Psychopharmacology (2005) 181: 761–770DOI 10.1007/s00213-005-0035-2

ORIGINAL INVESTIGATION

Fabiana Fratello . Giuseppe Curcio . Michele Ferrara .Cristina Marzano . Alessandro Couyoumdjian .Giovanna Petrillo . Mario Bertini . Luigi De Gennaro

Can an inert sleeping pill affect sleep? Effects onpolysomnographic, behavioral and subjective measures

Received: 20 January 2005 / Accepted: 6 April 2005 / Published online: 29 June 2005# Springer-Verlag 2005

Abstract Rationale: Since two recent meta-analyses onsleep changes associated with placebo in clinical trialssuggested a beneficial effect of placebo treatments, pointingto a dissociation between subjective and objective measuresof sleep, the current experiment was directly aimed to as-sess the effects of an inert compound, administered with thesuggestion that it was a hypnotic substance in subjects withmild sleep complaints. Objectives: The aim of this studywas to compare subjective, behavioral, polysomnographic(PSG), and quantitative electroencephalographic (EEG)changes during a night preceded or not by the intake of two50-mg lactose capsules. Methods: Ten female students,selected by the Pittsburgh Sleep Quality Index, slept forthree consecutive nights in a sleep laboratory, with the ex-perimental (EXP) night defined by the administration oftwo 50-mg lactose pills. Self-ratings of sleep quality andperformance were assessed upon morning awakening ofbaseline (BSL) and EXP nights. Results: The EXP nightswere self-rated as more restful and characterized by a de-creased number of nocturnal awakenings than the BSLnights. PSG measures showed that wakefulness after sleeponset significantly decreased during the EXP night as com-pared to the BSL night. The EXP nights also showed anincrease of 0.5–4.0 Hz power during nonrapid eye move-

ment sleep and a decrease of EEG activity in the betafrequency range during rapid eye movement sleep only atcentral brain sites. A specific improvement of behavioralmeasures was also found uponmorning awakening after theEXP night compared to the BSL night. Conclusions: Theadministration of an inert pill improves both the subjectiveand objective quality of sleep. The reduced sleep fragmen-tation and the effects on some quantitative EEG markers ofsleep homeostasis suggest that the experimental manipula-tion induced coherent changes in the subsequent sleep,resembling an enhancement of sleep pressure. The regionaldifferences of EEG activity suggest the involvement of aspecific physiological mechanism distinct from that of ef-fective treatments.

Keywords Placebo effect . Polysomnography . Sleepcontinuity . Behavioral measures . Subjective measures .Pittsburgh Sleep Quality Index (PSQI)

Introduction

Placebo effects on outcome measures in psychopharmacol-ogy trials vary widely, with placebo response rates rangingfrom 20 to 60% (Shapiro and Shapiro 1997; Quitkin 1999),and they can substantially affect conclusions about theefficacy of new medications. An effectiveness greater thanplacebo is particularly difficult when the primary measureof efficacy in treatment studies is based on self-ratings. Theparadox is that some medical syndromes, like depression,lack physiological outcome measures. On the other hand,some recent investigations using functional measures haveprovided new information on the neuroanatomical founda-tions of the placebo effect (Cook et al. 2002; Leuchter et al.2002, 2004; Mayberg et al. 2002; Petrovic et al. 2002).

Surprisingly, there is little information on placebo re-sponses during insomnia treatments. A significant effectof a placebo pill was found during an 8-week study aimedat investigating the effects of the intermittent use of zol-pidem on primary insomnia (Walsh et al. 2000). This studyshowed a progressive trend for better sleep in the placebo

F. Fratello . G. PetrilloDipartimento di Scienze Relazionali “G. Iacono”,Università di Napoli “Federico II”,Naples, Italy

F. Fratello . G. Curcio . M. Ferrara . C. Marzano .A. Couyoumdjian . M. Bertini . L. De Gennaro (*)Dipartimento di Psicologia, Sezione di Neuroscienze,Università degli Studi di Roma “La Sapienza”,Via dei Marsi, 78,00185 Rome, Italye-mail: luigi.degennaro@uniroma1.itTel.: +39-6-49917647Fax: +39-6-4451667

M. FerraraDipartimento di Medicina Interna e Sanità Pubblica,Università de L’Aquila,L’Aquila, Italy

group, as assessed by subjective estimates across the du-ration of the study, both during on-pill nights and no-pillnights. Two meta-analytical studies have recently estimat-ed the magnitude of placebo effects in insomnia clinicaltrials (Hrobjartsson and Gotzsche 2001; McCall et al.2003). Within a general meta-analysis of placebo effects,Hrobjartsson and Gotzsche (2001) pointed to a nonsignif-icant beneficial effect on sleep latency (a 10-min decreasein subjective estimates of sleep latency) in five clinicaltrials. McCall et al. (2003) showed a dissociation betweensubjective and objective outcome measures in five insom-nia medication trials. Subjective measures of sleep laten-cy demonstrated a significant reduction of 13.1 min forthe placebo groups, and subjective total sleep time dem-onstrated a significant increase of 13.5 min. On the otherhand, polysomnographic (PSG) sleep latency demonstrat-ed a nonsignificant reduction of 2.5 min. Hence, althoughempirical evidence of a placebo response in insomniatreatments is sparse, the central issue seems representedby the lack of parallel changes in objective (i.e., PSG) andsubjective measures of sleep.

The main aim of the current experiment is to assesswhether 100-mg lactose capsules, dispensed as a new hyp-notic to subjects with mild sleep complaint, affect sleepmeasures directly or indirectly associated to better sleepquality. More specifically, the protocol compared subjec-tive, behavioral, PSG, and quantitative electroencephalo-graphic (EEG) measures of sleep nights preceded or not byinactive pill intake. Changes in behavioral performanceduring the days after the baseline (BSL) and experimental(EXP) night were also evaluated.

Materials and methods

Subjects

From an original sample of 443 university students (meanage 22.29 years; range 20–26 years), who had participatedin another study (De Gennaro et al. 2004) filling in thePittsburgh Sleep Quality Index (PSQI; Buysse et al. 1989),ten women were selected as paid volunteers. The PSQIis a self-rating questionnaire consisting of 19 questions as-sessing a variety of factors relating to sleep quality (es-timates of sleep duration and latency and of the frequencyand severity of specific sleep-related problems). It yieldsan overall score between 0 and 21, consisting of sevencomponents of sleep quality (C1, sleep quality; C2, sleeponset latency; C3, sleep duration; C4, sleep efficiency; C5,sleep disturbances; C6, use of sleep medications; and C7,daytime dysfunction). An overall score greater than 5 isconsidered an indicator of sleep complaints (Buysse et al.1989). The Italian version has been translated from Englishto Italian, then retranslated for comparison with the originalversion.

The inclusion criteria were (1) a PSQI score ≥5 and ≤12,(2) a self-rated sleep latency ≥30 min once or twice eachweek (item 5a), and (3) a self-rated “fairly bad” sleep qual-ity (item 6). The subjects’ mean age was 23.5±1.58 (range

21–26 years). They were right-handed and reported drink-ing less than three caffeinated beverages per day and beingfree of any psychotropic drugs. They usually slept 6–7 h pernight, went to bed between 11:00 P.M. and midnight, and didnot take naps during the day. Other requirements forinclusion were no excessive daytime sleepiness and noother sleep, medical, or psychiatric disorders as assessed bya clinical interview.

The protocol of the study was approved by the localInstitutional Ethical Committee, and the subjects gave theirwritten informed consent according to the Declaration ofHelsinki and its amendments.

Procedure

During the week preceding the study, the subjects wereasked to respect their habitual sleep–wake rhythm andavoid napping; the compliance was controlled by means ofactigraphic recordings (AMI Minimotion logger). More-over, each morning, within 15 min from awakening, thesubjects filled in a standard sleep diary (De Gennaro et al.2003, 2004).

These data are reported in Table 1. Finally, 3 days beforethe start of the study, they were trained to reach a stableperformance level in the behavioral tasks (see below). Eachsubject spent three consecutive nights in the sleep labora-tory; to avoid any weekend-induced sleep–wake rhythmalteration,1 these nights were always scheduled from Tues-days to Thursdays. The participants were recorded duringthe follicular phase of their menstrual cycle and they werefree of any medication during the study and the week pre-ceding it.

The first adaptation night (AD) was followed by a BSLor by an EXP night: the lactose capsules were administeredonly during the EXP night. To avoid any sequence effects,the BSL and EXP nights were balanced between subjects:half of them received the capsules before the second night,and the others, before the third night.

The subjects arrived at the laboratory at 8:00 P.M. forelectrode hook-up, after which they completed the behav-ioral tasks. In the EXP night, half an hour before the ha-bitual individual sleep-onset time, the subjects took twocapsules (one blue and one white) containing a total of100 mg of lactose. The capsules were always administeredby the same experimenter (L.D.G.), known by the subjectsas the senior researcher of the study, who came to the sleeplaboratory only for this specific reason. The subjects weretold that the substance had hypnotic properties, that it hadbeen previously tested with good results, and that it wasfree of side effects, at variance of many other hypnotics thatproduce daytime sleepiness. They were then told that theaim of the study was to assess the effect of this new hyp-notic substance on sleep EEG features and performance.

1Actually, the length of sleep [weekdays, 415.4±38.5 min; week-ends, 424.1±89.8 min; F(1,9)=0.09; p=0.76] and the time of sleeponset [weekdays, 12:02 A.M. ±63.9 min; weekends, 12.32 A.M. ±60.7 min; F(1,9)=2.44; p=0.15] were not different during weekdaysvs weekends.

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The subjects and the experimenters/technicians conductingthe sleep recordings were blind with respect to the realcontents of the capsules and the specific aims of the study,that is, the assessment of the effects of an inert pill on sleepmeasures. In fact, they actually believed that they wereparticipating in a study on the effect of a new hypnoticcompound, and a debriefing interview confirmed this be-lief. The experimenters (undergraduate students) were alsotold that measures for the placebo group with an inert pillwould have been collected in a later phase of the study.Complete information on the study was actually given toeveryone concerned in a seminar at the end of the wholestudy.

The total sleep time allowed during the study was limitedto 7.5 h per night, and the exact amount of accrued sleepwas calculated by running a chronometer from the first Kcomplex or sleep spindle and by stopping it whenever aperiod of wakefulness or a movement time longer than 15 soccurred. Upon awakening, the subjects were again askedto fill in the standard sleep diary used in the week pre-ceding the experiment. Subsequently, 30 min after waking,the subjects completed the morning behavioral session.Then, they were free to leave the laboratory, with the rec-ommendation to avoid napping. Compliance was againchecked by actigraphic recordings (AMI Minimotion log-ger). Moreover, caffeinated beverages (a maximum of threeper day and only one after lunchtime) were not allowedafter 5:00 P.M. No alcohol was permitted for the duration ofthe study.

Polysomnographic recordings

An Esaote Biomedica VEGA 24 polygraph was used forpolygraphic recordings. EEG signals were high-pass fil-tered with a time constant of 0.3 s and low-pass filtered at30 Hz; four unipolar EEG channels were recorded fromscalp electrodes with mastoid reference (Fz-A1, Cz-A1, Pz-A1, and Oz-A1), using the international 10–20 system. Thesubmental electromyogram (EMG) was recorded with atime constant of 0.03 s. Bipolar horizontal and vertical eyemovements were recorded with a time constant of 1 s. Theimpedance of these electrodes was kept below 5 kΩ.

Cz EEG (Cz-A1), EMG, and electrooculography (EOG)were used to visually score sleep stages in 20-s epochs,according to the standard criteria (Rechtschaffen and Kales1968), by an experimenter who was blind with respect tothe treatment condition. With regard to slow-wave sleep

(SWS) scoring, the greater than 75 μV amplitude criterionwas strictly followed.

The following were considered as dependent variables:sleep-onset latency, defined as stage 1 latency; stage 2latency; total sleep time (TST), defined as the sum of timespent in stage 1, stage 2, SWS, and REM; total bedtime(TBT), sleep efficiency index (SEI, TST/TBT×100), num-ber of awakenings, wakefulness after sleep onset (WASO),the percentage of each sleep stage, and the percentage ofarousals.

Because sleep fragmentation is one of the PSG measuresmainly affected by hypnotics (Nowell et al. 1997), a furtheranalysis on EEG arousals, scored according to the Amer-ican Sleep Disorders Association (ASDA) and Sleep Re-search Society rules (ASDA 1992), was carried out. Theonly modification to the ASDA rules was the decision touse shorter intervals (1.5 s instead of 3 s) of EEG changes.This criterion allows increasing the time resolution of theanalysis (Mathur and Douglas 1995; De Gennaro et al.2001). Therefore, we scored as an arousal any shift in theEEG frequency to alpha or theta for at least 1.5 s, irre-spective of changes in submental EMG during NREMsleep, but accompanied by a 1.5-s increase in EMG am-plitude during REM sleep. The arousal index (AI) wasexpressed by the ratio between the number of arousalsdivided by sleep duration. As a further measure of sleepfragmentation, the greater than 60-s awakenings (numberper hour) were scored separately during NREM and REMsleep.

Quantitative analysis of signals

The polygraphic signals (four EEG channels, two EOG,and EMG) were converted online from analog to digital,with a sampling rate of 128 Hz, and stored on the disk ofa personal computer. Artifacts were excluded offline on a20-s basis by visual inspection; as regards to REM sleep,only tonic periods were included in the analyses to avoidthe artifactual influences of REM on EEG power. Thepower spectra of the four derivations along the anteropos-terior axis (Fz-A1, Cz-A1, Pz-A1, and Oz-A1) were com-puted by a Fast Fourier Transform routine for consecutive4-s epochs, resulting in a frequency resolution of 0.25 Hz.Values greater than 25 Hz were not used in the analysis. Bycollapsing four adjacent 0.25-Hz bins (1–25 Hz), the datawere reduced to a 1-Hz bin width. The only exception wasthe 0.5- to 1.0-Hz bin, for which two adjacent 0.25-Hz binswere collapsed.

A further data reduction of power spectra was achievedby averaging 15 consecutive 4-s epochs to yield a 60-sspectrum. As a result, this spectrum included three con-secutive 20-s visually scored epochs. Power spectra werecalculated separately for non-REM (stages 2+3+4) andREM sleep.

The bins are referred to and plotted in this study by thehighest frequency included (e.g., the 3-Hz bin refers to theaveraged values of the following bin intervals: 2.00–2.25,2.25–2.50, 2.50–2.75, and 2.75–3.00 Hz).

Table 1 Means and standard deviations (within brackets) of sleepmeasures during the week preceding the study, as assessed by astandard sleep diary and by the actigraphic recordings

Sleep latency (min) TST (min) WASO (min)

Sleep diary 23.05 (17.20) 420.92 (46.98) 7.79 (6.70)Actigraphicrecording

11.56 (4.68) 407.30 (37.25) 22.60 (10.43)

TST Total sleep time, WASO wakefulness after sleep onset

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EEG power values at each frequency bin were con-sidered as dependent measures. The absolute power valueswere log-transformed before the statistical tests to approx-imate a normal distribution.

Subjective measures

The subjective sleep estimates were obtained through astandard sleep diary filled in within 15 min after awaken-ing. The dependent variables were sleep latency (min),difficulty in falling asleep (range 1–6), number of nightlyawakenings, difficulty in falling asleep after nightly awaken-ings (range 1–6), total sleep time (min), sleep depth (range1–6), sleepiness upon final awakening (range 1–6), calmupon final awakening (range 1–6), and tiredness/restful-ness upon final awakening (range 1–6).

Behavioral tasks

The subjects were submitted to the following tests duringeach performance session: the Descending Subtraction Test(DST; Dinges et al. 1981), an auditory simple-reaction timetask (RTT), and a visual search task [Letter CancellationTask (LCT); Casagrande et al. 1997]. The test sequencewas kept constant within and between subjects.

Descending Subtraction Test

The DST was specially developed by Dinges et al. (1981)to tax cognitive functioning for a relatively brief time(3 min). In this task, the experimenter gives the subject athree-digit number, such as 853, which is to be repeatedaloud as the first response. The subject is then required tomentally subtract the number 9 from 853 and to say theanswer (844) aloud. This answer then becomes the newminuend, from which 8 must be subtracted. Thus, the sub-trahend progressively decreases by 1 until, after reachingthe value of 2, it returns to 9. The series is continued for3 min and the answers are tape-recorded. The instructionsemphasize both speed and accuracy. Because the taskrequires keeping in mind both the subtrahend and minuend,and because both change after each response, a consider-able load is placed on short-term memory. The subjects areallowed to correct any response. If they get lost in asequence, they are instructed to guess where they are and tocontinue.

The total number of responses (NR) and the ratio be-tween the number of correct responses and the total numberof responses (CR/NR) as indices of speed and accuracy,respectively, were considered as dependent variables.

Reaction Time Task

The subjects were asked to press a button as quickly aspossible when they heard a tone coming from a loud-

speaker positioned in front of them at a distance of 70 cm.Every beep was characterized by a frequency of 1,000 Hzand an intensity of 75 dB. The reaction times were recordedfrom both hands. The Reaction Time Task (RTT) lasted5 min and was administered with an interstimulus intervalvarying between 3 and 5 s. The dependent variable was themean reaction time (in milliseconds).

Letter Cancellation Task

The subjects were asked to find and mark three target let-ters on a sheet containing a matrix of 1,800 capital letters:300 were target and 1,500 were nontarget letters. The timeallowed was 5 min. Again, instructions emphasized bothspeed and accuracy: the dependent variables were thenumber of explored rows (NR) for speed, and the pro-portion of correct responses, that is, the ratio between thenumber of correct responses and the total number of ex-plored targets (% CR), as the measure of accuracy.

Data analysis

The subjective, behavioral, PSG, and quantitative EEGmeasures were submitted to one-way repeated-measuresanalyses of variance (rANOVAs), comparing BSL andEXP nights. The same rANOVA was carried out on themeasures of arousals, scored according to the modifiedASDA criteria.

With respect to the quantitative analysis of EEG, thepower values for each derivation were submitted to a 2×25two-way rANOVA [Treatment (baseline, experimental) ×Frequency (1, 2, 3 ..., 25 Hz)]. According to the aims of thecurrent study, a significant effect for the factor treatment ora Treatment × Frequency interaction would point to a dif-ference between BSL and EXP nights and a between-nightsdifference across the frequency range, respectively. Themeans of significant Treatment × Frequency interactionhave been compared by means of post hoc t test. To correctfor multiple rANOVAs and post hoc tests, the Bonferronicorrection was applied. Considering the mean correlationbetween the variables (r=0.70), the alpha level was thenadjusted, respectively, to ≤0.03 and ≤0.02.

Finally, the correlation between the size of significantsubjective, behavioral, and objective (PSG) changes wasassessed. The product–moment correlation was computedbetween the difference of experimental-minus-baseline PSGmeasures and those between the experimental-minus-base-line subjective estimates or behavioral performances.

Results

Polysomnographic measures

Table 2 reports the results of the ANOVAs on PSG var-iables. As detailed in the table, there was a significant de-crease in the percentage of wakefulness after sleep onset

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(WASO) during the EXP night, as compared to the BSLone. No other comparison was significant; in other words,the two nights completely overlapped, with the notableexception of the amount of intrasleep wakefulness. Fur-thermore, the other measure of sleep continuity, that is, thenumber of awakenings, also showed a nonsignificant ten-dency toward a decrease during the EXP nights.

As a further measure of sleep continuity, an independentscoring of the EEG changes resulting in fragmented sleep(ASDA 1992) and of the greater than 60 s REM andNREM awakenings were considered. The results of theANOVAs on these measures are reported in Table 3,pointing to a slight reduction during the EXP night ofmeasures usually associated to sleep fragmentation, al-though the between-night difference was significant onlyfor the greater than 60 s REM awakenings.

Quantitative analysis of EEG

The EEG exhibited the characteristic changes betweenREM and NREM stages and between different derivationsalong the considered frequency range. The EEG power

values across the 0.5- to 25.0-Hz frequency range are sep-arately illustrated in Fig. 1 for NREM (stages 2+3+4) andREM sleep.

The results of the Treatment × Frequency ANOVAs onthese EEG power values at each considered derivation arereported in Tables 4 and 5, respectively, for NREM andREM sleep. According to the aims of the current study, asignificant difference for the factor treatment or a Treat-ment × Frequency interaction would indicate an overalltreatment effect or a treatment effect for specific EEGfrequency ranges, respectively. The pattern of results seemsquite unequivocal: both NREM and REM sleep showsignificant effects involving the night factor only at theCz lead. In NREM sleep, the significant Treatment × Fre-quency interaction is mainly explained by changes in thedelta frequency range. As depicted in Fig. 2, the nightsin which subjects had the lactose pills were characterizedby a significant increase in EEG activity in the 1- to 4-Hzrange (post hoc probabilities, 1.0 Hz=0.03; 2.0 Hz=0.003;3.0 Hz=0.01; 4.0 Hz=0.05) as compared to the BSL nights.A decrease of beta power in the 19.0- to 25.0-Hz range wasalso observed in the EXP night compared to the BSL night,

Table 2 Means and standard deviations of the polysomnographic variables during the baseline and the experimental nights

Variables Baseline Experimental F(1,9) p

Mean SD Mean SD

Sleep latency (min) 8.13 10.48 14.1 18.57 1.48 0.25Stage 2 latency 10.37 10.09 16.37 18.50 1.57 0.24Stage 1 (%) 4.81 1.64 5.31 1.19 1.18 0.30Stage 2 (%) 48.44 9.05 46.98 10.47 0.74 0.41Stage 3 (%) 11.51 4.17 12.32 3.47 0.78 0.40Stage 4 (%) 12.38 5.35 11.76 7.34 0.22 0.65SWS (%) 23.88 7.47 24.08 9.82 0.02 0.90REM (%) 22.87 3.02 23.63 2.45 0.40 0.54WASO (%) 4.98 2.09 3.67 1.33 10.51 0.01*No. of awakenings 14.40 15.20 9.90 8.44 2.78 0.13Arousals (%) 4.06 1.47 3.95 1.62 0.24 0.63TST (min) 436.17 43.65 433.57 46.06 0.05 0.83TBT (min) 471.63 39.94 468.87 56.31 0.05 0.82SEI, % (TST/TBT×100) 92.43 3.59 92.68 4.06 0.02 0.89

The results of the one-way ANOVAs are also reported. The asterisk marks significant resultsSWS Slow-wave sleep, REM rapid eye movement sleep, WASO wakefulness after sleep onset, TST total sleep time, TBT total bed time, SEIsleep efficiency index

Table 3 Means and standard deviations of American Sleep Disorders Association (ASDA) arousal indices during the baseline and theexperimental nights

Variables Baseline Experimental F(1,9) p

Mean SD Mean SD

NREM AI (no. per hour) 9.37 2.77 8.01 1.56 2.93 0.12REM AI (no. per hour) 12.61 7.73 11.97 8.06 0.30 0.60>60 s NREM awakenings (no. per hour) 0.50 0.31 0.33 0.26 2.67 0.14>60 s REM awakenings (no. per hour) 0.49 0.41 0.06 0.13 9.16 0.007*

The results of the one-way ANOVAs are also reported. The asterisk marks significant resultsNREM nonrapid eye movement sleep, AI arousal index, REM rapid eye movement sleep

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although it did not reach statistical significance at anyfrequency bin (p≤0.08 and p≥0.06).

Similar effects were also found in REM sleep (Fig. 2).The significant Treatment × Frequency interaction is ex-plained by between-night changes mainly affecting thedelta and beta frequency ranges. A lower beta power char-acterizes the EXP as compared to the BSL nights (post hoc

probabilities, 20.0 Hz=0.03; 21.0 Hz=0.02; 22.0 Hz=0.05;25.0 Hz=0.05), whereas the increase in delta power at 2.0–4.0 Hz only approached significance (post hoc probabil-ities, 3.0 Hz=0.06; 4.0 Hz=0.09). A further significant dif-ference was found within the sigma frequency range: EEGpower at 12.0 Hz was lower during EXP sleep than duringBSL sleep (p=0.01).

Table 4 Results of the two-way repeated measure ANOVAs [Treat-ment (baseline, experimental) × Frequency (1, 2, 3, ..., 25 Hz)] onEEG power values at the four anteroposterior derivations (Fz-A1,Cz-A1, Pz-A1, Oz-A1) during NREM sleep

Derivation Effects F(1,24) p

Fz Treatment 0.99 0.35Frequency 931.63 <0.00000001*Treatment × Frequency 0.28 0.99

Cz Treatment 0.11 0.75Frequency 890.06 <0.00000001*Treatment × Frequency 2.22 0.001*

Pz Treatment 0.47 0.51Frequency 638.34 <0.00000001*Treatment × Frequency 0.65 0.90

Oz Treatment 0.45 0.52Frequency 486.40 <0.00000001*Treatment × Frequency 0.35 0.99

The asterisk marks significant results

Table 5 Results of the two-way repeated measure ANOVAs [Treat-ment (baseline, experimental) × Frequency (1, 2, 3, ..., 25 Hz)] onEEG power values at the four anteroposterior derivations (Fz-A1,Cz-A1, Pz-A1, Oz-A1) during REM sleep

Derivation Effects F(1,24) p

Fz Treatment 0.25 0.63Frequency 488.55 <0.00000001*Treatment × Frequency 0.61 0.92

Cz Treatment 0.31 0.59Frequency 517.78 <0.00000001*Treatment × Frequency 1.68 0.03*

Pz Treatment 0.11 0.75Frequency 439.84 <0.00000001*Treatment×Frequency 0.83 0.70

Oz Treatment 0.18 0.68Frequency 289.95 <0.00000001*Treatment × Frequency 0.35 0.99

The asterisk marks significant results

Fig. 1 Mean EEG power (logvalues of μV2 ± standard error)for each single Hz bin (0.5–25.0 Hz) over the four differentderivations during NREM sleep(stage 2 + 3 + 4, filled circles)and REM sleep (open circles)

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Subjective measures

Table 6 reports the results of the ANOVAs on subjectivesleep quality ratings assessed after each morning awaken-ing. As detailed in the table, no comparison was significant.The results on the number of nightly awakenings and calmupon final awakening are in line with the hypothesis of abeneficial effect of the experimental treatment, since thenumber of nightly awakenings showed a tendency to de-crease, and the EXP nights were assessed as being calmer,but they did not reach the statistical significance (p=0.10).

Since the greater sleep continuity in the EXP nightsparallels the subjective estimates of a decreased number ofawakenings, the correlation between the size of subjectiveand objective (PSG) changes was assessed. Pearson’s rcoefficient was equal to 0.87 (p=0.0009). Hence, the sub-jective and PSGmeasures seem to converge in pointing to abeneficial effect of the experimental manipulation on sleepfragmentation, subjectively and objectively assessed. Onthe other hand, the same relationship assessed between thesubjective measure and changes in delta power duringNREM sleep (0.5–4.0 Hz), in sigma power (12.0 Hz), andin beta power (19.0–22.00 and 25 Hz) during REM sleep

was not so robust. They did not reach statistical signif-icance (NREM delta power, r=0.28; REM sigma power,r=0.56; REM beta power, r=0.44).

Behavioral performance measures

Table 7 reports the results of the ANOVAs on performancemeasures assessed by the LCT, the DST, and the RTT aftermorning awakening. There was a significant difference forthe correct response ratio in the DST, as a measure of ac-curacy, with a significant increase in accuracy upon morn-ing awakening after the EXP night as compared to the BSLnight. No other comparison was significant. Therefore, asignificant improvement, although small, has been found inonly one performance test out of three.

Discussion

The main findings of this study are that the experimentaltreatment, that is, the administration of an inert compoundwith the suggestion that it is a hypnotic substance, was

Fig. 2 Mean EEG power ratios(± standard error) of the Czderivation, obtained by dividingthe experimental and the base-line values (horizontal dottedline). Shading indicates bins inwhich spectral EEG power sig-nificantly changed during theexperimental night compared tothe baseline night (p=0.02 at thepost hoc t tests). The left panelreports EEG power ratios duringNREM sleep (stages 2+3+4),and the right panel, those duringREM sleep. Values of the ex-perimental night are indicatedby filled circles for NREM sleepand by empty circles for REMsleep

Table 6 Means and standard de-viations of the subjective sleepvariables during the baseline andthe experimental nights

The results of the one-wayANOVAs are also reported

Variables Baseline Experimental F(1,9) p

Mean SD Mean SD

Sleep latency (min) 18.00 9.41 20.25 13.97 0.18 0.68Difficulty of falling asleep (range 1–6) 4.40 0.70 4.70 1.16 0.37 0.56No. of nightly awakenings 1.85 1.39 1.15 1.13 3.24 0.10Total sleep time (min) 484.50 51.56 471.00 47.77 0.80 0.39Sleepiness upon final awakening (range 1–6) 4.50 0.97 4.30 1.16 0.31 0.59Sleep depth (range 1–6) 4.70 0.67 4.80 0.92 0.10 0.76Calm upon final awakening (range 1–6) 4.30 0.95 5.00 0.82 3.64 0.09Tiredness upon final awakening (range 1–6) 4.50 0.71 4.60 1.26 0.13 0.73

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followed by a night with more sleep continuity, with ahigher delta power in NREM sleep and a lower beta andsigma power during REM sleep; some aspects of behav-ioral performance also slightly improved in the morningafter the final awakening.

More specifically, the amount of awakenings after sleeponset was significantly reduced and the number of awaken-ings decreased, albeit not significantly. Subjective ratingstended to parallel the PSG changes, with a reduction ofnightly awakenings and an increased calm. The EEG powerof NREM sleep showed a coherent pattern of changes, withan increase in delta and a close-to-significance decrease inbeta power. The same frequency bands changed similarly inREM sleep, although the beta power changes were, in thiscase, significant. In REM sleep, a decreased sigma power at12 Hz was also observed.

Therefore, the experimental manipulation induced con-comitant changes in sleep architecture and also distincteffects on the quantitative EEG markers of sleep homeo-stasis, consistent with a better sleep quality. It is of note thatgreater beta power in NREM sleep has been reported as anelectrophysiological correlate of subjective complaints inindividuals with chronic primary insomnia (e.g., Perliset al. 2001; Krystal et al. 2002). It is possible that thedecreased beta power may have positively influenced thesubjective ratings of sleep quality in our sample of subjectswith moderate sleep complaints.

Sleep changes

The specific pattern of sleep EEG changes shown by thecurrent study resembles several changes affecting humansleep recovery after sleep deprivation (e.g., Finelli et al.2001), like the increased low-frequency EEG activity andthe decreased sigma and beta power, although with smallereffect sizes as compared to sleep deprivation studies. Butthis parallelism is only partially true, since postdeprivationhomeostatic changes in quantitative EEG mostly affectfrontal and central areas (Finelli et al. 2001; Ferrara et al.2002), whereas we do not show any change in the low-frequency EEG activity on the frontal derivation. Further-more, after sleep deprivation, sigma power in NREM sleepdecreases compared to the BSL (e.g., Finelli et al. 2001;

Ferrara et al. 2002), whereas in the present study it did notshow significant changes.

Some analogies, on the other hand, also do exist, withthe pattern of EEG changes recently shown as a conse-quence of a nonpharmacological treatment for primaryinsomnia (Cervena et al. 2004). In that study, changes insubjective sleep quality and quantity, in PSG, and in EEGpower during sleep after 8 weeks of a cognitive behavioraltherapy (CBT) for insomnia were evaluated. In addition, inthat study, subjective and PSG measures of sleep fragmen-tation decreased as compared to pretreatment sleep, slow-wave activity increased, and beta and sigma activity werereduced. In short, the beneficial effects of CBT in severechronic insomniacs pointed to an enhancement of sleeppressure and to an improvement of homeostatic sleep reg-ulation (Cervena et al. 2004). Although one needs to becautious when comparing the physiological mechanisms ofan experimental manipulation, like the current one, withthose of pharmacological or nonpharmacological interven-tions, the striking similarity of our effects with those of aCBT treatment seems consistent with the hypothesis of animportant role of aspecific factors in the efficacy of bothinterventions.

The specific changes in sleep macrostructure, as as-sessed by the PSG standard scoring system (Rechtschaffenand Kales 1968) or by scoring arousals (ASDA 1992)found in the current study, present some analogies with theconsequences of pharmacological and nonpharmacologicaltreatments of sleep disorders (Smith et al. 2002). Consis-tently, one out of three of our behavioral measures, that is,the accuracy in the Descending Subtraction Test, amelio-rates after awakening from the EXP night as compared tothe BSL night, although this improvement does not seem tobe a consequence of the slightly better sleep quality, but ofthe experimental manipulation itself.

Whereas the current pattern of sleep changes mostlyresembles that after sleep deprivation and that following aspecific nonpharmacological treatment for primary insom-nia, it should be mentioned that, in the present study, thecommon spectral EEG signature of sleep induced bybenzodiazepines or by zolpidem and zopiclone (i.e., ago-nistic GABAA modulators), consisting of an increasedsigma and beta power and of a slow-wave activity re-duction (e.g., Borbely et al. 1985; Dijk et al. 1989; Trachsel

Table 7 Means and standard de-viation of the behavioral variablesduring the baseline and the ex-perimental nights

The results of the one-wayANOVAs are also reported. Theasterisk marks significant results

Variables Baseline Experimental F(1,9) p

Mean SD Mean SD

Letter Cancellation TaskSpeed (no. of scanned rows) 18.60 4.47 18.50 4.30 0.008 0.93Accuracy (hits ratio) 0.89 0.06 0.89 0.06 0.03 0.87Descending Subtraction TestSpeed (no. of responses) 36.2 10.99 36.70 11.72 0.06 0.81Accuracy (correct responses ratio) 0.87 0.06 0.93 0.04 6.38 0.03*Reaction times (RTs)Right-hand RT (ms) 238.6 33.0 238.3 28.6 0.004 0.95Left-hand RT (ms) 234.3 27.5 237.4 27.6 1.16 0.31

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et al. 1990; Brunner et al. 1991; Aeschbach et al. 1994;Landolt et al. 2000), was not found. On the contrary, ourresults on quantitative EEG measures go in an oppositedirection.

In actual fact, the administration of 20 mg of zolpidem30 min prior to recovery sleep after 40 h of sleep depri-vation prolonged TST and the duration of SWS and stage 4during the first 4 h, as compared to placebo (Landolt et al.2000). On the other hand, zolpidem prevented the sleepdeprivation-induced increase in delta and theta frequenciesin NREM sleep. The authors stressed the inadequacy ofstandard scoring criteria for faithfully representing thechanges in sleep induced by pharmacological agents. Thisinadequacy is largely confirmed by the present results.

The issue of distinct brain functional changes between“effective” placebo treatments and effective medicationtreatments is far from being elucidated also in other cases.For example, common physiological response effects, con-sisting of limbic–paralimbic metabolism decreases, werefound in hospitalized men with unipolar depression afterthe administration of placebo or fluoxetine (Mayberg et al.2002), whereas brain physiology, as measured by a specificmethod based on quantitative EEG, was altered in a dif-ferent manner (i.e., by different neural networks) in placeboresponders compared to antidepressant medication respond-ers (Leuchter et al. 2002).

Although the mechanisms of “effective” placebo treat-ments still await to be elucidated, the “placebo effect” herereported on different subjective and objective measuresseems more “coherent” than those seen after the intake ofmost hypnotic compounds; in fact, the close-to-signifi-cance change in subjective ratings, some PSG measures ofsleep continuity, specific regionally graded EEG frequen-cies, and also some aspects of diurnal performance, allconverge in pointing to functional changes in the directionof improved sleep-recuperative processes.

Methodological issues

Which aspect of the experimental manipulation affectedsleep measures? The 100-mg lactose intake per se, theexpectancy of receiving a hypnotic drug, the willingness toachieve the supposed experimental aims, or the procedureitself, envisaging the senior researcher coming to the sleeplaboratory and administering the capsules? The currentexperiment does not provide the necessary means for dis-entangling this issue. In fact, the aim of the current studywas only to assess the existence of objective changes insleep measures after the intake of lactose pills and theensuing congruency with subjective changes.

The search for the mechanisms of placebo effects im-plicitly follows the demonstration that these effects actuallyexist, and it needs different and specific experimental de-signs. For example, the role of expectancy to have a bene-ficial effect would have been assessed by a within-subject

design comparing the current procedure with another con-dition, in which the subjects were told that it was in-effective. With regard to this issue, two studies alreadyshowed that a quasi-desensitization placebo was associatedwith improved subjective sleep only when the participantswere told that it was beneficial (Steinmark and Borkovec1974; Carr-Kaffashan andWoolfolk 1979). However, in thepresent study, the suggestion of the pills’ efficacy, althoughpresent, was not emphasized, since a stronger suggestionmay have induced cognitive arousal resulting in significantincreases in objective sleep latency (e.g., De Valck et al.2004). In fact, sleep latency did not change as compared tothe BSL night.

With respect to the behavioral change in the accuracymeasure of the DST, a reasonable question refers to itsexplanation. Is this significant change primary or second-ary to the experimental treatment? In other words, is thebehavioral improvement a direct consequence of the exper-imental treatment, or alternatively, a consequence of thebetter sleep quality, as indicated by the subjective and PSGchanges? The current experimental design does not provideany indication between these two alternative explanations.However, the assessment of the association betweenbehavioral and PSG changes may give a partial answer tothe question. In fact, the product–moment correlation be-tween the size of behavioral improvement in the accuracymeasure of DST (EXP-minus-BSL) and the difference ofEXP-minus-BSL WASO points to the lack of any associ-ation between the two effects (r=0.04; p=0.92). Conse-quently, the small behavioral improvement in the morningafter the EXP night could be a primary consequence of theEXP manipulation instead of the reduction in WASO.

General conclusions

The current study represents the first evidence of a directconsequence of the administration of an inactive substancepresented as beneficial for sleep on PSG measures of sleepcontinuity and on quantitative EEG markers of sleep pro-pensity. Moreover, something akin to a placebo responsewas found associated with regionally specific changes inbrain function.

It has recently been shown that knowledge of achievablerecovery sleep time in a protocol of sleep deprivation in-fluences SWS amount (Price et al. 2002). Moreover, psy-chological factors, like the perception of having a difficultnext day, is associated with a decreased SWS amount(Kecklund and Akerstedt 2004) and delta power density(Hall et al. 2000). As stated by Price et al. (2002), thesefindings raise provocative questions regarding a possiblerole for cognition and expectation in sleep physiology. Ourresults strengthen this suggestion and open new insightsinto the possibility of developing new methods, not neces-sarily functionally equivalent to the active drug response,but for treating sleep disorders.

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