54 IEEE ENGINEERING IN MEDICINE AND BIOLOGY MAGAZINE JULY/AUGUST 2006

Functional Near-InfraredSpectroscopy

An Emerging Neuroimaging Modality

BY SCOTT C. BUNCE, MELTEM IZZETOGLU, KURTULUS IZZETOGLU, BANU ONARAL, AND KAMBIZ POURREZAEI

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Neurophysiological and neuroimaging technologieshave contributed much to our understanding ofnormative brain function as well as to our under-standing of the neural underpinnings of variousneurological and psychiatric disorders. Commonly

employed techniques such as electroencephalography (EEG),event-related brain potentials (ERPs), magnetoencephalogra-phy (MEG), positron emission tomography (PET), single-positron emission computed tomography (SPECT), andfunctional magnetic resonance imaging (fMRI) have dramati-cally increased our understanding of a broad range of brain dis-orders. Nevertheless, there is much that we still do not knowabout these syndromes. This is due, in large part, to the inher-ent complexity of the neurobiological substrates of these disor-ders and of the mind itself. However, in addition to thecomplexity of the neural substrates and of the disorders, eachof the research methods used to study brain function and itsdisorders has methodological strengths as well as its own inher-ent limitations. These limitations place constraints on our abili-ty to fully explicate the neural basis of neurological andpsychiatric disorders both inside and outside of the laboratorysetting and to use the information gleaned from laboratorystudies for clinical applications in real-world environments.New techniques that allow data to be gathered under morediverse circumstances than is possible with extant neuroimag-ing systems should facilitate a more thorough understanding ofbrain function and its pathologies.

The purpose of the this article is to describe an emergingneuroimaging technology, functional near-infrared spec-troscopy (fNIRs), which has several attributes that make itpossible to conduct neuroimaging studies of the cortex in clin-ical offices and under more realistic, ecologically valid para-meters. fNIRs is safe, noninvasive, relatively inexpensive,portable, and can be wireless, making it possible to designtranslational research and clinical studies that possess ecologi-cal validity not possible with the constraints of other neu-roimaging technologies.

Principles of Functional Near-Infrared SpectroscopyIt is well known that the functional state of tissue can influ-ence its optical properties (for instance, cyanosis in hypoxiaand pallor in anemia). The human brain undergoes a number

of physiological changes as it responds to environmental stim-uli; these changes in blood levels and electrochemical activityalso affect its optical properties. Functional optical imagingcapitalizes on the changing optical properties of these tissuesby using light in the near-infrared range (700–900 nm) to mea-sure physiological changes.

Brain activity is associated with a number of physiologicalevents; two of these events can be assessed using optical tech-niques. During neural activity, ionic fluxes across the cell’smembrane (e.g., shifts in sodium and potassium ions) result ina change in the membrane potential. The ionic fluxes alsocause changes in the magnetic and electrical fields, which,when summed across a large number of synchronously activat-ed neurons, can be assessed using EEG or MEG. Neuronalactivity is fueled by glucose metabolism, so increases in neuralactivity result in increased glucose and oxygen consumptionfrom the local capillary bed. A reduction in local glucose andoxygen stimulates the brain to increase local arteriolar vasodi-lation, which increases local cerebral blood flow (CBF) andcerebral blood volume (CBV), a mechanism known as neu-rovascular coupling. Over a period of several seconds, theincreased CBF carries both glucose and oxygen to the area, thelatter of which is transported via oxygenated hemoglobin in theblood. The increased oxygen transported to the area typicallyexceeds the local neuronal rate of oxygen utilization, resultingin an overabundance of cerebral blood oxygenation in activeareas [1]. Although the initial increase in neural activity isthought to result in a focal increase in deoxygenated hemoglo-bin in the capillary bed as oxygen is withdrawn from the hemo-globin for use in the metabolization of glucose, this feature ofthe vascular response has been much more difficult to measure,and more controversial, than hyperoxygenation (see [2] and [3]for a more detailed discussion of this topic).

Because oxygenated and deoxygenated hemoglobin (oxy-Hb, deoxy-Hb) have characteristic optical properties in thevisible and near-infrared light range, the change in concentra-tion of these molecules during neurovascular coupling can bemeasured using optical methods [4], [5]. The most commonlyused method of near-infrared spectroscopy measures changesin the ratio of oxy-Hb to blood volume. Most biological tis-sues are relatively transparent to light in the near-infraredrange between 700–900 nm, largely because water, a major

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component of most tissues, absorbs very little energy at thesewavelengths (see Figure 1). However, the chromophores oxy-Hb and deoxy-Hb do absorb a fair amount of energy in thisrange. As such, this spectral band is often referred to as theoptical window for the noninvasive assessment of brain activa-tion [6]. Photons introduced at the scalp pass through most ofthe tissue and are either scattered or absorbed by it. Because arelatively predictable quantity of photons follows a banana-shaped path back to the surface of the skin, these photons canbe measured at the scalp using photodetectors, as illustrated inFigure 2 [7]. If wavelengths are chosen to maximize theamount of absorption by oxy-Hb and deoxy-Hb, changes inthe chromophore concentrations cause changes in the numberof photons that are absorbed and the number of photons thatare scattered back to the surface of the scalp. These changes inlight intensity measured at the surface of the scalp are quanti-fied using a modified Beer–Lambert law, which is, essentially,an empirical description of optical attenuation in a highly scat-tering medium [8], [9]. By measuring absorption changes attwo (or more) wavelengths, one of which is more sensitive tooxy-Hb, the other to deoxy-Hb, changes in the relative con-centrations of these chromophores can be calculated. Usingthese principles, researchers have demonstrated that it is possi-ble to assess brain activity through the intact skull in adulthumans [10]–[14]. In addition to hemoglobin, other chro-mophores, including cytochrome-c oxidase can be assessedusing optical techniques. Cytochrome-c oxidase, a marker ofmetabolic demands, holds the potential to provide more directinformation about neuronal activity than hemoglobin [6], [15].However, as cytochrome-c oxidase is used much less fre-quently than the hemoglobin-based measures, it will not befurther discussed in this article (see [15] for more detail).

Typically, a functional near-infrared (fNIR) apparatus iscomprised of a light source that is coupled to the participant’shead via either light-emitting diodes (LEDs) or though fiber-optical bundles (the optode) and with a light detector thatreceives the light after it has interacted with the tissue.Because light is scattered after entering the tissue, a photode-tector placed 2–7 cm away from the optode can collect lightafter it has passed through the tissue. When the distancebetween the source and photodetector is set at 4 cm, the fNIRsignal becomes sensitive to hemodynamic changes within thetop 2–3 mm of the cortex and extends laterally 1 cm to eitherside, perpendicular to the axis of source-detector spacing [16].Studies have shown that at interoptode distances as short as2–2.5 cm, gray matter is part of the sample volume [16], [17].Using this technique, several types of brain activity have beenassessed, including motor activity, visual activation, auditorystimulation, and the performance of cognitive tasks [5].

Event-Related Optical SignalA second, much more controversial method, labeled the event-related optical signal, or EROS, capitalizes on the changes inthe optical properties of the cell membranes themselves thatoccur as a function of the ionic fluxes during firing [11]. Usinginvasive techniques, it has been well established that the opti-cal properties of cell membranes change in the depolarizedstate relative to the resting state ([3], [18], [19]) and that opti-cal methods can be used to detect these changes. The ability tomeasure the actual depolarization state of neuronal tissue pro-vides obvious advantages in that it is a direct measure of neur-al activity, with millisecond-level time resolution (as with

EEG and MEG) but with the superior spatial resolution lack-ing in EEG/MEG. However, there are also a number of limita-tions to the noninvasive use of the EROS signal in humans. Aprimary disadvantage of the fast optical signal is the low sig-nal-to-noise ratio (SNR) resulting from the need to imagethrough skin, skull, and cerebral-spinal fluid. Basic sensoryand motor movements such as tactile stimulation and finger-tapping require between 500–1,000 trials to establish a reliablesignal [20]. There have also been failures to replicate theresults of experiments reporting the fast optical signal inresponse to a visual stimulus among normal adult humans [3].The low SNR may play a role in current difficulties withexperimental replication; however, more cross-validationwork is warranted. The final constraint is that these methodsrequire a more expensive and cumbersome laser-based lightsource (versus an LED-based light source), they are notportable, and the potential risk of inadvertent damage to theeyes is increased relative to the systems available for measur-ing hemodynamic responses. (LED-based near-infraredsources pose very little, if any, risk upon eye exposure [21]).In spite of these current limitations, the fast optical signal con-tinues to be an important area of investigation because it offersglimpses of the “holy grail” of neuroimaging: the direct mea-surement of neuronal activity with millisecond time resolutionand superior spatial resolution.

Fig. 1. Absorption characteristics of oxy-Hb, deoxy-Hb, andwater according to the light wavelength.

Fig. 2. Banana-shaped photon path.

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fNIRs System TypesA wide variety of both commercial and custom-built fNIRinstruments are currently in use [22]. These systems differwith respect to their use and system engineering, with trade-offs between light sources, detectors, and instrument electron-ics that result in tradeoffs in the information available foranalysis, safety, and cost. Three distinct types of fNIR imple-mentation have been developed: time-resolved systems, fre-quency-domain systems, and continuous wave spectroscopysystems, each with its own strengths and limitations. Time-resolved and frequency-domain systems provide informationon shifts in both phase and amplitude of the light and are nec-essary for more precise quantification of fNIR signals.Continuous wave (CW) systems apply either continuous or aslow-pulsed light to tissue and measure the attenuation ofamplitude of the incident light. These systems utilize lesssophisticated detectors than time-resolved and frequency-domain systems, and, therefore, they cannot resolve the time-changing component of the light. As such, CW systemsprovide somewhat less information than time- or frequency-domain systems, but this tradeoff results in the capacity todesign more compact and inexpensive hardware, making itadvantageous for specified applications. They can be laser-based, but light-emitting diodes (LEDs) can also be used inCW designs to increase safety (particularly with respect to eyeexposure) and to again decrease both instrument size and cost,making it possible to deploy these systems in clinical or edu-cational settings. (See [3], [22]–[24] for a more thorough dis-cussion of these system differences.)

Comparison of fNIRs with Other Neuroimaging ModalitiesEarly efforts to develop neurobiological models of cognitionand emotion relied on electroencephalographic (EEG) or ERPmeasures of physiological function. These measures have sev-eral advantages for research, in that they are relatively inex-pensive, noninvasive, and have nearly instantaneous timeresolution. They can be used with infants and children, as wellas adults, and can be used repeatedly with no adverse effects.As a result, EEG and ERP paradigms have contributed impor-tant data for developing models of cognitive and emotionalprocessing. However, EEG measures are limited in their abilityto provide the precise location of an electrical source. EEGdoes yield spatial information, but this spatial informationmust be reconstructed by probabilistic models. Althoughmathematical models are improving, even when applied invery-high-density fields, EEG can only provide a relativeapproximation of current sources.

The introduction of neuroimaging modalities such asfMRI and PET has made it possible to examine much moreprecisely the anatomical location of the neural circuitryunderlying various mental events among human participants.Many clinicians are familiar with the basic principles offMRI and utilize the result of fMRI research to inform theirclinical practice and research. fMRI is currently consideredthe “gold standard” for measuring functional brain activationbecause it offers safe, noninvasive neuroimaging with highspatial resolution. It is therefore useful to briefly compareand contrast fNIRs with the well-known technology of fMRI.(Please see [25] for a clear and more comprehensive descrip-tion of the principles of fMRI). One of the primary measuresused for fMRI is the blood-oxygen-level-dependent (BOLD)

signal that accompanies neuronal activation in the brain sec-ondary to, for instance, the presentation of a stimulus. Aspreviously discussed, increased CBF to an active areaexceeds the additional neuronal metabolic demand, resultingin a decrease of deoxy-Hb concentration in the local tissue.The magnetic susceptibility of blood containing oxy-Hb dif-fers very little from water or other tissues, which have lowparamagnetic properties. However, deoxy-Hb is highly para-magnetic and, therefore, has very different magnetic proper-ties than surrounding tissues and can act as a naturallyoccurring contrast agent [26]. The presence of deoxygenatedblood in a given area results in a less uniform magnetic field.Because the MRI signal depends on the uniformity of themagnetic field experienced by water molecules, less unifor-mity (i.e., when more deoxy-Hb is present) results in agreater mixture of signal frequencies and, therefore, a morerapid decay of the overall signal. In contrast, as the deoxy-genated blood in a given area is replaced by oxygenatedblood, the local magnetic environment becomes more uni-form, and the MRI signal lasts longer and is consequentlystronger during image acquisition. The signal change is typi-cally around 1% or less, depending on the strength of themagnetic field. Therefore, fMRI, like fNIR, is an indirectmeasure of neuronal activity, assessing changes in the rela-tive concentration of deoxy-Hb in local tissue. There is nosimple relationship between the magnitude of the signalchange and any single physiological parameter because itrelies on changes in blood flow, blood volume, and localoxygen tension. There is also a time delay between when thelocal neurons are activated and begin to use oxygen andwhen vasodilation occurs, which allows an increased bloodflow and the transport of oxy-Hb to the area. Labeled thehemodynamic response, this process occurs over several sec-onds, following the initiation of neuronal activity.

The more commonly used fNIRs technology (i.e., utilizingthe measurement of hemoglobin-based chromophores) sharesmuch in common with the BOLD-based signal, as it measuresrelative changes in concentrations of deoxy-Hb that aredependent on the hemodynamic response. As such, both areindirect measures of neural activity, with temporal resolutionon the order of seconds because they are limited by the hemo-dynamic response. In addition, just as arterial spin labelingcan be used to calculate blood flow with fMRI, becausefNIRs measures relative changes in oxy-Hb as well as deoxy-Hb, total blood flow can be calculated from the differentialequation. Both technologies also provide a level of spatialresolution, are safe and noninvasive, and can be used repeat-edly with the same individuals. Due to their SNRs, both tech-nologies typically require some level of repeated stimulation,either in a block design or an event-related design. Fromthere, however, there are a number of important differencesbetween the two technologies.

fNIR is unlikely to supplant fMRI for basic research onthe neurophysiological underpinnings of various cognitive,emotional, and motivational processes for two importantreasons. First, fMRI has better spatial resolution, on theorder of 1 mm2, although the fast imaging of fMRI reducesits spatial resolution somewhat to a few millimeters relativeto conventional MRI. By contrast, due to the scatter of pho-tons in a diverse medium, current fNIRs systems have aspatial resolution on the order of 1 cm2. Second, fMRI hasthe capacity to image the entire brain, whereas fNIR is

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limited to the outer cortex. Although a large hemorrhagemight be able to be imaged as deeply as the thalamus withfNIRs, more subtle signals, such as those induced by a cog-nitive or emotional event, are limited to a depth of approxi-mately 2–4 mm of the cortex.

Conversely, fNIR has a number of advantageous propertiesthat hold enormous potential for research studies and clinicalapplications that require the quantitative measurement ofhemodynamic changes in the cortex under a variety of condi-tions not amenable to fMRI. The limitations of fMRI relativeto fNIRs include the fact that participants must lie within theconfines of the magnet bore, which limits its use for manyapplications, including the imaging of many patients with sig-nificant symptoms. The refrigerant systems used to supercoolthe magnets also produce loud noises, which can interfere withcertain protocols. fMRI is also highly sensitive to movementartifact; subject movements on the order of a few millimeterscan invalidate the data. The intense strength of the magnetsnecessary to create the MRI signal precludes the use of anyferrous metals in or around the magnet. Finally, fMRI systemsare quite expensive, with an initial cost of a few million U.S.dollars, depending on the strength of the magnet, and individ-ual participant runs can cost several hundred U.S. dollars each.

In comparison to fMRI, with fNIRs participants can situpright and work on a computer [27], watch television ormovies, and even walk on a treadmill. fNIRs systems are notas susceptible to movement artifact as fMRI, and algorithmsfor the removal of motion artifact during desktop use, as wellas ambulatory use, are currently being refined [27]. Theseattributes also allow fNIRs to be used with children and withpatient populations that may find confinement to an fMRImagnet overwhelming or painful. A number of sensor applica-tions exist, depending on their use, including caps, tensionstraps, and medical-grade adhesive applications. fNIR is quietand comfortable and is therefore amenable to sensitive proto-cols such as the induction of positive moods. It is readilyamenable to integration with a number of other technologies,including EEG. Portable systems exist that operate from a lap-top computer and a control box approximately 2 in × 6 in × 8in. Finally, fNIRs is relatively inexpensive, with available sys-tems ranging between US$25,000–$300,000.

InstrumentationThe goal of Drexel University’s Optical Engineering Team,located within the School of Biomedical Engineering, Scienceand Health Systems and the College of Medicine, has been todevelop fNIR systems that would allow low-cost functionalneuroimaging for a variety of clinical,research, and educational applications.To meet this goal, the team has beendeveloping several CW fNIR systemsand sensor designs that allow the tech-nology to be used for infants as well asadults, under stationary as well asambulant conditions, for laboratory orclinical applications.

fNIR System Designs

Portable fNIR SystemThe portable fNIR system used in ourstudies was originally described by [4].

The current generation is comprised of three primary compo-nents: 1) an LED-based sensor that covers the entire foreheadof the participant, 2) a control module (approximately 2 in × 6in × 8 in) with integrated power supply for sensor control anddata acquisition, and 3) a laptop computer for the data analysissoftware (Figure 3).

Wireless fNIR SystemThe wireless fNIR is a miniaturized CW system designed tomonitor hemodynamic responses of the cortex under ambulantconditions. The system consists of two primary components: awearable device to collect and transmit the data and a dataanalysis and display computer (see Figure 4). The wearabledevice comprises three elements: 1) a personal digital assistant(PDA), 2) a control circuit and battery holder, and 3) the sen-sor. The PDA (currently an HP iPAQ Pocket PC) supportsboth integrated Wi-Fi (IEEE 802.11b standard) and Bluetoothfor wireless communication. The customized PDA softwarecontrols the sensor circuitry, reading, saving, and sending thedata via a wireless network. The data acquisition rate of thesystem is 2 Hz (two data points per second).

fNIR Sensor Designs

Flexible Sensor DesignThe current flexible sensor, developed in the DrexelBiomedical Engineering laboratory, consists of four LED lightsources and ten detectors, which cover the forehead using 16voxels, with a source-detector separation of 2.5 cm [25], [28].The light sources (manufactured by Epitex Inc. type

Fig. 4. The wireless fNIR system design.

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L4X730/4X805/4X850-40Q96-I) contain three built-in LEDshaving peak wavelengths at 730, 805, and 850 nm, with anoverall outer diameter of 9.2 ± 0.2 mm. The photodetectors(manufactured by Bur Brown, type OPT101) are monolithicphotodiodes with a single supply transimpedance amplifierhaving the size of 0.90 in × 0.90 in. Communication betweenthe data analysis computer and the task presentation computeris established via a serial port connection to time-lock fNIRmeasurement to computer-generated task events.

The flexible sensor design consists of three parts: areusable, flexible circuit board that carries the necessaryinfrared sources and detectors, a replaceable cushioning mate-rial, and a disposable, single-use medical-grade adhesive tapethat serves to attach the sensor to the participant (see Figure 5).The flexible circuit provides a reliable and integrated wiringsolution as well as consistent and reproducible componentspacing and alignment. Because the circuit board and cushion-ing materials are flexible, the components move and adapt tothe various contours of the participant’s head, allowing thesensor elements to maintain an orthogonal orientation to theskin surface, dramatically improving light coupling efficiencyand signal strength.

Modular Sensor DesignCurrently, the optical team is working on a modular sensordesign with adjustable channel placements. The purpose ofthe modular design is to provide a low-cost, scalable sensorfor any forehead application. The modular design will allowthe investigator to place individual voxels according to theInternational 10/20 system [30], a measurement systemwidely used in EEG applications that allows the placementof sensors over consistent brain regions across differenthead sizes and shapes.

Software ApplicationsThe expanding scope of fNIRs has resulted in an increasingdemand for new signal processing algorithms, both to

increase the SNR of the fNIR system in the extraction of thehemodynamic response during cognitive tasks (to identify,eliminate, and/or compensate for noise and other signal dis-tortions, such as electronic drift) and to extract physiologi-cally relevant information from the measurements. Inaddition, algorithms are necessary to compensate for move-ment artifacts under ambulant conditions. The Drexel teamhas developed a number of data-processing algorithms toaddress these issues [24], [27]–[29], [31]–[34]. These algo-rithms are currently being refined and integrated into anend-user software package that controls the fNIR systemand allows postexperimental processing of the data and theproduction of images for data presentation.

Clinical ApplicationsTo date, there have been few clinical investigations thathave employed fNIRs (see [35] for a recent review). Thismay be due, at least in part, to the fact that fNIR technologyis still relatively new vis-a-vis other imaging technologies.The research published to date has also been relatively con-servative, focusing on establishing fNIRs as a valid and reli-able neuroimaging technology. As a result, the majority ofpublished fNIRs studies have not capitalized on the uniquecapabilities of the technique because of the need to validatethe results with known technologies such as fMRI. Giventhe spatial limitations of fNIR relative to fMRI, many clini-cians and researchers may be also hesitant to include fNIRin their literature reviews or in their research portfolios. Aprimary purpose of this article is to facilitate research byacquainting clinicians and researchers with the unique mer-its of fNIRs as a brain-imaging technology.

In the past decade, brain activation studies employingfNIRs have been conducted on the visual system [14], thesomatosensory system [36], the auditory system [38], [37],and the language system [39], [12] and during motor tasks[22]. fNIRs studies have also been used to examine a numberof cognitive tasks [12], [24], [28], [32], [40]. In general,

these studies have reported localizedincreases in oxy-Hb in response tofunctional challenge, and the resultshave largely been in agreement withcorollary fMRI studies.

The first clinical applications offNIRs have been in the investigation offetal, neonatal, and infant cerebral oxy-genation and functional activation. Forinstance, fNIRs studies have revealeddevelopmental alterations in the cere-bral hemodynamic response to auditoryand visual stimulation [42], [41]. fNIRshas also been used to characterize

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Fig. 5. (a) Flexible sensor design. (b) A participant wearing the flexible sensor.

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cerebral perfusion as a function of surgical events, such asbypass and reperfusion [43], and to measure fetal cerebraloxygen supplies during labor [44] and postbirth asphyxia [45].

Neurological applications have included an evaluation of thehemodynamic response during deep-brain stimulation inParkinson’s patients [46], brain activations during inducedseizures in patients with intractable epilepsy [39], an explo-ration of the pathophysiology of seizures in childhood epilepsy[47], and an examination of Alzheimer’s patients during verbalfluency and other cognitive tasks [48]. Psychiatric applicationshave included the comparison of prefrontal brain activations ofschizophrenic patients to healthy subjects during a mirrordrawing task [49] and a self-face recognition test [50], and dur-ing a continuous performance task [51] fNIRS was used todemonstrate heightened responses to trauma cues among vic-tims of the 1995 Tokyo Subway Sarin attack who developedposttraumatic stress disorder. Eschweiler et al. [52] foundfNIRs could be used to predict treatment response in a study ofthe effects of transcranial magnetic stimulation on depression.

To date, the research completed at Drexel has focused ondemonstrating the utility of an inexpensive, compact fNIR sys-tem for the purposes of: 1) integrating fNIR with event-relatedbrain potentials (ERPs) [53], [29], 2) event-related designs thattap ubiquitous cognitive functions such as target categoriza-tion [24], [29], and 3) one task that demonstrates the uniquecapacities of fNIR, deception detection [54].

The first two foci were integrated in a target categoriza-tion study [29], [53], which used a common visual oddballparadigm modified for use with fMRI by [55]. The stimuliwere two strings of white letters (XXXXX and OOOOO)presented against the center of a dark background. A totalof 516 stimuli were presented, 480 context stimuli(OOOOO) and 36 targets (XXXXX). Stimulus durationwas 500 ms, with an interstimulus interval of 1,500 ms.Target stimuli were presented randomly with respect tocontext stimuli, with a minimum of 12 context stimulibetween successive targets to allow the hemodynamicresponse an opportunity to return to baseline between tar-get presentations. Fifteen right-handed participants (fourfemales) were required to press one of two buttons on aresponse pad after each stimulus, while both fNIR andERPs were recorded. One button was pressed in responseto targets (Xs), and another button was pressed in responseto context stimuli (Os). The results for the ERP data wereconsistent with the literature (e.g., [56]); targets elicited arelatively sharp P3 component with an average peak at 365ms for both electrodes Cz and Pz [see Figure 6(a) and (b)].The peak amplitude response to target stimuli was largerthan the response to context stimuli at both Cz [t(14) =7.58; p < 0.001] and Pz [t(14) = 7.81; p < 0.001]. TheseERP results confirm that the task parameters and partici-pant responses were comparable to other ERP studies.

Fig. 6. Averaged ERP and fNIRs data for targets and contexts: (a) averaged ERPs from Cz electrode, (b) averaged ERPs from Pzelectrode, (c) location of the significant differentiation between targets and contexts, and (d) averaged fNIRs oxygenationdata on voxel 11.

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Controlling for family-wise error rates, a repeated-mea-sures ANOVA computed on the fNIR oxygenation datarevealed that oxygenation values were greater in response totargets than to controls in voxel 11, located over middlefrontal gyrus of the right hemisphere [see Figure 6(c)].Differentiation occurred between 6–9 s poststimulus [seeFigure 6(d)]. These results are consistent with the fMRI liter-ature for visual target categorization with respect toincreased oxygenation in response to targets, cortical loca-tion, and time course [55], [58], [57]. This study is impor-tant because it demonstrates that fNIRs and ERPs can bereadily integrated, allowing the simultaneous measurementof EEG, with its millisecond-level time resolution, andfNIR, which has reasonable spatial resolution.

The second study examined the potential to use fNIR todetect deception. Given the social, legal, and medical impli-cations of deception in human interactions, the detection ofconscious deception has received relatively little attentionfrom the scientific community [59]. Traditional deceptiondetection relies on measures of autonomic reactivity elicitedby emotionally relevant events. Detecting deception in thebrain is promising because the brain is the source of the cog-nitive elements of deception as well as its emotional corre-

lates. However, fMRI systems are too large, too expensive,and too constricting to be used in the field. The purpose ofthis study was to investigate the utility of fNIR measures ofcortical activity to differentiate lying from telling the truth.The study examined the brain responses of 21 right-handedindividuals (mean age 24.0 + 2.54 years) when they werelying versus telling the truth in a pokerlike card game [54].The study was designed to minimize anxiety in order toexamine the neural correlates of the cognitive aspects ofdeception. The results indicated that the Lie condition wasassociated with greater activation than the Truth condition inapproximate areas covering bilateral ventrolateral cortex(BA 47/46/45) and middle frontal gyrus (BA 10). A linearcombination of channels revealed that 20 out of 21 individu-als showed greater activation in the ventrolateral cortexwhen they were lying than when they were telling the truth(see Figure 7). Although more work needs to be done in thisarea, these results suggest that fNIR could potentially beused to detect deception in the field or in the clinic, an appli-cation that would be untenable with traditional fMRI.

These studies represent examples of how fNIR can be usedin research and clinical paradigms that may not be feasiblewith other neuroimaging technologies. There are several typesof clinical applications that could benefit from the uniqueattributes of fNIRS neuroimaging technology:➤ populations that may not be able to readily tolerate the con-

fines of an fMRI magnet or be able to remain sufficientlystill, e.g., schizophrenics, autistic children, neonates

➤ populations that require the long-term monitoring of cere-bral oxygenation, e.g., premature and other high-riskinfants

➤ studies that require repeated, low-cost neuroimaging, e.g.,treatment studies that image the cortex for efficacy

➤ applications where an fMRI system would be too expen-sive or cumbersome, e.g., for use in a clinical office

➤ applications that require ecological validity, e.g., workingat a computer or in an educational setting.

ConclusionsfNIR spectroscopy is an emerging technology that usesnear-infrared light to measure changes in the concentra-tion of oxygenated and deoxygenated hemoglobin in thecortex. Although fNIRs imaging is limited to the outercortex, it provides neuroimaging that is safe, portable,and very affordable relative to other neuroimaging tech-nologies. It is also relatively robust to movement artifactsand can readily be integrated with other technologiessuch as EEG. Current state-of-the-art technologies beingdeveloped at Drexel University include portable andwireless fNIR systems, data processing algorithms, andend-user software.

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Fig. 7. The pattern of increased fNIR activation evoked bylying relative to telling the truth, located over ventrolateraland dorsolateral prefrontal cortex. No areas of significantdeactivation were found.

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fNIRs has been demonstrated to have adequate validityin the measurement of functional brain activity during avariety of cognitive, emotional, and motor tasks and has thepotential to provide a flexible neuroimaging tool for clini-cians and researchers alike. The portable and wirelessinstrumentations, combined with robust analytic algorithmsand end-user software, make fNIR a viable option for thestudy of cognition- and emotion-related hemodynamicchanges in both adults and children, under either stationaryor ambulant conditions.

AcknowledgmentsThis work has been sponsored in part by funds from theDefense Advanced Research Projects Agency (DARPA)Augmented Cognition Program, the Office of Naval Research(ONR) and Homeland Security, under agreements N00014-02-1-0524, N00014-01-1-0986, and N00014-04-1-0119.

Scott C. Bunce is an assistant professor ofpsychiatry and director of the ClinicalNeuroscience Research Unit at DrexelUniversity College of Medicine. He hasconsiderable experience in both clinicaland individual differences research. Hisareas of expertise are in affective neuro-science, theory of mind, and the effects of

psychological trauma on information processing. A majorfocus in recent years has been on using neurophysiologicalmeasures (EEG, ERPs, ERD, EMG) to assess informationand emotional processing that cannot be reported by thepatient/participant. He has also played an integral role in thedevelopment of a safe, portable, near-infrared optical imagingdevice for the assessment of hemodynamic changes duringcognitive and emotional tasks.

Meltem Izzetoglu received the B.S. and theM.S. degrees both in electrical and elec-tronics engineering from Middle EastTechnical University, Ankara, Turkey, in1992 and 1995, respectively. She receivedthe Ph.D. degree in electrical and computerengineering from Drexel University,Philadelphia, Pennsylvania, in 2002. She is

currently a research assistant professor in the School ofBiomedical Engineering, Science and Health Systems atDrexel University. Her research interests include biomedicalsignal analysis, adaptive and optimal signal processing, bio-medical optics, and scale-space processing tools.

Kurtulus Izzetoglu gained his professionalsoftware development and medical imagingexperience as a member of a consultingcompany in the United States and theNetherlands, respectively. In these posi-tions, he worked as a senior analyst as wellas a software and analytical applicationsdeveloper. His experiences include the

development of professional medical imaging software pack-age, implementation of quantitative analysis, and imagingtechniques. After five years of industrial experience, he joinedthe functional optical imaging research team at DrexelUniversity where he currently serves as the project engineer.

His technical management responsibilities include develop-ment of cognitive workload assessment testing and analysisplatform, signal processing, and experimental protocol designand implementation. He received his M.S.E.E. from MiddleEast Technical University in Ankara, Turkey.

Banu Onaral received her Ph.D. from theUniversity of Pennsylvania in 1978 and herB.S.E.E. and M.S.E.E. from BogaziciUniversity in Istanbul, Turkey. Onaral’sacademic focus both in research and teach-ing is centered on biomedical signals andsystems engineering. She is a foundingmember of the Biomedical Information

Technology Laboratory, Scaling Signals and SystemsLaboratory, and the Bio-Electrode Research Laboratory. Shehas led several curriculum development initiatives, includingthe undergraduate telecommunication and biomedical engi-neering programs. She has developed several signals and sys-tems engineering software products and was recognized by theEDUCOM/NCRIPTAL Best Educational Tool Award. She isthe recipient of a number of faculty excellence awards includ-ing the 1990 Lindback Distinguished Teaching Award ofDrexel University. Her professional services include chair andmembership on advisory boards and strategic planning bodiesof several universities and funding agencies, including serviceon the National Science Foundation Engineering AdvisoryBoard (1997–1999) and on the proposal review panels andstudy sections. She is a Fellow of the IEEE Engineering inMedicine and Biology Society, a founding fellow of theAmerican Institute for Medical and Biological Engineering,fellow of the American Association for the Advancement ofScience, senior member of the Society of Women Engineers,and member of the American Society for EngineeringEducation and the Scientific Research Society Sigma Xi.

Kambiz Pourrezaei received his B.S.degree from Tehran University and M.S.degree from Tufts University. He earnedhis Ph.D. degree from RensselaerPolytechnic Institute, New York. He is cur-rently a professor with the School ofBiomedical Engineering, Science andHealth Systems, Drexel University.

Pourrezaei has active research programs in the areas of bio-nanotechnology and bio-optics. Currently, he is the codirectorof the Nanotechnology Institute in Philadelphia, Pennsylvania.

Address for Correspondence: Scott Bunce, DrexelUniversity College of Medicine, Philadelphia, PA 19104USA. Phone: +1 215 762 8387. Fax: + 1 215 246 5290. E-mail: scott.bunce@drexel.edu.

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