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Файл:Ординатура / Хирургия / Библиотека им академика М.И. Перельмана / Книга_5203_Библиотеки_им_академика_М_И_Перельмана.pdf
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Q. Wang et al.
Table 1.3
For drugs that received earlier approval for other indications, year of rst approval refers to initial
approval for a seizure-related indication
a
Year of rst approval of the most recently developed antiseizure medications (ASMs).
ASM Year of rst approval
Vigabatrin 1989 UK
Zonisamide 1989 Japan and South Korea
Lamotrigine 1990 Ireland
Oxcarbazepine 1990 Denmark
Felbamate 1993 USA
Gabapentin 1993 UK and USA
Topiramate 1995 UK
Fosphenytoin 1996 USA
Tiagabine 1996 France
Levetiracetam 2000 USA
Pregabalin 2004 European Union and USA
Runamide 2007 European Union
Stiripentol 2007 European Union
Lacosamide 2008 European Union and USA
Eslicarbazepine acetate 2009 European Union
Retigabine (ezogabine)
Perampanel 2012 European Union and USA
Brivaracetam 2016 European Union and USA
Everolimus 2017 European Union
Cannabidiol 2018 USA
Fenuramine 2020 European Union and USA
Cenobamate 2019 USA
Ganaxolone 2022 USA
Retigabine (ezogabine) was withdrawn from the market in in 2017
a
2011 European Union and USA
Country (or region) of initial
approval
spectrum of efcacy against different seizure types, approved indications, and
adverse effect prole. Details of their different properties are discussed in Chap. 3
of this volume, and only a few general considerations will be made here.
The rst consideration concerns the approach that led to their discovery [54].
Only few of these ASMs were designed rationally to produce the molecular actions
underlying their efcacy against seizures. Examples of drugs designed to engage a
specic target include vigabatrin (an inhibitor of GABA transaminase), tiagabine
(an inhibitor GABA reuptake), perampanel (an AMPA receptor blocker), and ganaxolone (a positive allosteric modulator of the GABAA receptor mimicking the
action of the endogenous neurosteroid allopregnanolone). Some of the other newer
ASMs, such as oxcarbazepine, eslicarbazepine acetate, fosphenytoin, pregabalin,
and brivaracetam, were developed by structural modication of pre-existing ASMs.
The mTOR inhibitor everolimus was approved initially for other indications, and its
investigation as an ASM in patients with tuberous sclerosis complex (TSC) was
based on the known pathogenic role of mTOR overexpression in TSC patients. The
1 Overview
remaining drugs were mainly developed by phenotypic screening in animal models
of seizures and epilepsy, in some cases based on erroneous hypotheses. Gabapentin,
for example, was synthesized as a GABA derivative, but its primary mechanism of
action is not GABA-mediated and consists in inhibition of voltage-sensitive Ca2+
channels through an action at the α2δ modulatory subunit of the Ca2+ channel [55].
Likewise, lamotrigine, which is not a folate antagonist, originated from structural
modication of folate antagonists based on the hypothesis that an action against
folate might produce antiseizure effects [56].
The second consideration about progress made during this period stems from
the clinical trial designs that led to regulatory approval of the “new” ASMs.
Clinical trial designs used in the ASM development evolved markedly during the
last 30years, from small cross-over single-center studies to large parallel-group
multicenter trials (Perucca, 1919). Trial endpoints also evolved over time, mainly
in order to adapt to changes in regulatory scenario and to address ethical concerns
related to the need to minimize prolonged exposure to placebo or ineffective treatments [57].
The third, and most important, consideration is a reection on the extent to which the
ASMs introduced since 1989 improved clinical outcomes for people with epilepsy. As
discussed in detail in recent articles, these medications have not increased substantially
the proportion of patients with epilepsy who can achieve freedom from seizures [58,
59]. The main contribution of ASMs introduced since 1989 is in permitting better tailor-
ing of drug therapy in order to improve tolerability and safety, although there can also be
benet from reduced seizure frequency or severity. Some of these medications, in particular, are devoid of enzyme-inducing potential, and are therefore, at lower risk of causing adverse drug interactions [60, 61] or some manifestations of chronic drug toxicity
[62]. Additionally, some of the newer ASMs, namely lamotrigine, levetiracetam, and
oxcarbazepine, also have a well-documented favorable safety record when used in
women of childbearing potential [63, 64]. An increase in their utilization, together with
a drastic reduction in the use of valproic acid in women with epilepsy of fertile age, has
translated over the years into a decrease in the number of births associated with major
congenital malformations [65]. However, not all the newer ASMs are safe with respect
to risks related to use during pregnancy. Exposure to topiramate, in particular, has been
associated with a comparatively high risk of congenital malformations [66] and of postnatal neurodevelopmental disorders in the offspring [67], and there have also been worrisome teratogenicity signals also for zonisamide [68].
21
1.3.5 The Present Scenario: Managing Epilepsy
withanArmamentarium ofMore than 30 ASMs
No doubt, opportunities to improve outcomes for people with epilepsy are much
greater today than they have ever been in the past [20]. There at least three reasons
for this: (i) a large armamentarium of effective ASMs [20, 69]; NICE, 2022; Perucca
etal., 2023a); (ii) an improved understanding on how to use these ASMs optimally
22
Q. Wang et al.
[20, 70–72]; and (iii) a greater awareness of the important role of epilepsy surgery
[73], dietary treatments [74], and neuromodulation [75] in the management of
patients with difcult-to-treat epilepsies.
With respect specically to the role played by ASMs, the availability of so many
medications allow to tailor drug choice to the individual’s characteristics and preferences. Improved tailoring of treatment is not limited to monotherapy but extends to
rational selection of ASM combinations, whenever use of polytherapy is justied
[76, 77]. Of note, selecting the best ASM for a given individual is only one component of optimal management. Other key components include tailoring of drug dosage based on individual needs (which may change over time due to a variety of
factors, such as intercurrent illness, pregnancy, or drug interactions), and regular
monitoring of clinical response. Measurement of serum ASM concentrations can be
valuable in clinical management, especially in selected situations, but it is important
that these measurements are done and interpreted appropriately, in line with existing
guidelines [78].
The availability of many ASMs is an advantage, but it can also complicate clinical management, particularly for non-specialists who nd it challenging to become
familiar with the indications, contraindications, adverse effects and optimal mode
of use of so many drugs. Therefore, the risk of suboptimal use of the available
ASMs is substantial, especially in non-specialist settings. This has stimulated the
development of tools to assist physicians in choosing the most appropriate ASM for
their patient. One example of such tools is a freely accessible Internet-based algorithm that provides suggestions for personalized ASM selection based on individual
characteristics such as seizure type, age, gender, comorbidities, and comedications
[79]. The algorithm, which is based on input from a group of experts, can be used
only for individuals whose epilepsy started at age 10years or older, and is more
easily applicable to patients with newly diagnosed epilepsy. In an external singlecenter validation study, use of ASMs preferred by the algorithm was associated with
higher seizure freedom rates and lower rates of discontinuation due to adverse
effects compared with ASMs rated as less desirable by the algorithm [78]. Treatments
preferred by this algorithm have also been found to be generally associated with
high retention in a national register database [80]. While this tool may be valuable
in some settings, it cannot substitute the physician’s competent clinical judgement,
because individual patients may have features that are not taken into account by the
algorithm. Another approach that is likely to be perfected in the future is the use of
computerized models to predict response to individual ASMs based on machine
learning-assisted big data analysis [81, 82].The machine learning-based prediction
models described to date do not appear to have the desirable level of performance,
but articial intelligence-based approaches, discussed in a separate chapter of this
volume, are likely to play an important role as an aid to clinical management in
the future.
Although progress is being made, epilepsy in many situations the existing level
of evidence to guide ASM selection remains very limited. Most randomized controlled trials have been designed to address regulatory requirements [31] or to support drug promotion in the market place [83], not to address important questions
1 Overview
faced by clinicians in everyday clinical management. In particular, physicians need
to have evidence from controlled studies on the comparative value of different
ASMs in a given population. Clearly, this information cannot be derived solely from
studies that simply compare one ASM with placebo, often using rigid dosing protocols [84]. In particular, there is a paucity of comparative studies in populations such
as infants and children [85], the elderly [86], patients with generalized epilepsies,
and patients with combined focal and generalized epilepsy syndromes [84, 87].
Admittedly, in recent years the pharmaceutical interest has shown an increasing
interest in developing ASMs for rare epilepsies. As shown in Table1.3, four of ve
ASMs introduced in the market since 2017 are drugs that target seizures associated
with orphan indications, namely tuberous sclerosis complex (everolimus, cannabidiol), Lennox-Gastaut syndrome (cannabidiol, fenuramine), Dravet syndrome
(cannabidiol, fenuramine) and CDKL5 deciency disorder (ganaxolone). For
many ultra-rare epilepsies, precision treatments are currently being identied and
investigated. These may include not only ASMs, but also dietary treatments and
medications approved for other diseases and repurposed for the management of
specic epilepsy syndromes [59, 88].
Despite many advances, the pharmacological treatment of epilepsy still faces
many unmet needs. In particular, we need (i) better tools to predict drug response;
(ii) more effective and better tolerated drugs to achieve freedom from seizures in
patients resistant to currently available ASMs; and (iii) drugs that not only suppress
the seizures, but also modify favorably the course of the disease (disease modifying
epilepsy drugs), and possibly prevent the development of epilepsy (antiepileptogenic drugs). The next section will briey discuss approached by which these unmet
needs could be fullled in the future. Although the discussion below only focuses
on pharmacological treatments, major advances are also expected to take place in
other therapeutic areas, including surgical therapies and neuromodulation-based
therapies.
23
1.3.6 Where Are WeGoing? AGlimpse into theFuture ofDrug
Treatments forSeizures andEpilepsy
As discussed in the previous section, at the present time ASMs are generally prescribed by a trial-and-error approach which takes into consideration a variety of
individual factors, such as seizure types, epilepsy syndrome, age, gender, comorbidities, comedications, and history of response to other drugs. These factors do
provide an estimate of the probability of achieving seizure control with the least
possible risk of adverse effects with a given ASM [20, 70–72]. However, it would
be desirable to have tools that predict with a higher level of condence the response
to specic ASMs, or combinations of ASMs. If such a tool were available, we would
be able to prescribe immediately the safest and most efcacious treatment for that
individual. As mentioned above, efforts are ongoing to use articial intelligence to
identify individualized predictors of response, based on a large number of clinical
24
Q. Wang et al.
variables through a machine learning approach [81, 82]. It is reasonable to expect
that future tools based on big data analysis will be strengthened by inclusion of
genomic, neuroimaging, electrophysiological, and neurochemical data, and other
biomarkers. As an extension of these research efforts, reliable articial intelligencebased tools could also be developed to predict the risk of seizure recurrence after a
rst seizure (in order to aid in the decision on whether to start or to defer treatment)
or the risk of seizure recurrence after ASM discontinuation in individuals who experienced prolonged seizure freedom and are being considered for possible ASM
withdrawal. It might also be possible in the future to develop predictive tools, possibly linked to innovative devices for continuous monitoring of EEG activity, to
identify periods of increased seizure susceptibility, which could be managed by
appropriate adjustment of antiseizure therapies before seizures occur, or become
exacerbated. Similar devices might also be developed to predict the occurrence of
individual seizures with sufcient anticipation to permit ‘on demand’ administration of a rapidly acting ASM in order to prevent or abort the seizure [89, 90].
Accurate predicting tools have the potential to improve the utilization of existing
ASMs, but they will not solve the problem of drug-resistant epilepsy. The need for
safer and more effective treatments is obvious, and intensive research efforts are
ongoing to discover/develop such treatments, which could consist of novel molecules, repurposed drugs currently used for other indications, and non- pharmacological
therapies [86]. Research is also ongoing on novel delivery systems for existing
ASMs, including direct intracerebroventricular (i.c.v.) infusions of ASMs to maximize their efcacy and limit peripheral adverse effects [91]. Such i.c.v. delivery
systems could also permit the utilization of molecules that do not penetrate readily
the blood-brain barrier [91]. Rational development of novel and better ASMs will
require deeper understanding of mechanisms of epileptogenesis and ictogenesis.
For some epilepsies, considerable progress has been made in characterizing not
only the underlying cause, but also the functional defects and pathogenic mechanisms involved. This is paving the way to novel paradigms in epilepsy drug discovery that are directed at targeting not the symptoms (seizures), but the underlying
cause of the disease. Examples of conditions for which precision treatments are
being developed include genetic epilepsies [88, 92], autoimmune seizure disorders
[93], and epilepsies in which brain inammation plays a major role [94–96]. The
potential advantage of etiology-targeted therapies is the feasibility of treating/preventing with a single medication (or an appropriate combination of medications)
not only the seizures, but also associated comorbidities, particularly if such treatments are started early in the course of the disease. Some highly innovative therapies already in clinical development include gene therapies, antisense
oligonucleotides, and direct transplantation of inhibitory interneurons into the epileptogenic brain tissue [20, 86]. Other lines of research that could lead to improved
treatments focus on the characterization of the microbiota–gut–brain axis in epilepsy [97, 98]. Many of these investigations and, ultimately, their clinical applications are likely to be guided by biomarkers that could assist in identifying the
mechanisms responsible for epilepsy, and their responsiveness to specic treatments, in a given individual. One example of such a biomarker that is receiving
1 Overview
25
attention is High Mobility Group Box 1 (HMGB1), a non-histone DNA-binding
protein that is being investigated as a mechanistic biomarker for epilepsy and as a
predictor of drug resistance [99, 100].
Treatments that are effective in preventing epilepsy in high-risk individuals, or
modify the course of epilepsy (and possibly even cure epilepsy) have been the Holy
Grail of epileptology for many years. However, thanks to improved understanding
of the mechanisms of epileptogenesis, such treatments are likely to become available in the future, and to vary according to the etiology of epilepsy and underlying
mechanisms [20, 26]. Again, development of these treatments will be conditional on
the availability of biomarkers to identify as early as possible those individuals who
are going to develop epilepsy due to the expression of pathogenic gene variants [92]
or after epileptogenic insults such a traumatic brain injury or stroke [101–104].
Biomarkers could also be used to monitor response to treatment. An example of a
treatment that in a recent study was suggested to be disease-modifying is provided
by the use of vigabatrin before the onset of clinical or electrographic seizures in
infants with tuberous sclerosis complex [105]. In that study, appearance of epileptogenic EEG abnormalities was the biomarker that permitted identication of infants
at risks, and the initiation of treatment before epilepsy could develop. As it is evident from the considerations above, the identication and use of appropriate biomarkers (or combination of biomarkers) is likely to represent a common denominator
to many strategies under investigation aimed at improving clinical outcomes and at
discovering novel, safe and effective treatments for seizures and epilepsy,
Although much remains to be done, we have gone a long way since the discovery
of bromide’s effectiveness in treating epileptic seizures. Thanks to improved knowledge of the causes and mechanisms of epilepsy, there are reasons to expect that
major therapeutic breakthroughs will occur in the near future. These breakthroughs
will probably generate new challenges. Because of the heterogeneity of the epilepsies, different precision treatments will need to be developed for many rare forms of
epilepsy, which requires continuous investment of resources and application of economic models to ensure return on investment. To date, novel medicines for rare
diseases have typically been made available at very high, often outrageous prices
[106] that only people, or a fraction of people, living in high-income countries are
able to afford [107–109]. In the long run, current models for the development and
marketing of treatments for rare diseases are not going to be economically and ethically sustainable. New models and new paradigms will need to be implemented to
ensure that life-changing medicines for people with epilepsy are not only made
available, but also made accessible and affordable everywhere in the world.
1.4 Research onAnimal Models ofEpilepsy
Epilepsy, characterized by recurrent seizures resulting from highly synchronized
abnormal neuronal discharges, is a spontaneous brain dysfunction [2]. The exploration of the underlying mechanisms and abnormal discharge patterns linked to
26
Q. Wang et al.
seizures has emerged as a central focus in epilepsy research, with the use of animal
models playing a pivotal role. Behavioral assessments and the evaluation of pathophysiological phenotypes in these models contribute to the testing of new antiepileptic drugs, gauging the effectiveness of novel compounds, and discerning
molecular and network mechanisms for the treatment of epilepsy and its
complications.
1.4.1 An Animal Model ofEpilepsy
For an animal model of epilepsy to be considered valid, it must mimic symptoms
and phenotypes of human seizures, such as convulsive seizures and abnormal discharges, which is referred to as face validity [110, 111]. Moreover, the model should
extend beyond face validity by eliciting molecular, cellular, and connectivity
changes specic to distinct types of epilepsy, thereby mirroring the pathogenic
mechanisms observed in human diseases—termed construct validity [110, 111]. As
the efcacy of targeted treatments for epilepsy faces growing limitations, it is
imperative for epilepsy animal models employed in the screening of potential antiepileptic drugs to faithfully reproduce treatment responses observed in clinical settings, known as predictive validity [111]. Currently, no epilepsy animal model
perfectly fullls all three validity criteria.
Epilepsy animal models are developed through the induction or genetic predisposition of specic species to epilepsy [111]. Almost all species with a central nervous system have the potential to develop epilepsy, thereby expanding the pool of
species available for epilepsy models [111, 112]. Spontaneous epileptic seizures in
many species occur sporadically, making them often unsuitable for experimentation
[113]. Ideally, the species chosen for an epilepsy model should readily exhibit spontaneous seizures or be easily induced under controlled experimental conditions.
Furthermore, the nervous system of the selected species should closely approximate
that of humans in terms of anatomy, physiology, or biochemistry. In the early stages
of epilepsy research, emphasis was placed on species such as cats, dogs, and nonhuman primates, which were prioritized for studying experimentally induced seizures
[111–113]. Nonhuman primates, including monkeys and baboons, possess brain
structures and genomes more akin to those of humans, rendering them invaluable
for elucidating neuroanatomical features and genetic foundations [111].
Considering the practical aspects of experimentation, the selection of species for
creating epilepsy models should prioritize the ease of breeding, raising, observation,
and specimen collection. Rodents, particularly Norway rats (Rattus norvegicus) and
mice (Mus musculus), have progressively become more prominent in epilepsy models, likely owing to their small size, docility, and convenience due to controlled
breeding environments [111]. Currently, rodents are the primary species used for
constructing epilepsy models [112]. Other species, including fruit ies, zebrash,
birds, sea lions, baboons, chickens, rabbits, hamsters, and pigs, also play roles in
epilepsy research [32, 111, 113].
1 Overview
27
The development of epilepsy animal models has evolved from simple acute seizure models to complex chronic seizure models, progressing from stimulus-induced
seizures to spontaneous seizures, closely resembling human epilepsy phenotypes.
Epilepsy animal models can be classied based on the causes of seizures into
genetic models and acquired epilepsy models (Table 1.4). Genetic models stem
from specic genetic changes leading to seizures, while acquired models are
induced in healthy animals through the application of specic chemicals, electrical
stimulation, or conditions such as trauma, stroke, and infection.
1.4.2 Acute Epilepsy Models
Seizures can be observed following acute injury or genetic manipulation in almost
all animals with a nervous system, rendering acute epilepsy models widely applicable. David Ferrier [114], an epilepsy research pioneer in the 1870s, conducted
groundbreaking work by directly stimulating the cortices of rabbits, guinea pigs,
cats, and dogs, revealing the occurrence of acute tonic–clonic seizure events similar
to those seen in human epilepsy. Commonly employed models for screening antiseizure drugs in acute settings include the maximal electroshock seizure (MES)
model, the 6Hz psychomotor seizure model, the acute pentylenetetrazol-induced
seizure model, and the local penicillin model.
1.4.2.1 Maximal Electroshock Seizure Model
In 1937, Merritt and Putnam [115] induced seizures in cats using electrical stimulation,
revealing the anticonvulsant effects of phenytoin. Swinyard [116] subsequently developed the standardized MES model for rodents, which mimics tonic–clonic seizures in
Table 1.4 Animal models of
epilepsy and seizures
Genetic animal models Acquired animal models
Rodent animal models Acute seizures
Absence seizure
models.
Reex seizure
models.
Non-rodent animal
models
Papio papio models. Electrical kindling models.
Zebrash models. Chemical kindling models.
Electrically induced seizures.
Chemically induced seizures.
Chronic seizures
Optogenetic kindling models.
Post-status epilepticus models
Trauma, stroke, infection-induced
models
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Q. Wang et al.
humans, and used this model for drug screening. The MES procedure involves placing
electrodes near the eyes or ears of the animal and applying a strong current to induce
brief electrical stimulation through the cornea or ears to the brainstem structures, resulting in generalized tonic–clonic seizures in the hind limbs (the endpoint of the test) [117,
118]. The stimulation parameters are generally 50mA for mice and 150mA for rats,
with corneal electrodes at 60Hz and a stimulation time of 0.2seconds [117].
1.4.2.2 6Hz Psychomotor Seizure Model
The 6Hz psychomotor seizure model, developed in 1951 by Toman [119], involves
prolonged (3 or 4s) low-frequency (6Hz) electrical stimulation of the corneas of
mice, which induces psychomotor seizures with minimal clonic periods, followed
by stereotypical spontaneous behavior, mimicking that of focal epileptic seizures
[111]. This model exhibits resistance to drugs such as phenytoin [118]. However,
recent experiments suggest that the drug resistance of the 6Hz psychomotor seizure
model should be considered in terms of animal strains and experimental conditions,
with CF-1 and B6 mice showing phenytoin resistance, while NMRI mice exhibit a
therapeutic response [111].
1.4.2.3 Acute Pentylenetetrazol-Induced Seizure Model
The acute pentylenetetrazol (PTZ)-induced seizure model is utilized to mimic
clonic seizures. PTZ, a GABA-A receptor antagonist, reduces the function of inhibitory synapses, increasing neuronal excitability, and triggering generalized seizures
[120, 121]. In various animal species, including mice, rats, cats, and primates, PTZ
is administered through injection (subcutaneous, intravenous, or intraperitoneal)
[122]. Common doses for inducing seizures in mice include 85mg/kg subcutaneously, 50mg/kg intravenously, and 50–75mg/kg intraperitoneally. In the acute PTZ
model for rats, observable effects include involuntary movements of the head, forelimbs, or hindlimbs, progressing to falling, clonic–tonic seizures, and complete
limb extension, with hindlimb extension as an observation endpoint [112]. Various
antiseizure drugs targeting ion channels or receptors, such as trimethadione and
ethosuximide [111, 117], have been identied using the acute PTZ model. Notably,
the MES model is considered pharmacologically independent, while the acute PTZ
model may interact with the tested antiseizure drugs [32, 112].
1.4.2.4 Local Penicillin Model
In 1945, penicillin, initially employed in neurosurgical procedures to prevent postoperative infection, was serendipitously discovered to possess a local proconvulsant
effect [123]. Placing cotton balls soaked in 1.7–3.4mM penicillin on the exposed
cortices of rats or cats, followed by the local placement of electrodes, enabled the
1 Overview
29
recording of recurrent interictal spike waves within minutes, resembling those
observed in human cortical electroencephalogram recordings [113, 124]. During
spike activity, neurons in the focal area tend to synchronize discharges [113]. In the
macaque hippocampus, the injection of penicillin established a temporal lobe epilepsy model characterized by behaviors such as motionless staring, head tilting, oral
chewing, and lip-smacking [125]. Pathological features, including neuronal loss,
glial cell proliferation, and hippocampal sclerosis, were detected [125] Although
the local penicillin model is instrumental for studying the neural basis and spread of
focal seizure activities, its initiation from known epileptic foci limits its ability to
fully replicate the complex mechanisms of human epilepsy [113].
Other compounds used for chemically induced acute seizure models include
bicuculline, which induces clonic seizures in mice at a subcutaneous injection dose
of 2.7mg/kg [126, 127]; picrotoxin, which induces seizures at an intraperitoneal
injection dose of 7.5mg/kg [128]; strychnine, which induces seizures at an intraperitoneal injection dose of 2.5mg/kg; and isoniazid, which induces seizures at an
intraperitoneal injection dose of 250mg/kg [126, 129].
1.4.3 Chronic Epilepsy Models
Acute seizure models are designed to characterize acute seizure events but are lacking in
representation of the chronic phenotype of spontaneous recurrent seizures. These models also lack the pathophysiological changes associated with chronic epileptic seizures,
such as neuroinammation and protein expression changes [130]. Consequently, as a
chronic epilepsy model, the kindling model has emerged to simulate the complexity of
human focal seizures and secondary generalized seizures [131]. Kindling refers to the
plasticity phenomenon induced by epileptic seizures [131]. When continuous low-dose
electrical or chemical stimulation is applied to specic regions, such as the amygdala or
hippocampus, the threshold for epileptic seizures decreases, and seizure susceptibility
gradually increases, leading to a kindling response [131]. The kindling model can be
categorized into one of three types based on the nature of stimulation: the electrical
kindling model, the chemical kindling model, and the optogenetic kindling model.
1.4.3.1 Electrical Stimulation Kindling Model
Electrical stimulation kindling typically involves the implantation of electrodes in
specic brain regions of the animal, administering subthreshold stimuli repetitively
and intermittently to achieve kindling effects [111, 131–133]. Commonly targeted
brain areas for kindling include the amygdala, hippocampus, and perirhinal cortex
[111, 131–133]. Even local electrical stimulation of the cornea has been shown to
induce kindling [130]. In rats, commonly used stimulation methods include 60Hz
sine-wave or biphasic pulses [132]. The kindling rate and seizure patterns exhibit
variation based on strain and age [134]. Racine [135] classied kindling-induced