fNIRS technology (use of the measurement of hemoglobin-based chromophores) has much in common with the BOLD-based signal in that it measures relative changes in concentrations of deoxy-Hb that

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 EMErGING COGNITIVE NEUrOSCIENCE AND rELATED TECHNOLOGIES depend on the hemodynamic response. Both are indirect measures of neural activ- ity, with temporal resolution measured in seconds, because they are limited by the hemodynamic response. Both provide spatial resolution, are safe, are noninvasive, and can be used repeatedly in the same people. Because of their signal-to-noise ratios, both technologies typically require repeated stimulation. There are also, however, important differences between the two technologies. fNIRS is unlikely to supplant fMRI in basic research on the neurophysiological underpinnings of various cognitive, emotional, and motivational processes, for two important reasons. First, fMRI has better spatial resolution, around 1 mm 2, although the fast imaging of fMRI reduces its spatial resolution somewhat (to a few millimeters) relative to conventional MRI. In contrast, because of the scatter of photons in a diverse medium, current fNIRS systems have a spatial resolu- tion of around 1 cm2. Second, fMRI has the capacity to image the entire brain, whereas fNIRS is limited to the outer cortex. Although a large hemorrhage might be able to be imaged as deep as the thalamus with fNIRS, more subtle signals, such as those induced by a cognitive or emotional event, are limited to a depth of about 2-4 mm of the cortex. fNIRS has a number of advantageous properties that hold enormous potential for research studies and clinical applications that require the quantitative mea- surement of hemodynamic changes in the cortex under a variety of conditions not amenable to fMRI. The limitations of fMRI relative to fNIRS include the need for subjects to lie within the confines of the magnet bore and the refrigerant systems used to supercool the magnets also produce loud noises that can interfere with some protocols. fMRI is also highly sensitive to movement; subjects’ movements of a few millimeters can invalidate the data. The intense strength of the magnets necessary to create the MRI signal precludes the use of any ferrous metals in or around the magnet. Finally, fMRI systems are expensive—an initial cost of a few million dollars, depending on the strength of the magnet—and individual participant runs can cost several hundred dollars each. FUNCTIONAL SPECIALIZATION The human brain evolved in layers, with evolutionarily newer structures covering older ones. The developing brain in a human embryo grows outward in a pattern that largely mirrors human evolution. The brain is divided into discrete regions that control vital functions, such as sensory transduction and cognition in the case of the cortex. Such functional specialization is a critical element in brain research, and it arises mainly from layered development. The functionally specific regions “activate” when a person is presented with a stimulus or task; for example, smells excite an area of the temporal lobe, and vision excites the occipital lobe. Mapping the areas of activation and the circuits that control specific behav- iors and cognitive processes is the goal of functional neuroimaging. It is an

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 AppENDIX D enormous goal in light of the relative size of the target, and creating even a crude map of the functionality of the brain is daunting. The brain involves many more connections than the most advanced computer because, unlike a computer that uses binary connections, brain circuits involve thousands of neurons and millions of connections in performing even the simplest task of cognition or behavior. Indeed, one can think of gray matter neurons as transistors and white matter fibers as the wires that connect the transistors, although in the brain each neuron can have multiple connections—even 10,000 or more. To provide some perspective on the enormity of the task of mapping con- nected areas, a typical human infant has about 1 billion gray matter neurons. With the exception of some interesting findings that suggest continuing neurogenesis in the dentate gyrus (a portion of the midbrain), the newborn will never grow any more neurons. If almost no new neurons are developing, from where does all the extra mass come? Although the number of neurons is largely fixed at birth, the brain continually forms complex white matter connections between neurons at an almost inconceivable rate. The human infant may form 20,000 distinct neural connections every second for the first year of life. Those are merely individual connections. If we factor in circuits that involve thousands or tens of thousands or even millions of reciprocal connections,1 it becomes clear that there are far more combinations of neural circuits in the cerebral cortex than atoms in the known universe.2 Cautious but undaunted, scientists are busily mapping the connectivity of the human brain in thousands of new papers published each year. Many studies are investigating correlations between traditional psychological testing, clinical observations, and brain scans to establish biomarkers of pathological states, cog- nitive and behavioral tasks, task-specific aptitude measures, detection of decep- tion, and even prediction of neuropathological propensity. REFERENCES Boas, D., J. Culver, J. Stott, and A. Dunn. 2002. Three dimensional Monte Carlo code for photon migration through complex heterogeneous media including the adult human head. Optics Express 10(3):159-170. Bozkurt, A., and B. Onaral. 2004. Safety assessment of near infrared light emitting diodes for diffuse optical measurements. BioMedical Engineering OnLine 3(1):9. Available from http://www. biomedical-engineering-online.com/content/3/1/9. Last accessed February 13, 2008. Buxton, R.B. 2001. The elusive initial dip. NeuroImage 13(6):953-958. Chance B., E. Anday, S. Nioka, S. Zhou, L. Hong, K. Worden, C. Li, T. Murray, Y. Ovetsky, D. Pidikiti, and R. Thomas. 1998. A novel method for fast imaging of brain function, non-invasively, with light. Optics Express 2(10):411-423. 1 For example, if there are 1,000 possible combinations in the first link of a neural circuit, the num- ber of combinations with a second reciprocal link would be 1,000 × 999 × 998 all the way down to 1, or 1000!, which is about 102568. 2There are around 1080 atoms in the visible universe and perhaps 1082 if we include nonluminous matter. For additional information, see http://www.holisticeducator.com. Accessed January 24, 2008.

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