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Research Report

Subjective feeling of psychological fatigue is related todecreased reactivity in ventrolateral prefrontal cortex

Masashi Sudaa, Masato Fukudaa,⁎, Toshimasa Satoa, Shinya Iwatab, Mingqiao Songa,Masaki Kameyamaa, Masahiko Mikunia

aDepartment of Psychiatry and Neuroscience, Gunma University Graduate School of Medicine, 3-39-22 Showa, Maebashi,Gunma 371-8511, JapanbGunma University Faculty of Medicine, 3-39-22 Showa, Maebashi, Gunma 371-8511, Japan

A R T I C L E I N F O

⁎ Corresponding author. Fax: +81 27 220 8187.E-mail address: fkdpsy@med.gunma-u.ac.j

0006-8993/$ – see front matter © 2008 Elsevidoi:10.1016/j.brainres.2008.11.077

A B S T R A C T

Article history:Accepted 18 November 2008Available online 6 December 2008

The purpose of this study is to examine the relationship between subjective fatigue andbrain function. Twenty-three healthy young volunteers participated in this study.Relationships were investigated between subjective fatigue assessed using visual-analogue scale (VAS) score and sleep duration, and cerebral cortex reactivity during averbal fluency task by 52-channel near-infrared spectroscopy (NIRS). The VAS scorenegatively correlated with oxygenated hemoglobin concentration ([oxy-Hb]) increases inthe bilateral channels over the regions from the ventrolateral part of the frontal lobe to theupper part of the temporal lobe during the verbal fluency task. Sleep duration in the previousnight positively correlated with [oxy-Hb] increases in the bilateral channels over thedorsolateral prefrontal lobe also during the verbal fluency task. No significant correlationsbetween the VAS score and sleep duration in the previous night with [oxy-Hb] increaseswere found during a control task, the left-finger-tapping task. The subjective feeling ofpsychological fatigue is related to decreased reactivities in the lateral frontal and superiortemporal cortices and is unrelated to sleep duration in the previous night, which is reflectedin the reactivity in the dorsolateral prefrontal cortices. These results suggest that transienthypofunction and persistent dysfunction in the lateral prefrontal and temporal lobes areamong the brain substrates of fatigue. These also demonstrate the advantage of NIRS forinvestigating brain function during subjective phenomena such as fatigue because itenables examination in a natural setting.

© 2008 Elsevier B.V. All rights reserved.

Keywords:Near-infrared spectroscopy (NIRS)Subjective fatigueFrontal functionSleeping hourVerbal fluency task

1. Introduction

Fatigue is a feeling frequently experienced in daily life by bothhealthy subjects and patients with various medical andpsychiatric conditions, and is classified into physiologicaland psychological fatigue. It is generally considered as one of

p (M. Fukuda).

er B.V. All rights reserved

the most important feelings in daily life because it is closelyrelated to the quality of life. However, fatigue is usuallyassessed only subjectively and no gold standard for itsobjective measurement has been established owing to itsvery complex nature and difficulty in providing a reliabledefinition.

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In the search for biological indices of fatigue, brain functioncorrelates of fatigue have been studied using, for example,event-related potentials (Lorist et al., 2005; Boksem et al.,2006). Recently, more direct studies of brain substrates offatigue have been carried out using functional neuroimaging,particularly for medical conditions such as chronic fatiguesyndrome (CFS) (de Lange et al., 2004; Tanaka et al., 2006; Cooket al., 2007),multiple sclerosis (Filippi et al., 2002; Roelcke et al.,1997), and Parkinson disease (Abe et al., 2000). Most of thesestudies demonstrated decreased brain activities in patientswith fatigue. Fatigue in healthy subjects is mainly studiedwith such subjects as the control group in the medical setting,and thus, studies focusing on fatigue in healthy subjects goingabout their daily lives are lacking. One exception is a study in

Fig. 1 – Grand averaged waveforms of oxygenated and deoxygen[deoxy-Hb] (blue line), respectively) changes during a 60-s verbalusing a 52-channel NIRS machine over frontal and temporal regioartifacts are shaded in gray. Yellow and green frames indicate chaand sleep duration inmultiple regression analyses, respectively.and anatomically labeled in standard brain space (Okamoto et al

which fatigue was induced by tryptophan ingestion in healthysubjects, which demonstrated smaller activation in theinferior frontal and the lateral orbital gyri during a Strooptask, using functional magnetic resonance imaging (fMRI)(Morgan et al., 2007).

One of the serious problems in functional neuroimagingstudies of fatigue is their examination settings: fMRI datahave to be obtained from subjects in the supine position in avery noisy room. Brain function examined under such anunusual environment does not necessarily reflect daily lifesituations. Near-infrared spectroscopy (NIRS) is one of thefunctional neuroimaging techniques that can enable thedetection of regional cerebral blood volume (CBV) bymeasuring oxygenated ([oxy-Hb]) and deoxygenated

ated hemoglobin concentration ([oxy-Hb] (red line) andfluency task (between two dotted vertical lines) measuredns. Channels excluded from the analyses because of motionnnels showing significant partial correlationswith VAS scoreThe location of NIRS channels was probabilistically estimated., 2004).

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hemoglobin concentration ([deoxy-Hb]) changes using near-infrared light (for reviews, see Hock et al., 1997; Strangmanet al., 2002; Fallgatter et al., 2004; Boas et al., 2004). NIRS hashigher time resolution such as 0.1 s than fMRI, and moredirect correspondence to brain structures beneath thantopographic EEG, and has been used to examine, forexample, the time course of brain activation (Sato et al.,2007; Hanaoka et al., 2007), language dominance (Watanabeet al., 1998), brain substrates of personality (Ito et al., 2005)and sleepiness (Suda et al., 2008) in healthy subjects, brainactivation in awake infants (Taga et al., 2003), and patho-physiology of psychiatric disorders (for example, see Suto etal., 2004; Kameyama et al., 2006; Uehara et al., 2007). Inaddition to its complete noninvasiveness and the portabilityof the apparatus, NIRS has another advantage for studies offatigue, that is, its examination setting: NIRS can measurethe brain activity of subjects in the sitting position in a quietroom. This advantage extends its applicability to normalchildren, healthy volunteers while writing and speaking, andpsychiatric patients.

In this study, we examined the relationship between thesubjective feeling of psychological fatigue and brain activationin healthy subjects going about their daily lives. The subjectivefeeling of psychological fatigue was assessed using the visualanalogue scale (VAS) score, and brain activation was mea-sured using NIRS during cognitive activation. In addition tosubjective fatigue, sleepiness was included in the clinicalassessment using sleep duration because fatigue and sleepi-ness are distinct but interrelated phenomena and are difficultto differentiate (Dawson and McCulloch, 2004; Shen et al.,2006). Brain activation was also measured during motoractivation as the control condition for contrasts with cognitiveactivation. We hypothesized that the fatigue-related decreasein brain activity observed in medical conditions associated

Fig. 2 – (a) Correlation between [oxy-Hb] changes in ch 50 (VLPFCfeeling of psychological fatigue. (b) Correlation between [oxy-Hb]duration in the previous night.

with fatigue is also observed in healthy subjects going abouttheir daily lives.

2. Results

2.1. Behavioral data

Behavioral data were as follows: VAS score (mean, 37.2; SD,17.4; range, 5–70), sleep duration in the previous night (mean,6.1; SD, 1.8; range, 1–10), average sleep duration in usual nights(mean, 6.4; SD, 1.4; range, 4–10), and task performance score(mean, 17.0; SD, 4.8; range, 9–26). Sleep duration in theprevious night was subjected to further correlational analysesbecause there was no significant difference between sleepduration in the previous night and average sleep duration inusual nights (t=−0.722, P=0.474). There were also no signifi-cant correlations among VAS score, sleep duration in theprevious night, and task performance.

2.2. NIRS data during verbal fluency task (Fig. 1)

2.2.1. [oxy-Hb] dataThe two-way repeated-measures ANOVA revealed a signifi-cant main effect of “task” in all the 31 channels (F=5.6 to 60.7,Pb0.02) and “segment” in 28 channels (ch 22–25, 28–36, 38–52;F=6.5 to 21.3, Pb0.002): [oxy-Hb] increases were significantlylarger during the VFT than during the finger tapping task, andduring the task segment than the pretask and the posttasksegments. Post hoc ANOVA demonstrated that the [oxy-Hb]increases during the verbal fluency task were significant in allthe 31 channels (F=9.48 to 40.55, Pb0.0015). The two-wayinteractions of ‘‘task’’ and ‘‘segment’’ were significant in 25channels (ch 22, 24–29, 32–40, 42, 44–51; F=3.4 to 17.6,

) during the verbal fluency task and VAS score of subjectivechanges in ch 38 (DLPFC) during verbal fluency task and sleep

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Pb0.036), indicating that the [oxy-Hb] increases during thetask segment relative to those during the pretask and theposttask segments were more pronounced during the VFTthan during the finger tapping task.

In the multiple regression analysis, the [oxy-Hb] increasesduring the verbal fluency task correlatedwith the VAS score inseven channels (ch 34–35, 40, 44–45, 50–51, yellow channels inFig. 1; beta=−0.669 to −0.419, P=0.002 to 0.038; Fig. 2), withsleep duration in seven channels (ch 26–27, 36, 38–39, 46, 49,green channels in Fig. 1; beta=0.676 to 0.435, P=0.001 to 0.026;Fig. 3), and with age in four channels (ch 29, 34, 40, 44; beta=−0.484 to −0.397, P=0.019 to 0.04). Task performance and sexdid not correlate with [oxy-Hb] increases in any channel. Thechannels showing significant correlation with fatigue werefound mainly in the ventral region and those with sleepduration in the dorsal region.

By dividing the 24 NIRS channels into four clusters ofneighboring six channels, namely, right VLPFC (ch 23, 24, 33,34, 44, and 45), left VLPFC (ch 29, 30, 40, 41, 50, and 51), rightDLPFC (ch 25, 26, 35, 36, 46, and 47), and left DLPFC (ch 27, 28,38, 39, 48, and 49) and averaging [oxy-Hb] changes in eachcluster with six channels, significant correlations wereobtained in the right VLPFC (r=−0.551, P=0.006) and leftVLPFC (r=−0.527, P=0.001) for VAS scores and right DLPFC

Fig. 3 – Pearson's r value graphs showing correlation at the point otask (between two dotted vertical lines) and VAS scores of subjeduration in the previous night (lower part) in the available 31 chancorrespond to 5% and 1% statistical significance levels, respectiv

(r=0.638, P=0.001) and left DLPFC (r=0.730, Pb0.001) for sleepduration.

The correlations between [oxy-Hb] changes during theverbal fluency task andVAS scores and sleeping hours at every0.1 s point are shown in Fig. 3. [oxy-Hb] changes correlatedwith both the VAS scores and sleep duration inmany channelswhen examined along the time courses of the task: significantcorrelations as high as 1% were obtained during the later partof the task segment in the channels corresponding to VLPFCfor the VAS scores and during the earlier part of the tasksegment in the channels corresponding to DLPFC for sleepduration.

2.2.2. [deoxy-Hb] dataThe two-way repeated-measures ANOVA revealed a signifi-cant main effect of “task” in 16 channels (ch 23, 25–29, 33, 39,44, 46–52; F=4.6 to 31.6, Pb0.018), and “segment” in 27channels (ch 22–25, 28–35, 38–52; F=3.4 to 19.9, Pb0.039):[deoxy-Hb] decreases were significantly larger during the VFTthan during the finger tapping task, and during the tasksegment than the pretask and the posttask segments. Post hocANOVA showed that the [deoxy-Hb] decreases during theverbal fluency task were significant in 22 channels (ch 23, 25–27, 29–30, 33–36, 38–41, 44–51; F=5.646 to 53.024, Pb0.036). The

f 0.1 s between [oxy-Hb] changes during a 60-s verbal fluencyctive feeling of psychological fatigue (upper part) or sleepnels as presented in Fig. 1. Blue and red lines in each r graph

ely.

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two-way interactions of ‘‘task’’ and ‘‘segment’’ were signifi-cant in ch 47 (F=7.8, P=0.001), indicating that the [deoxy-Hb]decreases during the task segment relative to those during thepretask and the posttask segments were more pronouncedduring the VFT than during the finger tapping task.

In the multiple regression analyses, there were no sig-nificant correlations except a negative correlation between[deoxy-Hb] decreases and sleep duration in the previous nightin ch 47 (beta=−0.695, P=0.0002).

2.3. NIRS data during finger tapping task

[oxy-Hb] changes during the finger tapping task were sig-nificant in four channels (Ch 33, 44–46; F=7.37–11.11, Pb0.003)and no channel exhibited significant [deoxy-Hb] changes (Fig.4). The correlations between [oxy-Hb] changes during thefinger tapping task and VAS scores and sleeping hours at every0.1 s point are shown in Fig. 5. There were no correlationsbetween [oxy-Hb] changes and VAS score or sleep duration inthe previous night.

3. Discussion

In this study, we examined the correlations of subjectivefatigue assessed in terms of the VAS score and sleep durationin the previous night with cerebral cortex reactivity in younghealthy volunteers during a verbal fluency task and a left-finger-tapping task using a multichannel NIRS machine. Theresults obtained demonstrated that (1) subjective fatiguenegatively correlated with [oxy-Hb] increases in the channelsover the ventrolateral prefrontal cortex in both hemispheres

Fig. 4 – Grand averaged waveforms of [oxy-Hb] (red line) and [detask (between two dotted vertical lines) measured using a 52-chshown in Fig. 1.

during cognitive task, (2) sleep duration in the previous nightpositively correlated with [oxy-Hb] increases in the channelsover the dorsolateral prefrontal cortex in both hemispheresalso during cognitive task, and (3) no such significantcorrelations of VAS score and sleep duration in the previousnight with [deoxy-Hb] decreases during the cognitive task orwith either [oxy-Hb] or [deoxy-Hb] changes during the simplemotor task were found. These findings suggest that thesubjective feeling of psychological fatigue, i.e., the subjectivelyperceived aspect of psychological fatigue, is related to decreasedreactivity in the ventrolateral prefrontal cortex and is unre-lated to sleep duration in the previous night, which is reflectedin the reactivity in the dorsolateral prefrontal cortex.

To the best of our knowledge, this is the first study inwhich the subjective feeling of psychological fatigue wasexamined using NIRS. The subjective fatigue related todecrease in ventrolateral prefrontal cortex reactivity inhealthy subjects is in good agreement with a previous fMRIstudy that demonstrated smaller activations in the inferiorfrontal and lateral orbital gyri during a Stroop task in healthysubjects who ingested tryptophan, which induces fatigue(Morgan et al., 2007). Fatigue-related abnormalities in thefrontal lobe have also been observed in patients with somemedical conditions such as chronic fatigue syndrome (CFS)(de Lange et al., 2004, Tanaka et al., 2006, Okada et al., 2004,Kuratsune et al., 2002, Cook et al., 2007), multiple sclerosis(Filippi et al., 2002, Roelcke et al., 1997), and Parkinsondisease (Abe et al., 2000).

NIRS methodology is assumed to be advantageous forobtaining such a finding because it enabled the measurementof brain activation in a natural setting, that is, in subjects inthe sitting position in a quiet room, instead of in the supine

oxy-Hb] (blue line) changes during a 60-s left-finger-tappingannel NIRS machine over frontal and temporal regions as

Fig. 5 – Pearson's r value graphs showing correlation at the point of 0.1 s between [oxy-Hb] changes during a 60-s left fingertapping task (between two dotted vertical lines) and VAS scores of subjective feeling of psychological fatigue (upper part) orsleep duration in the previous night (lower part) in the available 31 channels as presented in Fig. 1. Blue and red lines in each rgraph correspond to 5% and 1% statistical significance levels, respectively.

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position in a noisy gantry as in the case of fMRI studies. Theobtained results cannot be attributed to task-nonspecificphysiological factors possibly related to fatigue such asreduced neurovascular coupling due to altered autonomicfunction in fatigue, but are considered to reflect the function ofthe ventrolateral prefrontal cortex because significant correla-tions between NIRS data and the VAS score of subjectivefeeling of psychological fatigue were obtained only in the VFTtask but not in the finger tapping task.

Measurements that enable the differentiation of subjectivefeeling of fatigue and sleepiness are often difficult, asmentioned in the Introduction. To differentiate them, wealso examined the relationships of NIRS data with sleepduration in the previous night and the average in usual nights,which we used as alternative indices of the subjective feelingof sleepiness. A clear difference in their correlations suggeststhat the obtained findings are related not to sleepiness but tofatigue: the significant correlation of the NIRS data with theVAS score of the subjective feeling of psychological fatiguewas negative in the bilateral channels over the ventrolateralprefrontal cortex, and that with the sleep duration waspositive in the bilateral channels over the dorsolateralprefrontal cortex.

The latter finding is consistent with the studies showingdecreased cerebral blood flow in sleepiness during arithmetic(Drummond et al., 1999) and verbal working memory tasks(Mu et al., 2005a,b) and reduced cerebral blood volumeincreases in the medial prefrontal cortex during a verbalfluency task (Suda et al., 2008), but is inconsistent with thestudies showing increased cerebral blood flow in sleepinessusing verbal learning (Drummond et al., 2000), short-termattention (Portas et al., 1998), divided attention (Drummond etal., 2001), and grammatical reasoning tasks after total sleepdeprivation (Drummond et al., 2004), and is partly consistentwith the studies showing mixed results during verbal (Cheeand Choo, 2004; Habeck et al., 2004) and nonverbal (BellMcGinty et al., 2004) item recognition tasks. An increased brainactivity in sleepiness is interpreted as reflecting compensatoryefforts to overcome performance deficits after sleep depriva-tion (Drummond et al., 2005).

There are several methodological limitations of this study.First, fatigue was assessed only using the VAS score of thesubjective feeling; no established assessment scale of fatiguewas employed. Second, sleepiness was also assessed usingonly sleep duration without employing any assessment scaleof subjective sleepiness or an objective method such as

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electroencephalography. Third, the subjects included weregoing about their usual daily lives at the time of examinationand their fatigue or sleepiness was not controlled. Diurnalphysiological fluctuations might have had an effect on theresults of this study. In a future study, the subjects should becontrolled in terms of their condition or might be groupedaccording to the causes of fatigue and analyzed separately foreach cause. Fourth, only the VFT task was employed forcognitive activation. The relationship between psychologicalfatigue and activations over the ventrolateral prefrontal lobeshould be replicated using other cognitive tasks such asworking memory and executive function tasks. Moreover,repeated-measure design would be preferable. To repeat thetask such as stressful calculation to induce the psychologicalfatigue would make it possible to evaluate both objective andsubjective fatigue. Fifth, activation was examined only in thefrontal lobe but not in other cerebral cortices or deep brainstructures. Although focusing on cortical function using NIRSfavors the studies on the subjectively perceived aspect ofpsychological fatigue, future study is needed to assess theparticipation of deep brain structures such as the brainstem,thalamus, and limbic region in provoking the observed corticalchange. Sixth, there was a statistical problem. We did notapply the false-positive correction in multiple regressionanalyses, although we applied it in two-way ANOVA andpost hoc analyses. The main reason for this is that false-positive correction was already performed in the first step,that is, two-way ANOVA and post hoc analyses on a channel-by-channel basis. However, because the possible type I errorcannot be completely excluded, further study with a largenumber of subjects is required to exclude.

In conclusion, the subjective feeling of psychologicalfatigue was reflected in the decreased reactivities of theventrolateral prefrontal cortex during cognitive activation inhealthy subjects going about their daily lives. On the basis ofthe findings, we assume that transient hypofunction in theventrolateral prefrontal cortex is the brain substrate ofpsychological fatigue in healthy subjects, and a more persis-tent dysfunction of the lobes is observed under pathologicalconditions associated with fatigue. Further functional neuroi-maging studies specifically focusing on fatigue are requiredbecause elucidating the brain mechanism underlying psycho-logical fatigue is beneficial for promoting the quality of life ofhealthy subjects and patients suffering from fatigue. Amongseveral functional neuroimaging techniques currentlyemployed, NIRS is advantageous for studies of fatigue andsleepiness because it enables the measurement of brainactivation in a natural setting.

4. Experimental procedures

4.1. Subjects

Twenty-three young healthy volunteers participated in thisstudy (11 males and 12 females; average age 22.6 years, SD 2.8,range 19–27). All the subjects were determined to be right-handed using the Edinburgh Handedness Inventory scale(Oldfield, 1971). They had no history of any major psychiatricdisorder, neurological disorder, substance abuse, head injury,

or major physical illness, and they were not on any psycho-tropic medications at the time of the study. This study wasapproved by the Institutional Review Board of the GunmaUniversity Graduate School of Medicine. Written informedconsent was obtained from all the subjects prior to the study.

4.2. Assessment of subjective feeling of psychologicalfatigue

The subjective feeling of psychological fatigue was assessedusing the VAS. The participants were instructed to evaluatetheir subjective fatigue at the time of the examination in termsof the VAS from 0 (no fatigue) to 100 (total exhaustion)immediately before the NIRS measurement. VAS was selectedfor subjective fatigue assessment because it has been shownto provide valid measures of subjective feelings such as pain(McCormack et al., 1988, Price et al., 1983) and has actuallybeen employed in the studies of subjective fatigue (Schneideret al., 2004, Tanaka et al., 2006, Cook et al., 2007). Sleepduration in the previous night and the average in a usual nightwere also obtained.

4.3. NIRS measurements

4.3.1. Activation tasksCognitive and motor activation tasks were employed for NIRSmeasurements. The cognitive activation task was a modifiedletter version of the verbal fluency task. Each subject sat on acomfortable chair in a daylight roomwith his or her eyes openthroughout each measurement. The cognitive activation taskconsisted of a 30-s pretask baseline, a 60-s verbal fluency task,and a 70-s posttask baseline. During the verbal fluency task,the subjects were instructed to verbally generate as manywords whose initial syllable was either /a/, /ki/, or /ha/ as theycould. These three initial syllables were employed in theabove-mentioned order and changed every 20 s during the 60-s task to decrease the time during which the subjectsremained silent. The number of words generated during theverbal fluency task was determined as a measure of taskperformance. During the pretask and posttask baselineperiods, the subjects were instructed to repeat the syllables /a/, /i/, /u/, /e/, and /o/ as the Japanese counterparts of A, B andC in English.

The motor activation task was employed as a control taskunrelated to cognitive activation and consisted of a 30-spretask rest, a 60-s left-finger-tapping task, and a 70-sposttask rest. The left-finger-tapping task was selectedbecause skilled movement of the dominant hand, i.e., right-finger tapping, may result in exceptionally lower or higherbrain activity than other unskilled movements. The subjectswere instructed to tap their four fingers with their thumbalternately as quickly and accurately as they could. Theypracticed the left-finger tapping after receiving the instruc-tions for the task, and it was confirmed that they were able toperform the task correctly.

4.3.2. NIRS machineIn this study, changes in [oxy-Hb] and [deoxy-Hb] weremeasured using a 52-channel NIRS machine (Hitachi ETG-4000) at two wavelengths of near-infrared light (i.e., 780 and

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830 nm) whose absorption was measured, and [oxy-Hb] and[deoxy-Hb] were calculated. The distance between the pair ofemission and detector probes was 3.0 cm, and it wasconsidered that the machine measured points at a depth of2–3 cm from the scalp, that is, the surface of the cerebral cortex(Hock et al., 1997, Toronov et al., 2001).

The probes of the NIRS machine were placed on thesubject's frontal region. The frontal probes measured [Hb]changes at 52measurement points in a 6×30 cm area, with thelowest probes positioned along the Fp1–Fp2 line in accordancewith the international 10/20 system used in electroencepha-lography. The measurement points were labeled Channel 1 toChannel 52 from top to bottom. The correspondence betweenthe NIRS channels and the measurement points on thecerebral cortex was confirmed by a multisubject study ofanatomical craniocerebral correlation (Okamoto et al., 2004)and was displayed on the basis of the results of the virtualregistration method (Tsuzuki et al., 2007).

The absorption of near-infrared light was measured with atime resolution of 0.1 s. The obtained data were analyzedusing the “integral mode”. The pretask baseline was deter-mined as the mean across the last 10 s of the 30-s pretaskperiod, the posttask baseline was determined as the meanacross the last 10 s of the 70-s posttask period as describedpreviously (Suto et al., 2004, Kameyama et al., 2006), and linearfitting was applied to the data between these two baselines.The moving average method was used to exclude short-termmotion artifacts in the analyzed data (moving averagewindow: 5 s).

4.4. Data analyses

The waveforms of [oxy-Hb] and [deoxy-Hb] changes in all the52 channels were acquired from all the subjects during thecognitive and motor activation tasks. NIRS data of channelsthat clearly containedmotion artifacts, as determined by closeobservation of the subjects, namely, channels 1–21, wereexcluded from further analyses. Absence of clear artifacts inthe remaining NIRS channels was confirmed by close observa-tion of experimental situations and analysis of the dataobtained by two researchers.

[oxy-Hb] and [deoxy-Hb] data during the cognitive andmotor activation tasks were analyzed in two steps. In the firststep, the individually averaged [Hb] waveforms were dividedinto the following three time segments: the ‘pretask’ segmentfor 10 s before the task period, the ‘task segment’ for 60 sduring the task period, and the ‘posttask’ segment for 60 safter the task period. [Hb] datawere averaged across three tasksegments (pretask, task, and posttask) and were analyzedusing two-way repeated-measures analysis of variance(ANOVA) with “task” (VFT and finger tapping) and “segment”(pretask, task, and posttask) as independent variables, fol-lowed by post hoc one-way ANOVA comparison for thesignificant factor with significance levels corrected by thefalse discovery rate method (Singh and Dan, 2006).

In the second step, for the channels with significant [Hb]changes, as determined by a significant main effect of“segment” in each channel in the first step, the relationshipsof the [Hb] changes with subjective fatigue and sleep durationwere analyzed using multiple regression analyses with the

averages of [Hb] during the task period as dependent variablesand the VAS score, sleep duration, task performance score,sex, and age of the subjects as independent variables, toexclude the effects of sex, age, and performance score in thistask. The [deoxy-Hb] data were also analyzed in the samemanner as the [oxy-Hb] data.

In addition, we performed two types of analyses. First,the relationships between subjective fatigue or sleep dura-tion and response latencies in the time domain or phaseoffsets in the frequency domain during verbal fluency taskwere determined. We calculated Pearson's r value at thepoint of 0.1 s between [oxy-Hb] changes in each channel andVAS scores or sleep duration during the verbal fluency taskand the finger tapping task (shown in Figs. 3 and 5,respectively). Second, the localization of the channel thatcorrelated with VAS and sleep duration was carried out. Wedivided the NIRS channels into four clusters correspondingto brain regions, namely, right VLPFC (ch 23, 24, 33, 34, 44,and 45), left VLPFC (ch 29, 30, 40, 41, 50, and 51), right DLPFC(ch 25, 26, 35, 36, 46, and 47), and left DLPFC (ch 27, 28, 38, 39,48, and 49). The averaged [oxy-Hb] changes in each clusterwere calculated as the average of the six channels, [oxy-Hb]changes during the verbal fluency task segment. Then,simple correlation was conducted using the averaged [oxy-Hb] changes of each cluster and VAS scores or sleepduration, with significance levels corrected by the falsediscovery rate method (Singh and Dan, 2006).

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