Are individuals with paradoxical insomnia more hyperaroused than individuals with psychophysiological insomnia? Event-related potentials measures at the peri-onset of sleep

International Journal of Psychophysiology 81 (2011) 177–190

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International Journal of Psychophysiology j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / i j p s yc h o

Are individuals with paradoxical insomnia more hyperaroused than individuals with psychophysiological insomnia? Event-related potentials measures at the peri-onset of sleep Isabelle Turcotte, Geneviève St-Jean, Célyne H. Bastien ⁎ École de psychologie, Université Laval, Québec, Québec, Canada G1K 7P4 Laboratoire de neurosciences comportementales humaines, Centre de recherche Université Laval- Robert Giffard, 2525 de la Canardière, Québec, Québec, Canada G1J 2G3

a r t i c l e

i n f o

Article history: Received 25 November 2010 Received in revised form 8 June 2011 Accepted 11 June 2011 Available online 25 June 2011 Keywords: Insomnia Information processing Arousal Inhibition Event-related potentials wPN

a b s t r a c t Preliminary QEEG studies suggest that individuals with paradoxical insomnia (Para-I) display higher cortical arousal than those with psychophysiological insomnia (Psy-I). Lately, finer measures, such as event-related potentials, and especially the N1 and P2 components have been used to document arousal processes in individuals with insomnia. The objective of the present study was to further circumscribe arousal in Psy-I and Para-I using N1, P2 and the waking processing negativity (wPN). N1 and P2 were recorded in the evening, at sleep-onset and in early stage 2 sleep in 26 good sleepers, 26 Psy-I and 26 Para-I. An oddball paradigm was used and participants received the instruction to ignore all stimuli at all times. Three difference waves (wPNs) were computed to evaluate the transition from wakefulness to sleep onset, from sleep onset to sleep and from wakefulness to sleep. Results revealed that N1 was smaller during wakefulness and sleep onset for Psy-I, while it was larger for Para-I during these same times. P2 was smaller at sleep onset for Psy-I than for Para-I and GS, while P2 during wakefulness and stage 2 sleep was larger for Para-I than GS. WPNs revealed that Psy-I showed fewer changes in information processing, while Para-I showed larger changes between recording times. Psy-I appear to present an inability to inhibit information processing during sleep onset, while Para-I seem to present overall enhanced attentional processing that results in a greater need for inhibition. © 2011 Elsevier B.V. All rights reserved.

1. Introduction Recent epidemiological studies indicate that between 30 and 48% of adults complain of insomnia symptoms (Ohayon, 2002) while close to 10% suffer of an insomnia syndrome (severe and chronic insomnia complaints) (Morin et al., 2006). Many precipitating factors (Bastien et al., 2004) and maintaining factors (Morin and Espie, 2003) have been suggested as being linked to the appearance or perpetuation of the disorder. Nonetheless, the underlying cortical mechanisms associated with chronic insomnia are just beginning to be better understood (Bastien and Morin, 1998; Bastien et al., 2008; Devoto et al., 2005; Merica et al., 1998; Merica and Gaillard, 1992; Perlis et al., 2001; Sforza and Haba-Rubio, 2006). This study is one of the very few that actually measures the extent of information processing of external stimuli in different types of chronic insomnia during wakefulness, sleep onset and actual sleep.

⁎ Corresponding author at: École de psychologie, FAS-Local 1012, 2325, rue des Bibliothèques, Université Laval, Québec (Qc), CANADA G1V 0A6. Tel.: + 1 418 656 2131x8344; fax: + 1 418 656 3646. E-mail address: [email protected] (C.H. Bastien). 0167-8760/$ – see front matter © 2011 Elsevier B.V. All rights reserved. doi:10.1016/j.ijpsycho.2011.06.008

According to Edinger et al. (2004), individuals with psychophysiological (Psy-I) and paradoxical (Para-I) insomnia differ greatly regarding both objective and subjective sleep variables. The main feature of Psy-I is that they display conditioned sleep difficulty and/or heightened arousal in bed. For example, an inability to initiate sleep when wanted, sleeping better away from home, intrusive thoughts at night (mind racing), somatic tension, and a difficulty to relax in bed are reported. On the other hand, Para-I severely overestimate their sleep difficulties. Marked differences between subjective and objective sleep, more than 6 h of sleep on polysomnography (PSG) and a sleep efficiency N85% are often observed. Furthermore, ‘normal’ nights are rare, while sleepless nights and no naps are usually reported on the sleep diary. Power spectral analysis (PSA) differences in the EEG between good sleepers (GS) and individuals with insomnia are now well documented (Bastien and Morin, 1998; Merica and Gaillard, 1992; Merica et al., 1998; Krystal et al., 2002; Perlis et al., 2001). While traditional analyses of objective sleep (PSG) do not corroborate the severe sleep difficulty complaints of Para-I, PSA studies reveal that these individuals appear to display a perturbed microstructure of sleep compared to Psy-I (Edinger and Krystal, 2003; Krystal et al., 2002; Perlis et al., 2001; St-Jean and Bastien, 2008). In that regard, Perlis et al. (2001) have identified that during sleep, Para-I displayed greater Beta and Gamma

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activities (reflecting cortical arousal) than Psy-I. Subsequently, Krystal et al. (2002) have identified an absolute greater amplitude in Alpha and Beta activities in stages 2 and 4 of sleep in Para-I compared to Psy-I. These results indicate greater cortical activation in Para-I than in Psy-I, therefore supporting the neurocognitive model of insomnia (Perlis et al., 1997) that suggests that high frequency activity is a main feature of chronic insomnia that could interfere with sleep initiation as well as sleep maintenance. Furthermore, this increased cortical arousal would also lead to incompatible sleep activities such as enhanced sensory and information processing. However, inhibitory processes or the inability to de-arouse or disengage from active wake processing (Espie, 2002) that interferes with the normal initiation of sleep processes in individuals with insomnia was not taken into account in the previous PSA studies. Furthermore, participants did not specifically correspond to the criteria of Para-I as standardized research diagnostic criteria had not yet been established. As such, empirical evidence supporting deficits in cortical inhibition in insomnia individuals compared to GS are scarce, while the comparison of these processes between the different types of insomnia is non-existent. Event-related potentials (ERPs) are the electrical responses of the brain to external sensory stimuli or internal mental events that reflect how the brain “processes and classifies” stimuli. An external physical stimulus or internal psychological event elicits small amplitude changes in the EEG, therefore providing an excellent measure of the extent of information processing within the nervous system. The latency and amplitude of the successive positive and negative deflections following the onset of the stimulus are used to name the different components. As such, a negative component (“N1”), peaking at approximately 75 to 125 ms following the stimulus is followed by a positive component (“P2”), peaking at about 175 to 250 ms. N1 and P2 are often elicited in the so-called oddball paradigm in which a frequently occurring ‘standard’ stimulus is presented and at rare and unpredictable times, a feature of the standard stimulus is changed to form a ‘deviant’. Both the standard and deviant elicit N1 and P2 components. The N1 and P2 represent early sensory processing, although their amplitude is affected by both exogenous (e.g., stimulus characteristics) and endogenous (e.g., attention) factors (Kertesz and Cote, 2011). This “N1–P2” complex which is maximum in amplitude at the Cz site, is a measure of both sensory processing and the extent of attentional processing, since selective attention requires the processing of what is relevant (attended) but also the inhibition of processing of what is irrelevant (not attended). Attention allows individuals to become conscious of what is relevant, and it is this attention-related processing that must be inhibited during sleep onset in order for sleep to occur. Therefore, the transition from waking consciousness to sleeping (and in particular, non-REM) unconsciousness and the necessary inhibition of information processing in order to fall asleep is reflected by changes in ERPs. Several studies have now indicated that the amplitude of N1 following an auditory stimuli is very much reduced, while the amplitude of P2 is increased during sleep (Cote et al., 2002, Crowley et al., 2002, De Lugt et al., 1996). Those changes are thought to be due, in part, to the removal of a longlasting negative wave, called waking Processing Negativity (wPN), which occurs because of a disengagement of attention during the sleep onset period (Campbell and Colrain, 2002; Näätänen, 1990). The wPN is a separate and independent negative-going ERP component from N1 and P2 that represents the additional attention-related processing of information possible by the individual while awake. It is computed by subtracting sleep ERPs from waking ERPs. It reflects the variation in information processing due to wakefulness and more precisely, the extent of inhibition of information processing during sleep (Campbell et al., 1992). Beginning approximately 25 ms after stimulus onset, the long-lasting wPN overlaps and summates with both the N1 and P2 peaks causing them both to become more negative-going in the waking, attentive state. At sleep onset, with the loss of attention-related processing and the removal of the wPN, N1 is

much reduced but P2 appears to increase in amplitude. Thus, the wPN reflects the marked decrease in the ability to maintain attention to the external environment between the alert-waking and the drowsysleeping states (De Lugt et al., 1996). During sleep onset, it is critical in order for sleep to occur, that awareness of the external environment is inhibited. A possible problem for individuals with insomnia may be an inability to inhibit processing during sleep onset and within sleep. However, since it is impossible for individuals to respond verbally or behaviorally while they are sleeping, the study of information processing during the process of falling asleep and during sleep itself is very limited. ERPs represent an ideal technique to investigate the extent of information processing in insomnia participants during those times since the ERPs protocol used in sleep studies does not require any response from the individuals. If individuals with insomnia are unable to inhibit information processing, it would be expected that the changes from the waking ERPs to the sleeping one would be different from what is generally observed among GS. Although hyperarousal has already been investigated using the ERPs technique with insomnia individuals (Bastien et al., 2008; Devoto et al., 2005; Kertesz and Cote, 2011; Sforza and Haba-Rubio, 2006; Yang and Lo, 2007), the inability to inhibit information processing during sleep onset as well as during sleep itself remains to be clarified. The poor sleep experienced by insomnia individuals may be the result of an inability to inhibit external information processing of irrelevant stimulus during sleep onset and sleep and this enhanced information processing may result in hyperarousal. Devoto et al. (2005) suggested a state of hyperarousal in insomnia individuals compared to GS by using the P300 component amplitude as a measure of cortical arousal level. Both groups of participants received an oddball task in which they were required to detect a rare target tone by pressing a button, in a sequence of frequently occurring standard tones. Individuals with insomnia presented larger P300 amplitudes than GS 30 min prior to and following a subjective bad night of sleep. Sforza and Haba-Rubio (2006) measured the amplitude of N1, P2 and P300 to evaluate the pre-sleep to post-sleep variations in these ERPs in patients with sleep disorders. The authors did not observe any between group differences, from evening to morning, when insomnia individuals were compared to GS. On the other hand, Yang and Lo (2007) observed a larger N1 and a smaller P2 in individuals with insomnia than in GS during the first 5 min of continuous stage 2 sleep, supporting the hyperarousal hypothesis. Recently, our research group (Bastien et al., 2008) recorded ERPs over multiple nights during wakefulness and sleep onset as an oddball paradigm was delivered to Psy-I and GS during the 3rd and 4th nights in the sleep laboratory (in the evening and upon awakening), with the addition of sleep-onset recordings on the 4th night. All participants received the explicit directive to ignore all auditory stimuli. During wakefulness, the amplitude of N1 was larger for Psy-I compared to GS in the evening (on evening 4, following the standard tone, at Pz only) and the morning after evening 4 (following the standard tones, at Cz and Pz). On the other hand, the amplitude of N1 recorded at sleep onset and following standard stimuli was smaller for Psy-I than GS (at Cz only). Finally, the amplitude of P2 following deviant tones was greater in Psy-I than in GS at sleep onset (at Pz only). More recently, Kertesz and Cote (2011) investigated ERPs at sleep onset in Psy-I presenting sleep onset complaints specifically. Participants were administered an oddball task while awake in the morning and evening, and during repeated sleep-onset attempts. As they fell asleep, they were asked to signal detection of a higher pitch target tone. As previously reported by Yang and Lo (2007), the authors observed a smaller P2 amplitude following the standard stimuli for patients with insomnia compared to GS, when participants were instructed to respond to targets. These previous ERPs studies indicate that information processing seems to be altered in insomnia individuals; however, all those studies

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were limited to Psy-I and did not investigate information processing in Para-I. The oddball paradigm protocol permits to elicit N1 and P2 by both standard and deviant stimuli regardless of the nature of the instructions given to participants (to ignore or to attend to the auditory stimuli). Therefore, we used the oddball paradigm protocol to compare Psy-I and Para-I with GS during wakefulness, sleep onset and sleep. In addition, we measured the waking Processing Negativity (wPN) in order to compare the transition from wakefulness to sleep in Psy-I and Para-I in opposition to GS. To the best of our knowledge, no previous study has used the wPN to examine the difference in the extent of information processing during the transition from wakefulness to sleep in insomnia individuals. The objectives of the present study were, first, to measure the extent of information processing using the N1 and P2 waves in response to both standard and deviant stimuli during wakefulness (evening), sleep-onset and sleep (early stage 2) in individuals with chronic insomnia, Psy-I and Para-I, in comparison to GS. Furthermore, cortical activity was assessed as irrelevant stimuli were presented, so a non-response oddball paradigm was employed because the instruction to respond may interfere with the natural sleep onset process and responses are not possible in late stage 1 and stage 2 sleep. Previous PSA and ERPs studies revealed that cortical hyperarousal may be present at the peri-onset of sleep in insomnia individuals, and that Para-I appear to show even more signs of cortical arousal than Psy-I. However, the inability to fall asleep and to maintain sleep may also come from an inability to inhibit external information processing at the peri-onset of sleep. Therefore, the general hypotheses were that 1) both types of individuals with chronic insomnia (Psy-I and Para-I) will show more signs of cortical arousal and less information processing inhibition (larger N1 and a smaller P2 to standard and deviant stimuli) than GS; and 2) Para-I will show even more signs of arousal and less information processing inhibition (larger N1 and a smaller P2 to standard and deviant stimuli) than Psy-I. The second objective was to compare the wPN between the 3 groups in order to assess the changes in ERPs amplitudes from wakefulness to early stage 2 and to evaluate if these changes remain the same in Psy-I, Para-I and GS. We hypothesized that 1) both types of individuals with chronic insomnia (Psy-I and Para-I) will show fewer changes in N1 and P2 from wakefulness to sleep than GS; and 2) Para-I will show even less changes in the wPN than Psy-I since previous studies report greater cortical activation in Para-I than in Psy-I, and that this arousal appears to persist during sleep. In other words, there would be little difference in information processing between the waking and the sleeping states in insomnia individuals.

2. Methods

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2.2. Participants Participants were 78 adults, including 26 individuals suffering from chronic primary psychophysiological insomnia [i.e., 14 men; 43 years (9.00)], 26 individuals suffering from chronic primary paradoxical insomnia [i.e., 6 men; 40 years (9.00)], and 26 selfdefined good sleepers [i.e., 10 men; 37 years (9.00)]. The age range for all participants was 25 to 55 years. Participants had a mean education level of 15.0 years (SD = 3.0) and were predominantly married (61.5%). The majority of participants were employed (90.8%). The mean duration of insomnia was 10.3 years (SD = 8.1) for both insomnia groups. 2.2.1. Good sleepers (GS) Participants included in the GS group reported being satisfied with their sleep and a) did not have subjective complaints of sleep difficulties, b) did not meet diagnostic criteria for insomnia and c) did not use sleep-promoting medication. They also had to report a sleep efficiency of 85% or more in the sleep diaries as well as no sleep difficulty of a higher level then ‘mild’ on the ISI (Morin, 1993) (score less than 8 on severity scale). 2.2.2. Individuals with insomnia (INS) All participants suffering from insomnia were further divided into psychophysiological and paradoxical subgroups based on their PSG data and their sleep diaries obtained during their stay at the laboratory. For the purpose of this study, we decided to categorize participants in the appropriate subgroup if they met the diagnostic criteria for Night 2 or Night 3, since Night 1 was the adaptation night and they received auditory stimulations all through Night 4. Only two insomnia participants could not be categorized as psychophysiological or paradoxical since they did not meet the required criteria of either subgroup. Therefore, they were excluded from the study and only 26 participants were retained in each subgroup. 2.2.3. Psychophysiological insomnia participants (Psy-I) Individuals suffering from chronic psychophysiological insomnia met the following inclusion criteria: (a) presence of a subjective complaint of insomnia, defined as difficulty initiating (i.e., sleep-onset latency N30 min) and/or maintaining sleep (i.e., time awake after sleep-onset N30 min) present at least three nights per week; (b) insomnia duration of at least six months; (c) insomnia or its perceived consequences causing marked distress or significant impairment of occupational or social functioning; and (d) presence of a subjective complaint of at least one negative daytime consequence attributed to insomnia. These participants also corresponded to the criteria set forward by Edinger et al. (2004) for ‘psychophysiological’ insomnia.

2.1. Recruiting, screening and general procedure All participants were recruited through newspaper advertisements. Following a telephone interview, eligible participants were mailed questionnaires aimed at evaluating the presence of psychological symptoms (BDI; Beck et al., 1988b; BAI; Beck Anxiety Inventory; Beck et al., 1988a), sleep (two-weeks of daily sleep diaries) as well as severity of sleep disturbances (ISI; Insomnia Severity Index; Morin, 1993). Upon reception of questionnaires, prospective participants were invited for a clinical interview at the research center. Upon arrival, informed consent was obtained. The Structured Clinical Interview for DSM-IV (SCID-I; Spitzer et al., 1996) and the Insomnia Diagnostic Interview (IDI; Morin, 1993) were then administered. These evaluations were conducted respectively by a clinical psychologist and a sleep specialist. After the clinical evaluation, included participants were further invited to undergo four consecutive nights of PSG recordings at the sleep laboratory. Each participant received an honorarium for his or her participation in the study.

2.2.4. Paradoxical insomnia participants (Para-I) In addition to the mentioned chronic primary insomnia criteria, paradoxical insomnia participants had (a) a total sleep time of more than 6 h 30 min and a sleep efficiency greater than 85% on nocturnal PSG; (b) showed marked discrepancies between subjective and objective sleep measures (i.e. a difference of 60 min or more for total sleep time, or a difference of at least 15% between subjective and objective measures of sleep efficiency). The following observation was also common: complaint of severe sleep difficulties most of the time (sleepless nights on sleep diaries being an indicator of severe difficulties). These criteria for paradoxical insomnia categorization were derived from Edinger et al. (2004). The retained thresholds appeared reasonable in light of the previous literature regarding paradoxical insomnia. Exclusion criteria for all participants were: (a) presence of a significant current medical or neurological disorder that compromises sleep; (b) presence of a major psychopathology; (c) alcohol or drug

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abuse during the past year; (d) evidence of another sleep disorder such as sleep apnea (apnea-hypopnea index N15) or periodic limb movements during sleep (myoclonic index with arousal N15); (e) a score of 23 or higher on the BDI (Beck et al., 1988b); (f) use of psychotropic or other medications known to alter sleep; and (g) use of a sleep-promoting agent. For the participants with insomnia, the criteria are consistent with those of the DSM-IV (American Psychological Association, 1994) for chronic and primary insomnia. Participants in the insomnia group that used a sleep-promoting medication on occasional basis (twice a week or less often) were enrolled in the study after a two-week withdrawal period. 2.3. Material 2.3.1. Insomnia Diagnostic Interview (Morin, 1993) The IDI is conducted in a semi-structured format and assesses the presence of insomnia and potential contributing factors. It is designed to identify (a) the nature of the complaint, (b) the sleep–wake schedule, (c) insomnia severity, (d) daytime consequences, (e) the natural history of insomnia, (f) environmental factors, (g) medication use, (h) sleep hygiene factors, (i) the presence of other sleep disorders, (j) the patient's medical history and general health status, and (k) a functional analysis for antecedents, consequences, precipitating and perpetuating factors. 2.3.2. Sleep diary The Sleep diary (SD) (Morin, 1993) is a daily journal used to assess subjective sleep quality. The various sleep–wake parameters derived for this study were sleep-onset latency (SOL); wake after sleep-onset (WASO); total sleep time (TST); time in bed (TIB); and finally, sleep efficiency (SE), defined as the ratio of TST divided by TIB, expressed as a percentage. The SD is completed upon arising each morning for a 2-week baseline period in order to provide a stable index of sleep complaints (Morin, 1993). In addition, our participants completed the SD each morning upon awakening in the sleep laboratory. A mean was calculated for each of the derived variables.

on-going EEG (Gratton et al., 1983). Electrodes were referred to linked mastoids with a forehead ground and interelectrode impedance was maintained below 5 kΩ. In addition, respiration and tibialis EMG were monitored during the first night of PSG recording in order to rule out sleep apnea and periodic limb movements. Participants diagnosed with another sleep disorder were excluded and referred to an appropriate sleep specialist. A Grass Model 15A54 amplifier system (Astro-Med Inc., West Warwick, USA; gain 10,000; band pass 0.3– 100 Hz) was used. While PSG signals were digitized at a sampling rate of 512 Hz using commercial software product (Harmonie, Stellate System, Montreal, Canada), ERPs environment was controlled with the InstEP Systems™ (V4.2) using the same sampling rate. Sleep recordings were scored visually (Luna, Stellate System, Montreal, Canada) by qualified technicians according to standard criteria (Rechtschaffen and Kales, 1968) using 20-second epochs. Sleep staging was carried out using central and occipital EEG leads. Reliability checks were conducted by an independent scorer to insure a minimum of 85% inter-scorer agreement. In addition of being the screening night for sleep disorders other than insomnia, Night 1 constituted an adaptation night. Clinical sleep data were derived from Nights 2 and 3. Auditory stimuli were presented right before going to bed and 15 min after awakening on the 3rd and 4th PSG nights, as well as at sleep-onset and all night long on the 4th night. The present study reports data on wakefulness (evening), sleep-onset and sleep (early stage 2) ERPs recordings of Night 4 only. Objective measures of sleep included sleep onset latency (SOL) (defined as the interval from lights off with the intention to sleep to the first uninterrupted minute of stage 2), wake after sleep-onset (WASO), total sleep time (TST), sleep efficiency (SE), and proportion (%) as well as time spent (min) in stages 2, 3, 4 and rapid eye movement (REM). For ERPs classification purposes, the sleep onset period was defined as relaxed wakefulness (as subjects attempted to fall asleep) and stimulus presentation was halted upon the appearance of K-Complexes, a sign of definitive stage 2 sleep (Campbell and Colrain, 2002). 2.5. ERP protocol

2.3.3. Insomnia Severity Index The ISI (Morin, 1993) is a reliable and valid brief self-report instrument that yields a quantitative index of perceived insomnia severity (Bastien et al., 2001). The ISI comprises seven items targeting the severity of sleep disturbances, the satisfaction relative to sleep, the degree of impairment of daytime functioning caused by the sleep disturbances, the noticeability of impairment attributed to the sleep problem as well as the degree of distress and concern related to the sleep problem. Each item is rated on a 5-point Likert scale and the total score ranges from 0 to 28. A higher score reveals more severe insomnia. The ISI partly reflects the diagnostic criteria outlined in the DSM-IV (American Psychological Association, 1994). 2.4. Polysomnographic (PSG) and Event-Related Potentials (ERPs) recordings Participants spent four consecutive nights in the sleep laboratory. They were instructed to arrive at around 8:00 pm each night for electrode montage and preparation. Participants were asked to refrain from alcohol, drugs, excessive caffeine and nicotine before coming to the laboratory. Bedtime and time in bed were determined according to reported time on the SD. For all participants, lights-out was initiated after a bio-calibration, with no less than a fixed 8 h of PSG recordings. A standard PSG montage was used, including electroencephalographic (EEG; including C3, C4, O1, O2, Fz, Cz, Pz), electromyographic (EMG; chin) and electro-oculographic (EOG; left and right: supraorbital ridge of one eye and the infra-orbital ridge of the other) recordings. This placement allowed for the recording of horizontal and vertical eye movement artifacts and blinks to be subtracted from

For the pairing of individuals as well as for calibration purposes, each participant received an audiometric evaluation establishing normal hearing levels (15 dB ISO; 500, 1000, 2000 and 4000 Hz). Brief duration auditory stimuli were presented by ER-3A transducers through a 25 cm plastic tube and foam inserts were placed in the ear canal. The generation of auditory stimuli was controlled by the Presentation Software™ (Neurobehavioral Sciences). 2.5.1. Oddball The N1 and P2 waves were recorded with auditory stimuli consisting of standard and deviant tones. Standard stimuli had an intensity of 70 dB SPL; a duration of 50 ms, a rise-and-fall time of 2 ms, a frequency of 2000 Hz and a probability of .85. Deviant stimuli had an intensity of 90 dB SPL; a duration of 50 ms, a rise-and-fall time of 2 ms, a frequency of 1500 Hz and a probability of .15. The deviant stimulus varied in frequency, intensity and probability of occurrence. Because it was louder and rarer than the standard, it was expected to elicit larger N1 and P2 in the waking state. The interstimulus interval was kept constant at 2 s. The oddball paradigm consisted of 3 blocks of 180 auditory stimuli. One block lasted 6 min, for a total of about 18 min of stimulus presentation for the 3 blocks. For some participants, the sleep onset period did not permit the delivery of 3 full blocks of stimuli (shorter sleep onset latency). Nonetheless, at least one full block of auditory stimuli was delivered during the transition from wakefulness to sleep. Participants that received just one block of stimuli (135 standard tones and 45 deviant tones) during sleep onset still received a sufficient number of deviant tones. According to Picton et al. (2000), a minimum of 20 deviant tones is required in order to obtain a statistically stable average that is considered

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reliable and consistent. Time between blocks varied between 15 s to 2 min. Again, during the presentation of tones, participants were instructed to ignore the tones. While awake, participants were allowed to read a book/magazine during the presentation of the auditory stimuli. If excessive eye movements were displayed, the participants were instructed to stare at a fixed red line on the wall. 2.5.2. Data analysis Continuous EEG (Fz, Cz and Pz sites) was recorded and stored for off-line analysis. ERPs collected during wakefulness, sleep-onset and early stage 2 were averaged separately. Each ERP trial was binned according to stimulus category (standard and deviant) and then averaged accordingly. Sweeps of 550 ms were reconstructed with 50 ms prior to stimulus onset (baseline) and 500 ms post stimulus onset for the detection of ERPs. The amplitude and latency of N1 and P2 were measured for each block of sound presentation for each stimulus (standard and deviant) at each time period. N1 was defined as the most negative peak between 70 and 150 ms after stimulus-onset while P2 was defined as the most positive peak between 150 and 250 ms after stimulus-onset. Three wPN difference waves were computed: 1) the wPNa wave was measured by subtracting the sleep onset from the waking evoked potentials (wake– sleep onset), 2) the wPNb wave was measured by subtracting the stage 2 from sleep onset evoked potentials (sleep onset — stage 2) and 3) the wPNc wave was measured by subtracting the stage 2 from the waking evoked potentials (wake — stage 2). N1 and P2 data were scored at Cz, since all studied ERPs are usually maximal in amplitude at this site. Data were rejected if either the EEG or EOG exceeded ±100 μV, effectively removing artifacts resulting from large eye blinks and/or movements. Digital filtering was conducted with a band pass of 0.01–30 Hz for 12 dB. EOG correction/rejection was applied (Gratton et al., 1983). At sleeponset, any sweep containing high amplitude waves (e.g. vertex sharp waves), movement time or any sign of stage 2 sleep was excluded from further analysis and only artifact-free sweeps were included. In addition, trials containing K-complexes were removed from the analyses. All data were examined for outliers. 2.6. Statistical analyses One-way ANOVAs and Chi-square were used in order to compare the 3 groups on sociodemographic variables and sleep characteristics. Two mixed model ANOVAs including 2 within-subject factors (recording time, 3 levels; auditory stimuli, 2 levels) and one between-subject independent factor (group, 3 levels) were computed on measures of N1 and P2 (amplitude and latency). Post-hoc pairwise comparisons were also performed to identify significant differences between groups. In order to allow for multiple comparisons, the Bonferroni correction method was applied to post hoc analyses. When significant interactions were found, simple effects tests were performed. However, one major problem with the ANOVA procedure is that it is very conservative. Previous literature has consistently demonstrated changes in N1 and P2 from the waking to sleeping states. Thus, more liberal statistical procedures were also employed. Therefore, one-tailed t-tests were computed on the N1 and P2 amplitude and latency data in order to investigate between group differences. Finally, one-way ANOVAs were also computed on wPNa, wPNb and wPNc in order to assess the presence of any group differences. Follow up one-tailed t-tests were also run on wPNs.

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Table 1 Means and standard deviations of sociodemographic and clinical data for good sleepers (GS), individuals with psychophysiological insomnia (Psy-I) and individuals with paradoxical insomnia (Para-I).

Age (years) M Gender Female Male Insomnia duration M ISI M BDI M BAI M

GS

Psy-I

Para-I

n = 26

n = 26

n = 26

37.04 (9.04)

42.65 (8.53)

40.42 (9.04)

16 10 (months)

12 14

20 6

120.61 (99.14)

126.85 (97.45)

16.63 (3.20)

17.61 (2.92)

2.58ab (3.42)

7.35 (5.62)

6.95 (3.65)

1.85ab (2.62)

5.94 (5.00)

8.10 (6.88)

1.92

ab

(2.90)

Note: a) GS different from Psy-I, b) GS different from Para-I, c) Psy-I different from Para-I.

gender, χ 2 (2, N = 78) = 5.20, p N .05. Predictably, both groups of poor sleepers had higher scores on the ISI, F(2, 70) = 214.02, p b .01, revealing greater severity of insomnia symptoms in these groups. As such, both groups of insomnia individuals reported similar severity of sleep difficulties. Although all participants remained under the clinical threshold for psychiatric syndrome, both groups of poor sleepers displayed more depressive symptoms, F(2, 67) = 9.21, p b .01, on the BDI and more anxious symptoms, F(2, 61) = 9.52, p b .01, on the BAI than GS. 3.2. Subjective and objective sleep parameters Between group differences: Table 2 shows mean subjective and objective sleep laboratory parameters for Nights 2, 3 and 4 for the three groups of participants. 3.2.1. Night 2 Analyses revealed significant differences among groups on all subjective measures; SOL, F(2, 74) = 11.75, p b .01 , WASO, F(2, 71) = 42.57, p b .01, TST, F(2, 72) = 24.81, p b .01 , and SE, F(2, 72) = 41.34, p b .01 for Night 2. Specifically, compared to GS and Psy-I, Para-I reported taking longer to fall asleep. However, the three groups were significantly different from each other on WASO, TST and SE measures. More precisely, Para-I reported spending the longest time awake after sleep onset, sleeping the less time and having the lowest sleep efficiency, while GS reported spending the less time awake, sleeping the longest time and having the highest sleep efficiency of the three groups. With regard to the objective sleep variables during Night 2, significant differences among groups were found on SE, F(2, 75) = 6.28, p b .01 and WASO, F(2, 75) = 6.29, p b .01. Both groups of insomnia individuals had a lower sleep efficiency and spent more time awake after sleep onset than GS. Differences among groups were also observed for percentage, F(2, 75) = 3.74, p b .05, and time spent, F(2, 75) = 3.49, p b .05, in stage 3 and percentage, F(2, 75) = 5.55, p b .01, and time spent, F(2, 75) = 5.14, p b .01, in stage 4. Specifically, Psy-I had a lower percentage and spent less time in stage 3 than Para-I, while Para-I had a higher percentage and spent more time in stage 4 than GS and Psy-I.

3. Results 3.1. Characteristics of participants Table 1 shows sociodemographic data and clinical variables for the three groups of participants. Statistical analyses showed that the groups were similar according to age, F(2, 75) = 2,64, p N .05, and

3.2.2. Night 3 For Night 3, significant differences among groups were found again for all subjective sleep variables; SOL, F(2, 74) = 13.63, p b .01, WASO, F(2, 75) = 25.53, p b .01, TST, F(2, 75) = 26.78, p b .01, and SE, F(2, 75) = 38.27, p b .01. Although GS and Psy-I did not differ on these measures, Para-I reported taking longer to fall asleep, spending more time

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10.80 58.44 386.35 84.04 15.35 4.12 244.91 63.41 26.65 7.07 8.10 2.11 91.33 23.29 9.99 55.12 384.68 85.00 17.59 4.63 243.60 63.22 25.68 6.88 4.83 1.27 92.97 24.00

(8.11) (40.95) (44.81) (9.47) (9.57) (2.72) (40.50) (7.28) (19.86) (5.28) (13.33) (3.54) (25.41) (5.64)

awake and having a shorter total sleep time than the two other groups. However, the three groups were different on sleep efficiency with Para-I reporting the lowest efficiency and GS reporting the highest. Objectively, the analysis revealed significant differences among groups for SE, F(2, 74) = 4.80, p b .05, WASO, F(2, 74) = 4.57, p b .05, percentage, F(2, 74) = 3.81, p b .03 of stage 1 and percentage, F(2, 74) = 5.83, p b .01, and time spent, F(2, 74) = 6.31, p b .01, in stage 4. Psy-I had a lower sleep efficiency and spent more time awake after sleep onset than GS. They also had a higher percentage of stage 1 than Para-I, while Para-I had a higher percentage and spent more time in stage 4 than GS and Psy-I.

Note: SOL = Sleep-onset latency, WASO = Wake after sleep onset, TST = Total sleep time, SE = Sleep efficiency. a) GS different from Psy-I, b) GS different from Para-I, c) Psy-I different from Para-I.

11.73 (13.85) 52.77 (41.59) 410.99 (40.71) 85.96 (9.66) 12.42 (7.07) 3.08 (1.79) 253.23 (51.31) 61.25 (9.36) 36.72 (27.15) 9.16 (6.74) 12.03 (18.34) 3.00 (4.49) 96.59 (21.43) 23.52 (4.51) (9.88) (40.90) (49.09) (8.89) (13.20) (3.26) (39.81) (6.94) (18.28) (4.76) (4.58) (1.13) (27.29) (5.17) 10.50 56.25 401.88 85.00 18.47 4.67 262.42 65.39 21.39c 5.37c 2.38c 0.59c 97.22 23.98 6.35 (4.54) 23.98ab (22.06) 428.58 (52.16) 92.35ab (5.07) 14.72 (9.61) 3.50 (2.32) 278.60 (40.10) 65.03 (5.01) 26.53 (17.00) 6.14 (3.94) 4.37b (6.08) 1.01b (1.40) 104.38 (24.39) 24.32 (4.81)

5.60 20.26a 403.88 93.12a 11.51 2.94 260.07 64.31 25.16 6.46 3.08b 0.77b 104.05 25.52

(4.55) (17.65) (56.40) (4.08) (8.63) (2.33) (47.30) (6.28) (18.15) (4.83) (5.35) (1.31) (28.68) (5.33)

8.14 (7.33) 45.43 (37.52) 404.90 (44.53) 87.68 (7.59) 17.08 (11.88) 4.26c (2.93) 258.59 (48.58) 63.79 (8.28) 24.46 (20.16) 6.25 (5.33) 3.34c (6.41) 0.89c (1.75) 101.43 (28.61) 24.94 (6.14)

8.08 36.04 406.60 89.46 19.67 2.38 249.22 61.54 36.78 8.94 12.15 2.92 98.95 24.22

(7.48) (31.91) (37.25) (7.02) (51.15) (2.18) (39.15) (9.22) (29.63) (7.18) (15.98) (3.83) (21.61) (4.21)

4.60ab (3.57) 25.74ab (22.70) 411.08 (46.24) 92.04ab (5.03) 15.37 (8.26) 3.81 (2.17) 261.12 (48.49) 63.15 (7.46) 23.59 (17.90) 5.94 (4.79) 2.97 (6.72) 0.75 (1.67) 108.03b (23.64) 26.16 (4.47)

(8.35) (36.10) (44.01) (8.10) (9.69) (2.52) (47.59) (9.12) (20.47) (5.40) (8.67) (2.20) (26.11) (5.48)

48.80 133.50 274.96 59.28 25.46c (20.40) 57.52c (46.50) 378.35c (62.36) 81.87 c (12.39) 45.00 145.58 281.42 60.88 23.65c (20.15) 52.99c (51.91) 393.58c (60.22) 84.36c (10.08) 8.19b 15.65b 433.95b 94.83ab 45.96 (35.29) 126.46 (55.70) 315.79 (83.55) 65.12 (15.27) (23.37) (43.61) (62.46) (10.53) 23.96c 60.29c 401.20c 82.84c 12.19b (11.80) 17.92ab (18.75) 444.65ab (46.79) 93.53ab (5.91)

Subj measures SOL WASO TST SE (%) PSG data SOL WASO TST SE (%) Stage 1 time (min) Proportion (%) Stage 2 time (min) Proportion (%) Stage 3 time (min) Proportion (%) Stage 4 time (min) Proportion (%) REM time (min) Proportion (%)

Night 3

Para-I Psy-I Night 2

Table 2 Means and standard deviations of laboratory sleep parameters for GS, Psy-I and Para-I groups.

GS

(6.18) (18.25) (49.60) (4.52)

Psy-I GS

Para-I

(38.78) (103.17) (110.02) (22.22)

12.73b (13.51) 15.54ab (16.16) 420.92b (49.87) 92.63ab (5.72)

Para-I Psy-I GS

Night 4

(36.09) (72.72) (105.41) (21.93)

182

3.2.3. Night 4 During Night 4, the results were quite similar as in Night 2 for all subjective sleep measures, except for TST, where Para-I reported having less total sleep time than the 2 other groups. For objective sleep variables, significant differences among groups were observed on SE, F(2, 75) = 8.24, p b .01, SOL, F(2, 75) = 5.96, p b .01 and WASO, F(2, 75) = 7.22, p b .01. Precisely, GS had a higher sleep efficiency, took less time to fall asleep, and spent less time awake than the other two groups. GS also spent more time in REM sleep F(2, 75) = 3.50, p = .04 than Para-I. In summary, Para-I reported sleeping worse than Psy-I and GS on every night, while GS reported sleeping the better. Objectively, GS slept better than both groups of insomnia individuals. However, the data in Table 2 also reveal that our group of Psy-I did not present extremely severe sleep disturbances, even though all participants in this group met the chronic primary insomnia diagnosis criteria. Within groups differences: Paired sample t-tests were computed between objective sleep variables of Night 3 and Night 4 for each group in order to evaluate for possible differences that could be attributed to the presentation of auditory stimuli during Night 4. For the GS group, no significant differences were found for objective sleep variables between Night 3 and Night 4. Among Psy-I, significant differences were found for the TST, t (23) = 2.56, p b .05 and the total amount of time spent in stage 2, t (23) = 2.03, p b .05. This group slept longer and spent more time in stage 2 during Night 3 than during Night 4. For the Para-I group, between nights comparisons were significant for the following objective sleep variables: SE, t (25)= 2.51, p b .05, WASO, t (25) = −2.35, p b .05, percentage of stage 1, t (25)= −3.13, p b .01, total amount of stage 3 and percentage of stage 3, t (25)= 2.57, p b .05, t (25) = 2.76, p b .01 and total amount of stage 4, t (25) = 2.18, p b .05. Specifically, Para-I had a better sleep efficiency, spent less time awake after sleep onset, had a lower percentage of stage 1, a higher percentage and total amount of time spent in stage 3 as well as a higher total amount of time spent in stage 4 during Night 3 compared to Night 4. 3.3. ERPs measures See Table 3 for means and standard deviations and Fig. 1 for an illustration of the grand average ERPs for all three groups of participants. Fig. 2 illustrates the grand average ERPs recorded during wakefulness, sleep onset and stage 2 within each group. 3.3.1. N1 Mixed model ANOVAs revealed no significant difference among groups for N1 amplitude F(2, 66.9) = 1.84, p N .05. However, main effects of recording time F(2, 255.3) = 148.00, p b .01 and auditory stimuli F(1, 239.6) = 92.62, p b .01 were found. Furthermore, the Recording Time X Auditory Stimuli interaction was significant. Simple effects tests showed that the amplitude of N1 was larger for the standard stimuli in wakefulness and during sleep onset than during stage 2. For the deviant stimuli, the N1 amplitude was also larger during wakefulness and sleep onset than during stage 2. For N1 latency, no significant difference among groups was found F(2, 65.8) = .90, p N .05, but a main effect of recording time F(2, 263.5) =

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Table 3 Mean latency (in ms) and amplitude (in uV) of N1 and P2 (and standard deviation) measured at Cz for GS, Psy-I and Para-I groups. Cz

Latency Wakefulness

Sleep onset

Stage 2

Amplitude Wakefulness

Sleep onset

Stage 2

N1

P2

Standard

Deviant

Standard

Deviant

GS Psy-I Para-I GS Psy-I Para-I GS Psy-I Para-I

112.55 115.48 117.77 118.30 116.67 121.87 115.00 122.16 125.98

(12.77) (15.56) (12.75) (15.24) (10.53) (12.19) (22.86) (15.40) (14.98)

118.58 113.88 121.09 118.65 122.49 121.35 124.66 122.26 126.64

(14.82) (13.23) (9.34) (13.82) (11.32) (11.29) (14.08) (18.67) (20.39)

200.19 222.90 205.08 218.95 216.14 210.94 214.13 211.29 216.62

(14.99) (19.05) (23.25) (15.21) (16.35) (20.32) (19.46) (20.42) (20.20)

216.52 219.35 216.15 223.88 205.36 213.28 220.28 213.09 226.56

(18.87) (17.09) (21.93) (18.53) (19.30) (19.85) (18.61) (22.37) (19.78)

GS Psy-I Para-I GS Psy-I Para-I GS Psy-I Para-I

− 4.71 − 4.01 − 5.22 − 3.58 − 3.66 − 5.11 −.76 − 1.24 − 1.50

(2.75) (1.78) (2.68) (2.59) (1.73) (2.26) (1.45) (2.14) (2.70)

− 8.53 − 6.89 − 8.94 − 7.71 − 6.01 − 7.93 − 1.27 − 2.44 − 2.44

(3.14) (2.21) (3.72) (1.98) (2.74) (4.08) (2.51) (4.83) (4.83)

(2.38) (1.97) (2.30) (3.14) (2.15) (2.64) (2.17) (3.14) (2.43)

6.13 5.93 5.69 8.33 5.67 8.17 8.57 9.73 12.03

(4.09) (4.71) (2.89) (4.41) (3.61) (4.15) (4.19) (8.30) (6.36)

2.72 3.43 4.16 5.03 3.43 5.40 2.79 4.03 4.75

Note: a) GS different from Psy-I, b) GS different from Para-I, c) Psy-I different from Para-I.

5.17, p b .01 was observed. Post-hoc pairwise comparisons showed a significant difference between the N1 latencies recorded while awake (evening) and those recorded during early stage 2. The latency of N1 got longer from wakefulness to sleep. 3.3.2. P2 For P2 amplitude, again, no significant difference among groups was observed F(2, 66.8) = .73, p N .05, but main effects of recording time F(2, 249.0) = 12.29, p b .01 and auditory stimuli F(1, 233.8) = 126.46, p b .01 were found. In addition, Group × Recording Time and Recording Time × Auditory Stimuli interactions were found. The simple effects test performed on the Group × Recording Time interaction showed that the amplitude of P2 differed between GS and Para-I only during stage 2 sleep F(2, 121.4) = 4.03, p b .05. Indeed, Para-I presented larger P2 amplitude than GS for this recording time. The simple effects tests also revealed that the P2 amplitude was larger for the deviant stimuli during stage 2 than in wakefulness and during sleep onset. However, no significant difference was found between the recording times for the P2 amplitude for the standard stimuli. Analyses on P2 latency, revealed no significant difference among groups F(2, 68.6) =.12, pN .05. However, significant main effects of auditory stimuli as well as a significant Group×Recording Time and Group×Auditory Stimuli interactions were found. Simple effects tests revealed that for the GS, the P2 latency was longer during sleep onset than during wakefulness, while for the Para-I, the P2 latency was longer during stage 2 than in wakefulness. The Group×Auditory Stimuli interaction showed that the P2 latency was longer for the deviant stimuli than for the standard one, but only for GS and Para-I. Therefore, the P2 latency differed between the different recording times and auditory stimuli within the groups but no differences were present among the groups. 3.3.3. wPNs In order to evaluate the difference between information processing due to wakefulness and the extent of inhibition in information processing during sleep, a one-way ANOVA was conducted on the three wPNs. The wPNs were measured at two time points corresponding to the latencies of N1 and P2. The difference scores were obtained by subtracting ERPs amplitudes derived from sleep onset from those obtained while awake (wPNa), the ERPs amplitudes derived from stage 2 sleep from those obtained at sleep onset (wPNb) as well as the ERPs amplitudes derived from stage 2 sleep from those obtained during

wakefulness recordings (wPNc). Tables 3 and 4 show the means and standard deviations of the wPNs measured at two time points corresponding to the latencies of N1 and P2 at Cz for the three groups. The one-way ANOVA revealed only one difference among groups for the wPNb wave F(2, 34)= 3.84, p b .05. Post-hoc test revealed that the transition from sleep onset to stage 2 sleep for the time point corresponding to the latency of P2 (deviant stimuli) was different between GS and Para-I. Indeed, Para-I presented a much larger difference wave following the deviant stimuli than GS when the ERPs amplitudes derived from stage 2 sleep were subtracted from those obtained during sleep onset. Figs. 3 and 4 illustrates the wPNs measured at two time points corresponding to the latencies of N1 and P2 at Cz for all groups. 3.4. One tailed t tests for N1 and P2 Analyses performed on the ERPs amplitudes revealed that the N1 amplitude recorded during sleep onset, t (28) = −1.96, p b .05 was smaller following the deviant stimuli for Psy-I than for GS. The P2 amplitude was also different during sleep onset among these two groups, for both the standard stimuli t (32) = 1.69, pb .05 and the deviant one, t (28) = 1.79, p b .05, with Psy-I again presenting a smaller amplitude than GS. The N1 amplitude recorded during sleep onset, t (39) = 2.02, p b .05 was larger following the standard stimuli for Para-I than for GS. Differences among GS and Para-I were also observed for the P2 amplitude resulting from the standard tones recorded during wakefulness, t (34) = −1.84, p b .05, but also for the P2 amplitude during early stage 2 for both the standard, t (42) =−2.82, pb .01 and the deviant stimuli, t (39) = −2.09, p b .05. The P2 component was larger in Para-I when compared to GS for these two recording times. Finally, significant differences were identified among Psy-I and Para-I during wakefulness for the N1 amplitude resulting from the deviant stimuli, t (26) = 1.74, p b .05, as well as for the N1 amplitude during sleep onset, t (33) = 2.07, p b .05 for the standard tone which was significantly larger in Para-I than in Psy-I. The P2 amplitude was also larger in Para-I than in Psy-I during the sleep onset, for both the standard, t (33) = −2.36, p b .01 and the deviant stimuli, t (27) = −1.72, pb .05. Analyses also revealed that the P2 latency was longer for Psy-I than GS during wakefulness t (30) = −3.75, p b .01 for the standard stimuli, but that it was shorter for Psy-I than GS during sleep onset, t (28) = 2.68, p b .01 for the deviant stimuli. The N1 latency was shorter for GS than Para-I during early stage 2, t (42) = −2.00, p b .05 for the

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µV

µV

Wakefulness Standard

Wakefulness Deviant

N1

N1

500 ms 500 ms

P2 GS Psy-I Para-I

P2

Sleep Onset Standard

GS Psy-I Para-I

Sleep Onset Deviant

N1

N1

500 ms

500 ms

P2 GS Psy-I Para-I

P2

GS Psy-I Para-I

Early Stage 2 Deviant

Early Stage 2 Standard N1

N1

500 ms 500 ms

P2 GS Psy-I Para-I

GS Psy-I Para-I

P2 Fig. 1. Grand averages ERPs at Cz to standard and deviant stimuli during wakefulness, sleep onset and definitive sleep (stage 2). Note: The grand average does not always reflect the N1 and P2 means that were scored for individual subjects.

standard tones. Psy-I presented shorter latency than Para-I for the N1 resulting from deviant stimuli during wakefulness, t (26) = −1.68, p b .05, and the P2 latency during early stage 2 t (36) = −1.96, p b .05 for the deviant stimuli. Alternately, the P2 latency resulting from the standard tones during wakefulness was shorter among Para-I than Psy-I, t (34) = 2.47, p b .01. Significant differences were found among GS and Psy-I for the P2 amplitude from the wPNa, t (22) = −2.50, p b .01. and the wPNb, t (28) = 1.76, p b .05, for the standard tones, as well as for the N1 amplitude from wPNb, t (24) = − 1.94, p b .05 for the deviant stimuli. For all those wPNs, GS presented a larger difference than Psy-I in the ERPs components. Para-I presented significant larger differences than GS for the following: the P2 amplitude from the wPNb, for both the standard t (31) = 1.82, p b .05 and the deviant tones, t (44) = 3.57, p b .01; and the P2 amplitude from the wPNc resulting from the deviant tones, t (24) = 2.28, p b .05. Finally, Para-I presented larger differences than Psy-I for the N1 amplitude from the wPNb for the deviant stimuli, t (20) = 2.06, p b .05, and the P2 amplitude from the wPNc for the standard, t (30) = 1.95, p b .05 and the deviant tones, t (22) = 1.92, p b .05.

4. Discussion 4.1. Sleep variables As expected, differences between groups were observed on subjective measures of sleep, with Para-I reporting more complaints and sleep difficulties on all measures when compared with the other two groups. Significant differences were also found on objective sleep variables of latency to sleep onset, wake after sleep onset and sleep efficiency, as well as percentage and amount of time spent in different stages during the laboratory nights. Most differences were observed between Psy-I and GS, with a few exceptions. These results confirm that our categorizing procedure for Para-I appears to be quite sensitive and reflect the criteria set forth by Edinger et al. (2004). 4.2. Event-related potentials A maximum peak deflection algorithm was used to score N1 and P2. It is important to mention that a limit of this scoring procedure is that the maximum peak deflection procedure might mistakenly

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µV

185

µV

Standard

Deviant N1

N1

GS 500 ms

500 ms

P2 Wakefulness Sleep onset Stage 2

Wakefulness Sleep onset Stage 2

P2

Standard

Deviant N1

N1

Psy-I 500 ms

500 ms

Wakefulness Sleep onset Stage 2

Wakefulness Sleep onset Stage 2

P2

Standard

Deviant

N1

Para-I

500 ms 500 ms

P2 Wakefulness Sleep onset Stage 2

Wakefulness Sleep onset Stage 2

P2 Fig. 2. Grand averages ERPs at Cz to standard and deviant stimuli for GS, Psy-I and Para-I. Note: The grand average does not always reflect the N1 and P2 means that were scored for individual subjects.

Table 4 wPNs means and standard deviations at Cz for GS, Psy-I and Para-I groups. Amplitude

Wake — Sleep onset (wPNa)

Sleep onset — stage 2 (wPNb)

Wake — stage 2 (wPNc)

N1

GS Psy-I Para-I GS Psy-I Para-I GS Psy-I Para-I

P2

Standard

Deviant

Standard

Deviant

−.96 −.61 −.22 − 3.09 − 2.83 − 3.62 − 4.01 − 3.79 − 3.69

− 1.13 (2.36) − 1.26 (1.02) − 1.42 (3.45) − 6.59a (4.36) − 3.51c (3.45) − 6.68 (3.77) − 6.87 (4.89) − 5.49 (3.09) − 6.53 (3.96)

− 1.48a .60 − 1.00 1.75ab .02 −.01 −.15 .68c − 1.06

−.97 (4.73) −.73 (1.45) − 2.52 (4.81) −.25b (4.81) − 2.17 (8.27) − 6.65 (4.07) − 2.74b (4.83) − 2.68c (6.66) − 7.86 (6.59)

(2.40) (1.64) (1.81) (1.76) (2.18) (2.55) (2.51) (2.58) (3.27)

Note: a) GS different from Psy-I, b) GS different from Para-I, c) Psy-I different from Para-I.

(2.25) (1.74) (3.27) (2.89) (2.38) (2.66) (1.95) (2.23) (2.69)

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µV

µV

wPNa

GS

µV

wPNb

500 ms

500 ms

SO Stage 2

Wake SO

wPNc

500 ms

Wake Stage 2

Psy-I 500 ms

Wake SO

500 ms

SO Stage 2

500 ms

Wake Stage 2

Para-I 500 ms

Wake SO

500 ms

SO Stage 2

500 ms

Wake Stage 2

Fig. 3. Grand average ERPs at Cz to standard stimuli for GS, Psy-I and Para-I. The gray zone represents the difference in information processing between the two recording times.

identify noise as a true signal, particularly during the sleep period. It is likely that this could account for the differences between the mean data and the grand averages.

The mixed model ANOVA results indicate no significant differences for the N1 amplitude and latency between the three groups. The stimulus type had an effect on the amplitudes of either N1 or P2 peaks,

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µV

µV

wPNa

µV

wPNb

187

wPNc

GS 500 ms

Wake SO

500 ms

SO Stage 2

500 ms

Wake Stage 2

Psy-I 500 ms

Wake SO

500 ms

SO Stage 2

500 ms

Wake Stage 2

Para-I 500 ms

Wake SO

500 ms

SO Stage 2

500 ms

Wake Stage 2

Fig. 4. Grand average ERPs at Cz to deviant stimuli for GS, Psy-I and Para-I. The gray zone represents the difference in information processing between the two recording times.

since the deviant tone elicited larger amplitudes than the standard one. The recording time also had an impact on the amplitudes of N1 and P2. As expected, the amplitude of N1 decreased from wakefulness

to sleep, while the amplitude of P2 increased. These findings are consistent with other studies (Campbell et al., 1992; Crowley and Colrain, 2004; Kertesz and Cote, 2011). Finally, the recording time also

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influenced the latencies of both N1 and P2, as they got longer from wakefulness to sleep. It has been shown that the latency of N1 and P2 tend to become prolonged as the individual becomes increasingly drowsy and finally enters definitive sleep (Campbell et al., 1992; De Lugt et al., 1996). On the other hand, when one tailed t-tests were performed on the ERPs data, between groups differences emerged. The N1 amplitude recorded during sleep onset was the largest for Para-I while it was the smallest for Psy-I. During wakefulness, N1 was also larger for Para-I than for Psy-I. The larger N1 amplitude observed in Para-I during sleep onset supports the neurocognitive model of insomnia (Perlis et al., 1997) that suggests that high frequency activity is a main feature of chronic insomnia that could interfere with sleep initiation. This model also states that increased cortical arousal would also lead to incompatible sleep activities such as enhanced sensory and information processing which could be reflected by the larger N1 amplitude also observed in Para-I during wakefulness before going to sleep. Although we did not find significant larger N1 amplitude for the Psy-I group, our previous study (Bastien et al., 2008) revealed that they present larger N1 upon awakening in the morning. Thus, it is possible that the degree of arousal level varies during the day according to other factors. In that regard, Turcotte and Bastien (2009) investigated the relation between objective sleep parameters and the amplitudes and latencies of ERPs components N1 and P2 among Psy-I and GS. Pearson's correlation analyses were conducted between objective sleep measures and the amplitude and latency of N1 and P2 recorded during the evening, sleep onset and upon awakening. They showed that the increase in N1 and P2 amplitude observed for Psy-I seems to be directly linked to objective sleep quality while sleep quality seems to be directly associated to the larger ERPs amplitudes observed the next morning. Therefore, the extent of attentional processing could be waxing and waning with objective sleep quality. It is also possible that the stresses of daily activities (stress at work, taking care of the kids) influenced information processing. While the ERPs protocol used in this study relied only on a one night assessment, which does not permit to evaluate for stability, further studies should focus on multiple assessments over several nights and days in order to monitor the influence of sleep quality and daily activities on variation of attentional processing levels among insomnia individuals. Regarding the P2 amplitude, one tailed t-tests also revealed more between groups differences than the mixed model analyses. During wakefulness, the P2 amplitude was larger in Para-I than GS. During sleep onset, the P2 amplitude was smaller in Psy-I compared to GS, while it was larger in Para-I than in GS during stage 2 sleep. Again, these results provide support to the neurocognitive model of insomnia (Perlis et al., 1997). We hypothesized that insomnia individuals would present a smaller P2 as they would lack the ability to inhibit external stimulations. Therefore, the smaller P2 observed during sleep onset in Psy-I could reflect an inability to inhibit non-pertinent stimuli while trying to fall asleep. These results corroborate those obtained by Kertesz and Cote (2011) and indicate that Psy-I have not successfully disengaged or inhibited to the same extent as GS. On the other hand, the larger P2 observed among the Para-I across all recording times raises an interpretation challenge. The underlying neurological correlates or functional significance of the P2 is still poorly understood (Crowley and Colrain, 2004). In light of our previous results showing that Para-I appeared to be the group that was the most disturbed by the auditory tones delivered during the night according to their objective PSG parameters, it is possible to argue that the need for greater inhibition might come from the fact that they are more easily disturbed by the stimulations. Crowley and Colrain (2004) suggested that the amplitude of P2 following standard tones appears to increase with age (just like sleep fragmentation), therefore an enhanced P2 might represent an inability to inhibit or withdraw attention from irrelevant stimuli. A growing body of evidence suggests that cortical arousal is present in insomnia individuals. Insomnia being multifac-

eted, it is likely that other factors act to maintain sleep difficulties (e.g. repeated negative events, emotional arousal). Usually, Para-I produce seemingly normal PSGs (when not bothered by stimulations), which do not represent their sleep complaints. However, in this study, the Para-I group presented larger P2 amplitude during wakefulness and sleep than GS and larger P2 amplitude during sleep onset than Psy-I. While Turcotte and Bastien (2009) linked objective sleep quality with evening, morning and sleep onset ERPs components, they did not evaluate a possible association between N1, P2 and subjective sleep variables, neither did they have a Para-I group. Therefore, it is possible that enhanced P2 amplitude might be related to subjective sleep quality among this subgroup of insomnia individuals, since they also reported poor sleep efficiency on this night. It is also possible that the greater need for inhibition reflected by the larger P2 might come in response to the larger N1 also observed in this group. Therefore, the increased inhibition might be in response to compensate for the enhanced attentional processing. While no significant difference among groups was found concerning the latency of N1 and P2 in the results from the mixed model analyses, the one tailed t-tests revealed some. When compared to GS, a delayed P2 during wakefulness was observed among Psy-I, while a delayed N1 during stage 2 was found in Para-I following standard tones. According to previous studies (Bastuji and Garcia-Larrea, 1999; Colrain et al., 2000; Cote et al., 2002; Harsh et al., 1994), a latency delay in ERPs usually indicates slowed processing speed. However, during sleep onset, Psy-I showed faster P2 latency following deviant stimuli than GS. Although these results seem contradictory, it is possible to argue that insomnia individuals (Psy-I and Para-I) appear to present an alteration in information processing speed. The current research is novel in investigating the wPN, this long lasting negative difference wave that overlaps both the N1 and P2 peaks causing them both to become more positive as an individual falls asleep. We hypothesized that both types of chronic insomnia would show fewer changes in N1 and P2 amplitude than GS from wakefulness to sleep, since previous studies reported that hyperarousal seems to be constant and persistent. Part of this hypothesis was confirmed with Psy-I showing less difference than GS in the N1 amplitude from sleep onset to sleep for the deviant stimuli and in the P2 amplitude from wakefulness to sleep onset and sleep onset to sleep for the standard stimuli. At sleep onset, the ability to successfully disengage attention from the external stimulations usually concurs with the removal of the wPN, therefore causing N1 to get smaller and P2 to get larger among GS (Muller-Gass and Campbell, 2002; Näätänen, 1990). However, the smaller changes observed in Psy-I during these transition times appear to indicate that they have trouble disengaging attention or inhibiting stimulations coming from the external environment in order to sleep. These results provide support to Espie's insomnia model (2002) that states that inhibitory processes or the inability to de-arouse or disengage from active wakefulness processing interferes with the normal initiation of sleep processes in insomnia individuals. These results also corroborate a previous study by Nofzinger et al. (2004) that compared individuals with primary insomnia with GS using position emission tomography. They found that insomnia participants showed greater global cerebral glucose metabolism during sleep and while awake and a smaller decline in relative metabolism from waking to sleep states in wake-promoting regions. The authors concluded that the inability to fall asleep in insomnia individuals may be related to a failure of arousal mechanisms to decline in activity from waking to sleep. Alternately, the larger changes observed in the Para-I group for the N1 amplitude from sleep onset to sleep for the deviant stimuli and the P2 amplitude from wakefulness to sleep for both types of stimuli when compared to Psy-I, as well as the larger difference in the P2 amplitude from sleep onset to sleep, for both stimuli, and the P2 amplitude from wakefulness to sleep for deviant tones when compared to GS, appear more challenging to interpret. These results indicate a large amount of

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variation in the extent of information processing during sleep onset and sleep. Therefore, inhibition processes necessary to fall asleep are very different in Para-I and this group might have to show greater inhibition in order to close channels to irrelevant stimulations. Furthermore, this group reported taking longer to fall asleep than Psy-I and GS on this particular night, while this complaint was only partially corroborated by PSG. This suggests, once again, that the P2 amplitude might be associated with the subjective sleep perception. Moreover, between night comparisons revealed that GS were not affected by the presentation of stimuli all through the fourth night, while Para-I appeared to be the group that was the most disturbed by the auditory tones according to their objective sleep parameters. These results appear to contradict a study by Haynes et al. (1985) that investigated arousal thresholds in sleep-onset insomnia, Para-I, and GS. In this study, all three groups showed similar auditory arousal thresholds and no differences between groups were found in sensitivity to nocturnal auditory stimuli. However, at this time, no criteria had yet been established to subdivide insomnia individuals in Psy-I or Para-I, so only the objective sleep onset latency was used to separate these groups. Furthermore, Haynes et al. (1985) only recruited sleep-onset insomnia participants and they measured only the sleep onset latency, the number of awakenings and the latency to return to sleep after awakening as objective sleep variables. Haynes et al. (1985) presented a 1000-Hz tone with intervals of 13 s between tone presentations over a speaker suspended 42 cm above the bed. Decibel levels were increased 4–5 dB with each tone presentation until the subject acknowledged hearing the most recent tone presented. In our protocol, participants received standard (70 dB, 2000 Hz) and deviant (90 dB, 1500 Hz) stimuli through ear inserts and the interstimulus interval was kept constant at 2 s. Therefore, our protocol appears to be more intrusive and it is possible that in these conditions, the auditory arousal threshold might differ in Para-I and that the auditory stimuli disturbed or disrupted sleep and this disturbance was evidenced by other objective sleep variables.

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according to objective sleep parameters from the presentation of auditory tones. Individuals with psychophysiological insomnia showed fewer changes in information processing from wakefulness to sleep onset and from sleep onset to sleep, while the paradoxical group presented larger changes in information processing during the transition from sleep onset to sleep and during wakefulness to sleep. ERPs and PSA studies are beginning to reveal that these 2 subgroups appear to present distinct cortical activity related to information processing characteristics. Obviously, these results highlight the fact that brain activity in individuals with paradoxical insomnia requires much more investigation since information processing seems to be really altered in this group during transitional conscious to unconscious states and we currently are only beginning to clarify what might be happening in this group of sleepers in which the severity of sleep complaints does not reflect actual sleep. Also, further studies using multiple assessments and ERPs recordings during the night while also monitoring for subjective sleep quality and/or daily activities, and to another extent personality, could be informative on the degree of interference of these factors on information processing. Furthermore, studies evaluating the relationship between ERPs and the degree of misperception or discrepancy amid objective and subjective sleep variables might provide more information on variations in information processing and its link to a potential objective/subjective sleep difficulty continuum. Finally, it is noteworthy to mention that the definition of the sleep onset period is slightly different among studies according to the measured variables (i.e., EEG based or behavioral) and that it is possible that the amplitude of the wPN waves vary according to this definition. Therefore, studies focusing on the sleep onset period in insomnia individuals and the difference in information processing possible during this period is worthy of future investigation. The repeated sleep onset recording procedure previously used by researchers (Cote et al., 2002; Kertesz and Cote, 2011; Ogilvie et al., 1991) to investigate this critical period should be prioritized.

4.3. Insomnia subtypes References Considering the variability in sleep patterns of insomnia individuals, it can be difficult to categorize these individuals into Para-I or Psy-I subtype even with a standard set of criteria like the ones provided by Edinger et al. (2004). Our protocol required that participants spend four nights at the sleep laboratory, so multiple objective and subjective sleep recordings were obtained. While the diagnostic criteria put forward by Edinger et al. (2004) are certainly useful, they offer few indications regarding how many nights should be taken into account before categorizing insomnia participants as paradoxical or which cut-offs should be used to quantify the discrepancies between subjective estimates and objective measures. For the purpose of this study, we decided to categorize participants as individuals with paradoxical insomnia if they met the diagnostic criteria during Night 2 or Night 3. We also decided to use a 15% cut-off between subjective and objective measures of sleep efficiency, and a difference of 60 min or more for total sleep time. In light of the results obtained for the paradoxical insomnia group in this study, the combination of the standard set of criteria provided by Edinger et al. (2004) and the thresholds we decided to retain to quantify the discrepancies between subjective estimates and objective measures appears to be strongly justified. 5. Conclusion While individuals with psychophysiological insomnia showed an inability to inhibit information processing during sleep onset, individuals with paradoxical insomnia presented enhanced attentional processing and/or a greater need for inhibition during wakefulness, sleep onset and sleep. This group was also the most disturbed,

American Psychological Association, 1994. Diagnostic and Statistical Manual of Mental Disorders. American Psychiatric Association, Washington, DC. Bastien, C.H., Morin, C.M., 1998. Late-life insomnia: sleep patterns of drug-free and chronic users of benzodiazepines. Sleep 21, 145. Bastien, C.H., Vallières, A., Morin, C.M., 2001. Validation of the Insomnia Severity Index as an outcome measure for insomnia research. Sleep Med. 2, 297–307. Bastien, C.H., Vallières, A., Morin, C.M., 2004. Precipitating factors of insomnia. Behav. Sleep Med. 2, 50–62. Bastien, C.H., St-Jean, G., Morin, C.M., Turcotte, I., Carrier, J., 2008. Chronic psychophysiological insomnia: hyperarousal and/or inhibition deficits? An ERPs investigation. Sleep 31, 887–898. Bastuji, H., Garcia-Larrea, L., 1999. Evoked potentials as a tool for the investigation of human sleep. Sleep Med. Rev. 3, 23–45. Beck, A.T., Epstein, N., Brown, G., Steer, R.A., 1988a. An inventory for measuring clinical anxiety: psychometric properties. J. Consult. Clin. Psychol. 56, 893–897. Beck, A.T., Steer, R.A., Garbin, M.G., 1988b. Psychometric properties of the Beck Depression Inventory: twenty-five years of evaluation. Clin. Psychol. Rev. 8, 77–100. Campbell, K., Colrain, I.M., 2002. Event-related potential measures of the inhibition of information processing: II the sleep onset period. Int. J. Psychophysiol. 46, 197–214. Campbell, K., Bell, I., Bastien, C.H., 1992. Evoked potentials measures of information processing during natural sleep. In: Broughton, R., Ogilvie, R. (Eds.), Sleep, Arousal & Performance. Birkhauser Boston, Cambridge MA. Colrain, I.M., Di Parsia, P., Gora, J., 2000. The impact of prestimulus EEG frequency on auditory evoked potentials during sleep onset. Can. J. Exp. Psychol. 54, 243–254. Cote, K.A., de Lugt, D.R., Campbell, K.B., 2002. Changes in the scalp topography of eventrelated potentials during the sleep onset period. Psychophysiol. 39, 29–37. Crowley, K.E., Colrain, I.M., 2004. A review of the evidence for P2 being an independent component process: age, sleep and modality. Clin. Neurophysiol. 115, 732–744. Crowley, K.E., Trinder, J., Colrain, I.M., 2002. An examination of evoked K-complex amplitude and frequency of occurrence in the elderly. J. Sleep Res. 11, 129–140. De Lugt, D., Loewy, D., Campbell, K., 1996. The effect of sleep onset on event-related potentials with rapid rates of stimulus presentation. Electroencephalogr. Clin. Neurophysiol. 98, 484–492. Devoto, A., Manganelli, S., Lucidi, F., Lombardo, C., Russo, P.M., Violani, C., 2005. Quality of sleep and P300 amplitude in primary insomnia: a preliminary study. Sleep 28, 859–863.

190

I. Turcotte et al. / International Journal of Psychophysiology 81 (2011) 177–190

Edinger, J.D., Krystal, A.D., 2003. Subtyping primary insomnia: is sleep state misperception a distinct clinical entity? Sleep Med. Rev. 7, 203–214. Edinger, J.D., Bonnet, M.H., Bootzin, R.R., et al., 2004. Derivation of research diagnostic criteria for insomnia: report of an American Academy of Sleep Medicine work group. Sleep 27, 1567–1596. Espie, C.A., 2002. Insomnia: conceptual issues in the development, persistence, and treatment of sleep disorders in adults. Annu. Rev. Psychol. 53, 215–243. Gratton, G., Coles, M.G.H., Donchin, E., 1983. A new method for off-line removal of ocular artefact. Electroencephalogr. Clin. Neurophysiol. 55, 468–484. Harsh, J., Voss, U., Hull, J., Schrepfer, S., Badia, P., 1994. ERP and behavioral changes during the wake/sleep transition. Psychophysiol. 31, 244–252. Haynes, S.N., Fitzgerald, S.G., Shute, G., O'Meary, M., 1985. Responses of psychophysiologic and subjective insomniacs to auditory stimuli during sleep: a replication and extension. J. Abnorm. Psychol. 94, 338–345. Kertesz, R.S., Cote, K.A., 2011. Event-Related Potentials during the transition to sleep for patients with sleep-onset insomnia. Behav. Sleep Med. 9, 68–85. Krystal, A.D., Edinger, J.D., Wohlgemuth, W.K., Marsh, G.R., 2002. NREM sleep EEG frequency spectral correlates of sleep complaints in primary insomnia subtypes. Sleep 25, 630–640. Merica, H., Gaillard, J., 1992. The EEG of the sleep onset period in insomnia: a discriminant analysis. Physiol. Behav. 52, 199–204. Merica, H., Blois, R., Gaillard, J., 1998. Spectral characteristics of sleep EEG in chronic insomnia. Eur. J. Neurosci. 10, 826–834. Morin, C.M., 1993. Insomnia. Psychological Assessment and Management, New York, NY. Morin, C.M., Espie, C.A., 2003. Insomnia: A Clinical Guide to Assessment and Treatment. Kluwer Academic/Plenum Publishers, New York. 190 pp. Morin, C.M., LeBlanc, M., Daley, M., Gregoire, J.P., Mérette, C., 2006. Epidemiology of insomnia: prevalence, self-help treatments, consultations, and determinants of help-seeking behaviours. Sleep Med. 7, 123–130. Muller-Gass, A., Campbell, K., 2002. Event-related potential measures of the inhibition of information processing: I. Selective attention in the waking state. Int. J. Psychophysiol. 46, 177–195. Näätänen, R., 1990. The role of attention in auditory information processing as revealed by event-related potentials and other brain measures of cognitive function. Behav. Brain Sci. 13, 201–288.

Nofzinger, E.A., Buysse, D.G., Germain, A., Price, J.C., et al., 2004. Functional neuroimaging evidence for hyperarousal in insomnia. Am. J. Psychiatry. 161, 2126–2128. Ogilvie, R.D., Simons, I.A., Kuderian, R.H., MacDonald, D., Rustenberg, J., 1991. Behavioral, event-related potentials, and EEG/FFT changes at sleep onset. Psychophysiol. 28, 54–64. Ohayon, M.M., 2002. Epidemiological of insomnia: what we know and what we still need to learn. Sleep Med. Rev. 6, 97–111. Perlis, M.L., Giles, D.E., Mendelson, W.B., Bootzin, R.R., Wyatt, J.K., 1997. Psychophysiological insomnia: the behavioural model and a neurocognitive perspective. J. Sleep Res. 6, 179–188. Perlis, M.L., Smith, M.T., Andrews, P.J., Orff, H., Giles, D., 2001. Beta/gamma EEG activity in patients with primary and secondary insomnia and good sleeper controls. Sleep 24, 110–117. Picton, T.W., Bentin, S., Berg, P., Donchin, E., Hillyard, S.A., Johnson Jr., R., et al., 2000. Guidelines for using human event-related potentials to study cognition: recording standards and publication criteria. Psychophysiol. 37, 127–152. Rechtschaffen, A., Kales, A.A., 1968. Manual of Standardized Terminology, Techniques and Scoring System for Sleep Stages of Human Subjects. Brain Information/Brain Research Institute, UCLA, Los Angeles. Sforza, E., Haba-Rubio, J., 2006. Event-related potentials in patients with insomnia and sleep-related breathing disorders: evening-to-morning changes. Sleep 29, 805–813. Spitzer, R.L., Williams, J.B.W., Gibbon, M., First, M., 1996. Structured Clinical Interview for DSM-IV (SCID). American Psychiatric Association, Washington, DC. St-Jean, G., Bastien, C.H., 2008. Rem and N-Rem power spectral analysis on two consecutive nights in relation to sleep quality in psychophysiological and paradoxical insomnia sufferers. Sleep 31, A247. Turcotte, I., Bastien, C.H., 2009. Is quality of sleep related to the N1 and P2 ERPs in chronic psychophysiological insomnia sufferers? Int. J. Psychophysiol. 72, 314–322. Yang, C.M., Lo, H.S., 2007. ERP evidence of enhanced excitatory and reduced inhibitory processes of auditory stimuli during sleep in patients with primary insomnia. Sleep 30, 585–592.