Neuroscience 222 (2012) 89–99

EPILEPSY: EVER-CHANGING STATES OF CORTICAL EXCITABILITY

R. A. B. BADAWY, a,b,c* D. R. FREESTONE, c A. LAI d ANDM. J. COOK a,b

aDepartment of Clinical Neurosciences, St Vincent’s Hospital,

Fitzroy, Australia

bDepartment of Medicine, The University of Melbourne,

Parkville, Australia

cDepartment of Electrical and Electronic Engineering, The University

of Melbourne, Parkville, Australia

dBionics Institute, East Melbourne, Victoria, Australia

Abstract—It has been proposed that the underlying epileptic

process is mediated by changes in both excitatory and inhib-

itory circuits leading to the formation of hyper-

excitable seizure networks. In this reviewwe aim to shed light

on the many physiological factors that modulate excitability

within these networks. These factors have been discussed

extensively in many reviews each as a separate entity and

cannot be extensively covered in a single manuscript. Thus

for the purpose of this work in which we aim to bring those

factors together to explain how they interact with epilepsy,

we only provide brief descriptions. We present reported evi-

dence supporting the existence of the epileptic brain in sev-

eral states; interictal, peri-ictal and ictal, each with distinct

excitability features. We then provide an overview of how

many physiological factors influence the excitatory/inhibi-

tory balance within the interictal state, where the networks

are presumed to be functioning normally. We conclude that

these changes result in constantly changingstatesof cortical

excitability in patients with epilepsy. � 2012 IBRO. Published

by Elsevier Ltd. All rights reserved.

Key words: epilepsy, cortical excitability, seizures, peri-ictal,

physiological variations, stress.

INTRODUCTION

Epilepsy is a disorder characterized by the occurrence of

recurrent seizures. These seizures reflect abnormal

0306-4522/12 $36.00 � 2012 IBRO. Published by Elsevier Ltd. All rights reservehttp://dx.doi.org/10.1016/j.neuroscience.2012.07.015

*Correspondence to: R. A. B. Badawy, Department of ClinicalNeurosciences, St Vincent’s Hospital, 41 Victoria Parade Fitzroy,Victoria 3065, Australia. Tel: +61-3-9288-3068; fax: +61-3-9288-3350.

E-mail addresses: badawyr@unimelb.edu.au, rdwbadawy@yahoo.com (R. A. B. Badawy).Abbreviations: ACTH, adrenocorticotropic hormone; BECTS, benignchildhood epilepsy with centro-temporal spikes; BFNIS, benign familialneonatal-infantile seizures; CRF, corticotropin-releasing factor; EEG,electroencephalogram; fMRI, functional magnetic resonance imaging;GABA, gamma (c)-aminobutyric acid; GTCs, generalized tonic–clonicseizures; IGE, idiopathic generalized epilepsy; LGS, Lennox–Gastautsyndrome; NREM, non rapid eye movement; REM, rapid eye move-ment; SCN, suprachiasmatic nuclei; SMEI, severe myoclonic epilepsyof infancy.

89

hypersynchronous electrical activity of neuronal networks,

which are thought to be caused by an imbalance between

excitation and inhibition (McCormick and Contreras,

2001). The ratio of excitation to inhibition is themajor deter-

minant of excitability in the brain. Epileptogenesis refers to

the alteration of a normal neuronal network into a hyper-

excitable network leading recurrent, spontaneous seizures

to occur (Clark and Wilson, 1999). The proposed underly-

ing mechanisms for this process include neuronal loss,

neurogenesis, glial loss, gliogenesis, axonal and dendritic

plasticity and intracellular channelopathies or receptor dys-

function. A complete discussion of these mechanisms is

beyond the scope of this review and is extensively

described elsewhere. The aim of this review is to draw

attention to the dynamic variability in cortical excitability

within each individual with epilepsy. The epileptic brain

exists in many states, not just the well-established appar-

ently normal or interictal state in between seizures during

which the brain appears to function normally, and abnormal

orictal state characterized by widespread synchronous

activity occurring in a paroxysmal way, thereby impairing

brain functioning (Lopes da Silva et al., 2003). Not only

are these two states separated by the preictal state during

which physiological phenomena such as prodromal symp-

toms can occur and the postictal state during which the

brain is recovering from the seizure, there are also many

variations in cortical excitability within the interictal state it-

self. These changes are influenced by many physiological

factors each of which has been the subject of multiple

extensive reviews describing their pathophysiological ba-

sis and their relationship with epilepsy. To attempt to pro-

vide an exhaustive or full review of each in a single

manuscript would be an unrealistic and unachievable goal

and is far from our intention. We present a brief overview

of these factors to showhow theycanall co-exist in the same

person and influence clinical presentation. We attempt to

draw the bigger picture; to demonstrate the complex interac-

tion that results in constantly changing states of cortical

excitability in patients with epilepsy.

VARIATIONS IN INTERICTAL CORTICALEXCITABILITY

Sleep–wake cycle

The relationship between sleep and epilepsy is well rec-

ognized. Most studies confirm that sleep and circadian

variations in arousal not only affect the timing of seizure

occurrence, but also the frequency, morphology and

spread of interictal discharges on electroencephalogram

(EEG). Synchronized non rapid eye movement (NREM)

sleep facilitates seizures, whereas desynchronized rapid

d.

90 R. A. B. Badawy et al. / Neuroscience 222 (2012) 89–99

eye movement (REM) sleep discourages seizure occur-

rence (Foldvary-Schaefer and Grigg-Damberger, 2009).

The majority of generalized tonic–clonic seizures

(GTCs) in all forms of idiopathic generalized epilepsy

(IGE) occur after awakening and is particularly likely to

happen when the person is aroused after sleep deprivation

followed by brief sleep. This relationship to epilepsy on

awakening is particularly clear in patients with juvenile

myoclonic epilepsy (Niedermeyer et al., 1985). Patients

with IGE also show variation in the occurrence of interictal

epileptiform discharges with sleep. Interictal epileptiform

discharges are usually present in the wake EEG, but sleep

further activates interictal epileptiform discharges in

patients with absence and/or GTCs (Sato et al., 1973).

Typically, spikes increase with sleep onset progressively

through NREM 3, diminish sharply in REM sleep, and in-

crease again in the morning after awakening. During

NREM sleep, generalized spike-wave discharges often

become more disorganized, increase in amplitude and

slow in frequency, sometimes with the addition of poly-

spikes, whereas the morphology in REM sleep is similar

to wakefulness (Fig. 1).

Fig. 1. Schematic showing distribution of seizures and epileptiform disch

epilepsies. The sleep stages are scored based on normal sleep cycling betwe

eye movement sleep; (REM) cycle during the night. IEDs, interictal discha

epilepsy; FLE, frontal lobe epilepsy; TLE, temporal lobe epilepsy.

In focal epilepsy, timing of seizures appears to be gov-

erned by the type and location of the epileptic focus as well.

Seizures of mesial temporal origin may be particularly vul-

nerable to these effects. Seizures in patients with mesial

temporal lobe epilepsy (MTLE) tend to occur more

frequently during the day than during the night (Quigg

et al., 1998), while seizures in patients with extra-temporal

epilepsy seizures are more likely to occur during sleep

(Crespel et al., 1998). This is particularly more common

in patients with frontal lobe epilepsies in whom seizures

tend to cluster during sleep, almost exclusively during

NREM sleep. In addition, secondary generalization of

partial seizures tends to occur more often during sleep

compared with wakefulness, being more common in

temporal lobe than frontal lobe seizures (Fig. 1).

Focal interictal discharges are much more common

during sleep than during wakefulness (Sammaritano

et al., 1991). Interictal spikes increase at sleep onset,

peaking in NREM 3, and then falling in REM sleep to lev-

els lower than wakefulness. In addition, the field of an

interictal discharge typically enlarges during NREM sleep,

occasionally accompanied by new foci, and becomes

arges across a ‘typical’ 24-h sleep cycle for generalized and focal

en non-rapid eye movement sleep stages 1–4 (NREM1–4) and rapid

rges; IGE, idiopathic generalized epilepsy; JME, juvenile myoclonic

R. A. B. Badawy et al. / Neuroscience 222 (2012) 89–99 91

more diffuse in NREM 3 compared with NREM 1 and 2

and more constricted during REM sleep.

The circadian oscillations within the neuronal net-

works that generate wakefulness, NREM, and REM sleep

are driven by the suprachiasmatic nuclei (SCN), the dom-

inant circadian pacemaker in the mammalian brain. It is

still unknown how this molecular clockwork is controlled

by extracellular neuro-hormones and neurotransmitters

and which membrane receptors undergo circadian modu-

lation. The principal neurotransmitter on SCN synapses is

gamma (c)-aminobutyric acid (GABA), which acts at post-

synaptic GABAA receptors. Studies have shown that there

is daily variation in the postsynaptic GABAA-mediated

functions in the SCN (Kretschmannova et al., 2005).

Observations from patch-clamp studies suggest that

levels of synaptically released GABA from the terminals

of SCN output neurons can influence the relative contribu-

tion of pre- versus postsynaptic GABAB receptors in mod-

ulating both excitatory and inhibitory SCN innervation to

parvo-cellular neurons in the thalamus (Wang et al.,

2003). These studies also report diurnal fluctuations in

spontaneous excitatory postsynaptic activity within this

network that may contribute to the mechanisms for syn-

chronization of rhythms between individual SCN neurons

and may underlie the circadian variations in the spontane-

ous firing frequency of SCN neurons (Lundkvist et al.,

2002).

Sleep is induced by GABA-ergic cells located in the

basal forebrain and in the anterior hypothalamus. Cholin-

ergic neurons in the basal forebrain are directly inhibited

by GABA-ergic sleep active neurons leading to deactiva-

tion of the cortex. These cells are more active during

NREM sleep than they are during REM sleep or during

wakefulness and they also increase discharge rates with

sleep onset and continue to release GABA with increasing

levels as sleep continues (Siegel, 2004).

In generalized epilepsies, reduced cellular discharges

and chemical release in reticulo-thalamic pathways pro-

mote interictal epileptiform discharge generation during

NREM sleep, probably by enhancing the thalamo-cortical

EEG synchronization patterns that are associated with

spike-wave complexes. Sleep transients such as sleep

spindles and possibly even delta waves are contingent on

hyperpolarising GABA-ergic input from the thalamic reticu-

lar nucleus to the thalamo-cortical relay cells. Increased

GABA release from thalamic and cortical neurons is con-

sidered critical to the generation of the slow component

of these discharges (McCormick and Contreras, 2001).

Although the peak in GABA release that occurs during

NREM promotes interictal epileptiform discharges, it

seems to discourage clinically evident seizures such as

myoclonic jerks or GTCs. On the other hand, the moderate

level of reticular activation, chemical release and synchro-

nous thalamo-cortical discharge patterns during drowsi-

ness are conducive to generalized epileptic discharge

propagation with clinical accompaniment. In contrast to

NREM and drowsiness, extreme activation of ascending

brainstem afferents, particularly cholinergic cells that

occurs during wakefulness and REM sleep, abolishes

GABA-mediated synchronous thalamo-cortical discharge

oscillations and leads to desynchronization of the EEG.

This is thought to suppress both ictal and interictal events

during REM sleep and wakefulness (Shouse et al., 2000).

Much less is known about how sleepmodulates epilep-

tic discharges and seizures in focal epilepsies. Reduced

electrochemical activity in reticulo-limbic pathways most

parsimoniously explains interictal propagation from tempo-

ral or frontal lobe foci duringNREMsleep. The effects could

bemediated by direct innervation of focal epileptic neurons.

Studies indicate that local application of noradrenaline

receptor antagonists to limbic seizure foci promotes ictal

discharge propagation, whereas noradrenaline receptor

antagonists block seizure discharge generalization

(Shouse et al., 2000). In a recent transcranial magnetic

stimulation study involving patients with nocturnal frontal

lobe epilepsies, a marked decrease in intracortical inhibi-

tion during NREM sleep was found (Salih et al., 2007).

Mutations in genes coding for subunits of the neuronal nic-

otinic acetylcholine receptors (nAChRs) present in families

with autosomal dominant nocturnal frontal lobe epilepsies

result in a gain in receptor function (Marini and Guerrini,

2007). These studies suggest that increased response to

acetylcholine and enhanced GABA-ergic function may be

the basis for epileptogenesis in nocturnal frontal lobe

epilepsies.

Hormonal variations

Hormones associated with stress. Stress, and emo-

tional stress in particular, is ranked consistently as themost

common trigger of seizures independent of the type of

epilepsy (Frucht et al., 2000). Some have argued this is

predominantly due to the common association of sleep

deprivation and medication noncompliance with stress

(Frucht et al., 2000; Haut et al., 2007). However, there is

also a connection between stress and seizures indepen-

dent of these two factors (Haut et al., 2007). This is further

shown in a study demonstrating that audio and video

recordings designed to elicit empathetically stressful

responses were sufficient to induce spontaneous seizures

in patients with epilepsy (Feldman and Paul, 1976).

Moreover, patients with refractory epilepsy tend to report

triggering factors, such as stress, more often than patients

whose seizures are well controlled with medication. This

finding underscores the potential therapeutic benefits of

managing stress in patients with epilepsy (Sperling et al.,

2008). When faced with a stressful situation, faster, more

instinctual mechanisms regulated by the amygdala, hippo-

campus, and striatum take over, superseding themore log-

ical and analytical functions of the frontal cortex (Arnsten,

1998). The physiologic stress response is often divided into

two separate yet linked systems acting in a coordinated

temporal manner. The rapid response to a stressor

involves the sympathetic-adrenomedullary system, which

results in the activation of the sympathetic nervous system,

increased systemic levels of norepinephrine and epineph-

rine, and increased levels of norepinephrine in the brain.

The slower, longer-lasting response to a stressor involves

the hypothalamic–pituitary–adrenal axis and begins

with the paraventricular nucleus of the hypothalamus

92 R. A. B. Badawy et al. / Neuroscience 222 (2012) 89–99

releasing corticotropin-releasing factor (CRF) (de Kloet

et al., 2005). CRF is also present in the amygdala, hippo-

campus and cortex (Dunn and Berridge, 1990). It is an

important hormone in the regulation of the response to

stress andcanact asanexcitatory neurotransmitter or neu-

romodulator (Dunn and Berridge, 1990). It may also con-

tribute to seizure-related neuronal loss (Ribak and

Baram, 1996). CRF stimulates the pituitary to release adre-

nocorticotropic hormone (ACTH) into the bloodstream.

ACTH stimulates release of glucocorticoids, which

mobilize peripheral energy stores, dampen the immune re-

sponse, and act as mediators in negative feedback control

of the HPA axis (de Kloet et al., 2005). Glucocorticoidsincluding corticosterone and dexamethasone, facilitate

epileptiformdischarges and seizures in animals. This effect

may bemediated by type II glucocorticoid receptors, which

have a diffuse distribution in the brain (Paul and Purdy,

1992). The HPA axis and sympathetic-adrenomedullary

system work in conjunction with one another to coordinate

adaptive responses to a stressor. Chronic glucocorticoid

excess in the setting of chronic stress results in hippocam-

pal neuronal loss and loss of dendritic spines and branch-

ing (Sapolsky et al., 1990). This was postulated to occur

by potentiating NMDA receptor-dependent neurotoxicity.

Menstrual cycle and pregnancy. Many women with

epilepsy experience changes in seizure frequency and

severity over the menstrual cycle and with pregnancy.

The effect of pregnancy on seizure susceptibility is vari-

able, with no conclusive evidence of the effect of pregnancy

on seizure frequency (Harden et al., 2009). On the other

hand, it is well documented that seizures in many women

with epilepsy tend to cluster in relation to the menstrual

cycle, a condition referred to as catamenial epilepsy.

Usually, seizure exacerbation occurs during the peri-

menstrual phase or peri-ovulatory phase or during the

entire second half of menstrual cycles (Herzog et al.,

1997). This phenomenon has largely been attributed to

the neuroactive properties of steroid hormones and the

cyclic variations in their serum levels.Oestrogen increaseslate in the follicular (pre-ovulatory) phaseand thengradually

declines during the luteal (pre-menstrual) phase. It has

beenshown to lower seizure thresholds inmostadult animal

studies (Nicoletti et al., 1985). This effect on neuronal excit-

ability is mediated by increases in glutamate (Wong et al.,

1996) through cytosolic neuronal oestrogen receptors.

Progesterone, on the other hand, increases late in the

follicular phase and then gradually declines during the

luteal phase. It potentiates GABA-mediated inhibition

mainly by increasing the activity of GABAA receptors

(Kokate et al., 1994). This depresses neuronal firing, less-

ens epileptiformdischarges and elevates seizure threshold

(Nicoletti et al., 1985).

Given these competing properties, if seizure exacerba-

tion in women with epilepsy is linked to fluctuations in sex

hormone levels it would be predicted that this would typi-

cally occur when the oestrogen/progesterone ratio is at

its peak. This occurs during ovulation when oestrogen lev-

els are at their highest or right before and during menstru-

ation when the decline in progesterone can be regarded

as pro-convulsant. Indeed, these patterns are seen in

some women with catamenial epilepsy (Herzog, 2008).

However, seizure exacerbation during the entire second

half of the cycle (luteal phase) when progesterone levels

are expected to be high is also commonly reported (Herzog

et al., 2004). Thismay bedue to an inadequate luteal phase

with insufficient rise in progesterone levels to be protective

against seizures in these women (Herzog, 2008). Clinical

data indicating that the catamenial pattern of seizure exac-

erbation is more often observed in women with temporal

lobe epilepsy (Herzog et al., 2004), where reproductive

endocrine disorders such as anovulatory cycles and oligo-

menorhea are also commonly present (Morrell, 1998), and

may also support this proposition. However, this is not a

universal finding (Murri and Galli, 1997). Furthermore,

while most animal studies conclude that oestrogen has

pro-convulsant effects, there is evidence this effect is influ-

enced by the region, the neurotransmitter system, the sei-

zure type, the animal model, the distinct expression of

individual oestrogen receptor types, and the distinct

modulatory effects of oestrogens on the neurotransmitter

system involved in seizure genesis (Veliskova, 2007).

Some studies even report an anti-convulsant effect of

b-estradiol, which is one of the main metabolites of oestro-

gen (Veliskova, 2006).

It is known that progesterone metabolites function as

potent positive modulators of the GABAA receptor (Kokate

et al., 1994; Scharfman and MacLusky, 2006). However,

fluctuations in the circulating levels of this steroid at pub-

erty, during pregnancy, or following chronic stress produce

periods of prolonged exposure and withdrawal. This can

cause changes in GABAA receptor subunit composition

to compensate for sustained levels of inhibition (Smith

et al., 2007). These changes have been shown to pro-

foundly alter GABAA receptor structure and function

(Maguire and Mody, 2009) and subsequent seizure exac-

erbation in catamenial epilepsy. These data indicate that

there is a highly complex interaction between hormones

and the neurotransmitter systems in patients with epilepsy.

This interaction is likely to influence patterns of cortical

excitability and seizure risk across the menstrual cycle.

Blood sugar levels

Blood glucose levels show natural variability, and in gen-

eral, levels are lower after lack of food for extended periods

of time or following exercise. The relationship between

these fluctuations and cortical excitability is largely

unknown. There are several reports of seizures triggered

with lack of food or after prolonged exercise (Frucht et al.,

2000). Seizures are also very common in patients with

impaired transport of glucose across the blood–brain bar-

rier due to deficiency of themajor brain glucose transporter

GLUT1 (Roulet-Perez et al., 2008). These seizures can

occur in the classical severe GLUT1 encephalopathy, but

also in milder cases that have otherwise typical idiopathic

generalized epilepsy. Those patients respond to oral glu-

cose with significant improvement in both clinical seizures

and EEG findings (Suls et al., 2008). It is also well known

that seizures can occur as a complication to severe hypogly-

caemia induced by excess insulin (Malouf and Brust, 1985)

and epileptiform discharges have been recorded on EEG in

the setting of extreme hypoglycaemia. These changes are

R. A. B. Badawy et al. / Neuroscience 222 (2012) 89–99 93

reversed by glucose administration (Niedermeyer and

Lopes da Silva, 2005). It could be that variability in blood

glucose levels is associated with fluctuations in cortical

excitability. These changes may be sufficient to change

seizure threshold in certain patients.

TRANSITION FROM THE INTERICTAL TO THEICTAL STATE

Epilepsy is regarded as a chronic and persistent condition

with a persistent pathology. Therefore, it is fair to ask why

the symptoms are (seizures for example) not persistent.

The answer to this important question lies in the under-

standing of the ever-changing state of cortical excitability.

The intermittency of epileptic seizures poses major chal-

lenges in developing robust treatments. Therefore, under-

standing the mechanisms underlying the transformation

between the relatively normal interictal brain state and

clinical seizures (the ictal transition) is critically important.

Seizures generally occur without warning and

because of that it has largely been assumed that the shift

between the interictal and ictal states occurs as an abrupt

phenomenon. Over recent years, there is growing evi-

dence to indicate that this two-state model is inaccurate,

and that there is a prolonged transitional peri-ictal phase

between the seizure and the interictal state. Preictal pro-

dromal symptoms such as irritability or headache are fre-

quently reported by patients minutes, hours or even days

prior to clinical seizure onset (Delamont et al., 1999). Fol-

lowing a seizure, postictal changes such as confusion and

amnesia are commonly encountered by patients, making

the postictal period for some patients even more disturb-

ing than the seizure itself. In addition, postictal features

are frequently seen on EEG recordings and include regio-

nal or diffuse polymorphic delta activity, attenuation of

EEG rhythms or activation of focal spikes lasting for up

to hours following seizures (Kaibara and Blume, 1988).

Animal studies, show evidence that seizure initiation

depends on a loss of inhibitory control of the epileptogenic

zone resulting in increased excitability of neighbouring

neurons facilitating the spread of seizure activity (Depaulis

et al., 1994). Theoretical studies, involving mathematical

modelling, have demonstrated that seizure initiation may

result from multiple mechanisms. An important study by

Lopes Da Silva et al. (Lopes da Silva et al., 2003) hypoth-

esized three routes to seizures. The first transition is mod-

elled by a jump from normal brain dynamics to seizure

that is trigged by intrinsic neural noise or a particular stim-

ulus. This is illustrated in Fig. 2 where the brain state is

indicated by the grey ball. With no input, the ball will rest

at the bottom of the well (lowest energy point) on the left-

hand side. This position would correspond to the idle state

of the brain, such as alpha activity. With perturbations,

say sensory input, the brain state is free to roll along the

surface in the normal (green) region. The brain state is

effectively trapped in the healthy region and cannot tran-

sition to a seizure without an extremely large perturbation

to overcome the barrier. The brain can, however, still tran-

sition to the seizure state with a high-energy input (i.e.

electrical stimulation) or an extreme level of excitability.

Conversely in the epileptic brain, the transition threshold

(marked by the dashed line in Fig. 2) is lower enabling

transitions to seizure to be trigged by normal fluctuations,

with a sufficient level of excitability. This is the seizure

transition that Lopes Da Silva referred to as bi-stability.

Within this scenario, seizures are thought to be unpredict-

able as intrinsic neural noise (random walk) may trigger

the transition to seizure.

The second scenario presented by Lopes Da Silva

and his colleagues (Lopes da Silva et al., 2003) can be

described by a deformation of the surface that the ball

rolls along, such that the barrier gradually moves to the

right into the epileptic region with physiological changes.

Tracking the aspect of the physiology that deforms the

surface is the goal of seizure prediction.

The third scenario is changes in an exogenous param-

eter, or input, that triggers seizures without any underlying

changes within the brain. An example of this kind is the

well-known photosensitive epilepsy, where flickering light

may trigger seizures. Another example of seizures of this

kind is from the maximal electro-shock rat model of epi-

lepsy (Nelson et al., 2010). In this animal model, seizures

are initiated by electrically stimulating the motor cortex

(M1 region) of normally healthy rats.

It is likely that a combination of the theoretical transi-

tions to seizure presented by Lopes da Silva et al. (2003)

occurs in particular situations. For example, as discussed

in the previous sections there is evidence that seizures

cluster to particular times of the day, week or month. It is

well known that seizures cluster around times of stress,

sleep deprivation and around menstrual cycles (Frucht

et al., 2000). During these times of high seizure susceptibil-

ity it has been shown that, with care, patients can avoid sei-

zures (Spector et al., 2000). Therefore, it is reasonable to

consider these times of stress as a necessary but not suf-

ficient condition for seizure occurrence. In this scenario, a

combination of hyper-excitability (deformed dynamical

landscape) and a particular exogenous input may be

required to trigger an epileptic event.

The pre-seizure or pro-seizure hyper-excitable state has

been measured by multiple imaging modalities, but studies

using intracranial EEG have dominated the literature. This

is due to accessibility of data and the high fidelity of the

recordings. These studies report changes in neuronal com-

plexity and network activity on linear (Esteller et al., 2005)

and non-linear EEG analysis (Martinerie et al., 1998; Litt

et al., 2001; Iasemidis et al., 2005, Le Van Quyen, 2005),

optical recording of intrinsic signals (Zhao et al., 2007) and

a probing-stimulation technique (Kalitzin et al., 2005;

Freestone et al., 2011). These changes last from seconds

to hours prior to seizure onset. Over the past 4 decades this

has evolved into the field of epileptic seizure prediction and

control, with the goal to detect an impending seizure and

stop it before itmanifests clinically. A limitationof intracranial

EEG studies is that they typically use features of the signals

that are abstractions ofwhatwe reallywant tomeasure.This

is illustrated in Fig. 3 that depicts a cascade of events that

culminate in seizures. The goal of experimental studies in

monitoring pre-seizure excitability should be to track physio-

logical variables as far to the left, upstream in the cascade,

as possible. A critical link in the seizure cascade is the

increase in excitability. Another way is to use functional

Fig. 2. A simplified version of the dynamical landscape of healthy and epileptic brains. The solid black line within the axes represents a simplified

version of the brain’s dynamical landscape. The ball marks the current state of the brain. The ball (state) is free to roll across the landscape if it is

perturbed by an input. With a higher level of excitability the ball will have more energy to roll away from the trough given a perturbation from an input

or endogenous activity. In the epileptic brain, the landscape is deformed and the barrier between the normal and epileptic states is lower. Therefore,

given a sufficiently high level of excitability and a particular input the transition to seizure may occur more easily than the healthy brain.

Fig. 3. The seizure cascade. From left to right is a causally related cascade of events that may lead to epileptic seizures.

94 R. A. B. Badawy et al. / Neuroscience 222 (2012) 89–99

MRI (fMRI), a technique that assesses cerebral activity by

detecting signal changes related to focal alterations of de-

oxyhaemoglobin concentration (Ogawa and Lee, 1990).

This has demonstrated significant fMRI signal changes

occurring several minutes before the onset of seizures that

could be localized to the site of the presumed seizure focus,

aswell as to other brain regions (Federico et al., 2005). Non-

equivocal evidenceofamarked increase incortical excitabil-

ity changes lasting for up to 24–48 h before a seizure was

also found on transcranial magnetic stimulation studies

(Wright et al., 2006; Badawy et al., 2009).

Seizure termination is thought to be modulated by

both synaptic excitation and inhibition and is character-

ized by a strong depolarizing shift (block), hyperpolariza-

tion and recovery of neurons in all cortical areas (Pinto

et al., 2005). There is also evidence of relative hypoperfu-

sion in the hippocampus associated with the cessation of

neuronal ictal discharges on postictal brain perfusion

studies (Leonhardt et al., 2005). A prolonged marked

reduction in cortical excitability was also reported on

transcranial magnetic stimulation lasting for up to 24 h

postictally (Badawy et al., 2009). This demonstrated cor-

tical inhibition, possibly creates a physiological postictal

state that is likely to reduce the risk of further seizures.

VARIATIONS WITH TIME

Maturational changes

In many types of epilepsy, especially childhood epilepsy,

seizure types and EEG patterns are age dependent

(Fig. 4). Many epileptic syndromes are only seen in chil-

dren with striking age-dependent patterns that can evolve

or resolve over time (Dulac, 1994). It is also known that

the electro-clinical manifestations of seizures in newborns

are different to those during infancy and childhood, and

some types of seizures e.g. infantile spasms occur exclu-

sively during this early period of development. Normally, in

the first two years of post-natal life there is over-production

of synapses. This is facilitated by the relatively slow

maturation of inhibitory neurotransmitter systems and

R. A. B. Badawy et al. / Neuroscience 222 (2012) 89–99 95

the rapid maturation of excitatory systems. This creates a

functional imbalance between excitatory and inhibitory

synaptic neurotransmission in the brain (Holmes, 1997).

In the immature brain the effects of excitatory neurotrans-

mitter systems predominate initially and then become less

predominant as inhibitory systems gradually mature

(Brooks-Kayal, 2005). The function of the GABA-ergic

system also differs markedly in the mature and immature

brain. Whereas GABAA receptor activation results in neu-

ronal hyperpolarization and an inhibition of cell firing in the

mature brain, receptor activation results in membrane

depolarization and excitation in the immature brain

(Brooks-Kayal, 2005). This is followed by a longer pro-

cess, lasting through mid-adolescence, where pruning of

excessive synapses and activity-dependent refinement

of synaptic connections take place. The visual cortex

completes this process of pruning earlier than the motor

cortex (Huttenlocher and Dabholkar, 1997). Thus one of

the factors that may contribute to the increased suscepti-

bility of infants and young children to seizures is the imbal-

ance between excitation and inhibition in the immature

brain. While this imbalance is a transient and essential

component of normal brain maturation, it may be pro-

longed or even re-emerge later in development due to

various genetic, maturational or acquired factors (Holmes,

1997).

Idiopathic partial epilepsy especially benign childhood

epilepsy with centro-temporal spikes (BECTS) is consid-

ered to be disorders of abnormal brain maturation (Degen

Fig. 4. Time line showing distribution of age-specific e

and Degen, 1992). BECTS usually starts between four

and 11 years and almost all children achieve remission

by adolescence (Kramer et al., 1998). This includes chil-

dren whose seizures have been drug resistant.

Idiopathic generalized epilepsies on the other hand

are thought to mainly have a genetic basis (Helbig

et al., 2008). Genetically determined alterations in sodium

channel structure and function are widely described in

many IGEs. These include generalized epilepsy with feb-

rile seizures plus, severe myoclonic epilepsy of infancy

(SMEI), and benign familial neonatal-infantile seizures

(BFNIS) (Gardiner, 2005; Helbig et al., 2008). These are

strikingly different epileptic syndromes in terms of age of

onset, seizure type and severity, and developmental out-

come, the most benign being BFNIS and the most severe

being SMEI. Mutations in the genes encoding for the volt-

age-dependent potassium channels are described in

benign familial neonatal convulsions (Gardiner, 2005),

which is a rare, autosomal-dominant idiopathic epilepsy.

Seizures occur in well newborn infants from the second

or third day of life and usually remit by six weeks. Child-

hood absence epilepsy which comprises 8% of epilepsy

cases in school-aged (3–13 years) children, also shows

a striking age dependence with a third of the children

becoming seizure free by teenage while the rest either

develop GTCs or evolve into juvenile myoclonic epilepsy.

This pattern suggests that although an autosomal-

dominant pattern of inheritance with age-dependent pen-

etrance causing specific disturbances in ion channels

pileptic syndromes according to age of onset.

96 R. A. B. Badawy et al. / Neuroscience 222 (2012) 89–99

(sodium and calcium) and GABAA receptors has been

described (Helbig et al., 2008), a multifactorial pattern that

involves both genetic and environmental factors is more

likely.

Other common disorders with striking age dependence

are the childhood epileptic encephalopathies. These

include many syndromes in which seizures typically start

to occur during the neonatal period such as early infantile

epileptic encephalopathy to those that start during early

childhood such as epilepsy with myoclonic-astatic sei-

zures. One such syndrome is Lennox–Gastaut syndrome

(LGS). Childrenwith LGS characteristically present in early

childhood, either de novo or as an evolution of West syn-

drome (infantile spasms). Despite the homeogenity in the

electro-clinical presentation, this disorder is commonly

associated with a wide variety of diffuse or multifocal

pathologic processes predominantly, although not exclu-

sively, involving cortical grey matter and subcortical struc-

tures (Markand, 2003).

Progression to chronic epilepsy

Whether or not epilepsy is a progressive disorder is a

matter for debate. There is strong animal evidence con-

firming progressive changes associated with epilepsy.

Prolonged and recurrent seizures in these models lead

to cell loss and subsequent reorganization of synaptic net-

works (Holmes, 2002). A common pathological finding in

patients with focal epilepsy characterized by complex par-

tial seizures is hippocampal sclerosis which consists of

gliosis and neuronal loss primarily in the hilar polymorphic

region and CA1 pyramidal region of the hippocampus,

with relative sparing of the CA2 pyramidal region and an

intermediate lesion in the CA3 pyramidal region and den-

tate granule cells. The available evidence suggests that

status epilepticus and chronic epilepsy with recurrent sei-

zures are associated with neuronal injury and reactive

changes in human and animal hippocampi such that hip-

pocampal sclerosis is generally considered an acquired

lesion (Holmes, 2002). Anecdotally, however, there are

examples of individuals who experienced frequent com-

plex partial and generalized seizures but in whom both

in vivo magnetic resonance imaging (MRI) and postmor-

tem neuropathologic examination were remarkable for

the normality of both hippocampus and neocortex, at least

using qualitative assessment (Holtkamp et al., 2004). This

underlines the heterogeneity of individual susceptibility to

neuronal damage from severe epilepsy, possibly from as

yet undefined genetic factors.

Another commonly described abnormality associated

with seizures is mossy fibre sprouting leading to formation

of recurrent excitatory collaterals, increasing the net excit-

atory drive of dentate granule neurons (Sutula et al.,

1988). Nevertheless, there is evidence in some animal

studies that sprouting can occur without the development

of spontaneous seizures (Cavalheiro et al., 1991) and that

seizures can occur with severe to complete loss of sprout-

ing (Longo and Mello, 1997). There are also reports of

increased number or modified properties of NMDA

receptors (McNamara and Routtenberg, 1995) as well

as reports of glutamatergic modulation of GABA-ergic sig-

nalling among neuronal populations in the epileptic hippo-

campus (Kullmann and Semyanov, 2002). But it remains

difficult to elucidate what changes are due to the actual

underlying pathology or a compensatory mechanism

associated with recurrent seizures over time.

In patients, it is well recognized that complex febrile

seizures early in life are associated with the later develop-

ment of temporal lobe epilepsy (Annegers et al., 1987).

This transition from a latent period to a seizure disorder

is strong evidence of ‘‘progression’’ of the disorder. In

addition to having increased seizure susceptibility, many

if not most MTLE patients become refractory by adoles-

cence or early adulthood (Engel, 1999) and are often

associated with co-morbidities such as cognitive decline

(Marques et al., 2007), which indicates that some change

is occurring in the brain. Furthermore, the number of pre-

treatment seizures was shown to be related to the proba-

bility of subsequent remission (Mohanraj and Brodie,

2006) and in the refractory patients, longer disease dura-

tion has been consistently associated with progressive

atrophy of mesio-temporal lobe structures including the

hippocampus and entorhinal cortex (Bernasconi and

Bernhardt, 2010). There is also evidence of an associa-

tion between the severity of hippocampal damage and

the estimated total seizure burden and seizure frequency

(Briellmann et al., 2002). In addition, progressive neocor-

tical atrophy has been observed in patients with intracta-

ble temporal lobe epilepsy and correlated with epilepsy

duration (Bernasconi and Bernhardt, 2010). Furthermore,

there is recent evidence of progressive changes in cortical

excitability described in a longitudinal transcranial mag-

netic stimulation study on refractory patients with different

forms of idiopathic generalized and focal epilepsies

(Badawy et al., 2010; Badawy et al., 2012).

Conversely, there is growing clinical evidence that in

most cases the occurrence of seizures itself does not influ-

ence the long-term outcome of epilepsy (Berg and

Shinnar, 1997; Marson et al., 2005). These studies

indicate that with the exception of some rare syndromes,

human epilepsy is not a progressive, self-perpetuating

disorder. Furthermore, there is evidence that the co-

morbidities such as cognitive problems remain relatively

stable over time even in patients with refractory seizures

(Holmes et al., 1998) suggesting that recurrent seizures

do not have a major effect on brain function. Clearly, more

human studies need to be performed to resolve this

controversy.

CONCLUSION

In this review we have highlighted the complex and highly

variable patterns of cortical excitability in patients with epi-

lepsy. As summarized in Fig. 5, changes in excitability

can be a result of many factors however; it is a unifying

theme in almost all epilepsies. Bursting behaviour in neu-

rons may arise from a seemingly continuum of multiple

parameters (Marten et al., 2009), thus homoeostatic and

compensatory mechanisms may play an important role.

In order to understand this and the mechanisms behind

the highly variable nature of cortical excitability one must

measure a comprehensive suite of physiological parame-

ters simultaneously. Finding a correlation between a

Fig. 5. Schematic illustrating the different states of an epileptic brain and the different physiological factors that influence cortical excitability during

those state.

R. A. B. Badawy et al. / Neuroscience 222 (2012) 89–99 97

diseased state and a change in a single physiological var-

iable cannot provide a complete solution in bridging our

understanding. In addition, due to the heterogeneity of

epilepsies and diversities of possible mechanisms, a pa-

tient-specific approach must be taken to facilitate our con-

ception of these ever-changing states of cortical

excitability to form new and robust treatment strategies.

DISCLOSURE

None of the authors have any conflict of interest to

disclose.

Acknowledgments—The authors wish to thank Dr. Danny Flana-

gan and Mr. Simon Vogrin, for their insightful suggestions during

the preparation of this manuscript and help with the figures.

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(Accepted 10 July 2012)(Available online 17 July 2012)