The hyperarousal model of Primary Insomnia from a

neurobiological perspective.

Name: Martine Groefsema

Student number: 5622735

University of Amsterdam

MSc in Brain and Cognitive Science

Cognitive Neuroscience

Supervisor: dr. W. F. Hofman

Co-assessor: dr L. M. Thalamini

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Abstract

Despite the growing literature on insomnia, little is known about the underlying

pathophysiology causing the disorder. Previous literature has viewed primary

insomnia mainly as a psychological problem, but more recently studies began to find

more evidence for physiological differences in patients with primary insomnia. The

aim of this review is to discuss the concept of hyperarousal from the higher system to

the molecular processes, and discuss its relevance in the pathology of primary

insomnia. Electrophysiological studies demonstrate increased levels of cortical

arousal in primary insomnia during different stages of sleep. Studies on regional brain

metabolism are limited and are in the need for further research. I conclude that there is

an imbalance between arousing and sleep-inducing brain activity in primary insomnia,

resulting in hyperarousal. However, whether this is the main cause of primary

insomnia can not be concluded. Further research on genetic vulnerability is needed.

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Content Introduction………………………………………………………………. 4 Chapter 1: Different types and characteristics of insomnia…………….6 Chapter 2: Normal sleep processes……………………………………….8

2.1 Neurophysiology of normal sleep……………………………….9 2.2 Neurobiology of normal sleep…………………………………..10

Chapter 3: Hyperarousal model of insomnia……………………………15

3.1 Neurophysiology of primary insomnia…………………………15 3.2 Neurobiology of primary insomnia…………………………….20

3.2.2 Neurotransmitters…………………………………….22

Chapter 4: Heritability……………………………………………………23

Chapter 5: Treatment……………………………………………………..25

Chapter 6: Discussion……………………………………………………..28 References…………………………………………………………………..31

Appendixes………………………………………………………………….32

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Introduction

Patients with insomnia experience inadequate nocturnal sleep in some way.

They may describe difficulty falling asleep, frequent awakening, or early morning

awakening with inability to return to sleep. This disorder of initiating and/or

maintaining sleep causes sleep disruption and has major daytime consequences. There

are two types of insomnia; primary and secondary insomnia. Primary insomnia not

attributable to medical, psychiatric, or environmental causes, while secondary

insomnia is. This review will focus on primary insomnia because it has a

homogeneous character because it does not reflect effects of a comorbid disorder.

Primary insomnia affects approximately 3-5% of the general population (Ohayon,

2002) and is therefore an important topic of research.

A form of hyperarousal became the main concept of primary insomnia models.

The hyperarousal model assumes that an underlying state of arousal interferes with

normal biological processes associated with sleep initiation and maintenance (Bonnet

and Arand, 1997). Many different models were designed, mostly based on somatic

(e.g. heart rate) and cognitive arousal (e.g. dysfunctional thoughts). Riemann and

colleagues (2010) summarized the current literature and generated a neurocognitive

model of insomnia, consisting of a cognitive-behavioural and a neurobiological

domain. The authors emphasize that primary insomnia can not only be linked to

alterations on psychological level, but is also associated with measurable deviations of

neuroendocrine as well as electro-and neurophysiological alterations.

In this review the focus will be on the neurobiological domain, because

emerging techniques allowed us to investigate cortical activity more extensively.

Moreover, because primary insomnia is not related to a comorbid disorder, it can be

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hypothesized that there is some form of genetic vulnerability. This bottom-up

approach assumes a (genetically determined) dysfunction in sleep-wake regulating

neural circuitries originating from the brainstem and leading to sleep disruptions.

With the use of electroencephalography (EEG) and functional magnetic resonance

imaging (fMRI), cortical and even subcortical arousal could be investigated. And the

hyperarousal model can be reviewed with the focus on neurobiological arousal.

One limitation of studying insomnia is the occurrence of many different types.

In the first chapter of this review, the different types and characteristics of insomnia

will be discussed. The second chapter will provide some necessary background

information on normal sleep processes. Neurophysiological as well as neurobiological

processes of normal sleep will be quickly described. The third chapter is the focus of

this review. In this chapter the hyperarousal model will be described, with its evidence

based on electrophysiological and MRI studies. If a hyperaroused state is correlated

with the pathology of primary insomnia, it can be questioned whether this is a

predisposing factor or a consequence of the disorder. Therefore in the fourth chapter

heritability studies of primary insomnia will be discussed. The fifth chapter describes

current treatment of primary insomnia, which is mainly based on changing cognitive

arousal by cognitive behavioural therapy. However, if primary insomnia is caused by

a (genetic) hyperarousal of the neuronal sleep-wake circuitry, other treatment methods

based on a bottom-up approach may be more successful. In the last chapter of the

thesis the evidence will be considered and the main question will be answered: is

hyperarousal the model for explaining the pathology of primary insomnia, based on a

neurobiological perspective? Last, some suggestions for further research will be

proposed.

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Chapter 1: Different types and characteristics of insomnia.

In research on insomnia it is important to recognize the differences between

the different types (primary and secondary) of insomnia. The general definition of

insomnia is: ‘repeated difficulty with sleep initiation, duration, consolidation, or

quality that occurs despite adequate time and opportunity for sleep, and this results in

some form of daytime impairment’ (DSM-IV, 1994). The book ‘International

classification of sleep disorders’ distinguishes 11 different types of insomnia, of

which 3 types of primary insomnia. This heterogeneity of the disorder makes it

difficult to investigate and understand the psychopathology. Because of the possibility

that the different types of primary insomnia also have different underlying causes, it is

important to distinguish among the different types first.

The first type of primary insomnia is idiopathic insomnia. The definition of

idiopathic insomnia is: ‘a lifelong inability to obtain adequate sleep that is

presumably due to an abnormality of the neurological control of the sleep-wake

system’ (DSM-IV, 1994). So idiopathic insomnia is a long-standing disorder, which

typically begins during childhood, and has no clear environmental causes. The second

type of primary insomnia is called psychophysiological insomnia. The definition of

psychophysiological insomnia is: 'a disorder of somatised tension and learned sleep-

preventing associations that results in a complaint of insomnia and associated

decreased functioning during wakefulness' (DSM-IV, 1994). So psychophysiological

insomnia is a disorder which often begins with a period of stress and can be

developed at any time point in life. Unfortunately, while there are clear distinctions

between idiopathic and psychophysiological insomnia, such as the onset period and

what triggers the pathology, not many studies specified the subtypes of primary

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insomnia, and included idiopathic insomnia as well as psychophysiological insomnia

patients. And because not many studies made a distinction between these types, this

review includes both idiopathic as psychophysiological primary insomnia too. The

third and last type of primary insomnia is called sleep-state misperception (also

known as paradoxical insomnia). This type will not be included in this review,

because sleep-state misperception insomnia is referred as subjective insomnia since

the dysfunctional sleep can not be objectively measured using physiological

measurements (DSM-IV, 1994). Some studies suggest that sleep-state misperception

may be a transitional state of dysfunction between an objective sleep disorder

(idiopathic and psychophysiological) and normal sleep (Salin-Pascual et al, 1992;

Bonnet & Arand, 1997). However, because the distinct ability of this subtype is still

questionable (Edinger& Krystal, 2003), no studies including these patients are

reviewed.

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Chapter 2: Normal sleep processes

In order to say something about processes causing sleep disorders, we first

need to consider normal sleep processes. Many different models on normal sleep

regulation have been developed in the last decade. A very common model is the two-

process model by Borbély (1982). The two-process model postulates that two

processes are important in the regulation of sleep, a homeostatic factor (process S)

and a circadian factor (process C). The homeostatic factor rises during wakefulness

and declines during sleep. So this is an appetitive process that is determined by the

amount of time since the last bout of sleep. The longer the time spent awake, the

greater the drive for sleep. On the other hand, the circadian factor (process C) varies

with a 24-hour periodicity and is independent of the amount of preceding sleep or

wakefulness. Together these processes modulate the need for sleep and influence the

balance between central alertness and sleepiness (see figure 1).

A study of Perlis and colleagues (2001) suggested that this two-process model

should be expanded with a second homeostatic ‘process W’. Where the 'process S'

increases with extended wakefulness, the 'process W' is thought to increase with

extended sleep (Perlis et al., 2001). These two processes interact with each other and

deficits can cause sleep initiation and maintenance difficulties. A sleep disorder can

be caused by a decreased sleep propensity (so a low 'process S') or an increased wake

propensity (a hyperarousal or high 'process W'). In this case, primary insomnia can be

hypothesized as a sleep disorder mainly due to an abnormal or increased 'process W'.

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Figuur 1: Two-process model for normal sleep (from Borbély, 1982). The C refers to the circadian factor and the S to the homeostatic factor.

2.1 Neurophysiology of normal sleep

The beginning of sleep research dates back to 1930s, where the studies mainly

used electroencephalogram (EEG) techniques. Kleitman and Dement (1957) were the

first to specify rapid-eye-movement sleep (REM sleep) and defined the cyclic pattern

of sleep as one cycle of REM-nonREM that lasts 90-100 minutes, with 4-5 cycles

repeating during one night. The non-REM sleep period is more specified by a

distinction of 3 different stages, based on EEG wave patterns. Every stage has a

characteristic EEG frequency and waveform. The first stage is characterized by a

transition from alpha waves (8-13 Hz) to theta waves (4-7 Hz). During stage 2 sleep

spindles (11-16 Hz) and K-complexes can occur. Sleep spindles and K-complexes are

rapid bursts of activity. Going into detail on this phenomenon will be beyond the

scope of this review. The third stage, also called slow-wave-sleep (SWS), is

characterized by an extreme amount of delta waves (0-4 Hz) (Carskadon &

Rechtschaffen, 2000).

For primary insomnia, the transition from wakefulness to sleep, also called the

sleep-onset-period (SOP), is extremely interesting because the inability of patients to

initiate sleep. In normal sleepers, the SOP is characterized by a decrease of high

frequency and an increase of slow frequency EEG activity (De Gennaro et al., 2001).

These results show global differences in EEG patterns. A more precise and localized

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image of the processes during sleep can be made with the use of functional resonance

imaging (fMRI).

2.2 Neurobiology of normal sleep

Explaining the history of sleep research and describing all neuroimaging

studies on normal sleep processes would be beyond the scope of this review.

However, to get some background knowledge I will briefly summarize the current

literature of brain activation patterns during NREM and REM sleep in healthy

participants.

One main finding of early functional neuroimaging studies of sleep is a global

decrease of cerebral activity during NREM sleep compared to wakefulness, similar to

the EEG measurements (Buchsbaum et al., 1989; Maquet et al., 1992 ; Nofzinger et

al., 2002). Other studies found evidence for regional differences in activity patterns

during sleep. Decreased activity in thalamic structures during NREM sleep compared

to wakefulness has been found (Braun et al., 1997 ; Andersson et al., 1998; Kajimura

et al., 1999; Kjaer et al., 2002; Nofzinger et al., 2002). Second, a decrease in basal

ganglia structures (e.g. the caudate/ putamen) has been found repeatedly (Braun et al.,

1997; Kajimura et al., 1999). Third, a decrease in several frontal cortex areas (Braun

et al., 1997; Kajimura et al., 1999; Nofzinger et al., 2002). And fourth, REM sleep can

be characterized by an increased metabolism within the limbic system, pons and the

visual cortex (Maquet et al., 1996).

If we even zoom in more closely to the midbrain structures, a network that

promotes wakefulness can be defined, the ascending arousal reticular system (ARAS).

Evidence for the existence of an arousal system came from early work of Von

Economo (1930). He discovered that patients with encephalitis lethargica, who sleep

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excessively, had lesions at the junction of the midbrain and the diencephalon. This

area was thought to be the beginning of an arousal system, which ascends to the

forebrain and promotes wakefulness. Two decades later, a study of Moruzzi and

Mogoun (1949) clarified the ARAS more, using EEG techniques. Moruzzi and

Mogoun were the first to divide the ARAS into two branches, which were confirmed

in 2005 by Saper and colleagues (2005). One pathway, from the laterodorsal

tegmental nuclei (LDT) and pedunculopontine (PPT) to the thalamus, is the branch

that activates neurons crucial for the transmission of information to the cerebral

cortex. Neurons in this branch fire rapidly during wakefulness and REM sleep (figure

2, the yellow branch). The second important branch in the ARAS originates from the

upper brainstem and caudal hypothalamus (including the locus coeruleus (LC), the

raphe nuclei and the tuberomammillary nucleus (TMN)) and projects to the basal

forebrain. Neurons in this branch fire fastest during wakefulness, slowing down

during NREM sleep and stopping during REM sleep (figure 2, the red branch).

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Contrary to the ARAS, there is a network that promotes sleep. A key role in

this network is assigned to the ventrolateral preoptic nuclei (VLPO), a group of

neurons located in the hypothalamus. The VLPO appears to be strategically well

placed because of its robust connections with hypothalamic regions (Chou et al.,

2002). Moreover, major descending projections from the VLPO to the TMN and more

regions of the ARAS were found, using tracing methods (Sherin et al., 1998). The

neurotransmitters present in the VLPO are mainly gamma-aminobutyric acid

(GABA). GABA is known as the most important and ubiquitous inhibitory

neurotransmitters of the central nervous system. This suggests that the VLPO may

provide inhibitory GABAergic inputs to these cell bodies in the ARAS, and therefore

may play a key role in silencing the ARAS and promoting sleep (see figure 4).

Figuur 2: A schematic drawing showing key components of the ARAS. Red branch: neurons that fire during wakefulness and slow down during NREM/REM. Yellow branch: neurons that fire during wakefulness and REM sleep (from Saper et al., 2005, pg1258)

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The arousal and sleep promoting networks interact with each other creating the

balance between sleep and wake processes. The transition from wake to sleep occurs

very rapidly and it is therefore called a flip-flop switch, you are either awake or

asleep, but not much time is spent in the transitional state. The question that rises is:

what triggers this switch? Apparently, something makes the balance towards

activation of the one network, or the other. A neuropeptide ‘orexin’ seems to be

highly important. This neuropeptide is produced only in the posterior half of the

lateral hypothalamus (LH). The orexin neurons are mainly active during wakefulness

and can directly reinforce the arousal system (Lee et al., 2005). These orexin neurons

can have an indirect effect on the VLPO (see figure 3). During wakefulness the VLPO

is inhibited through the regions of the ARAS, which are directly reinforced by the

orexin neurons. On the other hand, during sleep, the VLPO inhibits the orexin neurons

Figuur 3: A schematic drawing showing primary projections of the VLPO to the main components of the ascending arousal system (from Saper et al., 2005, pg 1259).

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and the regions of the ARAS. This inhibition is strengthened by the fact that the

orexin neurons inhibit the ARAS regions even more.

Figuur 4: A schematic drawing of the flip-flop switch model (from Saper, 2005). a) the balance during wakefulness; b) the balance during sleep.

Taken together, these studies suggest that normal sleep can be characterized

by global and regional deactivations. During the SOP, the VLPO and several basal

ganglia areas are key factors in the regulation of sleep. During NREM sleep, the

thalamus, basal ganglia, pons and some prefrontal cortex areas show great

deactivation, and therefore may be important.

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Chapter 3: Hyperarousal model of insomnia

A hyperaroused state became the main concept of different models on primary

insomnia. This hyperarousal can be found in three different dimensions. For instance

somatic arousal causes you to have heightened sensory response, which can be seen

by increased automatic activity such as elevated heart rate/respiration and the blood

levels of stress hormones increase dramatically as has been found in poor sleepers

repeatedly (Monroe, 1967; Adam et al., 1986; Bonnet, 1995).

Another form of arousal is cognitive arousal. Cognitive arousal is reflected by

intrusive and negative cognitions and their associations with sleep complaints

(Wicklow & Epsie, 2000; Lichstein and Rosenthal, 1980). The last proposed form of

arousal is defined as cortical arousal. In this review I will investigate the current

literature on cortical (hyper)arousal in primary insomnia, this can also be called the

neurobiological aspects of insomnia. This research field has expended dramatically

the last decade, due to new techniques such as EEG and fMRI, which allow us to have

a closer look at the biological basis of hyperarousal.

3.1 Neurophysiology of primary insomnia (cortical arousal)

Research using quantitative EEG (QEEG) techniques provides insights in

cortical arousal in insomnia. For example, cortical electrophysiological signals in the

beta and especially gamma band have been hypothesized as a main feature of coherent

cortical processing of sensory information (Llinás & Ribary, 1993), where an EEG

power increase in this frequency range can be interpreted as a sign of cortical

hyperactivity or hyperarousal. Therefore, analysing EEG patterns in insomniacs can

provide meaningful information, in favour or against the hyperarousal hypothesis.

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As noted above, the transition from wakefulness to sleep, also called the sleep onset

period (SOP), entails a shift in the frequency power spectrum of the EEG from high

to low frequencies in healthy individuals (Wright et al., 1995). This period is of

specific interest in the light of primary insomnia. Merica and Gaillard (1992) were

one of the first to study the SOP in insomniac patients. They confirmed the idea that

the SOP of normal sleepers can be characterized by a rapid change in beta and delta

activities. Beta activity decreases and delta activity increases, both in insomniacs as in

healthy controls. However, insomniacs had higher beta and lower delta activity

compared to controls in the SOP and the first minutes of the first NREM cycle. The

differences in delta activity between insomniacs and healthy controls were significant.

The authors of this article suggest that this increased high frequency activity may

explain the tendency of insomnia patients to overestimate their sleep latencies.

Lamarche and Ogilvie (1997) performed a similar study, looking at the SOP in

psychophysiological insomniacs, non-specified psychiatric insomniac and control

sleepers. They extended previous findings by defining the SOP into four quartiles.

The results showed that insomniac exhibit less delta power in the SOP, specifically in

the last quartile. Reduced alpha activity was found during the first quartile of the SOP

in insomniacs, and it did not show a dramatic drop, which is common during normal

sleep. Moreover, they found that increased relative beta power during wakefulness in

primary insomnia patients.

In line with previous findings, Staner and colleagues (2003) found that

patients with primary insomnia did not experience a decrease of their alpha and beta

power during the SOP, and showed lower delta activity in the first 5 minutes of sleep.

They concluded that hyperarousal mainly affects the sleep initiation of primary

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insomnia patients whereas the homeostatic sleep regulation process seems to be

partially maintained.

In contrast to the study of Staner and colleagues, Merica and Guillard (1998)

questioned whether primary insomnia affected only the SOP, or if this dysregulation

can be seen in other sleep stage too. They were the first who did not limit their EEG

data to an interval at/around sleep onset and also examined the first four NREM/REM

cycles. Consistent with previous studies, increased beta power in insomnia patient

compared to healthy controls was found during the SOP. However, elevated beta

activity was found during the whole night in primary insomnia patients, emphasizing

the importance to investigate the whole sleep pattern instead of focussing only on the

SOP. Moreover, they found increased power in fast frequency bands and a decreased

power in the delta and theta bands in insomnia patients during REM sleep. One major

disadvantage of this study is that the authors did not remove all episodes of

wakefulness within each NREM/REM cycle before performing the power analysis.

They only excluded episodes that contained periods of wakefulness lasting 5 minutes

or more. This may have resulted in group differences for high frequencies, that can be

explained by differences in short periods of wakefulness. However, these results were

the first to show that primary insomnia also affects the REM sleep. Moreover, they

suggest that not only the sleep initiation is dysregulated in primary insomnia, but also

the maintenance of sleep.

In table 1 all the results are summarized. First, beta activity (14-35Hz) is

increased (or drops more slowly) in primary insomnia relative to good sleepers, both

around the SOP as during NREM sleep (Merica et al., 1992;1998; Nofzinger et al.,

1999; Perlis et al., 2001; Lamarche and Ogilvie, 1997). Second, insomnia patients

exhibit reduced levels of alpha power during NREM, wakefulness and sleep onset

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period (Merica et al., 1998; Lamarche and Ogilvie, 1997), and increased levels of

alpha activity during the SOP (Lamarche and Ogilvie, 1997; Staner et al., 2001).

Third, theta power during NREM and REM sleep was decreased in insomniacs

(Merica et al., 1998). Fourth, delta power appears to be lower in insomniacs during

the SOP, NREM and REM sleep (Lamarche and Ogilvie, 1997; Merica et al., 1998;

Staner et al.,2003). And fifth, higher gamma power was observed during NREM sleep

(Krystal et al., 2002). In conclusion, insomniacs show elevated levels of high

frequency and a reduction of slow frequency EEG activity during all phases of sleep

compared to normal sleepers, which is evidence in favour of the hyperarousal

hypothesis (see table 1).

Table 1: EEG differences in PI compared to healthy sleepers (during first NREM cycle, except for the study of Merica and Gaillard (1998) who investigated the first four NREM/REM cycles). Stage EEG frequency Effect Article

Wakefulness Alpha (8-12 Hz)

Beta (14-35 Hz)

Decreased in PI

Increased in PI

Lamarche and Ogilvie

(1997)

SOP Delta (0-4 Hz) Decreased in PI Merica and Gaillard

(1992),

Lamarche and Ogilvie

(1997) Alpha (8-12 Hz) Increased in PI Lamarche and Ogilvie

(1997)

Staner et al., (2003) Beta (14-35 Hz) Dropped more slowly/

increased in PI

Merica and Gaillard

(1992 ‘ns’; 1998)

Staner et al., (2003)

La Marche and Ogilvie

(1997)

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NREM

Delta (0-4 Hz) Decreased in PI Staner et al., (2003),

Merica and Gaillard

(2008) Theta (4-7 Hz) Decreased in PI Merica and Gaillard

(2008) Alpha (8-12 Hz) Decreased in PI

Merica and Gaillard

(2008) Beta (14-35 Hz) Increased in PI

Merica and Gaillard (1998) Nofzinger et al., (1999)

Gamma (25-100 Hz) Increased in PI

Krystal et al., 2002

REM Delta (0-4 Hz) Decreased in PI Merica and Gaillard

(2008) Theta (4-7 Hz) Decreased in PI Merica and Gaillard

(2008)

Alpha (8-12 Hz) Increased in PI Merica and Gaillard

(2008) Beta (14-35 Hz) Increased in PI Merica and Gaillard

(1998)

EEG: electroencephalography, SOP: sleep onset period, NREM: non-rapid-eye movement sleep,

REM: rapid-eye-movement sleep

There are several limitations of sleep research using QEEG measurements.

First, some studies focused on a limited portion of the sleep EEG spectrum (e.g.

Staner et al,, 2001) while others focused on a specific sleep period (e.g. Merica and

Gaillard, 1992; Lamarche and Ogilvile 1997). Second, the measurement is susceptible

to confounding artefacts from electromyography (EMG) signals (Goncharova et al.,

2003). And last, in contrast to the excellent temporal resolution of EEG, the spatial

resolution of is very limited. EEG is only able to measure cortical activity (and no

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subcortical brain structures) and therefore can not give information about more

subcortical brain activity. As in normal sleep, new techniques as MRI allow

researchers to measure brain activity at lower levels, including subcortical brain

circuits and areas. This may give new insights in the underlying brain mechanisms

controlling sleep.

3.2 Neurobiology of primary insomnia (sub-cortical arousal)

If abnormal sleep is a result of a failure of sleep promoting areas, we would

expect to find a decreased activity of the VLPO and several basal ganglia areas. If

abnormal sleep is a result of a failure of wake promoting areas, we would expect to

find an excessive ascending activation through increased activity areas located in the

ARAS (thalamus, basal ganglia, pons and prefrontal cortex). This last expectation is

the main idea of the hyperarousal hypothesis.

To my knowledge only two studies investigated functional abnormalities of

insomniacs, directly looking at brain metabolism with the use of MRI (Nofzinger et

al., 2004; Smith et al., 2002).

Smith et al., (2002) used a single photon emission computed tomography

(SPECT) method, to investigate the brain metabolism in insomniacs. Their results

showed a significant decreased regional cerebral blood flow in the frontal medial

cortex, frontal lateral cortex, basal ganglia, thalamus, pons and temporal, occipital

and parietal cortices during the first cycle of NREM sleep in insomniacs compared to

good sleepers.

And a recent neuroimaging of Nofzinger and colleagues (2004), who used

fluordeoxyglucose positron emission tomography (PET) to assess the regional

cerebral glucose metabolism (CMRglu). Contrary to the results of Smith and

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colleagues (2002), Nofzinger and colleagues (2004) showed that in the transition from

wakefulness to NREM sleep insomniacs showed increased global glucose metabolism

compared to healthy controls. Secondly, insomniacs exhibited less reduction of

relative CMRglu in the ARAS, hypothalamus, insular cortex, amygdala,

hippocampus, anterior cingulate cortex and the medial prefrontal cortex during

NREM sleep. Third, PI patients show an increased metabolism in the frontal cortex,

superior temporal cortex, parietal and occipital cortices, and in the thalamus,

hypothalamus, and brainstem reticular formation during wakefulness. These results

were the first to directly show a dysfunctional deactivation or an inhibition of the

arousal mechanisms at the transition from wakefulness to (NREM) sleep in humans

with primary insomnia. The differences in metabolism during wakefulness may be

responsible for the daytime impairments of insomnia, and are shown to be a related to

sleep deprivation (Thomas et al., 2000).

Differences between these two studies can be caused by several aspects.

Despite the advantages of MRI techniques, studying sleep parameters with the use of

a MRI scanner does not come without disadvantages. Two major problems of

studying sleep in the MRI scanner are: difficulties with co registration of the

polysomnography (a measurement of brain waves (EEG), eye movement, muscle

activity, of heart rhythm, used to define sleep stages) and functional imaging data.

And secondly, it is hard to capture tomography during sleep from uniform sleep

stages. Due to the magnetic field, the EEG signal can easily be disrupted, if the

subjects were able to sleep at all in the noisy MRI environment (Smith et al., 2002).

These general limitations of using the MRI scanner in sleep research may have

influenced the results of both studies in different ways.

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Another possible explanation of the different results may due to different

measurement techniques. Nofzinger and colleagues (2004) used PET recordings,

where Smith and colleagues (2002) used SPECT recordings. Both techniques use an

injection of a different short-lived radioactive tracer isotope, which decays by

emitting a positron. On the one hand, SPECT imaging is a fast scan completed, but

lacks the spatial resolution of PET imaging. Where on the other hand PET imaging

allows a more refined analysis at the neuroanatomical level, but involves a much

longer uptake window, because of the slow tracer. This results in much longer

scanning times (Meikle et al., 2006). Since blood flow is known to decline with

increasing duration of NREM sleep, these small differences due to different

techniques makes it difficult to compare the studies and to get a uniform picture of the

alternations in brain metabolism in primary insomnia.

3.2.2 Neurotransmitters

As pointed out before, sleep is a consequence of several brain areas connecting

with each other in a network. This occurs under the influence of neurotransmitters,

hormones, receptors and connections. The neurotransmitter GABA may have a key

role in promoting sleep by inhibiting midbrain areas of the ARAS. If insomnia

patients exhibit hyperarousal, this may be caused by decreased GABA to inhibit the

brain areas located in the ARAS. In patients with primary insomnia, reduced daytime

overall average brain GABA levels, averaged from basal ganglia, thalamus, and

parietal, occipital, and temporal white matter and cortical regions, were observed

(Winkelman et al., 2008). Remarkably, GABA levels correlated with both subjective

and objective sleep measures. Longer wake time after sleep onset was associated with

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lower levels of GABA. To our knowledge, this is the only investigation focussing on

neurotransmitters in primary insomnia.

Chapter 4: Heritability

If evidence is found for the occurrence of hyperarousal in primary insomnia, it

can be questioned if hyperarousal is a contribution to insomnia or a consequence of it.

This leads us to the question: are there predisposing factors in insomnia?

There are a couple studies who investigated this topic. Bastien and colleagues

(2000) evaluated the familial incidence of sleep disturbances among individuals with

sleep complaints. They found that 35% of patients consulting for insomnia had a

positive family history of sleep disturbances, with trends suggesting a higher

frequency among patients with primary insomnia, an early age of onset and sleep

onset insomnia. Particularly the mother was the most afflicted family member.

Similar results were found by Beaulieu-Bonneau and colleagues (2007), who reported

that 34.9% of their participants had at least one first-degree relative, with past or

current insomnia. And again, the mother was the most frequently afflicted (19.7%).

Two major disadvantages of the study of Bastien and colleagues (2000) were

that the data were obtained by self-report and the absence of a control group. This

way the results are based on subjective judgements instead of direct assessments and

individuals with past or current insomnia are more likely to report a positive family

history of insomnia than individuals without any history of insomnia (Beaulieu-

Bonneau et al., 2007). A study by Dauvilliers and colleagues (2005) did include a

control group. They compared familial insomnia in three groups, primary insomnia,

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psychiatric insomnia and a non-insomnia control groups. They results showed reports

of familial insomnia in 72.7%, 43.3% and 24.1% respectively. Similar to previous

studies, the mother was the relative most frequent affected and there was a tendency

to younger age at onset observed in familial and primary insomnia. From these studies

it can be concluded that there is strong evidence for heritability in primary insomnia if

we look at behavioural scores. This leads us to the question: ‘What is the genetic

component of primary insomnia?’.

Ambrosius and colleagues (2008) performed a classical twin study in

monozygotic and dizygotic twin pairs on the genetic effect of sleep EEG in healthy

participants. They found that the relative contributions of the delta, theta, alpha and

sigma frequency bands were significantly correlated to the genetic background. In

other words, the monozygotic twin pairs showed significantly higher within-pair

concordance in spectral power of these frequencies, compared to dizygotic twin pairs.

These results showed that the spectral composition of non-REM sleep in humans is

significantly influenced by genetics. And because it has been found that insomnia is

characterized by specific EEG pattern, these results suggest that a hyperaroused EEG

pattern may be the main cause of primary insomnia.

Sadly, no studies have investigated a possible genetic component in brain

alternations of the neuronal sleep-wake circuitry. This would be of specific interest in

the light of the hyperarousal hypothesis.

25

Chapter 5: Treatment

Current treatment options for primary insomnia are mainly based on

behavioural aspects, including stimulus control therapy, sleep restriction therapy,

relaxation therapy, cognitive behaviour therapy, sleep hygiene education (Principles

and practice of sleep medicine, pp. 726-737). The aim of cognitive behaviour therapy

for insomnia (CBT-I), which is considered the treatment of choice for primary

insomnia, is to change maladaptive sleep habits, reduce autonomic arousal and alter

dysfunctional beliefs as for instance rumination (Morin et al., 1994; Murtagh et al.,

1995). However, there is a significant group of patients (about 20%) that does not

respond to cognitive behaviour therapy (CBT) (Morin et al., 1994, Harvey et al.,

2003) and the patients that do respond, show an average improvement but not

sufficient to categorize them as ‘good sleepers’ (Harvey et al., 2003). I suggest that in

the light of the hyperarousal view it would be of interest to think about a treatment

approach that works from bottom-up instead of normal CBT, that is based on a top-

down view. Regulating the specific neurobiological alternations in insomnia patients

may result in a more successful treatment approach.

There are two different methods to achieve a bottom-up approach in treatment.

One of them is by using pharmacological interventions. Current pharmacological

treatment interferes with the function of neurotransmitters in the ARAS by

counteracting the result of wake-promoting systems. For instance, specific targets can

be regulated by adding a histamine H1-antagonist (e.g. Doxepin or Diphenhydramine)

to counteract histamine from the TMN or a serotonin 5-HT2a-receptor antagonist (e.g.

Trazodone) to block serotonin in the DR (Szabadi, 2006). Another method can be to

inhibit the wake-promoting system itself, instead reacting on the results of an active

26

ARAS. A benzodiazepine receptor agonist (BZRA) mimics the action of the VLPO

by inhibiting the ARAS through increased activity of GABA (Gottesman, 2002)

The main disadvantage of pharmacological treatment is that some drugs are

not prescribed for long-term use, because of their side effects (Ringdahl et al., 2004;

Kripke, 2006). Moreover, there is a risk for substance dependence. Even with relative

save drugs such as Zolpidem and Zopiclone, which are both prescribed for treatment

of insomnia (Hakak et al., 2003). Furthermore, not all sedatives show greater

improvement compared to CBT in older adults, who are more vulnerable for side

effects (Sivertson et al., 2006).

A possible new treatment to focus on the hyperarousal instead of cognitive

arousal, but without clear pharmacological side effects, is EEG neurofeedback.

Neurofeedback is a new method based on training a patients’ self regulation (Othmer

et al., 1999). The patient receives feedback of his EEG recordings and is trained to

normalize the functioning of the brain by inhibiting or reinforcing specific frequency

bands. In the light of hyperarousal as a leading cause of primary insomnia, and

significant EEG evidence for this, this treatment may be successful by training the

patients to regulate their cortical arousal. This may result in a decreased arousal and

therefore positive effect on primary insomnia. Because primary insomnia is

considered a 24-h disorder (Bonnet & Arand, 1995) training of wake EEG can result

in changes of the sleep EEG (Sterman et al., 1970). Thus neurofeedback may be a

successful new treatment possibility. Cartoos and colleagues (2010) performed an

exploratory study on the effects of neurofeedback and showed a significant

improvement in total sleep time after neurofeedback training. Further research on this

treatment method is needed.

27

Concluding, neurofeedback may be in interesting new treatment technique by

reducing the cortical hyperarousal in primary insomnia. However one shortcoming of

this technique is that no study investigated the effects of neurofeedback on subcortical

hyperarousal and the regulation of metabolism in for instance the ARAS system.

Based on the current evidence I suggest a combined treatment of neurofeedback and

pharmacological treatment for primary insomnia.

28

Chapter 6: Discussion

In this review, I summarized the current literature on the hyperarousal

hypothesis of sleep in primary insomnia, with the use of EEG or MRI methods. I

questioned whether there is evidence for a hyperarousal model on neurobiological

basis. I discussed the literature from cortical to subcortical levels of arousal. First

EEG studies were described, and after that the scarce literature on MRI studies was

described.

In EEG studies, elevated levels of high frequency and a reduction of slow

frequency EEG activity has been repeatedly found during all phases of sleep, in

insomnia patients compared to normal sleepers. Technical limitations result in an

inability to adequately localize regional activity throughout the brain. This resulted in

the need for another, more advanced, measurement technique. However, despite this

limitation, these results clearly support the hyperarousal hypothesis.

From MRI studies no clear conclusions can be drawn because currently

available data are limited and inconsistent. The results of the two current studies

(Smith et al, 2002; Nofzinger et al, 2004) are contradictive. A possible explanation for

this clear difference may lie within the changing of brain metabolism over time. To

date, no fMRI study recorded more than the first part of the first NREM cycle. Perlis

and colleagues (2001) showed that the heightened beta activity in insomniacs during

the SOP rapidly attenuates across the sleep-wake transition. This decline was found to

be significantly greater in patients with primary insomnia and leads to a brief period

of hypoarousal. With this difference in arousal over time, it is possible that the 2-min

time window of the study of Smith accidently recorded this temporary hypoarousal.

This emphasises the importance of future research on a whole night cycle with fMRI.

29

Such research can give more insight in the question whether primary insomnia

patients are generally hyperaroused during NREM sleep, as found by Nofzinger and

colleagues (2004) or if they show periods or hyperarousal alternating with periods of

hypoarousal.

A dysfunction of the sleep-wake circuitry may be a result of difference in

neurotransmitters. To date, only one study investigated differences in the amount of

neurotransmitters in primary insomnia. Winkelman and colleagues (2008) found

global decreased GABA in primary insomnia patients, suggesting a failure to inhibit

wake-promoting areas.

In the light of treatment possibilities, we propose a new treatment method. The

current behavioural treatments (Principles and practice of sleep medicine, pp. 726-

737) have proven to be successful in reducing arousal by changing mostly thoughts

and rumination. However, because primary insomnia can be caused by (sub)cortical

instead of cognitive arousal, other treatment methods may be more successful.

Pharmacological treatment has proven to be successful, and a new proposed method is

neurofeedback, which focuses on reducing cortical arousal. I suggest a combination

of these two treatment modalities. When combined, pharmacological treatment is used

to change the arousal on neurotransmitter level, where simultaneously neurofeedback

can result in reducement of cortical arousal. Together these two therapies may be the

most successful treatment method of primary insomnia.

The available data generally support the hyperarousal theory of insomnia with

increased cortical activity during NREM sleep. However, the key brain areas

responsible for the hyperarousal remain unclear. Further research on the

identification of regional brain activation should allow development of increasingly

specific medical treatments, to control abnormal activation.

30

Moreover, differences on neurotransmitter level and the temporal

characteristics of hyperarousal should be investigated. As said before, the study of

Perlis and colleagues (2001) suggest that hyperarousal may be a dynamic, instead of

static process. Therefore, a whole night fMRI study looking at the hyperarousal over

time would be very useful.

In this review I conclude that hyperarousal is key factor in the pathology of

primary insomnia, based on neurophysiological evidence. Moreover, the literature

suggests a hyperarousal of the ARAS as underlying factor of primary insomnia. But

due to limited research this hypothesis can not be confirmed (yet).

31

Appendix 1: Definitions of subtypes of insomnia, according to the ICSD.

Psychophysiological insomnia (307.42-0)

Learned insomnia, conditioned insomnia, functionally autonomous insomnia,

psychophysiological arousal, chronic somatised tension, internal arousal without

psychopathology.

Psychophysiological insomnia is a disorder of somatised tension and learned sleep-

preventing associations that results in a complaint of insomnia and associated

decreased functioning during wakefulness. Psychophysiological insomnia is an

objectively verifiable insomnia that develops as a consequence of two mutually

reinforcing factors: (a) somatised tension and (b) learned sleep-preventing

associations. Individuals who have psychophysiological insomnia typically react to

stress with somatised tension an agitation. The meaning of stressful events (other than

insomnia) is typically denied an represses, but manifests itself as increased

physiological arousal (e.g., increased muscle tension, increased vasoconstriction, etc.)

Idiopathic insomnia (780.52-7)

Childhood insomnia, lifelong insomnia, insomnia associated with problems within the

sleep-wake system, excessive arousal, inadequately developed sleep system.

Idiopathic insomnia is a lifelong inability to obtain adequate sleep that is presumably

due to an abnormality of the neurological control of the sleep-wake system.

32

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