NREM sleep alterations in narcolepsy/cataplexy

NREM sleep alterations in narcolepsy/cataplexy

Raffaele Ferria,*, Silvia Mianoa, Oliviero Brunib, Jitka Vankovac, Sona Nevsimalovac,

Stefano Vandid, Pasquale Montagnad, Luigi Ferini-Strambie, Giuseppe Plazzid

aDepartment of Neurology I.C., Sleep Research Centre, Oasi Institute (IRCCS), via Conte Ruggero, 73, Troina, Enna 94018, ItalybCentre for Pediatric Sleep Disorders, Department of Developmental Neurology and Psychiatry, University of Rome “La Sapienza”, Rome, Italy

cDepartment of Neurology, 1st Medical Faculty, Charles University, Prague, Czech RepublicdDepartment of Neurological Sciences, University of Bologna, Bologna, Italy

eDepartment of Neurology, Sleep Disorders Center, H San Raffaele Scientific Institute, Universita Vita-Salute San Raffaele, Milan, Italy

Accepted 4 August 2005

Abstract

Objective: NREM sleep patterns of narcoleptic patients with cataplexy were studied, focusing on their sleep ‘microstructure’, by analyzing

the cyclic alternating pattern (CAP).

Methods: Forty-nine HLA DQB1*0602-positive patients with narcolepsy/cataplexy (32 men and 17 women, aged 18–46 years) were

included together with 37 age-matched normal controls. Each subject underwent one polysomnographic night recording after an adaptation

night. Sleep stages were scored following standard criteria and CAP A phases were detected and classified into 3 subtypes (A1, A2, and A3).

Power spectra for frequencies between 0.5 and 25 Hz were obtained for each CAP condition, separately in sleep stage 2 and SWS.

Results: Narcoleptic patients displayed reduced total CAP rate. A selective reduction in the number of A1 subtypes/hour and a reduced A3

index were found in narcoleptics who had also a smaller average number of CAP sequences. Narcoleptic patients had higher power spectra

for fast frequencies mostly during SWS, while REM sleep power spectra showed significantly higher power density for frequency bins

0.5–1.5, 8.5–9.5, and 17.5–25 Hz. Similarly, CAP A1 subtypes and NCAP epochs during SWS displayed significantly higher power density

for fast frequency bins.

Conclusions: The main finding of this study is that the occurrence of the A1 CAP subtypes is impaired during NREM sleep in narcoleptic

patients. Thus, narcolepsy seems to be accompanied not only by alterations of REM but also NREM sleep which is subtly but significantly

impaired, as reflected by CAP and the corresponding EEG spectral analysis.

Significance: Our findings might indicate that in narcolepsy very-slow oscillation processes less effective than normal might be present, with

a subtly impaired capability of grouping the other sleep EEG activities; this aspect deserves further insight in order to obtain a better

understanding of its functional meaning.

q 2005 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Keywords: Narcolepsy; NREM sleep; Cyclic alternating pattern; EEG spectral analysis; Sleep microstructure

1. Introduction

Narcolepsy with cataplexy is a homogeneous (Sturze-

negger and Bassetti, 2004), disabling neurological disease

linked to the HLA-DQB1*0602 haplotype (Mignot et al.,

1994), affecting approximately one in 2000 individuals. It

is characterized by excessive daytime sleepiness (EDS),

1388-2457/$30.00 q 2005 International Federation of Clinical Neurophysiology.

doi:10.1016/j.clinph.2005.08.004

* Corresponding author. Tel.: C39 0935 653966; fax: C39 0935 936694.

E-mail address: [email protected] (R. Ferri).

cataplexy, sleep paralysis, hypnagogic hallucinations, and

disturbed nocturnal sleep (American Academy of Sleep

Medicine, 2001) and is related to a severe orexin

deficiency (hypocretin) (Dauvilliers et al., 2003; Mignot

et al., 2002; Nishino et al., 2000; Ripley et al., 2001). An

autoimmune mechanism has been implicated on the basis

of the strong association with the HLA-DQB1*0602

(Mignot et al., 1995). This was recently supported by

pathological findings and evidence of functional cholin-

ergic autoantibodies in the serum of narcolepsy patients

(Smith et al., 2004).

Clinical Neurophysiology 116 (2005) 2675–2684

www.elsevier.com/locate/clinph

Published by Elsevier Ireland Ltd. All rights reserved.

R. Ferri et al. / Clinical Neurophysiology 116 (2005) 2675–26842676

Hypocretin deficiency accounts for REM sleep abnorm-

alities, sleep onset REM periods and dissociated REM sleep

manifestations of cataplexy in experimental animals

(Bourgin et al., 2000; Burlet et al., 2002; Hungs and

Mignot, 2001), but also for non-rapid eye movement

(NREM) sleep abnormalities (Mochizuki et al., 2004).

This paper addresses the NREM sleep patterns of adult

and young adult narcoleptic patients with cataplexy,

focusing not only on conventional sleep parameters, but

also on sleep ‘microstructure’ by analysng the cyclic

alternating pattern (CAP) (Terzano et al., 1985, 1988).

2. Subjects and methods

2.1. Subjects

Forty-nine patients with narcolepsy (32 men with mean

age 30.1 years, SD 6.53, and 17 women with mean age 26.2

years, SD 4.85) were included in this study. The diagnosis

was based on clinical and laboratory criteria. All patients

had at least two sleep onset REM-sleep episodes upon the

multiple sleep latency test (MSLT), cataplexy and EDS,

reflected by a mean sleep latency at the MSLT of 5 min or

less, and all had the human leukocyte antigen (HLA)

DQB1*0602. None of the patients was taking drugs at the

time of recording.

Thirty-seven normal subjects (14 men with mean age

29.0 years, SD 4.12, and 23 women with mean age 28.8

years, SD 8.50) served as a control group. None had any

physical, neurological or psychiatric disorder or history of

sleep problems and none was taking medication at the time

of recording. The multifactor ANOVA of age per gender

and group did not disclose significant differences between

the 4 subgroups of subjects selected.

All patients and subjects gave their informed consent

according to the Declaration of Helsinki and the study was

approved by the Ethics Committee of the Oasi Institute

(Troina, Italy).

2.2. Polygraphic sleep recording

Each subject underwent one polysomnographic night

recording after an adaptation night, carried out in a sleep

laboratory with controlled sound (noise level to a maximum

of 30 dB). Subjects were not allowed to have drinks

containing caffeine during the afternoon preceding the

recording. Light-out time was based on the individual

habitual bed time and ranged between 09:30 and 11:30 p.m.;

subjects were allowed to sleep until spontaneous awakening

in the morning.

The following parameters were included in the poly-

somnographic study: EEG (at least 3 channels, one frontal,

one central and one occipital, referred to the contralateral

earlobe); electrooculogram (electrodes placed 1 cm above

the right outer cantus and 1 cm below the left outer cantus

and referred to A1), electromyogram (EMG) of the

submentalis muscle, EMG of the right and left tibialis

anterior muscle, and ECG (one derivation). Sleep signals

were sampled at 128 or 256 Hz and stored on hard disk in

European data format (EDF, see Kemp et al., 1992 for

details) for further analysis. EEG signals in particular were

digitally bandpass filtered at 0.1–50 Hz, 12-bit A/D

precision.

2.3. Sleep scoring

Sleep stages were scored following standard criteria

(Rechtschaffen and Kales, 1968) on 30-s epochs. Sub-

sequently, each CAP A phase was detected in each

recording on the C3/A2 or C4/A1 derivation, based on

the availability in the polysomnographic recording and on

the absence of long periods with artifacts; the side of this

EEG channel should not influence the detection of CAP

because CAP components have been shown to map

symmetrically over the scalp (Ferri et al., 2005b). All

CAP phases during NREM sleep were detected and

classified into 3 subtypes (A1, A2, and A3) according to

Terzano et al. (2001). As an example, Fig. 1 shows one

example of the different CAP A phases and the average

spectra obtained from these phases by means of a method

similar to that described below.

CAP was detected by the sleep analysis software

Hypnolab 1.2 (SWS Soft, Italy) which allows computer-

assisted detection of CAP A phase subtypes. With this

software, detection is performed by means of a human-

supervised automatic approach controlled by the scorer. The

performances of this system have been evaluated and

validated (Ferri et al., 2005a), but for this study the scorer

visually edited the detections proposed by the automatic

analysis, before the computation of the various CAP

parameters which were automatically generated by the

same software and used for statistical analysis.

2.4. Selection of EEG mini-epochs and power spectra

computation

The same channel used for the detection of CAP A

phases (C3/A2 or C4/A1), in each subject was divided into

two-second mini-epochs; as an example, a sleep recording

lasting 8 h was divided into 14,400 mini-epochs (8 h!60 min!60 s/2Z14,400). Each mini-epoch was assigned to

a sleep stage based on the sleep scoring previously

performed, for the analysis of power spectra of the different

sleep stages. Afterwards, only mini-epochs from sleep stage

2 and sleep stages 3 or 4 (SWS) were considered to assign

them to a CAP condition (based on the CAP detection

carried out previously); in particular, the following CAP

conditions were assigned: A1, A2, A3, and NCAP.

Additionally, CAP B phases were also indicated as B1 (B

phase following A1), B2 (B phase following A2) and B3

(B phase following A1). Only mini-epochs which

Fig. 1. Examples of the different CAP A phases from a normal control subject and the average spectra obtained from these phases by means of a method similar

to that described in this paper.

R. Ferri et al. / Clinical Neurophysiology 116 (2005) 2675–2684 2677

overlapped for more than 1 s with the same CAP condition

(A1, A2, A3, B1, B2, B3, and NCAP) were used for this

analysis.

Power spectra were calculated for each mini-epoch using

the sleep analysis software Hypnolab 1.2 (SWS Soft, Italy)

after Welch windowing (wnZ1K((n1/2(NK1))/1/2(NC1))2) to minimize the truncation error and reduce spectral

leakage by suppressing sidelobes (Press et al., 1989) by

means of the Fast Fourier Transform (Cooley and Tukey,

1965). The power spectrum was calculated for frequencies

between 0.5 and 25 Hz with a frequency step of 0.5 Hz.

Average spectra were obtained for each CAP condition,

separately in sleep stage 2 and SWS, for each subject.

2.5. Statistical analysis

The comparison between sleep staging and CAP

parameters obtained in normal controls and narcoleptic

patients was carried out by means of the multifactor

ANOVA, with group (controls/narcoleptic patients) and

gender as categorical predictors. Post hoc comparisons

were carried out with the Fisher LSD test, which is

equivalent to the Student’s t test and can be used to

determine the significant differences between group

means in an analysis of variance setting (Winer et al.,

1991).

The comparison between the power spectra of the

different CAP subtypes and NCAP periods during sleep

stage 2 or SWS was carried out by means of the Student’s t

test for unpaired data sets, which was computed for each

frequency bin in the spectra. In this case, in consideration of

the fact that multiple comparisons were carried out in each

analysis, the Bonferroni adjustment (Bland and Altman,

1995) was performed and differences were considered as

statistically significant at p!0.05/4Z0.0125 (number of

comparisons in each analysis).

The commercially available Statistica software package

(StatSoft, Inc., 2001. Statistica data analysis software

system, version 6. www.statsoft.com) was used for

statistical analysis.

Table 1

Comparison between the sleep staging parameters obtained in normal controls and narcoleptic patients

Controls Narcoleptic patients ANOVA Post hoc

Mean SD Mean SD Group, p! Gender, p! Controls vs.

narcoleptics,

p!

TIB, min 443.0 52.65 499.5 80.99 0.0002 NS 0.0004

SPT, min 426.5 54.55 485.9 78.26 0.0001 NS 0.0002

TST, min 409.9 54.52 422.5 87.52 NS 0.0082 –

SOL, min 12.9 11.74 8.4 6.35 0.0044 0.0119 0.026

FRL, min 81.6 50.39 17.1 31.95 0.0001 NS 0.00001

SS, h 11.1 2.75 12.8 3.71 0.0299 NS 0.025

AWN, h 1.6 1.18 3.9 1.85 0.0001 0.0256 0.00001

MT, h 1.3 0.70 1.2 1.02 NS NS –

SE, % 92.5 5.06 84.7 12.11 0.0037 0.0262 0.0004

WASO, % 3.9 3.60 13.0 12.04 0.0003 NS 0.00003

S1, % 1.6 1.75 3.7 3.18 0.0012 NS 0.0008

S2, % 46.1 7.15 36.6 11.26 0.0001 NS 0.00003

SWS, % 25.5 7.33 19.7 7.90 0.0018 NS 0.001

REM, % 22.9 5.14 27.0 8.06 0.0037 NS 0.01

TIB: time in bed; SPT: sleep period time; TST: total sleep time; SOL: sleep onset latency; FRL: first REM latency; SS, h: stage shifts per hour; AWN, h:

awakenings per hour; MT, h: movement time events per hour; SE: sleep efficiency; WASO: wakefulness after sleep onset; S1, S2: sleep stages 1 and 2; SWS:

slow-wave sleep; REM: rapid eye movement sleep.

R. Ferri et al. / Clinical Neurophysiology 116 (2005) 2675–26842678

3. Results

The ANOVA of the sleep staging parameters obtained in

the 4 subgroups of subjects studied showed a largely

significant effect of the group factor on almost all items

analyzed while a smaller significant effect was found for

gender on only 4 items (TST, SOL, AWN/h, and SE%—see

Table 1 for details). Our interest was focused on the

differences between the two diagnostic group and the post

hoc analysis was then performed only for this comparison.

The comparison between the sleep staging parameters

(Table 1) displayed longer TIB and SPT in narcoleptic

patients, whereas TST did not show significant differences.

Consequently, narcoleptic patients showed significantly

lower values of SE. Sleep onset latency and first REM

latency were both significantly shorter in the patient group,

Fig. 2. Examples of the hypnogram obtained in one patient with narcolepsy (up

indicated with a small vertical bar overimposed to the hypnogram. Also CAP sequ

S2, S3, and S4: sleep stages 1, 2, 3, and 4; REM: REM sleep.

the number of awakenings/h, the percentage of WASO, and

that of sleep stage 1 and REM were significantly higher,

while the percentages of sleep stage 2 and SWS were

significantly reduced in narcoleptic patients.

Fig. 2 shows two examples of the hypnogram obtained in

one patient with narcolepsy (upper panel) and in a normal

control. This figure shows the general tendency for patients

to show a lower number of CAP A phases.

The ANOVA of the CAP parameters obtained in the 4

subgroups of subjects studied showed a largely significant

effect of the group factor on many items analyzed while no

significant effect was found for gender (Table 2). The

comparison between CAP parameters (Table 2) from

controls and narcoleptic patients disclosed significantly

reduced total CAP rate (i.e. the percentage of NREM sleep

occupied by CAP sequences) in our patients with

per panel) and in a normal control. The occurrence of each CAP phase is

ences are indicated on the bottom of each graph. MT: movement time; S1,

Table 2

Comparison between the CAP parameters obtained in normal controls and narcoleptic patients

Controls Narcoleptic patients ANOVA Post hoc

Mean SD Mean SD Group, p! Gender, p! Controls vs. nar-

coleptics, p!

CAP rate, % 34.8 9.14 27.6 13.38 0.0055 NS 0.0064

CAP rate S1, % 7.7 10.64 6.1 7.87 NS NS –

CAP rate S2, % 22.3 9.32 17.4 11.87 0.0300 NS 0.043

CAP rate SWS, % 59.9 18.60 50.8 21.26 0.0450 NS 0.041

A1, % 81.5 7.32 75.4 9.78 0.0025 NS 0.0022

A2, % 9.2 4.08 12.1 6.15 0.0065 NS 0.016

A3, % 9.3 4.83 12.5 7.17 0.0380 NS 0.022

A1 index, n, h 38.0 11.57 29.5 14.97 0.0055 NS 0.005

A2 index, n, h 3.9 2.21 4.1 3.22 NS NS –

A3 index, n, h 3.3 2.09 2.3 1.73 0.0150 NS 0.021

A1 mean duration, s 8.1 1.94 8.0 1.50 NS NS –

A2 mean duration, s 11.2 2.11 12.0 3.97 NS NS –

A3 mean duration, s 15.4 2.92 13.0 3.09 0.0005 NS 0.0004

B mean duration, s 23.2 2.36 24.1 3.26 NS NS –

Cycle mean duration, s 32.3 1.93 33.2 3.32 NS NS –

Isolated A phases 54.1 13.87 57.7 17.88 NS NS –

CAP sequence mean

duration, s

225.0 72.91 207.4 75.55 NS NS –

Number of CAP

sequences

30.1 7.61 22.9 9.33 0.0007 NS 0.0003

R. Ferri et al. / Clinical Neurophysiology 116 (2005) 2675–2684 2679

narcolepsy, because of its reduction during sleep stage 2 and

SWS. The relative proportion of the different CAP subtypes

was also different in our patients, because of the reduction of

the percentage of A1 subtypes and the increase in A2 and A3

subtypes. This disproportion was due to a selective

significant reduction in the number of A1 subtypes/h (A1

index) and, to a lesser extent, a reduction in A3 index. As far

as the duration of these subtypes was concerned, only A3

CAP phases showed a slightly shorter duration in narcoleptic

patients. Finally, a significant difference was also found for

the average number of CAP sequences which was smaller in

narcoleptic patients than in controls.

The comparison between the EEG sleep power spectra of

narcoleptic patients versus controls showed overall higher

power density in narcolepsy (Fig. 3); however, this

difference was not statistically significant during sleep

stages 1 and 2. Narcoleptic patients had significantly higher

EEG power spectrum for frequency bins from 19.5 to

25.0 Hz in SWS and for frequency bins from 0.5 to 1.5, from

8.5 to 9.5, and from 17.5 to 25 Hz during REM sleep.

During NREM sleep stage 2 (Fig. 4). All CAP subtypes

during sleep stage 2 showed a higher power density

spectrum in narcoleptic patients; however, this difference

was not statistically significant for the CAP A1 subtype. The

power spectrum of narcoleptic patients was higher than that

of controls for frequency bins from 0.5 to 1.5 Hz, during

CAP A2 subtypes, and for frequency bins from 0.5 to 4.0 Hz

during CAP A3 subtypes. Also in NCAP narcoleptic

patients showed a higher power density for all frequency

bins, without statistical significance.

Finally, the comparison between the spectra of the

different CAP subtypes and NCAP periods during SWS

(Fig. 5) disclosed a significantly higher power spectrum for

CAP A1 (frequency bins from 19.5 to 25 Hz) and for CAP

A3 (frequency bins from 5.5 to 18.5 Hz) subtypes in

narcoleptic patients; while no statistically significant

differences were found for CAP A2 subtype power spectra.

In NCAP, spectra of narcoleptic patients showed a power

density significantly higher than that of controls for

frequency bins from 17.5 to 25 Hz.

4. Discussion

Our study shows that NREM sleep is also impaired in

narcoleptic patients. While our patients’ sleep structure

changes overlapped with previous data, NREM sleep

microstructure, as reflected by the CAP changes, was

significantly impaired. The sleep structure changes found in

our narcoleptic patients were those expected. In fact,

DQB1*0602-positive narcoleptic patients show a reduced

REM latency and sleep efficiency, and increased WASO

and stage 1, also in comparison to DQB1*0602-negative

narcoleptics (Hong et al., 2000). Our narcoleptic patients, all

DQB1*0602-positive, also shared other features common to

narcolepsy, such as reduced sleep stage 2 and SWS and

increased amount of REM sleep (Mukai et al., 2003).

The new finding of our study was a reduced amount of

CAP in DQB1*0602-positive narcoleptic patients. CAP is

composed of different transient events indicated as subtypes

A1, A2 and A3 (Terzano et al., 2001) which functionally are

thought to translate a condition of sustained arousal

instability oscillating between greater (phase A) and lesser

(phase B) arousal levels. Among the different subtypes of

Fig. 3. Mean all-night EEG power spectra for the different sleep stages. Left: absolute spectra–normal controls (dashed line), narcoleptic patients (continuous

line); right: relative spectra; each frequency bin of the different sleep stages of narcoleptic patients is expressed as a percentage of the corresponding bin of the

control spectra (100%). The black bar at the bottom of the right panels indicates the frequency bins in which the absolute power density of the two average

spectra differed significantly ( p!0.0125; Bonferroni-adjusted 2-tailed unpaired t tests).

R. Ferri et al. / Clinical Neurophysiology 116 (2005) 2675–26842680

the CAP A phases, the most common is the A1

characterized by sequences of K-complexes or delta bursts

in NREM sleep stages, associated with mild or trivial

polygraphic variations and activation of somatic and

autonomic systems (Terzano et al., 2001; Sforza et al.,

2000). This subtype accounts for nearly 90% of all CAP A

phases during normal sleep, occurring approximately

200–400 times per night depending on the age of the

subject (Bruni et al., 2002, 2005; Parrino et al., 1998). Our

results indicate that the occurrence of this CAP component

is impaired during NREM sleep in narcoleptic patients.

Thus, narcolepsy is accompanied not only by alterations of

REM but also NREM sleep which is subtly but significantly,

impaired, confirming a modified slow-wave activity during

NREM sleep organization (Ferri et al., 1999; Mukai et al.,

2003; Nobili et al., 1995; Tafti et al., 1992).

Fig. 4. Mean all-night EEG power spectra for the different CAP subtypes and NCAP during sleep stage 2. Left: absolute spectra–normal controls (dashed line),

narcoleptic patients (continuous line); right: relative spectra; each frequency bin of the different CAP subtypes of narcoleptic patients is expressed as a

percentage of the corresponding bin of the control spectra (100%). The black bar at the bottom of the right panels indicates the frequency bins in which the

absolute power density of the two average spectra differed significantly ( p!0.0125; Bonferroni-adjusted 2-tailed unpaired t tests).

R. Ferri et al. / Clinical Neurophysiology 116 (2005) 2675–2684 2681

The slow-wave activity during NREM sleep has been

indicated as a crucial component of the recently hypoth-

esized synaptic downscaling during sleep, probably import-

ant for cognitive processing (Huber et al., 2004; Massimini et

al., 2004; Tononi and Cirelli, 2003). In this respect, recent

studies suggest that neuropsychological impairments in

narcolepsy may include memory and attention deficits due

to possible alterations in cognitive preattentive and attentive

processing associated with altered functioning of the

prefrontal cortex in these patients (Naumann et al., 2001).

The slow-wave component of the A1 CAP subtypes has been

shown to map over the anterior areas of the scalp and is

probably generated by the frontal midline cortex (Ferri et al.,

2005b). All these findings may indicate a direct role of

disturbed sleep microstructure, as shown by the CAP changes

found in this study, in the psychophysiological basis of

Fig. 5. Mean all-night EEG power spectra for the different CAP subtypes and NCAP during SWS. Left: absolute spectra–normal controls (dashed line),

narcoleptic patients (continuous line); right: relative spectra, each frequency bin of the different CAP subtypes of narcoleptic patients is expressed as a

percentage of the corresponding bin of the control spectra (100%). The black bar at the bottom of the right panels indicates the frequency bins in which the

absolute power density of the two average spectra differed significantly ( p!0.0125; Bonferroni-adjusted 2-tailed unpaired t tests).

R. Ferri et al. / Clinical Neurophysiology 116 (2005) 2675–26842682

cognitive alterations in narcolepsy determined not only by

impaired diurnal functioning due to excessive somnolence

and impaired attentive capabilities (Hood and Bruck, 1996;

Rieger et al., 2003; Schulz and Wilde-Frenz, 1995).

The alternation between sleep and wakefulness seems to

be regulated by multiple arousal systems and each of them

seems to play a specific role in waking and sleep. During

SWS, they are submitted to an inhibitory influence arising

from particular GABAergic neurons co-distributed with

many neurons of the arousal systems (Jones, 2003). Unlike

norepinephrine and acetylcholine, Orexin seems only to

affect the nonspecific thalamocortical projection neurons,

with no effect on the specific sensory relay thalamic

neurons. Orexin may thus act in the thalamus to promote

wakefulness by exciting neurons of the nonspecific

thalamocortical projection system which stimulate and

R. Ferri et al. / Clinical Neurophysiology 116 (2005) 2675–2684 2683

maintain cortical activation via widespread projections to

the cerebral cortex (Bayer et al., 2002). Also in the cortex,

orexin has been shown to excite a specific subset of cortical

neurons which may also be involved in promoting wide-

spread cortical activation via corticocortical projections

(Bayer et al., 2004).

From the CAP standpoint, transient slow-wave activity

bursts (A1 subtypes) are considered cortical activation

events also accompanied by autonomic subcortical changes

(Ferini-Strambi et al., 2000; Ferri et al., 2000b; Sforza et al.,

2000). In narcolepsy, orexin deficiency may reflect in

reduced activity of cortical arousal regions, resulting in the

reducted CAP rate encountered in NREM sleep.

Besides the alterations of the visually derived CAP

parameters, we also used spectral analysis to quantitate the

EEG abnormalities during sleep in our narcoleptic patients.

Considering the classical sleep stages, power spectra of

narcoleptic patients were significantly higher mostly for

frequencies between 17.5–19.0 and 25.0 Hz in NREM sleep

stage 2 and SWS; during REM sleep power spectra of

narcoleptic patients showed significantly higher power

density for frequency bins from 0.5 to 1.5, from 8.5 to

9.5, and from 17.5 to 25 Hz. Since an increase in fast

frequencies (15.5–34.5 Hz) has been reported in normal

subjects during REM sleep (Ferri et al., 2000a, 2001, 2002),

our results might indicate a ‘leakage’ of EEG frequencies

typical of normal REM sleep into NREM sleep in

narcoleptic patients, in addition to the abnormally higher

power in a larger spectral band during REM sleep. These

results are only in partial agreement with those of Mukai et

al. (2003), but they pooled all EEG epochs in NREM sleep

and studied only 8 patients.

The presence of an abnormally high level of fast EEG

frequencies also affects the spectra of the CAP A1 subtypes

and NCAP sleep mostly during SWS. This seems to indicate

that CAP A1 subtypes are not only reduced in number in

narcolepsy but are also significantly different from normal

for an abnormal content in fast frequencies. The clear and

significant intrusion of fast EEG frequencies during CAP

and NCAP NREM sleep might indicate the persistence of

neurophysiological mechanisms typical of REM sleep

during these stages in narcoleptic patients. Finally, CAP

A2 and A3 subtypes of our narcoleptic subjects also showed

alterations in their spectra difficult to interpret at this stage.

There are at least 3 distinct delta sleep oscillations: a

very-slow (!1 Hz) cortically-generated oscillation (Acher-

mann and Borbely, 1997; Amzica and Steriade, 1997;

Steriade et al., 1993a,b), a clock-like thalamic oscillation

(1–4 Hz), and a cortical oscillation (1–4 Hz). The very-slow

(!1 Hz) oscillation seems to be reflected in the EEG as

rhythmic sequences of surface-negative waves (associated

with hyperpolarizations of deeply-lying neurons) and

surface-positive K-complexes (representing excitation in

large pools of cortical neurons). The very-slow oscillation is

believed to have the ability to trigger and to group the two

delta (1–4 Hz) oscillations (Amzica and Steriade, 1998;

Steriade and Amzica, 1998) and thalamically-generated

spindles and beta activities (Molle et al., 2002). We have

recently shown that A components of CAP might

correspond to periods in which the very-slow delta rhythm

of sleep groups a range of different EEG activities including

slow waves, and the sigma and beta bands, while the B

phase of CAP might correspond to a period in which these

activities are quiescent or inhibited (Ferri et al., 2005c). The

results of the present study might indicate that this

mechanism can be subtly altered in narcolepsy and that

very-slow oscillation processes less effective than normal

might be present, with an impaired capability of grouping

the other faster EEG activities indicated above.

In conclusion, our findings show that not only REM but

also NREM sleep is significantly altered in narcolepsy. The

neurophysiological alterations of NREM sleep in narco-

lepsy are significant, add new information on the sleep

neurophysiology of this clinical condition and deserve

further insight in order to obtain a better understanding of

their functional meaning.

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