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Event-related potentials (ERPs) provide an exquisite means to measure the extent of processing of external stimuli during the sleep period. This study examines ERPs elicited by stimuli with physical characteristics akin to environmental noise encountered during sleep. Brief duration 40, 60 or 80 dB sound pressure level (SPL) tones were presented either rapidly (on average every two seconds) or slowly (on average every 10 seconds). The rates of presentation and intensity of the stimuli were similar to those observed in environmental studies of noise. ERPs were recorded from nine young adults during sleep and wakefulness. During wakefulness, the amplitude of an early negative ERP, N1, systematically increased as intensity level increased. A later positivity, the P3a, was apparent following the loudest 80 dB stimulus regardless of the rate of stimulus presentation; it was also apparent following the 60 dB stimulus, when stimuli were presented slowly. The appearance of the N1-P3a deflections suggests that operations of the central executive controlling ongoing cognitive activity was interrupted, forcing subjects to become aware of the obtrusive task-irrelevant stimuli. The auditory stimuli elicited very different ERP patterns during sleep. During non-rapid eye movement (NREM) sleep, the ERP was characterized by an enhanced (relative to wakefulness) early positivity, P2, followed by a very prominent negativity, the N350. Both deflections systematically varied in amplitude with stimulus intensity level; in addition, N350 was much larger when stimuli were presented at slow rates. The N350, a sleep-specific ERP, is thought to reflect the inhibition of processing of potentially sleep-disrupting stimulus input. During rapid eye movement (REM) sleep, a small amplitude N1 was apparent in the ERP, but only for the loudest, 80 dB stimulus. A small (nonsignificant) P3a-like deflection was also visible following the 80 dB stimulus, but only when stimuli were presented slowly. The findings of the present study offer, on one hand, an explanation of the means by which consciousness is prevented during sleep but also, on the other hand, an explanation of how sleep can be disrupted and possibly reversed, leading to an awakening. Keywords: Consciousness, event-related potentials, information processing, intensity, rate of presentation, sleep
How to cite this article:
Muller-Gass A, Campbell K. The processing of infrequently-presented low-intensity stimuli during natural sleep: An event-related potential study. Noise Health 2010;12:120-8 |
How to cite this URL:
Muller-Gass A, Campbell K. The processing of infrequently-presented low-intensity stimuli during natural sleep: An event-related potential study. Noise Health [serial online] 2010 [cited 2023 Mar 24];12:120-8. Available from: https://www.noiseandhealth.org/text.asp?2010/12/47/120/63213 |
| Introduction | |  |
This special edition of Noise and Health examines the effects of acoustic noise on the quality of sleep. As is apparent in the various articles, the effects of noise are examined in different ways, often through the use of subjective questionnaires, objective physiological measures such as the quantity of different stages of sleep or changes in other physiological measures such as the heart rate and respiration. Nevertheless, very few external auditory stimuli actually awaken the sleeper. This does not imply, however, that the auditory stimuli are not processed. Somewhere in the brain, a decision must be made whether incoming stimulus input is relevant enough to disrupt sleep or allow sleep to continue undisturbed. Even if the incoming stimulus does not awaken the sleeper, it may produce a brief-lasting micro-arousal. [1]
The present article uses event-related potential (ERP) methodology to determine the extent of processing of auditory input in both the waking and sleeping states. In a recent review on measures of arousal during sleep, Bonnet et al. [2] make special mention of the utility of ERPs and in particular a late negative deflection peaking at about 350 milliseconds (thus called the "N350"). ERPs are the small changes in the activity of the scalp-recorded electroencephalogram (EEG) that are elicited by an external auditory stimulus. ERPs have the advantage of providing a real-time measure of the extent of auditory processing during an unconscious state such as sleep. Often, these changes are very minute and usually difficult to observe in the ongoing EEG. Signal averaging techniques are therefore required to reduce the amplitude of the background "noise" allowing the ERP to emerge from the EEG. The ERP consists of a series of negative- and positive-going components (see the accompanying Campbell review in this Edition for further detail about the component structure of ERPs). These scalp-recorded components represent the activity of different intra-cranial sources reflecting different aspects of both sensory and cognitive functioning.
The present study examines the role of the transient detector system in interrupting ongoing cognitive activity in the waking state and in disrupting the sleep process. NĠĠtĠnen's comprehensive model of auditory processing provides an elegant explanation of the functioning of this system. [3] The transient detector system, as its name implies, is responsible for the detection of changes in the transient energy of a stimulus, most often, the onset of a brief stimulus or the offset of a long duration stimulus. The output of this system is proportional to the change in energy (intensity level) and the rareness of stimulus presentation. Thus, activity in the transient detector system dramatically increases following the presentation of a loud sound that is infrequently presented compared to a soft sound that is frequently presented. The output of this system can be monitored through a negative ERP component, N1, peaking at about 100 milliseconds. When stimuli are presented relatively rapidly (every 0.5 to 4 seconds), the peak of N1 is maximum over fronto-central areas of the scalp and inverts in polarity (i.e., is recorded as a positive potential) at lateral, inferior regions below the Sylvian fissure. This scalp topography is best explained by source generators in and around the auditory cortex. [4] When the rate of stimulus presentation is slowed, the amplitude of N1 also increases and changes from its usual fronto-central maximum to a more central maximum. [5],[6],[7] A large number of studies have now indicated that the amplitude of N1 varies directly with the intensity level of the auditory stimulus.
The output of the transient detector system is forwarded to the central executive, controlling the allocation of attentional resources needed to meet the demands of ongoing cognitive tasks. When this output reaches a certain critical threshold, ongoing cognitive activity is interrupted and attention is then switched to the (task-irrelevant) auditory channel. This is also called "attention capture". This switching of attention may cause deterioration in performance on the relevant, ongoing cognitive task, the phenomenon being labeled as "distraction". The actual switch of attention away from relevant cognitive activity and toward the auditory channel is thought to be reflected by a later positive component, the P3a, peaking 250-300 milliseconds after stimulus onset. [8] This passively-elicited P3a is maximal over central areas of the scalp.
In order to sleep, the processing of all but the most relevant of stimulus input must be inhibited. A number of studies have employed ERP methodology to examine the extent of auditory information processing during sleep. In their reviews, Campbell and Colrain [9],[10] indicate that the amplitude of N1 has been consistently shown to gradually decrease during the sleep onset period and to reach baseline levels during definitive sleep (stage N2). The amplitude of N1 remains at baseline levels throughout non-REM (NREM) sleep. The reduction in the amplitude of N1 occurs independently of stimulus intensity level. [11] On the other hand, the amplitude of a subsequent P2, peaking at about 180 milliseconds, may increase dramatically during NREM sleep. [12] Very different results emerge during REM sleep. N1 can be elicited during REM sleep provided stimulus intensity level is quite high although it is reduced to about 15-25% of its waking amplitude. [13] Importantly, particularly loud, rare and/or psychologically relevant stimuli might continue to elicit a P3-like wave during REM sleep, but its amplitude is also much reduced compared to the waking state. [11],[14] The P3-like deflection cannot be recorded during NREM sleep even following presentation of a 100 dB SPL stimulus. [11]
Although the N1 and P3 ERPs are difficult to elicit in NREM sleep, a very large amplitude negative wave peaking at about 350 milliseconds, the N350, appears during the initial sleep onset period. It is maximal over the central areas of the scalp and appears to be identical to the classic vertex sharp wave, a marker of sleep onset. [15] Ogilvie et al. [16] and Harsh et al. [17] noted that N350 first emerges when subjects are no longer able to signal awareness of an external stimulus presentation during the sleep onset period. Colrain et al. [18] reported that the N350 was difficult to elicit during stage N1, when the EEG was dominated by alpha activity but was readily apparent when it was dominated by theta activity, a sign of definitive sleep. As such, the N350 can only be elicited during definitive sleep and is not apparent at all during wakefulness. The N350 thus appears to be associated with the inhibition of stimulus processing, allowing sleep to occur. The amplitude of N350 is much larger following presentation of high compared to low intensity level stimuli; once the N350 reaches a critical amplitude, Bastien and Campbell [19] postulate that a much larger amplitude K-Complex is triggered. Thus, the N350 is always elicited when the large amplitude K-Complex is elicited. However, the N350 is also elicited by less obtrusive stimuli that do not elicit the K-Complex.
The majority of ERP studies have employed moderate to high intensity stimuli presented at fairly rapid rates (every 0.5-2 seconds). In real world applications, the intensity of traffic (e.g., aircraft, train, automobile) and industrial noise is usually much lower in homes and noise occurrences are much less frequent. Basner et al. [20] note that low intensity 45-65 dB SPL aircraft noise does not produce large changes in macro-measures such as awakenings or sleep stages. They may, however, affect more subtle micro-arousals. In the present study, the intensity level of brief duration stimuli was set to be high (80), moderate (60) or low (40 dB SPL). Stimuli were presented rapidly (on average, every two seconds) or slowly (on average, every 10 seconds).
| Materials and Methods | | |
Subjects
Nine young adults (four females) in the age group of 19-24 years volunteered to participate in the study. Five of the subjects had previously participated in a sleep study. None reported a history of psychiatric, neurological or audiological disorder. All of them indicated that they were good sleepers and not easily disturbed by auditory noise. Each subject spent two nights in the sleep lab. They were asked to read and sign a consent form that provided details of the experimental paradigm and procedures. Each subject received an honorarium for participation in this study. This study was approved by the University of Ottawa's internal ethics committee and followed guidelines established by the Canadian Tri-Council (Natural, Health, and Social sciences) research board.
Auditory stimuli
A sequence containing 40, 60 and 80 dB SPL 1000 Hz pure tone stimuli having a total duration of 55 milliseconds and a five-millisecond rise-and-fall time was presented to the right ear using EAR 3A insert earphones. Use of an insert earphone controlled for consistency of stimulus presentation in spite of head movement and ear position during the night. Order of stimulus presentation of the three intensity levels was randomized. In different conditions, a stimulus was presented every 1.5-2.5 seconds (on average every two seconds) or every 8-12 seconds (on average every 10 seconds). The fast and slow conditions were presented in random order. Stimuli were presented in blocks lasting eight minutes. When stimuli were presented rapidly, the 40 dB stimuli were randomly presented 120 times, and the 60 and 80 dB stimuli, 60 times each per block. When stimuli were presented slowly, the 40 dB stimuli were presented 24 times and the 60 and 80 dB stimuli, 12 times each per block. Four blocks of stimuli for each condition were presented during wakefulness and in each stage of sleep. The duration of stages N3 and REM of sleep was too short to permit the presentation of all blocks within a single night. Subjects therefore spent two non-consecutive nights in the sleep lab. To decrease possible habituation effects, the time between recording nights varied between one and four weeks. Two complete blocks for each condition and stage were presented during each night.
Auditory stimuli were synthesized by a SoundBlaster 16-bit waveform generator card. Stimulus level was verified using a Bruel and Kjaer 2209 sound level meter and Bruel and Kjaer 4152 artificial ear with a 2 cm 3 coupler. The calibration of the artificial ear was checked with a Bruel and Kjaer 4220 pistonphone. Background sound level in the sleep room was less than 35 dBA during sleeping hours.
Procedure
Subjects arrived at the laboratory at approximately 20:00 hours to allow time for electrode application procedures, hearing threshold assessment, and waking data collection. Prior to the start of the experiment, the hearing threshold for each of the participants was assessed. Subjects were randomly presented with brief (50 milliseconds) 1000 Hz tones having an intensity of -10, +10 or +20 dB nHL (The normal hearing threshold level (nHL) was established using 12 young adults, none of whom participated in this experiment. This normative threshold was estimated using the method of limits with auditory stimulus equipment identical to that used in the present study). A total of 60 stimuli were presented at an interval that varied from two to three seconds. Subjects were asked to button press upon detection of the stimulus; all subjects were able to reliably detect (detection rate of .70 or more) the +10 and 20 dB nHL auditory stimuli. The detection rate for the below threshold -10 dB nHL stimulus did not exceed .10 for any subject.
Following the placement of electrodes, subjects were taken to a separate double-walled, sound-attenuated testing chamber. The waking data were collected between 22:00-23:00 hours. Subjects were asked to read a book or magazine of their choice and ignore the auditory stimuli. Horizontal eye movements were monitored to verify compliance with these instructions. Subjects were permitted to sleep at 23:30 hours. An experienced scorer carried out on-line classification of the stage of sleep and monitored the recording for evidence of arousal/movement. Ten minutes after entering definitive stage N2 sleep (marked by delta activity in the EEG, spindles and K-Complexes), stimuli were again presented in separate blocks. Time between blocks was approximately 10-15 minutes. If there was evidence of arousal or movement, stimulus presentation was paused and only resumed again if the subject returned to the same stage of sleep. In actual fact, arousals and movements were relatively rare, occurring on fewer than 10% of stimulus blocks. Only blocks in which the subject did not change sleep stage (i.e., the entire block consisted of a homogenous stage of sleep) were retained for further analysis. Most of stage N3 accumulates in the first half of the night while most of stage REM accumulates in the last half of the night. Possible differences in processing between the stages N3 and REM might thus be explained by time-of-night effects. An equal proportion of stage N2 occurs approximately in the two halves of the night. Stage N2 data were therefore compared in the first and second halves of the night to examine time-of-night differences.
Physiological recordings
The EEG was recorded from gold electrodes placed at midline frontal, central and parietal scalp sites (Fz, Cz, Pz, respectively) and referenced to the left mastoid. Horizontal eye movements (hEOG) were recorded from electrodes placed at the outer canthus of each eye. Vertical eye movements and blinks (vEOG) were recorded from electrodes placed at the supra- and infra-orbital ridges of the left eye. A ground electrode was placed on the forehead. Inter-electrode impedances were kept below 5 kOhms. The high frequency filter was set at 35 Hz. The time constant was one second. The physiological signals were sampled 256 times/second and stored continuously on hard disk for later off-line scoring and reconstruction.
Data analysis
Eye movement and blink artifact in the waking state were corrected using an algorithm operating in the time and frequency domain. [21] Eye movements during REM sleep are less problematic. This is because they occur at random during this stage of sleep (i.e., are not time-locked to the stimulus) and mainly consist of horizontal rather than vertical eye movements. Horizontal eye movements cause minimal artifact in midline scalp recordings. The higher intensity auditory stimuli presented at the slow rate at times elicited a K-Complex. The major component of the K-Complex is a very large amplitude (100-200 μV) negative deflection peaking at about 550 milliseconds that may overlap and summate with the earlier N350 thus distorting its true amplitude. For this reason, trials in which a K-Complex (defined as a negativity exceeding 75 μV peaking between 450-650 milliseconds following stimulus presentation) was elicited were manually identified and rejected from further analysis.
Off-line, the different stages of sleep were classified by two experienced scorers according to the American Academy of Sleep Medicine (AASM) scoring method. [1] A 16-second epoch was used for sleep staging rather than the usual 30-second epoch in order to increase the precision of the scoring. In cases of stage ambiguity, the entire eight-minute block of data was excluded from further analysis (In actual fact, rater disagreement was very rare because of the on-line rejection procedure. If a change of sleep stage occurred during the brief 8-minute presentation period, the entire block would have been rejected. Each block therefore represented an unambiguous stage of sleep). The continuous EEG recording was subsequently divided into 500-millisecond duration "trials" beginning 50 milliseconds prior to the onset of the stimulus. The single 500-millisecond trials were then sorted and averaged for each subject according to electrode site, intensity level, rate of presentation and stage of sleep. Data across blocks were collapsed, to improve the signal-to-noise ratio of the ERP. Data across different nights were found to be essentially identical and, therefore, collapsed. Trials in which the EEG exceeded 100 μV in the waking state were considered abnormal and therefore rejected. During sleep, trials in which the EEG exceeded 150 μV were also rejected. The resulting averages were digitally filtered using an inverted FFT algorithm with a 1-20 Hz bandpass.
The average of the 50-millisecond pre-stimulus activity served as a zero voltage baseline from which the ERPs were measured. During wakefulness, the peaks of both N1 and P2 were difficult to measure at the lowest stimulus intensity levels in the individual subject waveforms, particularly when stimuli were presented rapidly. During sleep, N1 was difficult to identify even at higher intensity levels. Instead of maximum peak detection methods, the ERP deflections were therefore quantified by computing mean ERP amplitudes. [22] Based on the grand averages (average of all individual subjects' averages), the peak latencies of N1, P2 and N350 (during sleep) were determined for each intensity level and each stage of sleep. Subsequently, all data points within ±20 milliseconds of the peak latency of N1, P2 and N350 were averaged in the corresponding individual subject waveforms. A P3a was also apparent in the waking data for the moderate and high intensity stimuli and at times, in stage REM of sleep. P3a was also quantified as the average of all data points within ±20 milliseconds of its peak latency. N1, P2, P3a and N350 were quantified at Cz, the site at which their amplitude tends to be largest.
Two-way repeated measures ANOVAs were computed to compare the effects of intensity (40, 60, 80 dB SPL) and stage of sleep (wake, N2 early, N3, N2 late, REM). Separate ANOVAs were run on the fast and slow rate of presentation data. Results were considered to be significant at an alpha value of .05. Greenhouse-Geisser correction factors were applied when appropriate.
| Results | | |
Fast rate of presentation
The grand-averaged waveforms following presentation of the 80, 60 and 40 dB SPL stimuli within the waking and sleep states are illustrated in [Figure 1]. Very large changes in the ERP morphology are apparent between the waking and NREM sleep states. ERPs return to a more wake-like appearance during stage REM.
A large amplitude N1 peaking at about 100 milliseconds was apparent in the waking state but difficult to observe during sleep, in particular during the NREM stages. During NREM sleep, N1 was therefore measured based on the peak latency that was observed during wakefulness. A significant Stage ΄ Intensity interaction was revealed, F (8, 64) = 14.66, P<.01. Simple main effects testing procedures were applied to isolate the sources of this interaction. The amplitude of N1 significantly decreased with decreasing intensity level during wakefulness and during REM sleep. N1 amplitude was not significantly affected by intensity level during any of the NREM stages. N1 differences among the various stages were also found at each intensity level. At each intensity level, N1 was significantly larger in the waking state than in either NREM or REM sleep. Further, the REM N1 was significantly larger than that observed during any of the NREM stages following presentation of the 80 dB SPL stimulus, but not the 60 or 40 dB stimulus.
N1 was followed by a positivity, P2, peaking at about 180 milliseconds. Significant main effects were found for Intensity, F (2, 16) = 26.58, P<.01 and Stage, F (4, 32) = 5.64, P< .01. Tukey post-hoc testing indicated that the amplitude of P2 systematically decreased as the intensity of the stimulus fell from 80 to 60 to 40 dB SPL. During NREM sleep, the amplitude of P2 was more than twice as large as that recorded during wakefulness and stage REM of sleep. P2 amplitude did not significantly vary within the different NREM stages. Moreover, the amplitude of the REM and waking P2 did not significantly vary.
During wakefulness, a small amplitude P3a was visible following presentation of the loud 80 dB SPL but not for the lower intensity level stimuli. A P3a was not visible at any time during sleep. This was confirmed by the application of confidence interval testing procedures. This procedure determined the probability that the mean value of P3a fell within an upper or lower range, relative to the zero baseline. If the lower limit was less than 0 μV (i.e., was a negative polarity), the peak was not considered to reflect a P3a. Only the 80 dB SPL stimulus in the waking state elicited a significant P3a.
A late negative deflection, the N350 was elicited during sleep. Confidence interval testing indicated that it was not elicited by any stimulus during wakefulness. The ANOVA was therefore carried out on only the sleep data. A significant Stage x Intensity interaction was revealed, F (6, 48) = 5.25 P< .01. The amplitude of the N350 significantly decreased as stimulus intensity level was lowered in all NREM stages and in REM sleep. The amplitude of the N350 did not significantly vary between stage N2 early, N2 late or N3 at any intensity level. It was much larger during the NREM stages than during stage REM except following presentation of the low intensity 40 dB SPL stimulus when the differences were not significant.
Slow rate of presentation
[Figure 2] illustrates the effects of slowing the rate of stimulus presentation from, on average, every two seconds to, on average, every 10 seconds. Generally, the amplitudes of N1 and P2 increased slightly. Much larger changes were seen for the amplitudes of P3a and N350 as these deflections became more prominent. The overall effects of stimulus intensity level and stage were, however, quite similar to those observed when stimuli were presented more rapidly.
In the waking state, N1 peaked somewhat later at about 120 milliseconds. Again, during NREM sleep, N1 was difficult to observe and was therefore measured based on the peak latency observed during wakefulness. A significant Stage x Intensity interaction was revealed, F (8, 64) = 12.35, P< .01. The sources of the interaction were similar to those observed when stimuli were presented rapidly. Thus, the amplitude of N1 significantly decreased with decreasing intensity level during wakefulness and during REM sleep, but the N1 was at baseline level during NREM sleep, regardless of stimulus intensity level. The amplitude of N1 was significantly larger in wakefulness compared to that observed in either stage REM or the NREM stages for all stimulus intensity levels. The amplitude of N1 in stage REM was significantly larger than in the NREM stages, but only for the 80 dB intensity level.
Significant main effects of intensity level and stage were again found for the amplitude of P2, F (2, 16) = 33.72 P< .01 and F (4, 32) = 9.14, P< .01, respectively. Its amplitude systematically decreased as the intensity level was lowered. The amplitude of the NREM P2 was much larger than that observed in the waking state or during REM sleep. Again, the amplitude of P2 did not significantly differ between the waking state and REM sleep.
A P3a was observed following the presentation of both the 80 and 60 dB SPL stimuli during wakefulness and its presence was confirmed by confidence interval testing. A small amplitude P3a was elicited by the 80 dB SPL stimulus during REM sleep but it was not significantly different from the zero voltage baseline level. Confidence interval testing again confirmed that a P3a was not elicited by any stimulus during the stages N2 or N3. However, a remarkably large (> 25 μV) N350 was apparent during the NREM stages. Confidence interval testing indicated that N350 was not elicited in either stage REM or wakefulness. The amplitude of N350 during NREM sleep significantly decreased as a function of decreasing intensity level, F (2, 16) = 19.73 P< .01. The amplitude of the N350 did not significantly differ among stages N2 early, N2 late and N3.
| Discussion | | |
The purpose of this study was to employ ERP methods to monitor the extent of information processing of acoustic stimuli that may disrupt sleep. Previous ERP sleep studies have concentrated on relatively high intensity stimuli (> 60 dB SPL) presented at rapid rates (> one stimulus per two seconds). The present study included these stimulus parameters, and largely replicated previous findings. In real-life situations, however, environmental noise rarely occurs every two seconds and often is of low intensity levels. For this reason, stimuli were also presented much more slowly, about once every 10 seconds. Furthermore, lower intensity 40 and 60 dB SPL stimuli were also employed.
In the waking state, the effects of stimulus intensity level and rate of presentation are well documented. When stimulus intensity increases and presentation rate decreases, the amplitude of N1, reflecting the output of the transient detector system, becomes more prominent. [4],[5],[6],[7] The results of the present study are in accordance with these findings. Further, in the NĠĠtĠnen model, when the output of the transient detector system reaches a critical level, processing in the central executive controlling cognitive resources is interrupted and attention is involuntarily switched to the processing of the auditory stimuli. [3] The P3a reflects this involuntary process and therefore can be taken as a measure of task disruption, at least in the waking state. Our wakefulness results show that only the 80 dB SPL stimuli elicited a P3a during the fast rate of presentation, whereas a P3a was also present following the 60 dB SPL during the slow rate of presentation. Thus, slowing the rate of stimulus presentation will increase the risk of unwanted attention capture not only for high but also for moderate intensity level stimuli.
Stimuli that are most likely to disrupt sleep are those that capture attention and intrude into consciousness in the waking state. In order to sleep, however, consciousness of the external environment must be prevented. The results of the present study offer an explanation of the means by which processing of such stimuli is inhibited during sleep.
NREM sleep
During both N2 and N3 stages of NREM sleep, N1 was not visible (i.e. at baseline amplitude) regardless of stimulus intensity level and rate of presentation. This would imply that inhibition of auditory information processing during NREM must occur prior to input into the transient detector system. Importantly, because of the minimal activation of this system, it would be unlikely that an interrupt signal would be sent to the central executive resulting in an intrusion into consciousness. Cote et al. [11] indicated that even very loud 100 dB SPL stimuli could not elicit an N1 during NREM when stimuli were presented rapidly. Further, Atienza et al[23] showed that N1 could not be elicited during NREM following moderate intensity stimuli presented every nine seconds. The present results indicate that this is the case for low to high intensity level, when presented rapidly or slowly.
The absence of an N1 does not mean that all processing simply ceases during NREM sleep. Obviously, certain stimuli must be processed for sleep to be reversed (i.e., an awakening) or for it to be disturbed in the form of a change in sleep stage or a brief micro-arousal. Even though N1 could not be elicited, a large P2 and subsequent N350 were apparent, a finding that replicates many other studies. The present study demonstrates that these ERP deflections were still apparent, albeit reduced, following low intensity stimuli. Campbell and Colrain [9] offer a detailed explanation of why N1 decreases while P2 increases in amplitude during NREM sleep. In brief, the N1-P2 observed in the waking state is overlapped by another negative-going deflection labeled the Processing Negativity (PN). [3] The PN reflects attention-related processing that is required in order to determine the relevance of that stimulus input, at which point further processing can cease if it is deemed irrelevant. Regardless of relevance, in the waking state, this attention-related PN activity summates with the scalp-recorded N1 causing it to appear larger (more negative-going) and P2 to appear smaller (less positive-going). This active attention-related route to consciousness must be halted in order for sleep to occur, and thus, N1 appears to be much reduced (less negative-going) and P2 much enhanced (more positive-going) during sleep.
A stimulus can still disturb sleep even if it does not result in an awakening or if the subject is not conscious that it was presented. There is good evidence that the N350, a deflection that is characteristic of NREM sleep, is associated with the inhibition of processing and the prevention of consciousness. It is initially apparent during the sleep onset period only when the subject no longer signals awareness of the external stimulus. [16],[17],[24] Importantly, the present study indicates that the N350 was much larger when stimuli were presented slowly and was even apparent when intensity levels were as low as 40 dB SPL. The amplitude of N350 can be interpreted in terms of the extent to which inhibition of processing is required, much more so to loud and rarely presented stimuli than to softer, frequently presented stimuli. It can thus be used as a predictor of the potential for an external signal to disrupt sleep. During NREM sleep, the inhibition associated with the N350 may prove to be insufficient to protect sleep. Bastien and Campbell [19] hypothesize that a secondary protective system, reflected by the K-Complex (a later and much larger negative ERP) is triggered when the N350 reaches a certain, critical threshold. The K-Complex is now considered by some researchers to be a marker of the fragmentation of sleep. [2]
REM sleep
Our results show that during REM sleep, N1 returned to about 20% of its waking amplitude. Furthermore, a small late P3a-like positivity was apparent in the ERP to the 80 dB SPL stimulus, but only when stimuli were presented slowly. The amplitude P3a did not, however, significantly differ from the zero voltage baseline level. This P3a was reduced in amplitude compared to that reported by Cote et al. [11] and Macdonald et al. [25] The intensity of their rarely-presented stimuli was, however, louder (100 and 90 dB SPL, respectively). There is some debate on the nature of the P3-like wave that has been reported during REM sleep. [26],[27] Certainly, during REM sleep, it would appear that the acoustic power of a stimulus has to be very high and it must occur infrequently in order for a P3a to be elicited. There is, however, also some evidence that psychologically relevant stimuli, such as the subject's own name [14] or stimuli that have taken on relevance prior to sleep [28] can elicit a P3-like deflection during REM sleep. The conditions, under which the different P3-like deflections are elicited during sleep, and crucially, the consequences of the different P3s on the quality of sleep, need to be investigated further.
| Conclusions | | |
ERPs have the advantage that they provide a direct measure of the extent of information processing and may serve to predict when acoustic noise will lead to peripheral-defined arousals/awakenings and when they will not. Stimuli in the present study were selected specifically because they have previously been shown not to awaken the sleeping subject. In spite of the fact that they rarely awoke the subject or produced arousals in the ongoing EEG (as defined by the recent AASM criteria), the ERP data do indicate that moderate to loud acoustic stimuli can potentially disrupt sleep, if presented rapidly but even low intensity acoustic stimuli can potentially disrupt sleep, if presented slowly.
In both laboratory and field studies on the effects of traffic and industrial noise on sleep, low intensity stimuli at about the same level as those employed in the present study (40-65 dBA) have at times awoken the sleeper but more often produced short- to long-duration arousals as measured by changes in sleep stage, in the ongoing EEG, or in peripheral measures such as the heart rate. [29],[30],[31] These noise stimuli are, however, acoustically much more complex; have considerably slower rise- and fall-envelopes and occur much less often than the abrupt pure tones used in this study. Importantly, the duration of the noise events is almost always very much longer than the very brief 50-millisecond tone pips that we employed. The acoustic power in a long duration stimulus is of course considerably more than that in a brief duration stimulus. An ERP labeled as the sustained potential (SP) is associated with the continued presentation of a long duration stimulus. [32] Little is, however, known about the effects of sleep on the SP (for more details on the SP, see the review by Campbell in this Special Edition). A large majority of the applied studies quantify arousals through slow changes in the EEG or through changes in peripheral, "autonomic" signals such as heart rate, respiration and skin potentials. Future ERP studies incorporating the types of ecologically-valid stimuli employed in field studies may thus prove worthwhile.
| Acknowledgments | | |
This research was funded by research grants from Natural Sciences and Engineering Research Council of Canada (NSERC). The data were collected and analyzed while A. Muller-Gass was a postdoctoral fellow at the School of Rehabilitation, University of Ottawa. The authors also wish to acknowledge the contribution of Parastoo Jamshidi and Margaret Macdonald in the collection of the data.
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Correspondence Address:
Alexandra Muller-Gass
Defence Research and Development Canada, 1133 Sheppard Avenue West, P.O. Box 2000, Toronto, Ontario M3M 3B9
Canada
 Source of Support: Research Grants from Natural Sciences and Engineering Research Council of Canada (NSERC)., Conflict of Interest: None  | Check |
DOI: 10.4103/1463-1741.63213
[Figure 1], [Figure 2] |
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