A High Density EEG Comparison of Sleep, Sleep Initiation, and Arousal Patterns in Insomnia Patients and Normal Controls
Conditions: Primary Insomnia
Sponsor: University of Wisconsin, Madison

 
 
 
 
 
 
A High Density EEG Comparison of Sleep, Sleep 
Initiation and Arousal Patterns in Insomnia Patients 
and Normal Controls 
 
 
Principle Investigator:   
Ruth Benca, MD, PhD 
Co-Investigators:  
 
Brady Riedner, PhD 
 
 
 
 
 
Meredith Rumble, PhD 
Institutional Affiliation: 
University of Wisconsin-Madison 
Protocol Version:  
 
9/8/2015 
Funding Sponsor:  
 
MERCK Sharp and Dohme Corporation 

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1. Project Summary 
 
Insomnia, defined as a subjective report of difficulty initiating sleep, maintaining sleep, 
and/or non-restorative sleep, leads to significant daytime dysfunction and increased health risks. 
A commonly held hypothesis is that insomnia is caused by a state of hyperarousal, but the 
neurobiological mechanisms of hyperarousal in insomnia are poorly understood, in part because 
of limitations in our ability to image the brain during normal human sleep with sufficient 
temporal resolution. Insomnia is particularly prevalent among depressed individuals, yet little is 
known about whether this same state of hyperarousal is present in comorbid depression and 
insomnia. Furthermore, the efficacy of insomnia treatment is judged by subjective report of the 
patient and demonstration of changes in sleep latency and/or sleep amount which are generally 
small in magnitude; there are currently no data to demonstrate that insomnia treatments correct 
any functional abnormalities in the sleep process that likely contribute to neurobehavioral 
abnormalities and health risks. The goals of the proposed study are to use hdEEG to define 
abnormalities in specific aspects of sleep in insomnia patients with and without depression 
compared to healthy sleeping control subjects to define biomarkers that will both increase our 
understanding of the pathophysiology of insomnia as well as provide targets to assess treatments 
for insomnia. 
 
2. Background and Significance 
 
2.1 Overview 
 
Insomnia is the most common sleep disorder (Ohayon 2002), with at least 10% of the 
general population suffering from chronic insomnia severe enough to impact adversely on health 
and quality of life (Benca 2005, Roth et al 2001). When combined, the high prevalence rate, 
daytime impairments, and other adverse effects of insomnia on the outcomes of comorbid 
psychiatric or medical conditions push estimates of the direct and indirect costs of chronic 
insomnia up to tens of billions of dollars annually (NIH 2005).  There is mounting evidence that 
insomnia contributes to increased risk for development of hypertension and diabetes (Vgontzas 
et al 2013), heart failure and overall mortality (Laugsand et al 2013), and mood disorders 
(Baglioni et al 2011, Suh et al 2013).  Currently, insomnia is a clinical diagnosis based on 
subjective complaints about quantity and/or quality of sleep that result in daytime impairment. 
Symptoms include difficulty initiating sleep, difficulty maintaining sleep, waking up too early, 
and sleep that is often described as “non-refreshing” or “non-restorative”. The pathophysiology 
of insomnia is poorly understood and there are no objective diagnostic measures currently in 
existence. The evaluation of treatment options, including behavioral therapy and 
pharmacotherapy, also suffers from the lack of an objective measure of sleep efficacy, relying 
instead on traditional objective measures of sleep quantity and/or subjective reports of sleep 
quality (NIH 2005).  
 
 
 
 
 
 

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2.2 Examining cortical sources of abnormal activity during sleep in insomnia with hdEEG 
  
One of the most common theories of insomnia is focused on the idea of hyperarousal (for 
a review see (Riemann et al 2010)).  Although there is support for this theory from a wide range 
of fields, including physiological and neuroendocrine studies, the majority of evidence comes 
from either electroencephalographic (EEG) or neuroimaging investigations.  Several studies have 
reported increases in higher frequency EEG activity (i.e. beta and gamma bands) during various 
stages of sleep (Buysse et al 2008, Freedman 1986, Krystal et al 2002, Merica et al 1998, Perlis 
et al 2001a, Perlis et al 2001b) suggestive of an aroused brain.  Unfortunately, all of these studies 
derived their results based on the few EEG channels typically included in a routine sleep 
laboratory polysomnography (PSG), making it impossible to determine if the increase in high 
frequencies was ubiquitous across the whole brain or whether certain cortical areas were more 
aroused than others.  The seminal work of Nofzinger et al. (Nofzinger et al 2004) using positron 
emission tomography (PET) provided the first direct evidence of regional hyperarousal in 
insomnia, showing that the attenuated decline of metabolism, although global, was highest in 
several cortical regions, including the insular cortex, anterior cingulate, and prefrontal cortices.  
However, although PET imaging provides increased spatial resolution over limited channel EEG, 
it provides a limited imaging window (approximately 20 minutes) that cannot provide temporal 
information across an entire night of sleep or examine the processes sleep initiation or arousal 
with sufficient temporal resolution.  An earlier study using single photon emission tomography 
(SPECT), instead showed decreased blood flow (i.e. decreased activity) across all regions of 
interest (including frontal medial and lateral cortices) around the time of sleep onset (Smith et al 
2002).  Most likely these conflicting 
results are related to limited time 
imaging windows (both during sleep 
onset, but SPECT integrating only 
over several minutes).  What is 
needed is to explore the role of 
hyperarousal in insomnia is an 
imaging tool that is able to 1) resolve 
temporally whether hyperarousal is 
constant, fluctuates based on the 
ongoing pattern of EEG, or is a 
specific, abnormal reaction to 
incoming stimuli; 2) resolve 
spatially the difference between 
global and regional cortical arousal; 
and 3) is conducive to examining sleep.  
Recent advances in electroencephalographic recording techniques have produced new 
ways to probe the process and function of sleep.  Through the use of high-density EEG (hdEEG, 
256 channels), we are able to approach the spatial resolution of other brain imaging modalities 
while affording the millisecond temporal resolution of EEG and providing a direct measure of 
the underlying brain activity, unlike the indirect and/or secondary biophysical signals of brain 
hemodynamics/metabolism obtained with PET or fMRI that are suboptimal for exploring the 
short-lived spatio-temporal dynamics of many brain processes.  While most EEG analysis is 

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performed using scalp voltages, the use of hdEEG provides sufficient data to accurately model 
the cortical sources of scalp electrical activity.  Our group at UW has developed hdEEG in sleep 
as a neuroimaging tool and demonstrated its utility for studying the role of sleep in normal brain 
function. For example, we have shown that both slow waves and spindles, characteristic sleep 
EEG waveforms, are useful measures of localized brain activity.  HdEEG has revealed that sleep 
is more intense (more slow wave activity, EEG power between 0.5 – 4 Hz) in the cortical regions 
that learn the most during waking, thus demonstrating that not only do slow waves reflect sleep 
intensity, but they also reflect the underlying the cellular need for sleep in a regionally specific 
manner (Huber et al 2007, Huber et al 2006, Huber et al 2004, Huber et al 2008, Matta et al 
2010, Sarasso et al 2010). Additionally, sleep slow waves have been shown to travel across the 
cortical mantle from distinct origins (Massimini et al 2004).  Notably, the cortical hot spots for 
slow wave origination and propagation include the insula and the anterior cingulate, PET-
identified regions of hyperactivation in insomnia (Murphy et al 2009)(Figure 1). 
We have extensive experience using hdEEG technology to study brain activity and sleep 
abnormalities in various neuropsychiatric 
conditions, including insomnia.  We have 
identified sleep spindle abnormalities in 
schizophrenia, which have been suggested 
to have an etiopathologic role in the 
disorder and may be one of the most 
specific biomarkers for the disorder 
(Ferrarelli et al 2007, Ferrarelli et al 2010).  
In depression, we have found evidence for 
abnormalities in sleep homeostasis through 
analyses of brain activity during sleep and 
wakefulness prior to and following 
nocturnal sleep (Goldstein et al 2012, 
Plante et al 2013b) as well as a regionally  
specific decrease in slow waves in 
hypersomnolent depressives (Plante et al 
2012b).  Our preliminary work in insomnia 
under previously approved protocols H-
2007-0150, and continuing with H-2009-
0019, (comparing 9 subjects with primary 
insomnia, 9 age- and sex-matched 
depressives and 9 matched healthy sleepers, 
Table 1) revealed that beta and gamma 
activity were increased globally in both 
insomnia and depression in comparison to 
controls, but only alpha activity, 
particularly in deeper sleep (stage N3) distinguished primary insomnia from depressed and 
control subjects.  Notably, when localized in the cortex, these increases in alpha during N3 sleep 
were most prominent in primary sensory and associative cortices (including somatosensory, 
auditory and visual cortices), suggesting that even during the deepest stage of sleep, sensory 
areas are still relatively active in insomnia relative to controls (Figure 2).  Our primary aim, then, 
would be to extend and confirm this result in a larger group of primary insomnia participants in 

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order to increase our localization power, to see whether this increase persists throughout the 
night during normal sleep, or is specific to stage N3, and to determine if it is particularly 
associated with sleep onset and/or sleep maintenance difficulties; we will also examine how this 
finding relates to the process of falling into and arousing from sleep. 
   
2.3 Defining abnormal activity during sleep transitions in insomnia with hdEEG  
 
 
Recently we have begun to 
use hdEEG to examine the process 
of falling asleep in normal subjects.  
Although it has long been 
recognized that falling asleep 
involves a process developing over 
time (for instance see Hori’s nine-
stage system and EEG waveforms, 
(Hori et al 1994), how this process 
develops across the cortex is just 
now being elucidated.  We recently 
demonstrated that cortical areas that 
have been overly taxed during the 
day may go offline even while the 
rest of the cortex remains awake 
(Hung et al 2013).  Moreover, we 
have used serial awakenings 
(repeatedly presenting stimuli to 
subjects to systematically wake them up throughout the night) in a group of normal subjects to 
describe how different waveforms contribute to falling asleep in a regionally specific manner by 
examining hdEEG during equally distributed time periods between the end of posterior alpha 
(10-20 channel Oz) and the first slow wave burst (2 consecutive slow waves without an arousal 
(Siclari et al. in preparation).  In good sleeping controls, slow waves followed two spatially and 
temporally distinct processes during the transition from wakefulness to sleep.  The early process 
was characterized by isolated, large amplitude slow waves that involved mainly the frontal 
regions and was associated with high gamma power.  The late process was marked by numerous 
smaller slow waves that tended to originate more diffusely over the cortex, and to involve also 
the temporal, lateral parietal and occipital brain regions.  The falling asleep process is thus 
characterized by a transition from predominantly local to increasingly global sleep patterns.  This 
process may be disrupted in insomnia, particularly given the similarities between areas from 
which slow waves involved only later in the falling asleep process originate and areas exhibiting 
alpha activity during deep NREM sleep in insomnia patients. 
Certainly sleep initiation is not the only potential problem in people with insomnia; 
frequent awakenings during the night are commonly reported by many patients.  However, there 
is surprisingly little literature examining the response of insomnia subjects to arousing stimuli.  
Limited channel event related potential studies during sleep seem to support the theory of 
hyperarousal in insomnia subjects, especially during the sleep onset period (Bastien et al 2008, 
Devoto et al 2005, Spiegelhalder et al 2012, Yang & Lo 2007), despite similar auditory arousal 
thresholds as controls (Mendelson et al 1986).  However, without the ability to localize the 

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cortical sources of the brain’s response to such stimulation, it is difficult to draw strong 
conclusions.  We now know from other imaging techniques as well as from our own work with 
hdEEG that external stimuli do reach the cortex even during the deepest stages of sleep (Dang-
Vu et al 2011, Riedner et al 2011).  The degree to which such stimuli could be locally arousing 
the cortex is unknown, and it is likely that insomnia patients may show different patterns of 
reactivity than healthy sleepers.    
   
In summary, the use of hdEEG to study sleep in insomnia with and without depression 
affords a unique opportunity to image the brain with exquisite temporal resolution throughout the 
sleep period.  Not only can we study the spatial and temporal dynamics of sleep throughout the 
night, but we can also examine the processes of falling asleep and arousing from sleep; these 
critical events are likely to be particularly important for understanding insomnia, since they 
reflect the primary complaints of insomnia patients—difficulty falling asleep and difficulty 
maintaining sleep.  No other currently available imaging technique is capable of providing 
functional imaging data throughout the sleep process or in individuals who can sleep without 
restriction of their normal nocturnal movement. Furthermore, in contrast to other imaging 
procedures, hdEEG is relatively inexpensive, portable, and can performed repeatedly making it 
ideal for longitudinal studies.  Our preliminary data in a small number of subjects already shows 
significant differences in topographic patterns of sleep EEG activity in comparison not only to 
healthy sleepers but also depressed subjects, suggesting that the technique will be able to detect 
abnormalities in brain activity patterns that are specific for insomnia.  Even more importantly, 
we can localize one of these insomnia-specific abnormalities, increases in alpha activity during 
deep stages of sleep, to sensory areas of the cortex, strongly suggesting that these specific areas 
remain relatively activated during sleep.  The proposed study will provide novel data regarding 
mechanisms of insomnia and will be used to design future studies that will assess the effects of 
insomnia treatments on patterns of abnormal brain activity.  The identification of specific 
abnormalities during sleep as well as in the processes of falling asleep or arousing from sleep 
will potentially allow us to distinguish the effects of pharmacologic treatments that promote 
sleep through different mechanisms, such as by increasing GABA transmission, blocking 
histamine receptors or blocking orexin receptors.  
 
3. Specific Aims 
 
3.1. Primary Objectives: 
 
1. Examine differences in the cortical sources of sleep waveforms in insomnia patients with and 
without depression compared to healthy sleeping controls. 
2. Define cortical source abnormalities in the processes of falling asleep and arousing from 
sleep in insomnia patients with and without depression compared to healthy sleeping 
controls. 
 
3.2 Secondary Objectives: 
 
1. Correlate abnormalities in sleep EEG patterns with specific insomnia symptoms, including 
sleep onset difficulties, sleep maintenance problems, nonrestorative sleep and daytime 
dysfunction.  

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2. Define abnormalities in overnight changes in waking EEG activity in insomnia patients with 
and without depression compared to healthy sleeping controls. 
3. Explore whether abnormalities in sleep and waking EEG activity in insomnia patients, with 
and without depression, normalize following treatment with a sleep medication. 
 
 3.3 Clinical Hypotheses: 
 
1. Insomnia patients will show increased regional EEG alpha activity in sensory cortical areas 
particularly during sleep. 
2. Insomnia patients will show abnormalities in the process of sleep initiation, including 
regional sources of high frequency EEG activity that will interfere with the normal 
progression of the sleep process.  
3. Insomnia patients will show abnormalities in the regional patterns of cortical arousal 
responses to external stimuli during sleep, particularly in the sensory cortical areas exhibiting 
increased alpha activity.  
4. Abnormalities in sleep EEG patterns may be correlated with specific insomnia symptoms, 
particularly difficulty with sleep initiation or maintenance. 
5. Waking EEG in insomnia patients will not show overnight recovery compared to controls, 
which will be correlated with specific EEG abnormalities during sleep, such as elevations in 
higher frequency activity. 
6. Explore whether insomnia patients with and without depression differ in abnormalities in 
sleep EEG patterns. 
 
4. Research Design and Methods 
 
4.1 Study Population 
 
Studies will be carried out in 20 individuals with insomnia, 20 individuals with 
depression and insomnia, and 20 age- and sex-matched healthy controls (women and men aged 
18-45 years who are English speaking).  We will ensure that our sample includes individuals 
with both sleep onset and maintenance issues, and that at least 1/3 of the sample is male.  Strict 
inclusion/exclusion criteria will be applied to the sample to reduce the variability of the data and 
avoid confounding factors.   
 
4.1.1 Inclusion Criteria 
 
To be included in the insomnia group, participants will need to score ≥ 11 on the ISI 
(Morin et al 2011), meet RDC (Edinger et al 2004) for insomnia, and have insomnia for 6 
months or longer. To be included in the depression and insomnia group, participants will need to 
meet insomnia criteria and additionally meet criteria for a Major Depressive Episode as assessed 
by the SCID. To be included in the healthy control group, participants will need to score ≤ 7 on 
the ISI and not meet RDC for insomnia.   
 
4.1.2 Exclusion Criteria 
 

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Exclusionary criteria for all participants will include: age younger than 18 or older than 
40; inability to speak, read, and write in English; body mass index > 40; history of significant 
head trauma or loss of consciousness > 30 minutes; a score less than 27 on the Mini-Mental 
Status Exam (MMSE) (Folstein et al 1975); regular psychotropic medication use within two 
weeks of beginning the protocol with the exception of those in the depression and insomnia 
group (these individuals will be allowed to remain on psychotropic medications with the 
exception of sleep medications or other psychotropic medications with large concern for 
impacting hdEEG recordings; if participants are on medications of concerns, they will be 
excluded from the study) (Bastien et al 2003, Borbely et al 1985, Brunner et al 1991, Feige et al 
1999, Monti et al 2000); current regular tobacco use; > 3 caffeinated beverages per day; 
significant neurologic or medical illness, including dementia; women who are pregnant, < 6 
months post-partum, or planning to become pregnant during the study; and left-handedness (due 
to effects on sleep topography). Participants will be excluded if they indicate imminent risk for 
self-harm or suicide (APA 1994), alcohol or drug dependence/abuse within the last 6 months, or 
any other primary sleep disorder including apnea, restless legs, circadian rhythm disorder, 
parasomnia, or primary CNS hypersomnia. To ensure exclusion of participants with a circadian 
rhythm disorder, all participants must demonstrate a typical sleep phase between 9pm and 9am 
(confirmed via self-report and actigraphy). To ensure exclusion of participants with sleep apnea, 
participants must exhibit an apnea-hyponea index (AHI) less than 10 (as assessed via 
ApneaLink). Participants in the insomnia and control groups will also be excluded if they met 
criteria for any active DSM-IV Axis I disorder other than insomnia. Participants in the 
depression and insomnia group will be excluded if they indicate a lifetime history of bipolar 
disorder or schizophrenia.  
 
4.1.3 Subject Identification and Recruitment 
 
Subjects will be recruited via advertisements (i.e., newspaper, internet, newsletters, local 
postings), referrals from health care providers, referrals from patient advocacy/support groups, 
and word of mouth. A phone screening will be used to pre-select the subjects eligible to 
participate before their first visit to our laboratory (see section 4.2.1).  
Subjects with insomnia and/or depression will primarily be recruited via advertisements 
and referrals from local physicians and mental health care providers, including through the UW 
Sleep Disorders Center and the UW Department of Psychiatry. Clinicians, including 
investigators involved with this study, may inform their referrals and patients about the study, 
either verbally or with printed materials approved by the IRB. Patients who may be eligible will 
also be reviewed through the medical chart. Following the review of their medical record, 
providers will receive a prompt that the patient is potentially eligible for the study along with a 
quick checklist of I/E criteria to complete. The prompt will be delivered via HealthLink message, 
and the checklist will be placed in the provider's clinic mailbox. Providers introducing referrals 
or patients to the study can provide their patients with the study’s contact information to contact 
us directly themselves or will obtain the patient's permission via permission to contact form prior 
to providing researchers with contact information. Patients may have the option to meet with 
study staff face-to-face before leaving the clinic from an appointment with his/her provider 
(contingent upon study staff availability and patient’s preference) versus being contacted by 
phone for the screening interview. If a potential subject is a patient of one of the investigator’s 
clinic patients, another investigator who does not have a clinical relationship with the subject 

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will conduct the screening interview. The clinical care of the potential subject will in no way be 
affected by their decision to participate or not. We will also recruit from UW Health clinics and 
University Health Services. In these settings, flyers will be posted with information about how to 
contact the study coordinator if interested. Interested individuals will complete the screening 
interview over the phone to determine initial eligibility and then will be scheduled for a face-to-
face screening appointment. 
For healthy control subjects, advertising, particularly via posted flyers, electronic 
newsletters, and other newspaper or internet announcements, will be the primary recruitment 
method. Subjects who contact the investigators will complete the same screening interview as 
psychiatric subjects (see section 4.2.1).  
 
4.2 Study Protocol 
 
4.2.1 Screening for Eligibility 
 
Eligibility will be determined through a three-part screening process including a screening 
interview, baseline screening, and at-home overnight sleep study with actigraphy and sleep logs. 
 
Screening Interview 
Interested individuals will first undergo a screening interview to determine initial 
eligibility for the study. After providing a description of the study procedures, subjects will be 
asked a series of questions by a study staff member about their physical and mental health, sleep, 
and other inclusion/exclusion criteria. Screening interview data from subjects who are not 
eligible or do not ultimately sign a consent/HIPAA form will be destroyed. Some participants 
will complete this screening in person at a regular clinic visit if their provider refers them to the 
study and the study team is available. For these participants, verbal consent will be obtained 
prior to the screening like with screenings completed over the phone. Written informed consent 
will be obtained for all participants during the baseline screening visit. 
 
Baseline Screening (Visit 1) 
This visit will begin with the informed consent process. As part of this consent procedure, 
participants may give permission for the UW study team to contact them again for participation 
in future studies. If permission is given, the UW study team will store their names and contact 
information (i.e., telephone number and/or email address). This information will not be 
distributed to any other non-UW study entities (e.g., Merck). Participants then will be evaluated 
for insomnia with RDC criteria and complete the ISI. They will also complete the Edinburgh 
Handedness Questionnaire (EHQ)(Oldfield 1971), answer some demographic questions, and 
undergo the Structured Clinical Interview for DSM-IV Axis I Disorders (SCID)(Spitzer et al 
1992), MMSE, Hamilton Rating Scale for Depression (HRSD) (Hamilton 1996), and an 
unstructured clinical interview for sleep disorders, medical disorders and habits.  Participants 
may be audio and video recorded during these assessments except when illicit substance use is 
assessed to ensure that interviews are valid and reliable. Recordings will only be viewed by study 
team members and will be kept until completion of the study and then will be destroyed. Height 
and weight will be collected for all participants. Women will complete a urine pregnancy test and 
phase of menstrual cycle and birth control medication will be monitored (via self-report) 
throughout participation in the study. After initial screening, participants will complete 

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questionnaire measures of pre-sleep somatic and cognitive arousal (i.e., the Pre-Sleep Arousal 
Scale, PSAS(Nicassio et al 1985)), thought content when having difficulty sleeping at night (i.e., 
the Glasgow Content of Thoughts Inventory, GCTI(Harvey & Espie 2004)), negative sleep-
related cognitions (i.e., the Dysfunctional Beliefs and Attitudes about Sleep Scale, DBAS (Morin 
et al 2007), and general somatic and cognitive arousal (i.e., the Depression Anxiety Stress 
Scales, DASS (S.H. & P.F. 1995) and Penn State Worry Questionnaire, PSWQ (Meyer et al 
1990)). If time permits, we may also administer the University of Pennsylvania Computerized 
Neuropsychological Panel (Penn CNP) to cover other cognitive domains such as verbal memory, 
emotion recognition, and abstract reasoning/decision making. Please find a more detailed 
description of the Penn CNP in the supplemental materials section of the IRB Initial Application. 
Although all tasks may be administered (all listed in supplemental attachment), the tasks that we 
most commonly use are highlighted on the first page. This first visit will last approximately 3 to 
4 hours. 
All study questionnaires will be reviewed by one of the study clinicians (i.e., Drs. Benca, 
Rumble, or Hanley) before the participant departs. If participants report depression and/or 
suicidality on their study questionnaires or interviews, they will be provided with a list of 
community resources (see Supplemental Materials) and encouraged to seek outside treatment. If 
they endorse suicidality that is at a level of imminent risk, they will be directed to the emergency 
department for hospitalization. Study staff will ensure that the participant reached the hospital 
via follow-up with the participant and hospital staff. Participants who are referred for depression 
treatment may still be eligible to participate in our study provided that they continue to meet 
inclusion/exclusion criteria. However, participants at imminent risk of harm to themselves will 
not be eligible (as noted in the exclusion criteria). 
 
At-Home Overnight Sleep Study and Actigraphy with Sleep Logs (prior to Visit 2) 
Participants will complete an at-home screening test for sleep apnea, using a three 
channel recording of airflow, respiratory effort and oximetry with the Apnea Link™ (ResMed 
Corp, Poway, CA). Persons who demonstrate an AHI > 10 will be excluded.  Participants who 
have completed a full clinical sleep study within the past year will not need to complete the 
Apnea Link procedure and the necessary screening information will be collected from their 
medical record.  Sleep-wake patterns will be evaluated over a two-week period using wrist-worn 
actigraphy (a wrist-watch-like device that measures activity level; Actiwatch, Respironics Inc, 
Murraysville, PA) supplemented by sleep-wake logs to confirm self-reported sleep-wake 
patterns.. Activity profiles will be analyzed using Actiware. Of all published quantitative criteria 
to discriminate those with insomnia from good sleepers, sleep-wake log cut-off values have been 
the most reliable, even in comparison to PSG (Edinger et al 2013, Lineberger et al 2006). Thus, 
quantitative criteria derived from sleep-wake logs will be used to classify whether insomnia 
participants have sleep initiation (i.e., an average of 20 minutes or greater of SOL) or sleep 
maintenance insomnia (i.e., an average of 20 minutes or greater of WASO, excluding terminal 
WASO). If insomnia participants do not meet either of these established quantitative criteria, 
they will be excluded from the study. Actigraphy will be used to confirm classification and to 
further rule out any participant who has a circadian rhythm disorder (i.e., regular sleep phase 
occurring out of the range of 9pm-9am). 
 
4.2.2 Post-Screening Study Visits 

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Baseline hdEEG Sleep Recording (Visit 2) 
Participants will come to the Wisconsin Sleep laboratory (accredited by the American 
Academy of Sleep Medicine) for their first hdEEG night approximately 1 to 2 hours before their 
usual bedtime. During this visit, waking and sleep hdEEG (256 channels) recordings will be 
acquired using an Electrical Geodesics NetAmps 300 System. The hdEEG and PSG systems 
(i.e., Geodesics System and Alice 5 System) have 510(k) clearance and are being used in 
accordance with the indications in their labeling. Prior to sleep, spontaneous eyes open and eyes 
closed EEG (2-4 sessions > 2 minutes long), along with peripherally evoked potentials (auditory, 
50 ms 2000 Hz pure tones; visual, checkboard; somatosensory, electrical stimulation of the 
median nerve 10% above threshold), measures of arousal (computerized infrared pupillography 
(DP2000 Human Laboratory Pupillometer, Neuroptics, Inc., Irvine, CA) and flicker fusion rate 
(Flicker fusion analyzer, Lafayette Inc., Loughborough, UK)), and/or several short vigilance 
tasks (the Psychomotor Vigilance Test ; PVT or brief version, PVT-B (Basner, Mollicone, & 
Dinges, 2011), the Sustained Attention to Response Task (SART) (Van Schie et al., 2012), the 
Compensatory Tracking Task (CTT) (Huber et al., 2013), and/or the Divided Attention Driving 
Task (DADT) (Sunwoo et al., 2012) may be collected 1 hr prior to the subject’s usual bedtime.  
Participants will also complete some questionnaire measures prior to bedtime, including 
measures of arousal and mood (i.e., DASS, Visual Analogue Scale (VAS) and State-Trait 
Anxiety Inventory (STAI)). The sleep hdEEG will be integrated with clinical polysomnography 
(PSG) using the Alice 5 Sleepware system to further rule out common sleep problems such as 
periodic leg movements (PLMs). Sensors to be included for the clinical PSG will be: EOG, chin 
and leg EMG, EKG, and SpO2; optional PSG sensors may be included depending on the subject 
comfort or if the ApneaLink results were inconclusive, including nasal cannula, thermistor, 
respiration belts, a snore microphone, and a position sensor. The entire setup for this recording 
takes approximately 45-60 minutes. Audio and low-resolution video using an infrared camera 
will also be recorded during the sleep nights to assist with sleep scoring of the EEG and to allow 
real-time monitoring of subjects. In addition to providing important information for assessing 
sleep, audio/video monitoring provides additional subject safety by allowing contact with the 
subject at all times. After the completion of the study, these recordings will be erased. 
Participants will be excluded if they evidence a periodic limb movement arousal index >10. 
Oximetry data will be evaluated by the physician and any subjects who shows evidence of sleep 
apnea (ODI >5) or hypoxemia (oxyhemoglobin saturation <89% for more than 5 min) will be 
excluded; this is unlikely after baseline screening.  Participants will also complete some 
questionnaire measures upon awakening, including measures of arousal and mood (e.g., GCTI, 
PSAS, VAS, STAI, Post-Sleep Questionnaire) in addition to waking EEG, evoked potential 
recordings, and the brief attention tasks, time permitting.   
 
Serial Awakening hdEEG Sleep Recording (Visit 3) 
Visit 3 will be scheduled for the following night, unless scheduling does not permit. In 
the event that the participant is unable to return the following night, Visit 3 will be scheduled for 
within two weeks of Visit 2 and participants will wear actigraphy during that time. For 
participants completing Visit 3 the following night, they will spend the next day in their usual 
activities but will be instructed not to sleep; they will wear actigraphy to verify that they were 
not sleeping or resting during the day. They will return that night approximately 1 to 2 hours 
before their usual bedtime to complete a second hdEEG study (Visit 3).  During this visit they 

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may repeat the waking EEG, evoked potential recordings, arousal measures, and attention tasks. 
They will also complete some questionnaires prior to bedtime (i.e., VAS and STAI). Additional 
PSG channels (including EOG, EMG, EKG, and optional PSG sensors if warranted) will be 
applied prior to lights out to assist in accurate sleep staging. All participants will then complete 
the serial awakening night in which participants are periodically probed with auditory stimuli 
during the night. After the onset of sleep, participants will be awakened repeatedly using 10 sec 
tones starting at 40dB and increasing by 5 dB every 30 sec until a full awakening is achieved. 
This procedure has been used effectively to estimate the effects that background alpha and sleep 
spindle activity have on sleep stability (Dang-Vu et al 2010, McKinney et al 2011). After 
indicating that they have heard the tone, subjects will confirm that they are awake by answering 
two questions “What was the last thing going through your mind after hearing the sound” and 
“were you awake or asleep”.  Participants will then be encouraged to fall back asleep. We will 
aim to evoke at least 1-2 awakenings in each stage (N1, N2, N3, REM) for the first 3 sleep cycles 
so as to have a minimum of 12 total awakenings. The timing of these awakenings will be 
approximated based on the sleep architecture of the baseline night. Sleep recordings will end 
when the participant awakens in the morning, or if they cannot return to sleep during the night. 
No awakenings will be attempted after the subject’s normal waking time and they will be 
allowed to sleep ad libitum after this time if they wish. Participants will also complete some 
questionnaire measures upon awakening, including measures of arousal and mood (e.g., GCTI, 
PSAS, VAS, STAI, Post-Sleep Questionnaire), as well as waking EEG, evoked potential 
recordings, and the brief attention tasks if time permits. As before, participants will be under 
constant staff supervision during the recording. If participants are unable to sleep longer but do 
not feel rested, we will provide transportation back home. 
 
Follow-up hdEEG Sleep Recording (Visit 4) 
Visit 4 is an optional study visit for all subjects. This third hdEEG study will occur at 
least 1 but not more than 4 weeks after Visit 3. Pre-recording activities and setup will be exactly 
as in the Visit 3 recording except no auditory tones will be played during the night and 
participants will complete the DASS prior to bedtime. This recording will be used to establish 
the stability of baseline sleep recordings. Likely all insomnia participants will be invited to this 
visit. At least 10 healthy sleepers will be invited as stability of recordings is less of a concern, 
though collecting a sub-sample will help to confirm stability nonetheless. Participants with 
depression and insomnia will be invited if their participation is deemed clinically appropriate by 
study clinicians (e.g., if a participant is not on a psychotropic medication that will interfere with 
recordings at baseline, but has desire to start a psychotropic medication for depression that would 
interfere with recordings in the near future, we would not invite this participant so that his/her 
study participation time is kept to minimal time and depression treatment can commence). 
 
Repetition of Visits 2 and 3 in Insomnia Patients on Sleep Medication (Visits 5 and 6) 
 
Visits 5 and 6 are optional for participants with insomnia, either with our without 
depression. Some participants in the study may choose to return to or initiate treatment for 
insomnia with a sleep medication under the supervision of their personal doctor. Participants 
who choose to begin a sleep medication following completion of Visits 2 and 3 (and 4, if they 
opt to complete this optional visit) will be invited to return to the laboratory to repeat Visit 2 (as 
Visit 5) and Visit 3 (as Visit 6) procedures. Visits 5 and 6 will follow exactly the procedures 
outlined in Visits 2 and 3, respectively.  

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Visits 5 and 6 will be scheduled for at least 1 week after participants start a sleep 
medication. 
 
For Visit 2, 3, 4, 5, or 6, if technical problems arise during completion of the protocol (e.g., 
mechanical issues, mistakes with administration of the protocol), study staff may ask participants 
to complete that visit again. If the participant agrees, the visit will be rescheduled at the 
participant’s convenience. They will be paid again for the visit. 
 
Table 1 
Table 1 specifies the assessments and questionnaires that may be completed at each of the 
study time points. 
 
 
Study Visit 
Assessment or 
Questionnaire 
Phone 
Screening 
Baseline 
Screening 
(Visit 1) 
At-Home 
Sleep Study 
Baseline 
Sleep 
Recording 
(Visits 2 and 
5) 
Serial 
Awakening 
Sleep 
Recording 
(Visits 3 and 
6) 
Follow-Up 
Sleep 
Recording 
(Visit 4) 
Phone screening  
X 
 
 
 
 
 
Demographics 
Height and weight 
 
X 
X 
 
 
 
 
Pregnancy/Menstrual 
Cycle 
 
X 
 
 
 
 
ISI 
 
X 
 
 
 
 
Handedness 
 
X 
 
 
 
 
SCID 
 
X 
 
 
 
 
MMSE 
 
X 
 
 
 
 
Medical history 
RDC Criteria 
 
X 
X 
 
 
 
 
HRSD 
 
X 
 
 
 
 
PSAS 
 
X 
 
X 
X 
X 
GCTI 
 
X 
 
X 
X 
X 
DBAS 
 
X 
 
 
 
 
DASS 
 
X 
 
X 
 
X 
PSWQ 
 
X 
 
 
 
 
Penn CNP 
 
X 
 
 
 
 
VAS 
 
 
 
X 
X 
X 
STAI 
 
 
 
X 
X 
X 
ApneaLink 
 
 
X 
 
 
 
Actigraphy 
 
 
X 
 
 
 
Sleep logs 
 
 
X 
 
 
 
Pupillometry 
 
 
 
X 
X 
X 
Flicker Fusion Rate 
 
 
 
X 
X 
X 

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PSG/EEG 
 
 
 
X 
X 
X 
Post-Sleep 
Questionnaire 
 
 
 
X 
X 
X 
 
4.3 Data Safety and Monitoring Plan 
 
In this study, as in similar studies, there is no formalized Data Safety Monitoring Board 
(DSMB). However, serious adverse events and unanticipated problems would be reported to the 
IRB in accordance with posted IRB guidance 
(http://kb.wisc.edu/images/group78/18324/ReportingTimeframesJanuary2013.pdf). 
In addition, there will be a formal process for review and monitoring of study-related 
adverse events. All adverse events are evaluated at each visit by study staff and if any arise, will 
be reported to the principal investigator within 24 hours – or immediately depending on severity. 
The principal investigator and main co-investigators will review cumulative data on adverse 
events at least every 3 months. If any changes in protocol or procedure are warranted by this 
review, they will be filed with the IRB, and the affected study visits will not continue until 
changes are approved. If any pattern of adverse events occurs, the principal investigator and 
main co-investigators will form an ad hoc panel including other investigators at UW to review 
the events and determine the appropriate course of action. Outside consultation will be obtained 
if the situation requires. 
Furthermore, all study team members will be trained on the IRB-approved protocol. We 
will meet at least monthly to discuss study progress, which will include a review of any changes 
to the IRB-approved protocol, as needed. In addition, all study team members will immediately 
be alerted to changes in the protocol via email or in person discussions. We will conduct regular 
(i.e., at least monthly) internal audits of all study materials (e.g., completed participant materials, 
blank study forms, study protocols) to assure that the proper, IRB-approved forms are being used 
and that there are no deviations from the IRB-approved protocol. 
 
4.4 Statistical Considerations 
 
4.4.1 Sample Size Justification 
 
 The strength of this study design is that it will allow us to characterize the cortical activity of 
insomnia patients with a unique combination of temporal and spatial resolution during sleep 
initiation, normal sleep, and awakening from sleep. As such, a number of the questions that can 
be addressed with this design are highly novel for which there is little direct evidence on which 
to base sample size calculations. However, the substantial pilot data collected from a population 
of insomnia patients as well as age- and sex- matched controls for one of the primary hypotheses 
(2.7.2a) allows us to confidently support our proposed choice of sample size. The Cohen’s d 
effect size averaged across the significant source cluster was 1.15. Our power to detect an effect 
of this magnitude in our proposed final sample size of 20 per group using an alpha level of 
p=.05, 2-tailed would be approximately 94%. Our power to detect the difference between 
potential subgroups of sleep maintenance versus sleep onset with the insomnia group alone (10 
per group) would be approximately 68%. Furthermore, on the basis of other similar analyses 
with relatively small sample sizes (e.g. - <20 subjects per group) examining local sleep 
homeostasis (Huber et al 2004), the traveling phenomena of slow waves (Massimini et al 2004), 

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the cortical localization of evoked K-complex slow waves (Riedner et al 2011), slow wave 
reduction in hypersomnolent depressives (Plante et al 2012b), sleep spindle reductions in 
schizophrenia (Ferrarelli et al 2007, Ferrarelli et al 2010), the current study design should 
provide us with adequate statistical power.  
 
4.4.2 Proposed Data Analytic Strategy 
 
Ruth Benca MD, PhD (PI), Brady Riedner, PhD, and Meredith Rumble, PhD will be 
responsible for performing and overseeing data collection and analysis. Statistical analysis will 
be planned and executed in conjunction with UW BARD (https://ictr.wisc.edu/Biostatistics). 
Although our preliminary work has allowed us to identify several primary objectives, described 
below, with clearly identified primary outcome measures and a priori analysis plans, the 
protocol is also largely designed to be exploratory in nature. Therefore, it is likely that several 
promising analysis paths will emerge once the data have been collected that cannot be formally 
identified in advance, but that are in keeping with the primary and secondary objectives of the 
study. Such additional exploratory analyses naturally raise the issue of multiple comparisons. 
Our laboratory has been a leader in designing and implementing the use of hdEEG in sleep, 
particularly in clinical populations, and has been successful in funding and publishing this type 
of exploratory research. Where appropriate, established procedures will be used to evaluate a 
family of related questions (e.g., ANOVA for comparison between groups across frequency 
bands) with reasonably chosen post-hoc corrections for multiple comparisons (e.g., Bonferroni). 
However, in all cases these procedures will be adapted to account for the most pervasive multiple 
comparison problem in hdEEG and other neuroimaging (independent tests between hundreds of 
electrodes or thousands of potential cortical sources) using statistical nonparametric mapping 
techniques (SnPM) as described below.  
 
Normal hdEEG sleep imaging (Primary Objective 1) 
  
Sleep stages will be visually scored for 30-s epochs according to standard criteria 
(AASM). The study Principle Investigator, Dr. Benca, a board-certified sleep specialist with over 
25 years of scoring experience and the medical director of the Wisconsin Sleep laboratory, will 
supervise the scoring and review all studies for the presence of any clinical sleep disorders. Data 
preprocessing and analysis of sleep data will be performed using NetStation (EGI) as well as 
custom made software using Matlab (Mathworks) and EEGlab packages. Power spectra of 
consecutive 6-s epochs (FFT routine, Welch’s averaged modified periodgram with Hamming 
window) will be computed for all derivations in order aid in identification of artifacts and for 
initial scalp exploration. Only epochs without artifacts will be used for further analysis. Given 
the frequency of muscle and eye movements, additional REM artifacts will be removed using 
scalp-level temporal independent component analysis (ICA). Data will be analyzed both in the 
time (e.g. slow wave and spindle waveform detection) and frequency domains. As stated above, 
one of the primary study objectives is to examine differences in the cortical sources of sleep 
waveforms in insomnia patients with and without depression compared to healthy sleeping 
controls during normal sleep. The initial step of the planned analysis will be to explore the scalp 
level EEG sleep power topographies of different frequency bands (Delta, Theta, Alpha, Sigma, 
Beta, Gamma) across the groups and across sleep stages (N1, N2, N3, REM) throughout the 
entire night in order to identify reasonable temporal window(s) for further analysis as 
computational demands of cortical source imaging require that the data to be analyzed is on the 

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order of minutes instead of hours. Preliminary results suggest that tonic alpha power during N3 
sleep may distinguish between these groups, but it is also conceivable that events like slow 
waves or spindles may provide additional distinguishing information, and windows around these 
events may be relevant. The outcome measure addressing this first primary study objective 
will be the cortical localization maps of band-pass filtered EEG data in the frequency range of 
interest (identified by the scalp-level analysis from the initial steps, e.g. alpha) using a distributed 
inverse solution (i.e. LORETA, for details of the methods involved see (Murphy et al 2011)). All 
group comparisons of distributed source localization maps will be analyzed using statistical 
nonparametric mapping (SnPM)(Nichols & Holmes 2002) which is ideally suited to address the 
multiple comparison issues inherent to neuroimaging and which does not make unwarranted 
assumptions about data distribution. This method has been successfully applied in a number of 
hdEEG studies in our laboratory (Ferrarelli et al 2007, Huber et al 2006, Huber et al 2004), and 
compares favorably with Statistical Parametric Mapping for analyses having low degrees of 
freedom. 
 
Falling asleep imaging (Primary Objective 2a) 
  
During both the baseline and serial awakening sleep nights, the descent into (or back 
into) sleep will be analyzed by dividing the interval between the last appearance of occipital 
alpha and the first instance of a burst of slow waves (more than 2 slow waves consecutively 
without an arousal) into 10 equally spaced temporal bins prior to cortical source estimation. 
Distributed source localization maps for individual frequency ranges will then be average within 
subject and then within group prior to statistical analysis.  
      
Sleep arousal imaging (Primary Objective 2b) 
During both the baseline and serial awakening sleep nights, spontaneous 
arousals/awakenings will also be explored using similar methods to the falling asleep analysis 
except the windows of interest will be fixed at 12 seconds (10 intervals = 2 minutes) given that 
there is no a priori criteria for establishing the arousal onset. Additionally, for the serial 
awakening sleep nights, stimulus evoked responses during sleep will be examined using similar 
methods as described above, both in time (evoked potential analysis) and time-frequency (event 
related spectral perturbation) as we have done previously (Landsness et al 2009, Riedner et al 
2011) except the analysis window will be temporally fixed around the stimulus trigger (15 sec 
window, including 2 seconds before and 3 seconds after 10 second auditory stimulus onset and 
offset, respectively). Arousals will be scored according to established arousal criteria (Bonnet et 
al 2007). Stimuli will be categorized into those that did not cause an arousal, those that did cause 
an arousal, and those that resulted in a full awakening. The outcome measures addressing the 
second primary objective will be similar to the outcome measure for the first primary objective, 
cortical localization maps of band-pass filtered EEG data, except that the temporal windows of 
interest will be predefined as described above. Further exploratory analyses will employ Cox 
regression (see McKinney et al) to investigate the ability of alpha in particular cortical regions of 
interest (defined in the baseline analysis) to predict sleep stability in insomnia patients and 
controls.  
 
Correlations between EEG abnormalities and behavioral variables 
Comparison of behavioral data, as well as traditional sleep architecture variables will be 
analyzed using established procedures (e.g. ANOVA for repeated measures and post-hoc tests).  

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Correlations with EEG and/or source localization of power will either be examined using a 
region of interest approach or using SnPM techniques to explore cortical areas whose activity 
may be related to the variable of interest, depending on the nature of the exploratory analysis.  
 
Waking EEG and Evoked Potentials analysis 
EEG data will be analyzed similar to sleep and the presentation of stimuli during sleep 
except that planned comparisons will be performed between recordings made during the evening 
before and morning after baseline sleep. Exploratory analyses will also be conducted on this 
comparison across the serial awakening night to examine the differential effect of sleep 
disruption.   
 
4.5 Data and Record Keeping  
Self-report data will be collected using electronic (e.g., computer tasks or questionnaires) and 
paper-based (e.g., paper questionnaires and interviews) formats. The study data will be managed 
by trained research personnel, including the investigators, a study coordinator, and approved 
research assistants.  Coded data will be retained for at least 5 years or until the study is 
completed, whichever is longer. At that time, the research information will either be destroyed or 
all the information that identifies subjects will be removed from the study results and the key 
code will be destroyed.  
4.5.1 Confidentiality Protections 
 
All participants are assured of confidentiality of the information obtained during their 
participation. All participants are assigned a subject number for the internal purposes of the 
research, and the patients’ identity is indicated only by their subject number and initials. Data 
(including audio and video recordings of mental health assessments and sleep studies) will be 
stored in a secure (password-protected and firewalled) database that is only accessible by study 
personnel. Subjects will be recognizable (i.e., face and voice) in the recordings. Paper copies of 
questionnaires or other data will be stored in locked cabinets in locked offices at UW-Psychiatry 
or Wisconsin Sleep. There will be a paper and electronic copy of the key code linking 
participants’ names to the data through a participant identification number. The paper copy of the 
key code will be kept in a locked filing cabinet that is only accessible by study personnel with 
permitted access to PHI, and the electronic copy of the key code is stored in a secure (password-
protected and firewalled) database separate from the main database that is only accessible by 
study personnel with permitted access to PHI. The full electronic database will contain the 
participant’s unique study identifier and some date elements (such as visit date), but will 
otherwise be clean of identifiers. Participants will be advised that confidentiality could be 
breached in the event of an audit by the parent institution or the sponsor. All audio and video 
recordings of mental health assessments and sleep studies will be destroyed (i.e., erased from the 
electronic database) at the end of the study (i.e., once recruitment is complete and all necessary 
information, such as validity of assessments, is taken from the recordings). 
 
Collection of sensitive information about participants will be limited to the amount 
necessary to achieve the aims of the current study. Screening interviews and other study contact 
that could potentially reveal private or harmful information will always be conducted in private 

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rooms. Participants will be reminded that they do not have to answer any questions they feel 
uncomfortable answering. We will be collecting information on illicit drug use to determine 
study eligibility. Once eligibility is determined, we will destroy information collected on illicit 
drug use. Furthermore, no single question about illicit drug use is included in the phone 
screening interview. 
 
Finally, all research personnel will be required to maintain current training in Protection 
of Human Subjects provided by the CITI web program. 
 

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