CONTROL AND ANALYSIS OF SEIZURE ACTIVITY IN A SODIUM CHANNEL MUTATION MODEL OF EPILEPSY
by
KARA BUEHRER KILE
Submitted in partial fulfillment
of the requirements for the degree of
Doctor of Philosophy
Dissertation Advisor: Dominique M. Durand, Ph.D.
Department of Biomedical Engineering
CASE WESTERN RESERVE UNIVERSITY
January 2009
CASE WESTERN RESERVE UNIVERSITY
SCHOOL OF GRADUATE STUDIES
We hereby approve the thesis/dissertation of
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candidate for the ______degree *.
(signed)______(chair of the committee)
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(date) ______
*We also certify that written approval has been obtained for any proprietary material contained therein.
DEDICATION
To my parents, Dr. Richard E. Buehrer and Maureen J. Buehrer, for the many ways they
have enriched my life, one of which was instilling in me a passion for academia.
To my husband, Warren R. Kile, for his unconditional love and limitless understanding.
To my daughter, Rose Marie Kile, for enhancing every moment of my work with a
greater perspective, motivation, and joy.
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TABLE OF CONTENTS
DEDICATION………………………………………………………………………….III
TABLE OF CONTENTS………………………………………………………………IV
LIST OF TABLES…………………………………………………………………...VIII
LIST OF FIGURES…………………………………………………………………….IX
ACKNOWLEDGEMENTS……………………………………………………………XI
ABSTRACT……………………………………………………………………………XII
CHAPTER 1 ……………………………………………………………………………..1
DISSERTATION INTRODUCTION AND OBJECTIVES
1.1 EPILEPSY…………………………………………………………………….1
1.2 GENETIC ORIGINS OF EPILEPSY…………………………………………1
1.3 TRANSGENIC ANIMAL MODEL…………………………………………..3
1.4 CLINICAL TREATMENT OF EPILEPSY…………………………………..4
1.5 DEEP BRAIN STIMULATION………………………………………………6
1.6 THESIS OBJECTIVES AND ORGANIZATION……………………………9
1.6.1 Objective I…………………………………………………………..9
1.6.2 Objective II………………………………………………………...11
1.6.3 Objective III………………………………………………………..12
CHAPTER 2…………………………………………………………………………….16
SCN2A SODIUM CHANNEL MUTATION RESULTS IN HYPEREXCITABILITY IN THE HIPPOCAMPUS IN VITRO
2.1 ABSTRACT………………………………………………………………….16
2.2 INTRODUCTION……………………………………………………...……17
2.3 METHODS…………………………………………………………………..20
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2.3.1 Animals…………………………………………………………….20
2.3.2 Histology and cerebral spinal fluid extraction……………………..22
2.3.3 Hippocampal slice preparation and perfusion……………………...23
2.3.4 Electrophysiology and data analysis……………………….………23
2.4 RESULTS……………………………………………………………………25
2.4.1 Spontaneous activity in Q54 slices…………………...……………25
2.4.2 Evoked PS amplitude response curve in Q54 slices…………….…26
2.4.3 Cresyl violet histology of Q54 slices………………………………27
2.4.4 Cerebral spinal fluid of Q54 mice……………………………….…27
2.4.5 Paired pulse test of recurrent inhibition……………………………28
2.4.6 Response to high-frequency stimulus……………………………...28
2.5 DISCUSSION………………………………………………………………..30
CHAPTER 3…………………………………………………………………………….48
EFFECT OF LOW FREQUENCY DEEP BRAIN STMIULATION ON SEIZURE ACTIVITY IN VIVO
3. 1 ABSTRACT…………………………………………………………………48
3.2 INTRODUCTION…………………………………………………………...49
3.3 METHODS…………………………………………………………………..54
3.3.1 Animals…………………………………………………………….54
3.3.2 Electrode implantation……………………………………………..55
3.3.3 Stimulation and recording………………………………………….56
3.3.4 Data analysis……………………………………………………….57
3.4 RESULTS……………………………………………………………………57
3.4.1 Baseline seizure activity…………………………………………...57
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3.4.2 High frequency oscillations during seizures……………………….59
3.4.3 Reduction of seizure frequency during LFS……………………….60
3.4.4 Effect of stimulation state on seizure frequency………..………….61
3.5 DISCUSSION………………………………………………………………..61
CHAPTER 4…………………………………………………………………………….81
A NOVEL MULTI-PRONGED ELECTRODE FOR DEEP BRAIN STMIULATION OF WHITE MATTER
4.1 ABSTRACT………………………………………………………………….81
4.2 INTRODUCTION…………………………………………………………...82
4.3 METHODS…………………………………………………………………..83
4.3.1 Bioelectric field model.…………………………………………….85
4.3.2 Electrode fabrication...……………………………………………..86
4.3.3 Impedance measurements………………………………………….87
4.3.4 Axonal stimulation by electrode prototypes……………………….87
4.3.5 Data analysis………………………….……………………………88
4.4 RESULTS……………………………………………………………………89
4.4.1 Bioelectric field model.…………………………………………….89
4.3.2 Electrode fabrication...……………………………………………..92
4.5 DISCUSSION………………………………………………………………..92
CHAPTER 5…………………………………………………………………………...111
CONCLUSIONS AND FUTURE DIRECTIONS
5.1 FULFILLMENT OF THESIS OBJECTIVES……………………………...111
5.1.1 Objective I………………………………………………………...111
5.1.2 Objective II……………………………………………………….112
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5.1.3 Objective III………………………………………………………113
5.2 CONCLUSIONS AND FUTURE DIRECTIONS…………………………114
REFERENCES………………………………………………………………………...117
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LIST OF TABLES
Table 1.1: Channelopathies: Voltage-gated sodium channel genes associated with human idiopathic epilepsy syndromes……………………………………………………….…..13
Table 1.2: Voltage-gated Na+ channel types and expression…………………………….14
Table 2.1: Quantitative histology………………………………………………………...38
Table 2.2: Slices with CA1 activity following tetanic stimulus…………………………39
Table 3.1: Signal power in frequency bands……………………………………………..68
Table 4.1: Effect of current injection on activation of target area…………………….....96
Table 4.2: Effect of electrode geometry on current density……………………………...97
Table 4.3: Effect of configuration on activation of target area………………………….98
Table 4.4: Electrode prototype impedance measurements………………………………99
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LIST OF FIGURES
Figure 1.1: Scn2a sodium channel mutation in Q54 mice………...……………………..15
Figure 2.1: Spontaneous activity in Q54 hippocampal slices……………………………40
Figure 2.2: Evoked CA1 population spike response curve………………………………41
Figure 2.3: Morphology of the hippocampus in Q54 hippocampal slices……………….42
Figure 2.4: Response to paired pulse stimuli in Q54 hippocampal slices……………….43
Figure 2.5: Response to tetanic stimulus in Q54 hippocampal slices……………………44
Figure 2.6: Duration of evoked after discharge in CA1………………………………….45
Figure 2.7: Frequency analysis of tetanically induced activity…………………………..46
Figure 2.8: CA1 population spike between tetanic stimulus trains……………………...47
Figure 3.1: Surgical targets………………………………………………………………69
Figure 3.2: Surgical implantation………..………………………………………………70
Figure 3.3: Q54 model seizures………………………………………………………….71
Figure 3.4: Chronic recording……………………………………………………………72
Figure 3.5: Daily seizure frequency...……………………………………………………73
Figure 3.6: Signal frequency analysis……………………………………………………74
Figure 3.7: Very high frequency band spectral density during seizure…………….……75
Figure 3.8: Changes in DPE signal power over frequency bands...... ……………………76
Figure 3.9: Low frequency stimulation (LFS) protocol…….……………………………77
Figure 3.10: Stimulation during chronic recording…...………………………………….78
Figure 3.11: Effect of low frequency stimulation (LFS) no seizure frequency….………79
Figure 3.12: Effect of stimulation state on seizure frequency…...………………………80
Figure 4.1: Deep Brain Stimulation (DBS) target……...………………………………100
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Figure 4.2: Medtronic DBS electrodes………..………………………………………..101
Figure 4.3: Bioelectric field model design…..………………...………………………..102
Figure 4.4: Electrode prototype fabrication………………...…………………………..103
Figure 4.5: Model validation…………………….……...………………………………104
Figure 4.6: Stripped end (SE) current density profiles…………………………………105
Figure 4.7: Stripped middle (SM) current density profiles...…………………………...106
Figure 4.8: Current density along electrode edge………………...…………………….107
Figure 4.9: Electrode contact configurations…………………………………………...108
Figure 4.10: Electrode prototype impedance..………………...………………………..109
Figure 4.11: Evoked population spike……………………...…………………………..110
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ACKNOWLEDGEMENTS
I would like to extend my sincerest gratitude and thanks to the numerous individuals without whom I could not have completed this project, including but not
limited to the following. My advisor, Dominique M. Durand, provided extensive
guidance and foresight as well as continuous, encouraging support in my becoming a
competent research scientist. My committee members, David Friel, Joseph Nadeau,
Dawn Taylor, and Mary Ann Werz, provided invaluable thoughts and ideas which
contributed greatly to the development and assessment of this project. My lab mates,
Alicia Jensen, Andrew Kibler, David Tang, and Nan Tian, were instrumental in their
companionship, assistance, and intellectual support. My dear friends, Deborah
Barkauskas, Rachel Maulucci, Jennifer Parker, and Christa Wheeler, enhanced my
quality of life as a graduate student and continually showed me how to be a better person.
My brothers, R. Michael Buehrer, Gregory T. Buehrer, Brian J. Buehrer, and Mathew W.
Buehrer, gave thoughtful advice and set an example for me to follow. The faculty and
staff within Departments of Biomedical Engineering, Neuroscience, and Genetics,
created an atmosphere supportive of challenging research and great collaborations within
Case Western Reserve University. Dr. Miriam Meisler and the Human Genetics
Department at the University of Michigan, who graciously donated Q54 strain colony
founders. Lastly, I would like to acknowledge the following institutions for their
financial support of this project: The National Institutes of Health (R01-NS-40785), Ohio
Board of Reagents (Innovation Incentive Fellowship), United States Department of
Education (Neural Engineering Training Grant), and Walter H. Coulter Foundation.
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Control and Analysis of Seizure Activity in a Sodium Channel Mutation Model of Epilepsy
Abstract
by
KARA BUEHRER KILE
Individuals with epilepsy experience recurrent and unprovoked seizures characterized by uncontrolled, excessive neurological activity. Seizures can be debilitating and often resistant to available drug therapies. Deep brain stimulation is an excellent new therapy in the treatment of Parkinsons, nevertheless its mechanisms of action are not clearly understood. Ongoing research is essential for a complete understanding of the mechanisms of action of DBS in order to determine the most effective stimulation parameters for epilepsy therapy including target location, frequency, amplitude, and duration.
Genetic models of disease can provide invaluable insight into disease development, progression, and treatment. The Q54 model, is a mouse model of epilepsy resulting from a single sodium channel mutation that was utilized in this study to examine inherited seizure characteristics in vitro and in vivo, and evaluate the application of novel
DBS parameters.
The data presented here suggest that Q54 mice experience increased excitability and spontaneous activity in the hippocampal slice in vitro, as well as chronic recurrent hippocampal seizures in vivo. Furthermore, low frequency stimulation applied to the ventral hippocampal commissural fibers (VHC) in Q54 mice is successful in the reduction of seizure frequency and is therefore a potential new therapy for the treatment
xii
of epilepsy syndromes. In addition, an electrode model was developed for application of low frequency deep brain stimulation to white matter tracts, such as the VHC, in the treatment of epilepsy.
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Chapter 1: Dissertation Introduction and Objectives
1.1 EPILEPSY
Epilepsy is the most prevalent chronic neurological disorder, affecting over 3
million Americans with approximately 200,000 new cases reported each year
(epilepsyfoundation.org). Although there are multiple epilepsy syndromes, all are characterized and identified by the presence of seizures. Seizures are the result of a disturbance among neuronal populations that leads to uncontrolled neuronal firing
characterized by large electrical field oscillations in one or more areas of the brain.
1.2 GENETIC ORIGINS OF EPILEPSY
Clinically, epilepsy is classified as either causative or idiopathic. However,
idiopathic epilepsy is often considered synonymous with genetic epilepsy because those
seizures that arise devoid of an apparent external cause are thought to develop from an
inherent genetic origin. The variety of cellular and molecular mechanisms that give rise
to epilepsy provide a myriad of target sites for epilepsy triggering mutations, including
genes for ion-channel function, brain development, and cerebral energy metabolism (Bate
and Gardiner, 1999a, b).
Many ion channels are involved in neuronal activity, but sodium channels play a
key role in epilepsy. Two well known antiepileptic drugs (AEDs), carbamazepine
(Tegretol) and phenytoin (Dilantin), act by enhancing the inactivation property of the sodium channel. Enhancing inactivation increases the refractory period of the cell, thus slowing or preventing the occurrence of rapid repetitive firing. In addition, increased
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brain sodium channel transcript levels are known to occur in the epileptic human brain
(Lombardo et al., 1996), further supporting the conclusion that sodium channels are likely to be the primary mechanism for most, if not all forms of epilepsy (Tian et al.,
1995).
Mutations in ion channel encoding genes, ‘channelopathies’, alter the normal function of a specific channel resulting in altered brain excitability and the initiation of epileptic seizure. Several channel mutations have been identified in the development of epileptic seizure, including those that act to alter the function of both ligand-gated and voltage-gated sodium channels (Table 1.1).
Voltage-gated sodium channels consist of a single pore-forming α-subunit as well as one or more auxiliary β-subunits (Table 1.2). There are at least four sodium channel β- subunits (Scn1b-4b) and nine α-subunits (Scn1a-11a), four of which are primarily responsible for encoding sodium currents in the brain: Scn1a, Scn2a, Scn3a, and Scn8a
(Catterall et al., 2005). Specifically, Scn1a subunits are involved in somatodendritic sodium influx necessary for dendritic integration while Scn2a subunits are primarily involved in axonal fast sodium influx necessary for action potential initiation and propagation (Kullmann, 2002).
Slight variations in protein-coding sequences can significantly modify these structures and their gating kinetics. Mutations in three genes encoding isoforms of the voltage-gated sodium channel subunits (Scn1a, Scn2a, Scn1b) have been identified in human idiopathic epilepsies including generalized epilepsy with febrile seizures plus
(GEFS+) (Wallace et al., 1998; Escayg et al., 2000; Escayg et al., 2001; Lerche et al.,
2001; Sugawara et al., 2001a; Sugawara et al., 2001b; Wallace et al., 2001; Wallace et
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al., 2002; Kearney et al., 2006a), severe myoclonic epilepsy of infancy (SMEI) (Claes et
al., 2001; Ohmori et al., 2002; Sugawara et al., 2002; Claes et al., 2003; Fujiwara et al.,
2003; Ceulemans et al., 2004a; Kamiya et al., 2004; Ohmori et al., 2006; Suls et al.,
2006), and benign familial neonatal-infantile seizures (BFNI) (Heron et al., 2002;
Berkovic et al., 2004). GEFS+ is characterized as a childhood onset syndrome featuring
febrile convulsions and a variety of afebrile epileptic seizure types with autosomal
dominant inheritance (Scheffer and Berkovic, 1997; Berkovic and Scheffer, 1999).
SMEI is characterized by clonic and tonic-clonic seizures in the first year of life that are often prolonged and associated with fever (Dravet and Bureau, 1981). The substantial incidence of mutations in genes encoding sodium channel subunits that have been associated with the development of epilepsy confirm that alteration in sodium channel genetics is a primary cause of inherited epilepsy syndromes.
1.3 TRANSGENIC ANIMAL MODEL
Biomedical research has been revolutionized by the availability of genetically
altered mice as models of human disease. Insight can be gained into the genetics of
disease pathogenesis, leading to progress in therapeutic intervention. However, data
obtained from such genetically altered mice must be interpreted carefully, and
appropriate mouse model selection is very important. One Scn2a mutation, GAL879-
881QQQ (Figure 1.1), alters the structure of the S4-S5 linker of alpha-subunit domain
two and results in delayed channel inactivation and increased persistent current when
expressed in Xenopus oocytes (Smith and Goldin, 1997; Kearney et al., 2001).
3
Introduction of this missense mutation into mice resulted in the development of
the Q54 model of temporal lobe epilepsy (Kearney et al., 2001). Voltage dependence of
inactivation of the mutant sodium channel, and its persistent current in the Q54 strain of transgenic mice expressing the GAL8790881QQQ mutation of Scn2a gene were studied
in detail by Kearney et. al. Characterization of the mutant channel in Xenopus oocytes showed that the mutant channel inactivated more slowly than the wild type channel.
Recent Q54 model research has revealed that genetic background can significantly influence the severity of phenotypic expression (Bergren et al., 2005; Kearney et al.,
2006a). Nevertheless, as with most genetic animal models of human disease, the mechanisms behind the development from genotype to phenotype in this unique model of temporal lobe epilepsy remain unclear and further investigation is required. Objective one of this thesis was to characterize Q54 hippocampal brain slices in vitro, to broaden the understanding of the development of seizures in this animal model and contribute to the overall understanding of phenotype development in genetic animal models of nervous system disease in general.
1.4 CLINICAL TREATMENT OF EPILEPSY
Epilepsy symptoms are most commonly treated with medication by way of
antiepileptic drugs (AEDs). The most commonly prescribed AEDs have one or more of
the following mechanisms of action: blockage of voltage-gated calcium or sodium
channels, increased GABA inhibition, or decreased glutamatergic excitation. For
example, sodium channel blockers commonly prescribed include phenytoin (Dilantin),
carbamazepine (Tegretol), and topiramate (Topamaz). Valproic acid (Depankene,
4
Convulex) is thought to block both sodium channels and calcium channels, as well as enhance GABA transmission.
Because of the multitude of AEDs available and their varied mechanisms, patients usually cycle through several AEDs before finding a “best fit” and even then treatment often does not eliminate seizures completely nor does it come without unwanted side effects. Thus medicinal therapy of epilepsy symptoms is a dance that can last throughout a patient’s lifetime that may never find an acceptable rhythm. Alternatively, intractable
AED resistant seizures can be treated with neurosurgery, but often the ablation or removal of epileptic foci can have more damaging consequences to the patient than the seizure activity itself. More recently, vagal nerve stimulators have added another alternative to AEDs through the use of electrotherapy as a means of treatment for seizure disorders. For this reason, it is also thought that electrotherapy applied directly to the brain, deep brain stimulation (DBS), may provide a more successful therapy option.
Similarly, seizure development is multifactorial, and the significance of each component will likely change between clinical classifications of epilepsy. Identification of specific genetic mutations and their association with known forms of epilepsy could provide a unique insight to specific disorder varieties. Such an addition to our current understanding will help to further define the critical factors in seizure development on a broader scale. An in depth examination of the characteristics of the Scn2a mutation, as well as its mechanisms of action broadens our understanding of genetic models of human disease, specifically the role of the Scn2a mutation in seizure development. These insights can then be applied to enhance clinical diagnosis, and eliminate unnecessary
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treatment steps toward establishing the ideal therapy for the management of epilepsy syndromes that are disease, and perhaps even mutation specific.
1.5 DEEP BRAIN STIMULATION
A great number of epilepsy patients have persistent debilitating seizures that are resistant to AED therapy, creating a demand for alternative therapies. Despite the success of resective brain surgery in reducing seizure frequency, permanent neurologic deficits can result from the removal of brain tissue containing epileptic foci. Vagus nerve stimulation (VNS) is a growing therapy that can result in up to a 50% reduction in seizure frequency (Salinsky et al., 1995). Limited success of VNS has led to the study of electrical stimulation therapy applied to new targets that are closer to the affected tissue deep within the brain.
Deep brain stimulation (DBS) is a surgical treatment involving the implantation of a brain pacemaker, a device that delivers electrical impulses to a specific region of the brain. DBS has provided remarkable therapeutic benefits for several treatment-resistant disorders. DBS is currently recognized as a therapy for the treatment of Parkinson’s disease (PD) (Obesco et al., 2001), essential tremor (Benabid et al., 1996), and dystonia
(Vidailhet et al., 2005). More recently, it has been used to treat other neurological conditions including depression (Mayberg et al., 2005), obsessive-compulsive disorder
(Gabriels et al., 2003), and epilepsy (Hodaie et al., 2002). In addition, the effects of DBS on brain activity appear to be reversible unlike other neurosurgical therapies such as lesioning of the affected area.
6
Although high frequency stimulation (HFS) parameters are generally used in DBS therapies, low frequency stimulation (LFS), in the range of 0 - 10 Hz, is also a strong candidate for epilepsy therapy. While HFS is thought to inhibit neuronal activity through
axonal conduction block, LFS may inhibit activity by increasing the threshold for the
firing of neuronal action potentials through more complex mechanisms such as long term
depression (LTD) (Albensi et al., 2004; Schrader et al., 2006). This suggests that LFS could have a longer lasting effect on target tissue, requiring fewer stimulation periods and less current injection overall. This is in addition to the fact that LFS inherently requires less current injection, due to the reduced number of stimulation pulses per second.
Minimizing current injection is an important factor in the enhancement of stimulation
electrode stability as well as in the reduction of local tissue damage.
To date, LFS has shown success in several animal models of epilepsy. Low frequency stimulations, ranging from 0.1 - 10 Hz, were able to suppress high extracellular
potassium and bicuculine induced seizures in the rat hippocampus in vitro (Jerger and
Schiff, 1995; (Albensi et al., 2004). Similarly, multiple studies have shown a suppressive effect on afterdischarges elicited by kindling in the amygdala of the rat in vivo, when kindling was followed or preceded by 1-3 Hz stimulation (Velisek et al., 2002;
(Goodman et al., 2005). Suppression of seizure activity has also been seen in a limited number of human studies. For example, LFS of 0.5 Hz applied to ictal zones resulted in a reduction of seizure initiation in 4 of the 5 identified seizure onset zones (Schrader et al.,
2006).
Despite the long history of DBS, its underlying principles and mechanisms of action are not clearly understood. Several factors can influence the clinical response to
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DBS including the disease state of the patient, anatomical target selected for stimulation, location of the electrode within the target, electrode geometry, and stimulation parameters (current amplitude, duration, waveform, and frequency). DBS has been applied to a number of targets with varying results. Targets studied include the thalamus, the subthalamic nucleus (STN), cerebellum, caudate nucleus, and hippocampus. For
DBS to become a successful therapeutic strategy in the treatment of seizure disorders, the effect of stimulation parameters and target location on reducing or blocking unwanted neuronal activity needs to be evaluated. Identification of ideal parameters could result in a new and potentially superior therapy option for many epilepsy syndromes with limited and reversible side effects. In the case of epilepsy, there are often many seizure foci which can lie in several regions of the brain. One potential target for LFS that could potentially affect several regions at once would axon-rich fiber tracts that connect regions afflicted with seizure foci. For the treatment of seizures in the hippocampus, such as those in Q54 mice, an ideal downstream target is the ventral hippocampal commissural
(VHC) fibers. Stimulation of the VHC activates neuronal populations in the entorhinal cortex, dentate gyrus, CA1, CA2, and CA3 regions of the hippocampus. Objective two of this thesis was to examine the effects of low frequency (1Hz and 3Hz) DBS applied to the VHC on hippocampal seizure activity in the Q54 model of epilepsy.
In addition, long term DBS therapy requires a steady and reliable delivery of stimulation with minimal impact on surrounding tissue. The only available DBS electrodes currently approved by the FDA are the Medtronic 3387 and 3389 (Medtronic
Inc., Minneapolis, MN). Both of these models are identical in principle, with one notable difference in the distance between stimulating contacts (0.5 or 1.5mm). Several
8
problems have been reported with this electrode model including lead breakage, and a significant foreign body reaction (FBR) (Oh et al., 2002). In addition, encapsulation, often 500 µm thick, by a FBR limits the volume of tissue activated. As modeled by
Butson and collegues, a cathodic square wave stimulus pulse with a 120µs pulse width and an amplitude of 4V would normally activate an area greater than 150mm3, but when
the electrode is encapsulated by a typical FBR, the same activation area shrinks to less
than 50mm3 (Butson et al., 2006) Furthermore, if we wish to stimulate small fiber tracts
without damaging a significant number of axons forming vital connections within the
CNS, a smaller stimulation electrode is needed. Thus there is a need for the creation of a
DBS electrode that minimizes neuronal damage and implant-induced encapsulation,
while allowing for substantial activation of the target tissue volume. Objective three of
this thesis was to design and evaluate a novel DBS electrode to stimulate small axon-
rich regions of the brain for the treatment of epileptic seizures.
1.6 THESIS OBJECTIVES AND ORGANIZATION
The objectives of this research were: (i.) to characterize in vitro epileptiform
activity in Q54 mice, (ii.) to characterize and evaluate the efficacy of low frequency
deep brain stimulation as a seizure therapy in Q54 mice, and (iii.) to design and
evaluate a novel deep brain stimulation electrode for axon-rich areas of the central
nervous system.
------
1.6.1 Objective I: To characterize in vitro epileptiform activity in Q54 mice.
------
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The hippocampal formation has been well studied, and the excitation and
inhibition pathways of this system are well established. Because the hippocampus is
often involved in seizure activity, in vitro hippocampal slice studies have long been
utilized for epilepsy research. The presence of abnormal currents recorded by Kearney et
al in CA1 pyramidal cells of the hippocampus indicated that it may be an origin of the
phenotypic seizure activity that develops in Q54 transgenic mice. From this data, we
anticipated that Q54 transgenic hippocampal slices would demonstrate abnormal activity
in vitro.
In order to test the hypothesis that Q54 mice with Scn2a mutation exhibit
increased excitability in vitro, brain slice experiments were conducted on two groups of
mice: Q54 progeny with (tg/+) and without (+/+) the Scn2a mutation. Orthodromic and
antidromic CA1 field potentials were recorded, and slices were stimulated at low
frequencies (≤0.2 Hz) to monitor slice health and viability. Non-evoked activity was
recorded from CA1 and CA3 fields for extended periods in normal artificial cerebral
spinal fluid (nACSF). Activity was evaluated and characterized by burst amplitude,
bursting frequency, and signal power analysis.
Burst amplitude in response to varying current will be analyzed to determine
input-output curves for both groups. A shift in the input-output curves could be a sign of variable excitability. Furthermore, paired-pulse stimulation was utilized to investigate variations in facilitation or inhibition between Q54 groups. The hypothesis that
increased excitability in Q54(Tg/+) mice was correlated to a reduction in inhibition
was tested. To test the hypothesis that abnormal activity in (Tg/+) mice is not a result
10
of cellular damage, histological tests were conducted. Nissl stain was applied to assess
gliosis and the presence of pyramidal cell bodies.
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1.6.2 Objective II: To characterize and evaluate the efficacy of low frequency deep
brain stimulation as a seizure therapy in Q54 mice.
------
Applied neural stimulation is a promising new therapy for intractable epilepsies.
The vagus nerve stimulation (VNS) therapy system (Cyberonics, Inc., Houston, Texas),
was approved by the FDA in 1997 for its ability to significantly reduce seizure frequency.
Deep brain stimulation has been applied to seizure foci in a variety of areas of the brain
including: cerebellum, caudate nucleus, centromedian thalamus, anterior thalamus, sub
thalamus, hippocampus, and neocortex.
Because the mechanisms of deep brain stimulation are not well understood, a
variety of stimulation paradigms have been explored with minimal success. Previous
studies have primarily focused on high frequency stimulation applied directly to seizure
foci, with few examining the effects of low frequency stimulation applied upstream from
seizure foci. By application of stimulation to axonal-rich white matter tracks we can
maximize therapeutic effect by targeting multiple downstream epileptic foci.
Our hypothesis is that low frequency stimulation of 1Hz and/or 3Hz applied to
the ventral hippocampal commissural (VHC) fibers will reduce seizure frequency in
Q54 mice. To test this hypothesis, we implanted stimulation electrodes into the VHC of
seizure prone Q54 transgenic mice and evaluated seizure frequency before, during, and
after applied low frequency stimulus.
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1.6.3 Objective III: To design and evaluate a novel deep brain stimulation electrode for axon-rich areas of the central nervous system.
------
In order to activate a large fiber tract such as the VHC in the CNS, a new DBS electrode design is needed. The goals of objective three in this work were to construct and evaluate a suitable electrode design in a finite element model (FEM), and to build and test an electrode prototype based on the FEM results. Our hypothesis was that a multipronged thin wired electrode could sufficiently activate the target stimulation area, VHC, while minimizing damage to the surrounding axonal populations.
Maxwell 3-D (Ansoft, LLC., Pittsburg, PA) was used to build the FEM, which was utilized to examine the effects of contact size, number, and position on the area of activation. Several prototypes were constructed, their impedance measured, and tested for their ability to evoke a neuronal population response in vivo.
Each chapter of this dissertation is written in a format suitable for submission for publication. A review of relevant topics is provided in chapter one as background material intended to develop the appropriate context for the work presented in the following chapters. Chapters two, three, and four present the methods used and findings of aims one, two, and three respectively. Summary and conclusions, as well as an indication towards the direction of future work are presented in chapter five.
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Table 1.1—Channelopathies: Voltage-gated Sodium Channel Genes Associated with Human Idiopathic Epilepsy Syndromes
Gene Protein Clinical References Syndrome SCN1A Na+ Ch α-subunit GEFS+ (Escayg et al., 2000; Escayg et al., 2001; Lerche et al., 2001; Sugawara et al., 2001a; Wallace et al., 2001; Kearney et al., 2006b) SMEI (Abou-Khalil et al., 2001; Claes et al., 2001; Ohmori et al., 2002; Sugawara et al., 2002; Claes et al., 2003; Fujiwara et al., 2003; Ceulemans et al., 2004b; Suls et al., 2006) SCN2A Na+ Ch α-subunit GEFS+ (Sugawara et al., 2001b) BFNI (Heron et al., 2002; Berkovic et al., 2004) SMEI (Kamiya et al., 2004) SCN1B Na+ Ch β-subunit GEFS+ (Wallace et al., 1998; Wallace et al., 2002)
Table 1.1—Channelopathies: Voltage-gated Sodium Channel Genes Associated with
Human Idiopathic Epilepsy Syndromes: Several sodium channel gene mutations affecting both the alpha and beta channel subunits have been identified in families with a history of inherited epilepsy; GEFS+: Generalized epilepsy with febrile seizures plus;
BFNI: benign familial neonatal-infantile seizures, SMEI: severe myoclonic epilepsy of infancy (Adapted/Expanded from (Meisler et al., 2001))
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Table 1.2—Voltage-gated Na+ Channel Types and Expression
Protein Name Gene Name Auxiliary Expression Subunits Profile * Nav1.1 SCN1A β1, β2, β3, β4 CNS, PNS, CM Nav1.2 SCN2A β1, β2, β3, β4 CNS, PNS * Nav1.3 SCN3A β1, β3 CNS, PNS, CM Nav1.4 SCN4A β1 SM * * Nav1.5 SCN5A β1, β2, β3, β4 CM, SM , CNS * Nav1.6 SCN8A β1, β2 CNS, PNS, CM Nav1.7 SCN9A β1, β2 PNS Nav1.8 SCN10A Unknown PNS Nav1.9 SCN11A Unknown PNS
Table 1.2—Voltage-gated Na+ Channel Types and Expression: A number of different sodium channel genes encoding the alpha subunit have been identified; CNS: central nervous system, PNS: peripheral nervous system, CM: cardiac muscle, SM: skeletal muscle, * = minor expression (adapted from (Catterall et al., 2005))
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Figure 1.1—Scn2a sodium channel mutation in Q54 mice: Three glutamines replace a
glycine-alanine-leucine sequence on S4-S5 linker (Kearney et al.).
15
Chapter 2: Scn2a Sodium Channel Mutation Results in Hyperexcitability in the Hippocampus in vitro
The following chapter was published in the March 2008 issue of Epilepsia 49(3): 488-
499.
2.1 ABSTRACT
Purpose: To investigate in vitro, the cellular network activity of the hippocampus
in Q54 mice that display spontaneous seizures because of a gain-of-function mutation of the Scn2a sodium channel gene. Methods: Extacellular recordings were obtained from
CA1 and CA3 pyramidal neurons in hippocampal slices prepared from Q54 transgenic
and nontransgenic littermates (WT) under physiologic conditions as well as during
periods of orthodromic stimulation of the Schaffer collaterals. Cerebral spinal fluid
samples were analyzed and cresyl violet histology of the hippocampus was conducted.
Results: Increased spontaneous extracellular activity was found in both CA1 and CA3
regions of Q54 hippocampal slices. Q54 slices also demonstrated significantly greater
spontaneous and afterdischarge activity as well as population spike amplitude and
duration following tetanic stimulus in comparison toWT slices. Frequency analysis of tetanically stimulated recordings indicated high-frequency components (100 and 200 Hz) unique to Q45 slices. Analysis of cresyl violet histology supports healthy Q54 slices up to
10 weeks, while Q54 cerebral spinal fluid shows elevated osmolarity. Conclusion:
Evidence for hyperexcitability and increased synaptic efficacy in Q54 mice was found by
observing spontaneous activity as well as evoked activity. Response to tetanic stimulation
included unique high-frequency oscillations, and resulted in an increased population
16
spike amplitude and duration. Histological assessment shows equivalent neuronal
development in both experimental groups. The data support the hypothesis that modified
Scn2a channels in Q54 mice result in network hyperexcitability of the hippocampus
necessary for the development and maintenance of temporal lobe seizures.
2.2 INTRODUCTION
Epilepsy is the most prevalent chronic neurological disorder, affecting over 3
million Americans with approximately 200,000 new cases reported each year
(epilepsyfoundation.org). Although there are multiple epilepsy syndromes, all are characterized and identified by the presence of seizures. Seizures are the result of a chemical imbalance affecting neuronal populations that leads to uncontrolled neuronal firing characterized by large electrical field oscillations in one or more areas of the brain.
Many ion channels are involved in neuronal activity, but sodium channels play a key role in epilepsy. Two well known antiepileptic drugs (AEDs), carbamazepine and phenytoin, act by enhancing the inactivation property of the sodium channel. Enhancing inactivation increases the refractory period of the cell, thus slowing or preventing the occurrence of rapid repetitive firing. In addition, increased brain sodium channel transcript levels are known to occur in the epileptic human brain (Lombardo et al., 1996), further supporting the conclusion that sodium channels are likely to be the primary mechanism for most, if not all forms of epilepsy (Tian et al., 1995).
Several sodium channel mutations have been identified in the development of epileptic seizures. Voltage-gated sodium channels consist of a single pore-forming α- subunit as well as one or more auxiliary β-subunits. There are at least four sodium
17
channel β-subunits (Scn1b-4b) and nine α-subunits (Scn1a-11a), four of which are primarily responsible for encoding sodium currents in the brain: Scn1a, Scn2a, Scn3a, and Scn8a (Catterall et al., 2005). Slight variations in protein-coding sequences can significantly modify these structures and their gating kinetics. Mutations in three genes encoding isoforms of the voltagegated sodium channel subunits (Scn1a, Scn2a, Scn1b) have been identified in human idiopathic epilepsies including generalized epilepsy with febrile seizures plus (GEFS+)(Wallace et al., 1998; Escayg et al., 2000; Escayg et al.,
2001; Lerche et al., 2001; Sugawara et al., 2001a; Sugawara et al., 2001b; Wallace et al.,
2001; Wallace et al., 2002; Kearney et al., 2006b), severe myoclonic epilepsy of infancy
(SMEI) (Claes et al., 2001; Ohmori et al., 2002; Sugawara et al., 2002; Claes et al., 2003;
Fujiwara et al., 2003; Ceulemans et al., 2004a; Kamiya et al., 2004; Ohmori et al., 2006;
Suls et al., 2006), and benign familial neonatal-infantile seizures (BFNI) (Heron et al.,
2002; Berkovic et al., 2004). The substantial incidence of mutations in genes encoding sodium channel subunits that have been associated with the development of epilepsy confirm that alteration in sodium channel genetics is a primary cause of inherited epilepsy syndromes.
One Scn2a mutation, GAL879-881QQQ, alters the structure of the S4-S5 linker of alpha-subunit domain two and results in delayed channel inactivation and increased persistent current when expressed in Xenopus oocytes (Smith and Goldin, 1997; Kearney et al., 2001). Introduction of this missense mutation into mice resulted in the development of the Q54 model of temporal lobe epilepsy (Smith and Goldin, 1997; Kearney et al.,
2001). Seizure behaviors were observed in Q54 transgenic mice beginning with focal seizures that seem to originate in the hippocampus between 2 and 3 months of age.
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Frequency and duration of seizure episodes increased with age, with generalized seizures
observed as early as 3 months of age. Whole-cell patch clamp recordings of CA1
pyramidal cells detected a significant increase in persistent current for sodium channels in
Q54 transgenic mice at the age of 1 month. Finally, premature death commonly occurred at between 5 and 6 months of age (Smith and Goldin, 1997; Kearney et al., 2001).
Additional work with the Q54 model has revealed that genetic background can significantly influence the severity of phenotypic expression (Bergren et al., 2005;
Kearney et al., 2006a). Nevertheless, the mechanisms behind the development from genotype to phenotype in this unique model of temporal lobe epilepsy remain unclear and further investigation is required.
Brain slice recording is a well-established method for in vitro study of intracellular and extracellular CNS activity. In particular, murine hippocampal slices are economical and well-understood models that have yielded a wealth of information in epilepsy studies (Fisher, 1989; Durand, 1993). Unfortunately, seizures are primarily induced in this preparation via pharmacological or stimulatory application and the resultant seizure activity is often termed epileptiform, rather than epileptic, in order to distinguish it from its naturally occurring counterpart. Alternatively, human epileptic tissue slices are difficult to obtain, often damaged by surgical removal techniques, and limited by inadequate control tissue (Avoli et al., 2005). New developments in murine genetics have led to a wealth of disease models based on human mutations and matching their phenotypes, notably the Q54 model of temporal lobe epilepsy. Although patch- clamp and EEG studies have led to valuable insights into the possible brain locations and channel involvement during phenotypic seizures, our understanding of the network
19
activity involved in seizure generation and propagation is incomplete. In this study, we investigated extracellular properties of a genetically epileptic, Q54 hippocampal slice model in order to uncover the mechanisms behind phenotypic development in genetic models of epilepsy.
2.3 METHODS
2.3.1 Animals
Experiments were performed on the Q54 strain of transgenic mice expressing the
GAL879-881QQQ mutation of Scn2a (Kearney et al., 2001). Q54 transgenic mice were
originally generated by microinjection of (C57Bl/6J × SJL/J)F2 oocytes, and a congenic
line C57Bl/6J × Q54 (B6Q54) was established though ten successive generations of backcrossing to recipient strain, C57Bl/6J (B6), as previously described (Kearney et al.,
2001; Bergren et al., 2005). Founder B6Q54 mice were obtained from the laboratory of
M.H. Meisler (Department of Human Genetics, University of Michigan) and a colony was established at Case Western Reserve University. B6Q54 founder males were bred to
C57BL/6J (B6) (Stock 000664) and SJL/J (SJL) (Stock 000686) female mice obtained from Jackson Laboratory (Bar Harbor, ME, U.S.A.). These standard inbred mouse strains were selected because they are both well-established, readily available, and similarly
invulnerable to kainic acid-induced neurotoxicity (Schauwecker, 2002). B6Q54 founder males were backcrossed to B6 female mice to maintain the inbred B6Q54 line, and outcrossed to female SJL/J mice to create experimental mice, (B6Q54 × SJL)F1
(SJLQ54). Approximately 50% of all B6Q54 offspring were heterozygous for the Scn2a missense mutation (tg/+), with the remainder homozygous wild type (WT) (+/+). For our
20
experiments, transgenic SJLQ54 (tg/+) mice were used for experimental data and age-
matched sibling SJLQ54 (+/+) mice as WT controls. Both male and female mice were
used in experiments, but their age was limited to a window of 3–10 weeks, prior to the
onset of generalized seizures. All animals were housed in microisolator cages maintained
in a veterinarianmonitored animal care facility.
Offspring were weaned and tagged at 3 weeks of age, and a small tail biopsy was
taken. Genomic DNA was isolated from tail biopsies via proteinase K digestion,
phenol/cholorform extraction and ethanol precipitation. Mice were genotyped by
polymerase chain reaction (PCR) and electrophoresis of extracted tail DNA. PCR mix for each tail sample composed of (in ul): 2.5 10 × PCR buffer (without MgCl2), 1.7 MgCl2,
5 1 mM dNTPs, 1.5 Primer A1 (5_ GAT GCT CTT CTC CAC AAT GCT AAC C 3_),
1.5 Primer A2 (5_ GGG GAA ATC TTA ACA CCA GTC ACA C3_), 1.0 Primer N1 (5_
ATC CTT CCT TGG CTG CTT CAG ACT TG 3_), 1.0 Primer N2 (5_ CTC TTC TGC
AAT GCG CTG TTC GAT AG 3_), 8.6 DII H2O, 0.2 Taq (5U/μl), and 2 tail DNA for a total volume of 25 μl. Two primer sets were used; N1-2 primers (product length = 960 bp) provided mutation detection while A1-2 primers (product length = 146 bp) served as
PCR control. DNA amplification was conducted by PCR on a Mastercycler (Eppendorf
AG, Hamburg, Germany). Samples were denatured for 2 min at 94◦C, followed by 33 cycles of 30 s at 94◦C, 30 s at 65◦C, 75 s at 72◦C. Once PCR cycles were completed, 5 μl bromophenol blue marker was added to each sample and the mixture was electrophoresed on a 1% agarose gel (120V), visualized by ethidium bromide fluorescence, and measured against a 1 Kb DNA ladder.
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All animal protocols were reviewed and approved by the Institutional Animal
Care and Use Committee of Case Western Reserve University.
2.3.2 Histology and cerebral spinal fluid extraction
The brain was removed from Q54 and WT mice at 4, 6, 8, and 10 weeks using the method described above. Following hemisphere sectioning, each half of the brain was immediately fixed in 10% formalin and later embedded in paraffin. Six sagittal hippocampal slices (20 μm thick) were cut from each animal. Cresyl violet stain was applied to mark Nissel bodies. Final sections were viewed with a light microscope and captured with digital imaging software. Quantitative histological measurements of the
CA1 and CA3 pyramidal cell layers were completed with Java image processing software, ImageJ (NIH, Bethesda, MD, U.S.A.). Both cell layer measurements were taken a minimum of three times per slice, combined and averaged measurements were rounded to the nearest 10 μm. Murine cerebral spinal fluid (CSF) samples were isolated through a microdissection technique with limited blood contamination (<5%) as described in DeMattos et al. (DeMattos et al., 2002). 50 μl CSF samples obtained from
Q54 and WT siblings were analyzed for [Na+], [K+], [Cl−], and osmolarity using a
Dimension RXL chemical analyzer (Dade Behring, Deerfield, IL, U.S.A.). In addition,
100 μl “normal” artificial cerebral spinal fluid (nACSF) samples were tested for comparison with electrolyte composition of experimental perfusion solution.
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2.3.3 Hippocampal slice preparation and perfusion
Three to ten week old Q54 and age-matched WT mice were decapitated under ethyl ether anesthesia. The brain was then rapidly removed and sectioned twice, removing the cerebellum and separating the two hemispheres by cutting midsagittally.
Each hemisphere was glued (sagital face down) to a specimen disc with cyanoacrylate and placed into the cutting chamber of a vibratome (VT1000S, Leica, Nusslock,
Germany) filled with ice-cold (3–4◦C), sucroserich artificial cerebrospinal fluid (sACSF), containing (in mM): 220 sucrose, 3 KCl, 1.25 NaH2PO4, 2 MgSO4, 26 NaHCO3, 2
CaCl2, and 10 dextrose, saturated with 95% O2/5%CO2 gases (pH, 7.4). Sagittal hippocampal slices (350–400 μm thick) were cut and transferred to an incubation chamber filled with nACSF containing (in mM): 124 NaCl, 3.75 KCl, 1.25 KH2PO4, 2
MgSO4, 26 NaHCO3, 2 CaCl2, 10 dextrose, saturated with 95% O2/5% CO2 gases (pH,
7.4) at room temperature (25◦C) for at least 1h. Postincubation period, brain slices were transferred to an interface-recording chamber (Harvard Apparatus, Holliston, MA).
Stimulation and recording of slices were conducted at 34 ± 2◦C in nACSF, unless otherwise noted. Slices were discarded 6–8 h postincubation.
2.3.4 Electrophysiology and data analysis
Field potentials were recorded with a low-impedance glass micropipette (2–6
MΩ) filled with 150 mM NaCl. CA1 pyramidal cell population spikes (PSs) were evoked using a cathodic stimulus pulse (100 μsec, 10–350 μA, 0.05–0.1 Hz) delivered to the
Schaffer Collaterals (orthodromic) by a tungsten electrode. All slices evoked a PS ≥1.0 mV to ensure consistent slice viability between experiments.
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Paired-pulse and tetanic stimulation were applied to Q54 and WT brain slices to
evaluate local circuitry. Paired stimuli (100 75 – 250 μA, 10 – 100 ms delay) were
applied to Schaeffer collaterals at a frequency of 0.05 Hz. Delay between stimuli was
varied from 100 to 10 ms at 10 ms intervals, while amplitude of stimulation was constant
and determined during initial health check from the stimulus required to activate 75% of
the maximum evoked PS in CA1 pyramidal neurons. Furthermore, a tetanization protocol
was adapted from previous studies where sustained epileptiform discharges, or primary
after discharges (ADs), were evoked in CA1 pyramidal neurons (Rafiq et al., 1995;
Jahromi et al., 2002). Ten, two second stimulus trains (100 Hz, 100 μs, 75 – 250 μA) were applied to the Schaeffer collaterals of each slice at 10 min intervals. Stimulus
amplitude was determined during initial health check as above.
Epileptiform activity was determined and quantified by evaluation of burst frequency (Hz), interburst frequency (Hz), and burst duration (ms). Burst frequency was measured by counting the number of interictal-like events per second during set time duration. Interburst frequency was measured by counting the number of recorded depolarization spikes per event per second over a set time duration (minimum peak-to- peak threshold was 0.25– 0.5 mV). Burst duration was determined by measuring the average time between burst onset and burst termination in ten consecutive bursts. All signals were amplified with an Axoprobe-1A microelectrode amplifier (Axon
Instruments, Inc., Union City, CA, U.S.A.), further amplified and filtered by an FLA-01 eight pole Bessel filter/amplifier (Cygnus Technology, Delaware Water Gap, PA,
U.S.A.), and recorded on a digital tape recorder DT-200 (Microdata Instruments, S.
24
Plainfield, NJ, U.S.A.). Off-line data analyses were performed using Matlab Software
(The Math-Works, Inc., Natick, MA, U.S.A.).
Measurements throughout this text are expressed as mean ± standard deviation
(SD) or mean ± standard error of the mean (SEM), with n indicating the number of
animals, or slices, or samples of CSF per test group in each study. Results obtained were
evaluated using statistical analysis methods including analysis of variance (ANOVA) and
Student’s t-test, with a significance level, p < 0.05.
2.4 RESULTS
2.4.1 Spontaneous activity in Q54 slices
Initially, extracellular activity was recorded in Q54 (tg/+) and WT (+/+) slices to examine cellular activity under “normal” physiologic conditions. For several hours, spontaneous extracellular signals were recorded from the CA1 or CA3 pyramidal cell layer of hippocampal slices perfused with nACSF (saturated with 95% O2/5% CO2 gases, pH 7.4) at 34◦C. As expected, spontaneous activity was not seen in either CA1 or
CA3 pyramidal cell layer recordings from WT slices (n = 8). An example of a CA1 recording taken from WT slices is shown in Fig. 2-1A, (top). Approximately one-third of the field potential recordings obtained from the CA1 pyramidal cell layer of slices from
Q54 mice (n = 12) showed abnormal spontaneous activity (Fig. 2-1B, middle). This spontaneous activity is similar to that of inter-ictal activity, with isolated or small groups of primarily unipolar field potential spiking and a mean burst frequency range of 0–15
Hz. In separate recordings, just over one-third of the field potential recordings from the
CA3 pyramidal cell layer of slices from Q54 mice (n = 8) also showed similar abnormal
25
spontaneous activity to that found in CA1 (data not shown).Moreover, a power analysis
of field activity from all recordings revealed a significant increase in activity in both CA1
(+380%, p < 0.01) and CA3 (+120%, p < 0.01) from Q54 slices when compared to
activity in WT slices (CA1, +9%, CA3, +6%). Power analysis was determined from an average of 15 power calculations, conducted over twenty second windows of recorded
data taken between 55 and 65 min into each recording. Although no seizure-like-event
(SLE) was observed in any slice, the increase of the network excitability was investigated
by first testing the response to orthodromic stimulation.
2.4.2 Evoked PS amplitude response curve in Q54 slices
CA1 pyramidal cell PSs were evoked by a range of orthodromic stimuli (20–300
μA, 100 μs, 0.2 Hz) applied to Schaeffer collaterals in both Q54 (n = 5) and WT (n = 7)
hippocampal slices. A linear regression fit to the linear portion of each input-output curve
(60–160 μA) results in a slope of 0.03 mV/μA for both Q54 and WT response curves.
Although both groups maintain nearly identical response curves during initial stimulus
magnitudes, Q54 evoked PS amplitudes significantly deviate at stimuli ≥ 200 μA,
reaching a maximum of 4.03 ± 0.02 at 280 μA (Fig. 2-2). Conversely, WT amplitudes continue to increase in amplitude with increasing stimulus magnitude, and do not reach maximum of 6.08 ± 0.61 until 320 μA. Notably, Q54 mean PS amplitudes were found to be significantly different (p < 0.05) from WT amplitudes at stimulus magnitudes ≥ 200
μA (see Fig. 2-2).
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2.4.3 Cresyl violet histology of Q54 slices
The reduced PS amplitude in Q54 mice suggested the possibility of cellular
damage, therefore a histological analysis of cresyl violet stained hippocampal slices from
both Q54 and WT mice was carried out. Sagittal sections (20 μm, n = 6) were cut at four
consecutive two week intervals for both Q54 (n = 3) and WT (n = 3) mice at each age
group ranging from four to ten weeks of age. Visual inspection of cresyl violet stained
sections did not indicate any significant differences between Q54 and WT at any age
level. An example of ten week old Q54 and WT sections are shown in Fig. 2-3. Normal neuronal development was further supported by quantitative analysis of pyramidal cell layer regions CA1 and CA3 (Table 2-1). In both Q54 (n = 18) and WT (n = 18) slices the average width of the CA1 pyramidal cell layer ranged from 90 to 110 μm, while the average width of the CA3 pyramidal cell layer ranged from 70 to 110 μm in WT slices
and 90 – 130 μm in Q54 slices. Regardless of this variation in average ranges, no
significant difference was found between WT and Q54 measurements in either CA1 or
CA3 pyramidal cell layers during any age period.
2.4.4 Cerebral spinal fluid of Q54 mice
Changes in the ionic concentrations of the extracellular space can have a significant impact on neuronal membrane potentials and excitability. Electrolytes ([Na+],
[K+], [Cl−]) and osmolarity of isolated CSF samples (< 5% contamination) were
analyzed to evaluate the similarities between Q54 CSF, WT CSF, and conventional in
vitro ACSF (nACSF). CSF was extracted from Q54 (n = 6) and WT (n = 6) mice using a
microdisection technique, then ran on a chemical analyzer against normal artificial
27
cerebral spinal fluid (nACSF) (n = 11). While extracellular chloride concentration was found to be comparable among all groups, extracellular sodium concentrations were found to be significantly higher and extracellular potassium was found to be significantly lower in both Q54 and WT when compared to nACSF (p < 0.05, Table 2-2). Osmolarity was also found to be significantly higher in Q54 only, when compared to both WT and nACSF samples (p < 0.05, Table 2-2).
2.4.5 Paired pulse test of recurrent inhibition
To evaluate the contribution of local inhibitory networks on CA1 pyramidal cell abnormal activity, a paired pulse stimulus paradigm was applied to the Schaeffer collaterals of Q54 (n = 5) and WT (n = 5) brain slices. Interpulse interval between two consecutive stimuli was varied by 10 ms steps from 10 ms to 100 ms, and the resultant PS amplitudes were recorded from CA1 (Fig. 2-4). A ratio of the amplitude of the second evoked response to the amplitude of the first evoked response gives an indication of local facilitation (>1) or inhibition (<1). Q54 slices reach their peak facilitation at 20 ms, while WT peak at 30 ms. It is also interesting to note that neither Q54 nor WT demonstrated a significant level of inhibition, which is normally expected when interpulse interval is close to 10 ms.
2.4.6 Response to high-frequency tetanic stimulus
In order to assess the threshold for inducing primary ADs using electrical stimulation, a sequence of ten, two second subthreshold tetanic stimuli (100 Hz, 100 μs,
75–250 μA) were applied to the Schaeffer collaterals of Q54 (n = 5) and WT (n = 5)
28
hippocampal slices. Although the stimulus amplitude was markedly decreased from
previously established protocols (Rafiq et al., 1995; Jahromi et al., 2002), primary ADs
were detected in the CA1 pyramidal neuronal layer in both Q54 and WT (Fig. 2-5A and
B). Spontaneous activity (SA) following stimulation was also detected in several slices, primarily in Q54 slices (Fig. 2-5C and D). Analysis of evoked activity immediately following stimulus train application showed fewer occurrences of an AD event in WT (n
= 6/50 trains) when compared to Q54 (n = 24/50 trains) (Table 2-2). SA also occurred
more regularly following tetanic stimulus in Q54 slices (n = 19/50 trains) than in WT
slices (n = 5/50 trains) (Table 2-2). The duration of ADs generated by each pulse are plotted in Fig. 2-6. The duration of ADs are significantly higher in the Q54 when compared to the WT slices. The greatest average duration of AD response in Q54 mice was 6.8 ms and occurred following the fifth stimulus train (T5) compared to a 0.6 ms
maximum average value for WT following the second stimulus train (T2) (Fig. 2-6). The
increased presence of ADs as well as SA indicates an increased excitability in Q54 slices.
Analysis of interspike intervals showed key frequency components in both AD
and SA recordings (Fig. 2-7). Primary frequencies recorded in Q54 AD were between 0–
10 Hz, with additional secondary components in the 98–102 Hz range. Comparatively,
WT AD data contained a significant amount of low frequency 0–10 Hz spiking, but
lacked any significant high-frequency activity. The analysis of the frequency content of
the SA induced by the stimulation revealed the presence of a high-frequency component
(210–220 Hz) only in the Q54 mice. Furthermore, CA1 PS responses were recorded prior
to the first stimulus train (T0) and prior to each additional train (T1–T10). A plot of CA1
PS amplitudes over all stimulus trains reveals a significant difference between linear
29
regressions of the magnitudes of WT and Q54 over stimulus trains, with Q54 slices also
having significantly higher amplitudes at individual trains, T0–T6 (Fig 2-8A, top).
Additionally, the linear regression of CA1 PS duration also shows a significantly higher magnitude in the Q54 when compared to WT, with significantly different train activity at
T0, T1, T2, and T8 (Fig 2-8B, bottom). The linear regression of evoked PS amplitude is significantly different between Q54 and WT with a p-value < 0.05, but the slope of each linear regression is strikingly similar: Q54 amplitude (m = 0.5 mV/train) and duration (m
= 0.07 ms/train); WT amplitude (m = 0.3 mV/train) and duration (m = 0.06 ms/train).
The presence of higher frequency components in bursting activity of Q54 slices in addition to increased amplitude of evoked PSs further demonstrate an increased response of Q54 slices to tetanic stimulation.
2.5 DISCUSSION
The most direct way to study basic physiological mechanisms underlying epilepsy
is to explore the properties of human epileptic neuronal tissue in vivo. Recent
developments in epilepsy surgery have led to an increase interest in the study of epileptic
brain slices in vitro, unfortunately, human epileptic tissue is limited, difficult to maintain,
and often damaged during removal. In addition, experimental control tissue for these
studies is often inadequate (Kohling and Avoli, 2006). Recent developments in genetic
mutations have led to numerous mouse models of human disease that match mutations
found in human orthologs and result in similar disease phenotypes. In the case of
heterozygous mutation models, age-matched littermate WT controls are ideal and readily
available in their nontransgenic siblings. In addition, murine tissue is in greater supply
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and easier to harvest. For these reasons, genetically modified murine tissue is an ideal
alternative to human tissue when studying the underlying mechanisms of disease, its
development, and potential treatment strategies. The Q54 transgene, contains a missense
mutation resulting in a three amino acid substitution, GAL879–881QQQ, of sodium
channel gene, Scn2a. While this specific missense mutation has not been identified in
humans, numerous mutations of both Scn1a and Scn2a have been discovered in families with inheritable epilepsy syndromes, including GEFS+, SMEI, and BFNIS (Meisler and
Kearney, 2005), highlighting the importance of sodium channel function in the development of these seizure phenotypes. Moreover, several of these missense mutations, primarily Scn1a, are gain-of-function mutations resulting in increased persistent sodium current (Stafstrom, 2007), as was found in the Q54 hippocampal neurons (Kearney et al.,
2001). Because the Q54 mouse model of epilepsy stems from a persistent sodium channel gain-of-function mutation that results in seizures within the temporal lobe, it is a useful model for the study of epilepsy mechanisms, primarily those involved in idiopathic or genetically inherited epilepsies of the temporal lobe and the transition from genotype to
phenotype.
Our Q54 studies were conducted on mice outcrossed to SJL/J which has shown an
increased expression of the Scn2a transgene and severity of the epilepsy phenotype,
which could be a result of the heterozygosity of two modifier loci which are known to
differ between B6 and SJL strains (Bergren et al., 2005). Q54 mice on (B6 × SJL)F2 or
F3 background can be homozygous for these modifier loci, but are known to exhibit
spontaneous focal seizures within 2–3 months, and EEG recordings from these animals
demonstrated seizure activity primarily in the hippocampus (Kearney et al., 2001).We
31
suspected that hippocampal tissue from Q54 mice would demonstrate spontaneous seizure activity in vitro. To test this hypothesis, unstimulated extracellular recordings
were conducted in Q54 and WT hippocampal brain slices perfused with nACSF, from
mice with a (B6 ×SJL)F1 background. While spontaneous epileptiform activity was not
detected, interictal-like SA was observed in both the CA1 and CA3 regions of the
hippocampal pyramidal cell layer of Q54 brain slices. This SA was not found in any of
the WT control slices. Similarly, human epileptic brain slice studies have shown little
evidence to support any alterations in the intrinsic properties of cortical or hippocampal
neurons, yet experimental data does support a decrease in functional inhibition and/or an
increase in synaptic excitation (Schwartzkroin, 1994).
Initially, local neuronal damage was suspected as a potential cause for the
inability of pyramidal neurons to drive seizure activity in Q45 slices. Hippocampal
sclerosis is a common feature of temporal lobe epilepsy, found in approximately 50–70%
of surgical resections of the hippocampus from temporal lobe epilepsy patients (Honavar
and Meldrum, 1997). In a study of the mechanisms of the pilocarpine rat model of
temporal lobe epilepsy, maximal amplitude of orthodromically evoked response in
epileptic slices was found to be reduced by about half that of control tissue (Sanabria et
al., 2001). It was further suggested that the decreased PS amplitudes in epileptic mice were due to a reduction in neuronal density supported by prior evidence of status epilepticus-induced death of CA1 pyramidal cells (Mello et al., 1993; Liu et al., 1994). A similar reduction in PS amplitude was seen in our Q54 slices in comparison to WT, therefore we examined histological sections from a range of Q54 and WT mice across our
experimental age window, 2–10 weeks, to determine the onset of cellular damage.
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Previous histological assessment of Q54 hippocampal slices from (B6 × SJL)F2 and F3
mice showed no histological abnormalities at 3 weeks, yet by 2 months of age extensive neuronal cell loss and gliosis were visible in animals with frequent seizures (Kearney et al., 2001). In contrast to the previous histological evaluation, our quantitative and visual interpretation of histological sections supports healthy development up to ten weeks in the Q54 hippocampus. One key difference from the previous histological study is that only “mice with frequent seizures” exhibited physiological neuronal damage in the hippocampus, indicating the possibility of a limited occurrence of damage within this subset of Q54 mice. Our statistical analysis suggests that neuronal damage is neither widespread nor significant prior to 10 weeks of age in (B6 × SJL)F1 Q54 mice, and supports that the abnormal PSs and SA recorded in nACSF of Q54 hippocampal slices are not necessarily due to pyramidal cell death or gliosis. Furthermore, data presented here supports previous evidence that gliosis and neuronal cell loss is a consequence of overt seizure activity, rather than the aging of genetically susceptible mice.
Another possible explanation for the lack of seizure activity in Q54 slices could be an electrolyte imbalance caused by the presence of increased persistent sodium current from the Scn2a mutation in Q54 mice. CSF electrolyte screening was conducted to evaluate differences in extracellular space composition. Electrolyte measurements
([Na+], [K+], [Cl−]) of CSF samples indicated no significant difference between Q54 and
WT mice, yet both groups demonstrated a significantly higher sodium concentration and significantly lower potassium concentration when compared to nACSF solution.
Moreover, the CSF samples from Q54 mice had a significantly higher osmolarity than nACSF. Such deviations of chemically imbalanced CSF from conventional ACSF
33
electrolyte composition could affect the excitation state of brain slices during in vitro
experiments. For example, osmotic pressure was determined to be critical determinant of
endogenous firing patterns of CA1 pyramidal cells in rat hippocampal slices (Azouz et
al., 1997). The same study also concluded that perfusion of hippocampal brain slices with
elevated osmolarity suppressed endogenous burst firing, while reducing osmolarity converted nonbursting neurons to bursting neurons. Although, preliminary testing of modified ACSF with elevated sodium concentration (180 mM), did not result in significantly different behavior in the in vitro slice prep of Q54 mice (n = 2), changes in ionic balance due to perfusion with nACSF could facilitate increased excitability and resultant SA seen in Q54 slices. Experiments with decreased [K+]O or increased
osmolarity were not carried out because both are known to decrease the susceptibility to
seizure like events (Durand, 1993).
It has been hypothesized that a loss of inhibition among local circuit interactions
is involved in the development of epileptiform activity within the hippocampus and
several AEDs including diazepam are thought to act by exciting inhibitory interneurons
(Knowles and Schwartzkroin, 1981). A recent study of Scn1a mutant mice found a
significant decrease in action potential generation in dissociated hippocampal
interneurons of Scn1a mutants and proposed the loss of inhibitory interneuron excitability as a possible mechanism for the resultant epilepsy phenotype in these mice (Yu et al.,
2006). Recurrent inhibition describes the method by which local interneurons, excited by the firing of pyramidal cell axon collaterals, return inhibitory GABAergic processes back to pyramidal cell somas forming a negative feedback loop (Andersen, 1975). In this study, we tested the hypothesis that recurrent inhibition was reduced in hippocampal
34
brain slices of Q54 mice with paired-pulse stimulation. Although we did not detect a
significant difference in local inhibition when compared to WT, it is important to note that neither group demonstrated a significant amount of recurrent inhibition. Normally, as the delay between stimuli decreases, local inhibition is seen as a reduction of the second
PS. In the case of both Q54 and WT, recurrent inhibition was rarely detected at all. Even more intriguing is that recurrent inhibition was found in a different strain of mice, namely
C57Bl/6J (data not shown). These data support that the hyperexcitability observed in these slices is not mediated by a lack of inhibition alone. Therefore there is another factor, perhaps genetically strain-based, that could be involved in the development of seizure activity in these animals which is further supported by recent evidence in strain susceptibility to the Scn2a mutation (Bergren et al., 2005; Kearney et al., 2006a).
It is possible that a critical mass is required to develop full-blown seizure activity in the absence of pharmacological or stimulatory intervention. This critical mass theory is further supported by the fact that the removal from the host environment, and the slicing of brain tissue leads to physical damage that may affect distal as well as local networks and their ability to trigger and maintain synchronous seizure waveforms, primarily a lack of recurrent inhibitory network loops. Because of this and the apparent reduction of local inhibition in Q54 slices demonstrated in our paired-pulse study, we decided to evaluate the response of Q54 slices to high-frequency stimulation. Highfrequency tetanic stimulus trains have been shown to drive epileptiform primary and secondary ADs in the entorhinal cortex-hippocampal slice (Rafiq et al., 1993). In addition, self-sustained, or SA in addition to ADs has been shown in response to tetanic stimulus in the hippocampal- parahippocampal slice (Rafiq et al., 1995). In this study, we applied a series of tetanic
35
stimulus trains with minimized amplitude to evaluate the sensitivity of Q54 hippocampal neurons to drive seizure-like activity. In our study, the stimulus amplitude was set to that required to drive 75% of the CA1 pyramidal cell response, and commonly found to be less than five volts (current injection less than 150 μA).
To evaluate the viability of the neural tissue during tetanic recordings, orthodromically evoked CA1 PSs were measured periodically. While PS amplitude and duration increased at a similar rate, both variables were consistently significantly higher in Q54 slices suggesting an elevated level of synaptic excitation. High-frequency stimulus trains triggered both ADs as well as SA in Q54 slices nearly four times as often as in WT slices, further supporting hyperexcitability and increased synaptic function in the hippocampus due to the expression of altered Scn2a sodium channels in Q54 mice.
SA recorded was similar to that recorded in normal ACSF without stimulation, with the exception that it contained a much higher interburst frequency close to 200 Hz.
In the hippocampus, synchronized neuronal population activity is categorized according to their frequency as theta (4–12 Hz), gamma/beta (15–70 Hz) or high- frequency/very fast oscillations (>70 Hz) (Buzsaki, 2002; Traub et al., 2004). While theta oscillations are thought to represent the “on-line” or “ready” state of the hippocampus
(Vertes and Kocsis, 1997), high-frequency oscillations are associated with epileptiform activity in both humans and rats (Bragin et al., 2002; Bragin et al., 2004) and have been found to be nonsynaptic in nature (Draguhn et al., 1998; Hormuzdi et al., 2001). An evaluation of frequency components during spontaneous and AD activity revealed highfrequency oscillations of 100 and 200 Hz, in Q54 slices that were not detected in WT slices, supporting the presence of a nonsynaptic component to Q54 hyperexcitability.
36
Theta band oscillations were found to be present in SA as well as AD responses of both
WT and Q54 hippocampal slices.
In conclusion, electrophysiological in vitro studies were conducted to study
abnormal activity in the hippocampus of Q54 mice expressing modified Scn2a sodium channels. A significant amount of spontaneous firing was found in both CA1 and CA3 regions of Q54 hippocampal slices, but absent in WT slices. Spontaneous interictal like activity was seen more commonly following brief periods of high-frequency tetanic stimulus in both Q54 and WT slices. Q54 had four times the amount of spontaneous as well as AD activity during tetanic stimulus application suggesting increased sensitivity to external input. The hypothesis that neural tissue in Q54 mice was hyperexcitable was further supported by significantly higher PS amplitude and duration in Q54 slices throughout tetanic stimulus testing. Paired pulse analysis did not show evidence of increased inhibition in Q54 mice, yet both Q54 and WT mice demonstrated substantial facilitation. Cresyl violet histology did not reveal any obvious cell loss, and CSF samples suggest the need for correction of perfusion solutions as well as a seemingly compensatory elevation of osmolarity in Q54 mice. Finally, high-frequency oscillations unique to spontaneous and AD activity of Q54 slices following tetanic stimulus were observed. These data support the hypothesis that modified Scn2a channels in Q54 mice result in hyperexcitability of the hippocampus as well as an increased response to orthodromic input most likely involved in the development and/or maintenance of temporal lobe seizures.
37
Age CA3 Width (µm) Genotype CA1 Width (µm) (weeks) WT 110 ± 20 70 ± 20 4 Q54 90 ± 10 100 ± 30 WT 90 ± 10 100 ± 20 6 Q54 100 ± 10 90 ± 20 WT 90 ± 10 110 ± 10 8 Q54 110 ± 30 130 ± 20 WT 100 ± 10 110 ± 30 10 Q54 90 ± 10 110 ± 20
Table 2.1—Quantitative Histology: Quantitative measurement of cresyl violet stained hippocampal slices demonstrate no significant difference in CA1 or CA3 pyramidal cell layer between Q54 (n = 18) and WT (n = 18) littermates at four, six, eight, and ten weeks of age. Data presented rounded to nearest tens ± SD.
38
Activity Genotype T0 T1 T2 T3 T4 T5 T6 T7 T8 T9 T10 WT * * * 20 20 20 20 20 * * AD Q54 40 60 60 80 60 40 60 60 20 * WT * * * * 40 * * * * 20 20 SA Q54 20 * 60 40 60 60 60 60 60 20 20
Table 2.2—Slices with CA1 activity following tetanic stimulus: Both CA1 after discharge (AD) and spontaneous activity (SA) responses were detected less often in WT than in Q54 slices following the application of a high frequency tetanic stimulus trains
(100 Hz, 100 µs, 75 – 250 µA) to Schaffer collaterals (* = 0%). Mice were 8-10 weeks old.
39
Figure 2-1—Spontaneous Activity in Q54 hippocampal slices: Extracellular recordings from CA1 or CA3 pyramidal cell layers in the hippocampus show spontaneous activity in some CA1 (33%, n = 12) and CA3 (37.5%, n = 8) pyramidal cell layer of Q54 slices, but was not found in CA1 (n = 8) or CA3 (n = 6) pyramidal cell layer of WT slices from Q54 and WT mice aged 8-10 weeks. A) extracellular trace from CA1 of WT slice in nACSF;
B) extracellular trace from CA1 of Q54 slice in nACSF showing spontaneous activity
(scale = 0.5mV, 10s); C) expanded segment (indicated by bar) of extracellular Q54 trace shown in Fig.1B. (scale = 0.5mV, 0.2s). D) Power analysis of recorded signals supports a significant increase in spontaneous activity in Q54 mice. Error bars represent SD.
40
CA1 Population Spike vs Stimulation Magnitude
8 A 7 * * * 6 * * * * 5 B *
4
3 PS Amplitude (mV) Amplitude PS
2
1
0 0 50 100 150 200 250 300 350 400 Stimulus Current (uA)
Q54 WT
Figure 2-2—Evoked CA1 population spike (PS) response curve: Q54 hippocampal slice
(n = 5) exhibit significantly smaller CA1 PS amplitudes when evoked by Schaffer collateral stimuli ≥ 200 µA in comparison with WT slices (n = 7) from mice aged 4-10 weeks (* indicates p<0.05); A) characteristic CA1 PS in WT slice at 320 µA; (scale is
1mV, 5ms); B) characteristic CA1 PS in Q54 slice at 320 µA; (scale is the same as in
Fig.2A) ( indicates stimulus artifact; error bars represent SD).
41
Q54 WT
1mm
200 um
Figure 2-3—Morphology of the hippocampus in Q54 hippocampal slices: Nissel bodies stained with cresyl violet exhibit regular neuronal development of the hippocampus in both Q54 (n = 18) and WT (n = 18) slices at ten weeks. Scale bar for A and B is shown in A (1 mm). Scale bar for C and D is shown in C (200 µm).
42
Q54 Paired Pulse Analysis
1.8
1.6
1.4
1.2
1
0.8
0.6
PS Amplitudes, A2/A1 Amplitudes, PS 1.0 mV 0.4 40 ms 0.2
0 10 20 30 40 50 100 Paired Pulse Delay (ms)
Q54 WT
Figure 2-4—Reponse to paired pulse stimuli in Q54 hippocampal slices: Q54 mice (n =
5) do not show a significant difference in comparison to WT mice (n = 5), however both groups maintain facilitation despite a short paired pulse delay suggesting compromised local inhibitory network activity. Characteristic extracellular trace of paired pulse stimulus is shown in inset (scale is 1 mV, 40 ms; indicates stimulus artifact; error bars represent SEM).
43
Figure 2-5—Response to tetanic stimulus in Q54 hippocampal slices: Ten, two second tetanic stimuli (100 Hz, 100 µs, 75 – 250 µA) were applied to the Schaeffer collaterals of
Q54 (n = 5) and WT (n = 5) hippocampal slices from mice aged 8-10 weeks. A) Typical extracellular field potential after discharge following the application of a high-frequency stimulus train recorded in CA1 of Q54 brain slice, B) Expanded segment (bar) from A;
C) Spontaneous activity recorded in CA1 of Q54 slice; D) expanded segment (bar) from
C ( indicates stimulus artifact in A and B).
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CA1 After Discharge Duration
20 * 18 16 * 14 12 10 8 * Duration (sec) Duration 6 * 4 * * * * * 2 0 T1 T2 T3 T4 T5 T6 T7 T8 T9 T10 Stimulus Train
Q54 AD WT AD
Figure 2-6—Duration of evoked after discharge in CA1: Recorded after discharge (AD) durations were markedly increased in Q45 slices when compared to WT (* p<0.01), with maximum average duration following the fifth stimulus train (T5). Mice were 8-10 weeks old. Error bars represent SD.
45
A Histogram of WT Afterdischarge Spike Frequency B Histogram of WT Spontaneous Activity Spike Frequency 18 180
16 160
14 140
12 120
10 100
8 80
6 60
4 40
2 20
0 0 0 50 100 150 200 250 0 50 100 150 200 250 Frequency (Hz) Frequency (Hz)
Histogram of Q54 Afterdischarge Spike Frequency Histogram of Q54 Spontaneous Activity Spike Frequency C 200 D 800
180 700 160 600 140 500 120
100 400
80 300 60 200 40 100 20
0 0 0 50 100 150 200 250 0 50 100 150 200 250 Frequency (Hz) Frequency (Hz)
Figure 2-7—Frequency analysis of tetanically induced activity: Histograms of frequency components found in WT (A, B) and Q54 (C, D) slices during afterdischarge
(AD) or spontaneous activity (SA) following tetanic stimulation. Mice were 8-10 weeks old.
46
A Amplitude of CA1 Population Spike
12
10 *
8 * * * 6 * * 4 *
Total Amplitude (mV) Amplitude Total 2
0 012345678910 Stimulus Train Number
Q54 WT Linear (Q54) Linear (WT)
B Duration of CA1 Population Spike
1.6 * 1.4 1.2 1 * * 0.8 * 0.6 0.4 Total Duration(ms) 0.2 0 012345678910 Stimulus Train Number
Q54 WT Linear (Q54) Linear (WT)
Figure 2-8—CA1 population spike between tetanic stimulus trains: Orthodromic population spike (PS) was recorded prior to the first (0) and following each subsequent tetanic stimulus train (1-10). Linear regressions of PS amplitude (A) and duration (B) are significantly different between Q54 and WT, p<0.01 (* per train, p<0.05). Mice were 8-
10 weeks old. Error bars represent SEM.
47
Chapter 3: Effect of Low Frequency Deep Brain Stimulation
on Seizure Activity In Vivo
The following chapter will be submitted for publication in Epilepsia.
3.1 ABSTRACT
Purpose: To investigate chronic recordings from Q54 mice that display spontaneous seizures because of a gain-of-function mutation of the Scn2a sodium
channel gene, and to evaluate the efficacy of low frequency deep brain stimulation (DBS)
for seizure frequency reduction. Methods: EEG, EMG, and hippocampal deep electrodes
were implanted into Q54 mice expressing an epileptic phenotype (n = 6). Chronic six
channel recordings (wideband, 2KHz sampling rate) were stored 24 hours a day for more
than 12 days. LFS (3Hz, square wave, biphasic, 100µs, 400µA) was applied to ventral
hippocampal commisures (VHC) in alternating five minute cycles (on or off) 24 hours a
day for a period of four days. Results: Frequency analysis of spontaneous seizures
indicated a significant and unique increase in signal power recorded from hippocampal
deep electrodes over all frequency bands. LFS (3Hz) resulted in a significant reduction
in seizure frequency (p<0.05) when applied to the VHC of epileptic Q54 mice (n = 6), but seizure frequency was not directly affected by stimulation state (on or off).
Conclusion: Analysis of seizure activity in Q54 mice reveals a robust and well maintained seizure frequency over several days with seizures that are characterized by increased power in all frequency bands. LFS applied at a frequency of 3Hz significantly
reduces seizure frequency in the Q54 model. Furthermore, the reduction of seizure
48
frequency by 3Hz LFS is not immediate, and may have a lasting effect, supporting
complex, secondary mechanisms of action such as long term depression (LTD).
3.2 INTRODUCTION
Epilepsy is one of the most prevalent neurologic disorders and affects approximately 1% of the population (Hauser et al., 1993). Epilepsy is characterized by
the presence of recurrent, unprovoked seizures, defined by uncontrolled excitation of
neuronal populations within the brain. While many there are many epilepsy syndromes,
the first course of treatment for the majority of epileptics is pharmacotherapy with anti-
epileptic drugs (AEDs). Phenytoin, a voltage-gated sodium channel inhibitor, was first
synthesized in 1908 and remains one of the most well studied and initially prescribed
AEDs following an epileptic diagnosis (Bazil and Pedley, 1998).
Voltage-gated sodium channels plan an essential role in both the development and
in the treatment of patients with epilepsy. The genetic component of inherited epilepsies
in humans has been linked to mutations in several genes coding for the sodium channel
protein, including: Scn1a, Scn2a, and Scn1b (Wallace et al., 1998; Escayg et al., 2000;
Claes et al., 2001; Escayg et al., 2001; Lerche et al., 2001; Sugawara et al., 2001a;
Sugawara et al., 2001b; Wallace et al., 2001; Ohmori et al., 2002; Sugawara et al., 2002;
Wallace et al., 2002; Claes et al., 2003; Fujiwara et al., 2003; Ceulemans et al., 2004a;
Kamiya et al., 2004; Kearney et al., 2006a; Ohmori et al., 2006; Suls et al., 2006). A
similar mutation of the Scn2a gene in the Q54 line of mice developed by Kearney et. al.,
results in a voltage-gated sodium channel gain-of-function. The specific gain-of-function
is that of a persistent sodium current through voltage-gated sodium channels in
49
hippocampal pyramidal cells, which leads to the development of spontaneous,
generalized seizures in these animals (Kearney et al., 2001). Two of the most commonly
prescribed AEDs are thought to minimize seizure frequency through the modification of
neuronal activity through the inhibition of sodium channels: phenytoin (Dilantin) and
carbamazepine (Tegretol) (Kandel et al., 2000).
Unfortunately, more than 25% of patients suffering from epileptic seizures do not
respond well to medicinal therapies, or become resistant to them over time (Enna and
Coyle, 1998). Only about half of these individuals are considered good candidates for
neurosurgery, and these patients also face significant risk associated with the surgical resection of foci often located deep within vital regions of the brain. One potential
alternative therapy for medically intractable epilepsies is deep brain stimulation (DBS).
DBS is a surgical treatment involving the implantation of one or more electrodes into the
central nervous system in order to deliver electrical impulses to specific target regions of
the brain. DBS directly changes brain activity in a controlled manner and is a recognized
therapy for the treatment of Parkinson’s deisase (PD) (Obesco et al., 2001), essential
tremor (Benabid et al., 1996), and dystonia (Vidailhet et al., 2005). The Food and Drug
Administration (FDA) approved DBS as a treatment for PD and essential tremor in 1997
(Halpern et al., 2007), and dystonia in 2003 (Yu and Neimat, 2008). More recently, it has been used to treat other neurological conditions including depression (Mayberg et al.,
2005), obsessive-compulsive disorder (Gabriels et al., 2003), and epilepsy (Hodaie et al.,
2002).
Although high frequency stimulation (HFS) parameters are generally used in DBS therapies, low frequency stimulation (LFS), in the range of 0 - 10 Hz, is also a strong
50
candidate for epilepsy therapy. While HFS is thought to inhibit neuronal activity through
axonal conduction block, LFS may inhibit activity by increasing the threshold for the
firing of neuronal action potentials through more complex mechanisms such as long term
depression (LTD) (Albensi et al., 2004; Schrader et al., 2006). This suggests that LFS could have a longer lasting effect on target tissue, requiring fewer stimulation periods and less current injection overall. This is in addition to the fact that LFS inherently requires less current injection, due to the reduced number of stimulation pulses per second.
Minimizing current injection is an important factor in the enhancement of stimulation
electrode stability as well as in the reduction of local tissue damage.
To date, LFS has shown success in several animal models of epilepsy. Low frequency stimulations, ranging from 0.1 - 10 Hz, were able to suppress high extracellular
potassium and bicuculine induced seizures in the rat hippocampus in vitro (Jerger and
Schiff, 1995; Albensi et al., 2004). Similarly, multiple studies have shown a suppressive effect on afterdischarges elicited by kindling in the amygdala of the rat in vivo, when kindling was followed or preceded by 1-3 Hz stimulation (Velisek et al., 2002; Goodman et al., 2005). Suppression of seizure activity has also been seen in a limited number of human studies. For example, LFS of 0.5 Hz applied to ictal zones resulted in a reduction of seizure initiation in 4 of the 5 identified seizure onset zones (Schrader et al., 2006).
In fact, the majority of uncontrolled human studies have yielded exceptional seizure control, but reduction in seizure frequency has been insignificant in controlled human studies (Lüders, 2004). One of the reasons for the inability of this success to translate to controlled studies is likely due to the fact that ideal parameters have yet to be identified and customized specifically for seizure suppression. Previous studies have
51
built upon the success of PD therapy, and have used similar techniques to treat a disease
with significantly different mechanisms of development. For example, stimulation of the
subthalamic nucleus (STN) was originally examined based on its success in PD and the
convenience it provided for approving experimental protocols. However, when treating
seizures that involve a variety of brain regions, a more diverse stimulation may be
required to affect multiple epileptic foci.
Many forms of epilepsy, including the Q54 model, involve the temporal lobe.
Specifically, the hippocampus, a commonly studied and well-documented portion of the
brain responsible for relational learning and memory, is a common site for epileptic foci
in temporal lobe epilepsy. Because the hippocampus is curved in two directions along
two axes, a slice cut perpendicular to its long axis yields the same circuit. This highly
laminar structure of the hippocampus renders it especially useful for research purposes
(Carlson, 2004). Signals in the hippocampus are transmitted from the dentate gyrus to
CA3 via mossy fiber axons and then to CA1 through Schaffer Collaterals. In many
studies, a stimulating electrode is inserted into the Schaffer Collateral region, and a
recording electrode is inserted into the CA1 region. Neural activity can then be recorded
and stored on computers for future data analysis.
The aim of this study is to suppress spontaneous seizures through stimulation of
white matter tracts. It is hoped that stimulation of white matter tracts directly connected
to epileptic zones may disrupt seizure activity by overdriving epileptic foci within the
temporal lobe. In addition, by targeting these white matter tracts, we can activate multiple epileptic foci with a single target area for stimulation. In particular, the ventral hippocampal commissure (VHC) is composed of axonal fibers which connect the right
52
and left hippocampi of the temporal lobes. Because the Q54 Scn2a mutation affects pyramidal cells of the hippocampus and seizures dominate this area in Q54 mice, the primary stimulation target for this study is the VHC (Figure 3.1, A). In addition, the corpus callosum (CC), one of the largest and most prominent axonal pathways in the
CNS, consists of over one million fibers that connect the cerebral hemispheres (LaMantia and Rakic, 1990). In fact, one current therapy for intractable epilepsy is a corpus callosotomy, which is a surgical procedure where the CC is cut in an attempt to isolate the cerebral hemispheres resulting in a significant reduction (70-90%) of seizure frequency (Jenssen et al., 2006). For these reasons, a secondary stimulation target would be the CC (Figure 3.1, A).
Because the mechanisms of deep brain stimulation are not well understood, a variety of stimulation paradigms have been explored with minimal success. As noted, previous studies have primarily focused on high frequency stimulation applied directly to seizure foci, with few examining the effects of low frequency stimulation applied upstream from seizure foci. Application of stimulation to axonal-rich white matter tracks can maximize any therapeutic effect by targeting multiple downstream epileptic foci.
The resultant hypothesis is that low frequency stimulation of 3Hz applied to the ventral hippocampal commissural (VHC) fibers will reduce seizure frequency in Q54 mice. To test this hypothesis, stimulation electrodes were implanted into the VHC of seizure prone
Q54 transgenic mice and seizure frequency was evaluated before, during, and after applied low frequency stimulus.
53
3.3 METHODS
3.3.1 Animals
Experiments were performed on the Q54 strain of transgenic mice expressing the
GAL879-881QQQ mutation of Scn2a (Kearney et al., 2001). Q54 transgenic mice were bred as previously described (Kile et al., 2008a). Mice were weaned and tagged at three weeks of age, and a small tail biopsy was taken. Genomic DNA was isolated from tail biopsies via proteinase K digestion, phenol/cholorform extraction and ethanol precipitation. Mice were genotyped by polymerase chain reaction (PCR) and electrophoresis of extracted tail DNA. PCR mix for each tail sample composed of (in ul):
2.5 10 × PCR buffer (without MgCl2), 1.7 MgCl2, 5 1 mM dNTPs, 1.5 Primer A1 (5_
GAT GCT CTT CTC CAC AAT GCT AAC C 3_), 1.5 Primer A2 (5_ GGG GAA ATC
TTA ACA CCA GTC ACA C3_), 1.0 Primer N1 (5_ ATC CTT CCT TGG CTG CTT
CAG ACT TG 3_), 1.0 Primer N2 (5_ CTC TTC TGC AAT GCG CTG TTC GAT AG
3_), 8.6 DII H2O, 0.2 Taq (5U/μl), and 2 tail DNA for a total volume of 25 μl. Two primer sets were used; N1-2 primers (product length = 960 bp) provided mutation detection while A1-2 primers (product length = 146 bp) served as PCR control. DNA amplification was conducted by PCR on a Mastercycler (Eppendorf AG, Hamburg,
Germany). Samples were denatured for 2 min at 94◦C, followed by 33 cycles of 30 s at
94◦C, 30 s at 65◦C, 75 s at 72◦C. Once PCR cycles were completed, 5 μl bromophenol blue marker was added to each sample and the mixture was electrophoresed on a 1% agarose gel (120V), visualized by ethidium bromide fluorescence, and measured against a
1 Kb DNA ladder.
54
All experiments were conducted on heterozygous female Q54 transgenics (n = 6), between two and six months, ensuring the onset of generalized seizures while minimizing the possibility for seizure induced damage. Individual mice were identified by right (R) or left (L) ear tag serial number: 042R, 829R, 871L, 881R, 882L, and 898R. All animals were housed in microisolator cages and maintained in a veterinarian monitored animal care facility with a 12hr:12hr light:dark cycle at room temperature (20-25°C). All animal protocols were reviewed and approved by the Institutional Animal Care and Use
Committee of Case Western Reserve University.
3.3.2 Electrode implantation
Adult Q54 transgenic mice (n = 6) were anesthetized with isoflurane (5% induction, 2% maintenance) inhalation, and mounted into a stereotaxic frame. Polyimide- insulated stainless steel monopolar microelectrodes (0.1mm diameter) (Plastics One Inc.
Roanoke, VA) were implanted bilaterally into the pyramidal cell layer of the posterior hippocampus (AP, ±3 mm from Bregma; ML, -2.8 mm, and DV, -3.5 mm from surface of skull). A twisted-pair polyimide-coated stainless steel bipolar electrode (0.25mm diameter) (Plastics One Inc. Roanoke, VA) was implanted into the ventral hippocampal commissural (VHC) fibers (AP, -0.8; ML, -0.5; DV, -2.5). In addition, four 1/16 in. stainless steel EEG screws (A-M Systems, Carlsberg WA) were implanted into the lateral frontal and lateral parietal (AP, 1.5; ML, ±1.5; DV, 0; AP, -2.5; ML, ±1.0; DV, 0) regions of the skull for differential EEG recordings (Figures 3.1 and 3.2). EMG signals were recorded from fine polyimide insulated stainless steel wire electrodes sewn into the neck muscles (Cooner Wire, Chatsworth, CA). Chronic recording and stimulation targets are
55
shown in Figure 3.1, and stereotaxic implantation sites are shown in relation to the mouse skull in Figure 3.2. Following electrophyisiological experiments, mice were anesthetized and decapitated using a small animal guillotine. The brain was rapidly removed and fixed in 10% formalin. Nissl stained coronal sections (60 μm thick) were viewed with a
light microscope to verify electrode placement.
3.3.3 Stimulation and recording
Ten days following implantation, six-channel (4 EEG, 1 EMG, 1 Deep
Hippocampal Electrode) wideband (0.3 – 300 Hz) recordings of electrical activity were
acquired at a rate of 2KHz 24 hours per day for a minimum overall period of 12 days
consisting of the following consecutive 4 day periods: baseline (BL), 3Hz stimulation (S),
3Hz recovery (R) During periods of stimulation, animals were stimulated with low
frequency (3Hz) charge-balanced biphasic, square wave pulses (100us, ≤400μA)
delivered to the VHC. Stimulation was continuously delivered with a 50% power cycle
(5 min on, 5 min off). Simultaneous video monitoring and six-channel electrical
recordings were maintained throughout.
Seizure classification was conducted from EEG recordings and video observed
behavior according to an adjusted version of the Racine scale (Racine, 1972): stage 1:
EEG seizures without detectable motor manifestation, 2: mouth and facial clonus, head
nodding, 3: bilateral forelimb clonus, 4: forelimb clonus and rearing, 5: forelimb clonus,
rearing, and falling.
All signals were amplified (5000 gain) with a GRASS EEG Amplifier (Model
7P511J/K, Grass Technologies, West Warwick, RI), and recorded onto a personal
56
computer using a National Instruments Data Acquisition System and Labview software
(National Instruments, Austin, TX). Stimulation current was applied with a digital stimulus isolator (Model DS8000/DLS100, World Precision Instruments, Sarasota, FL).
Off-line data analyses were performed in Polyman (v1.2.6.603, Kemp & Roessen, Den
Haag, Netherlands), Spike2 (v5.02, Cambridge Electronic Design Limited, Cambridge,
England), and Matlab (v7.6, Mathworks, Natick, MA) Software. Video monitoring was conducted with small USB digital video camera (Creative Labs, Singapore) and video monitoring freeware.
3.3.4 Data analysis
Measurements throughout this text are expressed as mean ± standard deviation
(SD) unless otherwise noted, with n, h, d, s, and m, indicating the number of animals, hours, days, seizures, or total measures evaluated per test. Seizure frequency data was found to be normally distributed as confirmed by both Kolmogorov-Smirnov and Ryan-
Joiner goodness-of-fit tests (p-values >0.15 and >0.1 respectively). Results obtained were evaluated for statistical significance using statistical analysis methods including analysis of variance (ANOVA) and the Student’s t-test. Statistical tests were performed with a significance level, p < 0.05, unless otherwise noted, using Minitab 15 (Minitab Inc., State
College, PA) software.
3.4 RESULTS
3.4.1 Baseline seizure activity
57
In order to evaluate the effect of LFS on seizure activity, chronically recorded seizures in Q54 mice needed to be characterized and quantified. After a minimum of six
days of recovery from surgical implant, baseline activity was recorded for a period of at
least four days. Baseline data was analyzed for the presence of high frequency, high
amplitude activity characteristic of seizure in EEG channels and matched with video
recordings to confirm the presence of seizure activity (Figure 3.4). Seizures were
evaluated according to modified Racine scale (Racine, 1972), and only those seizures
confirmed by video recording to be greater than or equal to stage four were counted in
seizure frequency measurements. A typical seizure as viewed within six-channel
chronically recorded data is shown in Fig 3.4. Seizure activity was primarily identified
by the presence of high frequency activity across all channels including EEG, EMG, and
deep electrodes (DPE). Seizures were confirmed in video footage by the presence of
bilateral forelimb clonus, rearing, and falling behaviors (Figure 3.2). The two final days
of baseline data, prior to stimulation, were analyzed for each animal (n = 6), and seizure
frequency per hour noted. The average seizure frequency was 14.6±6 seizures/hr, (n = 6,
d = 2, h = 24, m = 288) (Figure 3.5). Seizure frequency appears to be well maintained
across all hours of the day with a mean seizure frequency range from 12.4 to 16.9
seizures/hr over the entire 24 hour period. Seizure frequency was found to be slightly
greater during more active hours (6pm-6am), 14.9±1 seizures/hr (n = 6, d = 2, h = 12, m =
144) versus 13.8±1 seizures/hr (n = 6, d = 2, h = 12, m = 144), although this result was
not found to be a statistically significant difference. From these data, hours 9am – 12pm
were selected for seizure frequency analysis during days when stimulation was applied.
This period of time was selected because mean seizure frequency was comparable to
58
overall average with a decreased variability, as well the fact that the animals were generally less active, minimizing EMG interference. During this time the average seizure frequency was 14.8±5 seizures/hr (n = 6, d = 4, h = 4, m = 96).
3.4.2 High frequency oscillations during seizure
To further characterize seizures in Q54 animals, frequency components from the chronically implanted electrode recordings were evaluated during a 10 sec interval immediately preceding and 10 sec into seizure activity. The frequency components of the recorded signals were evaluated over ten second intervals during baseline recordings: baseline non-seizure (BL), pre-seizure (PS), and during seizure (SZ) activity (Figure 3.6).
Because seizures were identified by their motor involvement on the Racine scale, the start of SZ activity was identified according to video monitored events. Time zero was noted as the start of rearing during a previously identified seizure. BL non-seizure activity was evaluated over a 10 second interval starting one minute prior time zero. Because seizures rarely occurred within two minutes of each other, BL windows did not contain seizure activity as confirmed in both raw signal and video analysis. The PS period was evaluated as a ten second window immediately prior to SZ. Ten seizures were evaluated per animal
(s = 10, n = 6, m = 60), all of which had a minimum duration of 10 seconds in their motor manifestation as confirmed by video. Several frequency bands of interest were evaluated over the three periods of interest including low (L, 1-15Hz), gamma (G, 25-80 Hz), high
(H, 100-200 Hz), and very high (V, 200-300Hz) frequencies. The fast Fourier transform of the recorded signal data over the frequency ranges of interest was used to determine the relative power (V2) in each frequency band. An example of spectral density plots for
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EMG and DPE signals in the very high frequency band during seizure is shown in Figure
3.7. Because of the variation in signal noise due to slight variations in implantation procedure and recovery, power in both PS and SZ periods were normalized to the average
BL power over the 10 seizures for each individual animal. Power was found to be significantly higher in all frequency bands for both EMG and depth electrode (DPE) channels during seizure periods in comparison with baseline (p-value<0.05, Table 3.1,
Figure 3.8). However, cross-correlations of EMG and DPE channels for all animals (n =
6), resulted in absolute values <0.5 at time 0 (data not shown).
3.4.3 Reduction of seizure frequency during LFS
LFS of 3 Hz was applied to the VHC in mice expressing seizures due to a sodium channel mutation. Biphasic (cathodic-anodic) square wave pulses with a 200μs pulse width (100μs per phase) and ±400μA amplitude were applied at a frequency of 3 Hz cycling between on and off periods every 5 min. This cycling paradigm was applied continuously throughout each day (24 hrs) for a period of four days (3Hz1 – 3Hz4). At the end of four days, stimulation was turned off completely and followed by another four day recording segment without stimulation, recovery period (R1-R4) (Figure 3.9). An example of chronic recordings during periods of 3 Hz stimulation is shown in Figure
3.10.
Animals (n = 6) were evaluated both individually and together during four day experimental periods (BL, 3Hz, and R). Five of six animals showed a decrease in mean seizure frequency during 3Hz LFS from BL, as well as during R, four of which animals were statistically significant reductions (p-value < 0.05, d = 4, h = 4, m = 16). The one
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animal that did not experience a decrease during BL or R periods, experienced an
increase in mean seizure frequency by 0.88 seizures/hr during 3Hz LFS and a further
increase of 2.31 seizures/hr during R. Average mean seizure frequency for all animals
decreased from 14.8±5 seizures/hr during BL to 11.7±5 during 3Hz LFS and finally,
10.3±5 seizures/hr during R (n = 6, d = 4, h = 4, m = 96). Overall, animals exhibited a significant decrease in mean seizure frequency from BL during both 3Hz LFS and R (p- value <0.05, Figure 3.11). In terms of percent, this equates to an average 20.9% reduction in seizure frequency during 3Hz LFS, or an average 30.4% decrease in seizure frequency during recovery (n = 6).
3.4.4 Effect of stimulation state on seizure frequency
To evaluate the effect of stimulation state on seizure frequency, seizures occurring
on stimulation days were noted as occurring during five minute “on” intervals versus five
minute “off” intervals. The percent of total seizures per hour occurring in either on or off
periods was calculated for each hour and then averaged over all hours evaluated. During
3 Hz stimulation the mean percent of total seizures during “on” periods was 52.2±17.2%.
Of the 96 measures (n = 6, d = 4, h = 4, m = 96), t-tests revealed no significant difference
between “on” versus “off” states during the 3Hz LFS period (Figure 3.9).
3.5 DISCUSSION
For patients suffering from medically intractable epileptic seizures and are not
candidates for surgical resection or prefer a more reversible therapeutic strategy, deep
brain stimulation offers a promising alternative. Before deep brain stimulation (DBS)
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can be administered as a successful seizure therapy, proposed stimulation targets and
waveform parameters need to be identified and evaluated within a realistic model of
human epilepsy. This study investigates a potential stimulation target and stimulation
paradigm for the treatment of hippocampal seizures in an idiopathic model of epilepsy
with three key findings. First, analysis of seizure activity in Q54 mice reveals a robust
and well maintained seizure frequency over several days with seizures that are
characterized by increased power in all frequency bands. Second, low frequency
stimulation (LFS) at a frequency of 3Hz significantly reduces seizure frequency in a transgenic model of inherited epilepsy. Lastly, the presence of LFS does not seem to
have a direct and immediate effect on seizure frequency.
The emergent and diverse body of work investigating the mechanisms behind the
ability of LFS to suppress neuronal excitability promotes the need for continued research
in this field. Several animal studies have been conducted on a variety of epilepsy models, using varied stimulation parameters applied to different regions of the brain. While data presented here is unique in its combination of stimulation parameters as well as the epilepsy model they are applied to, it does agree with the several findings in related studies contained within the preceding work.
The effects of externally applied DC electrical fields have been studied in a variety of animal models both in vitro and in vivo. Both uniformly applied and locally
applied fields are thought to have an effect on excitability by modification of membrane polarization near the soma or neurites. Hyperpolarization of the soma generally increases neuronal inhibition, while sufficient depolarization near the soma will result in the generation of an action potential (Durand and Bikson, 2001). AC electrical fields have
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also been studied in detail, but the mechanisms by which they affect the excitability of
neuronal populations are more complex.
While traditional use of electrical stimulation within the brain was targeted at
excitation and synchronization of neuronal activity, there are electrical stimulation
protocols that have been able to directly suppress neuronal action potentials or interfere with neuronal synchronization (Durand et al., 2006). Many studies, primarily on the
kindling model of epilepsy, have shown that LFS can have an inhibitory effect on seizure
generation and propagation and the results presented here are consistent with these
studies. LFS (0.1 - 10 Hz) was able to suppress high extracellular potassium and
bicuculine induced seizures in the rat hippocampus in vitro (Jerger and Schiff, 1995;
Albensi et al., 2004), and multiple studies have shown a suppressive effect of 1-3Hz LFS on afterdischarges elicited by kindling in the amygdala of the rat in vivo (Gaito, 1980;
Gaito et al., 1980; Gaito, 1981; Gaito and Gaito, 1981; Weiss et al., 1995; Velisek et al.,
2002; Goodman et al., 2005; Carrington et al., 2007; Zhu-Ge et al., 2007). The kindling
model of epilepsy elicits electrographic and behavioral seizures in response to repeated
application of intermittent trains of electrical stimulation (Goddard et al., 1969). Because
Goddard indicated a reduced probability of eliciting seizure activity at frequencies
outside of 60Hz, Gaito evaluated the effect of several frequencies on the kindling effect
in vivo, and determined that 1Hz or 3Hz stimulation was unable to elicit seizure
behaviors (Gaito, 1980). Furthermore, 3Hz stimulation applied before and after 60Hz
kindling trains was found to have a suppressive effect on kindling due to what was
suggested to be an “interference effect” (Gaito et al., 1980).
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Clinically, LFS (0.5-1 Hz) applied to epileptic zones in humans was shown to have an inhibitory affect (Schrader et al., 2006). McIntyre et al has shown that LFS applied to results in an increase in afterdischarge threshold, but the molecular mechanisms involved in this elevation of threshold to firing remain unclear.
As previously mentioned, HFS is thought to inhibit neuronal activity through axonal conduction block, while LFS is thought to inhibit activity by increasing the threshold for the firing of neuronal action potentials through more complex mechanisms such as long term depression (LTD) (Albensi et al., 2004; Schrader et al., 2006). LTD is a long-lasting decrease in synaptic efficacy which can be induced by 1Hz or 3Hz LFS applied to the Schaffer collaterals in the hippocampal slice preparation (Christie et al.,
1994; Albensi et al., 2007). While the specific role of LTD was not evaluated in this study, the results do support this type of action. For one, LFS does not appear to have an immediate effect on seizure frequency, but rather a significant reduction occurs over the course of several days. This is demonstrated by the results from the evaluation of the percent of seizures occurring during the five minute periods of LFS cycling. It was found that seizure frequency was not affected directly by the presence of stimulation in that the number of seizures occurring in a given hour was occurring at roughly equal times, during both “on” and “off” periods. This balanced rate was maintained throughout the entire LFS period. In addition, significant reduction in seizure frequency lingered into the recovery period, after stimulation was turned off. These data suggest that LFS could have a longer lasting effect on target tissue. As mentioned previously, this would be beneficial in that LFS protocols would require fewer stimulation periods and less current injection overall. In addition to the fact that LFS inherently requires less current injection,
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due to the reduced number of stimulation pulses per second, an overall minimization of current injection is favorable in the reduction of local tissue damage, making LFS preferable to HFS therapies.
Alternatively, reduction of seizure activity could result from a delayed neuronal desynchronization across the white matter tracts similar to the effect resulting from a corpus callostomy, where the connections are cut to reduce seizure propagation and thus frequency. LFS applied to the VHC could also affect the CC disrupting action potential propagation through this area, assisting to blocking the propagation of seizures between cortical hemispheres or between hippocampi specifically. Data presented here support disruption of seizure activity as demonstrated in the statistically significant reduction of mean seizure frequency during periods of LFS. In addition, application of LFS supports that LFS may inhibit neuronal activity through longer lasting mechanisms, as the stimulation seems to have a lasting effect during the recovery period following stimulation.
However, it appears although LFS can significantly reduce the number of seizures, the effect is a modest 20 percent decrease in seizure frequency. Thus, LFS applied to the VHC is unable to block seizures completely. This could be due to the fact that the animals in this study have a uniquely high seizure frequency during baseline recordings stemming from foci outside of the stimulation targeted regions. The Q54 model of epilepsy, while based on a sodium channel mutation similar to those found in inherited human epilepsy syndromes may be more distributed throughout the brain than standard kindling models of spontaneous seizures, involving a greater number of brain nuclei and subsequently, a greater number of seizure foci. Thus, while LFS therapy
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could be acting to reduce the connectivity similar to a corpus callosotomy (Jenssen et al.,
2006), due to the possibility of a large number of foci, it cannot eliminate seizures in their
entirety. Presumably, in practice this therapy could be administered prior to reaching this
heightened disease state, and thus may have a greater effect on overall seizure reduction.
Further studies in additional epilepsy models and perhaps in the Q54 model at an earlier stage of disease development, are required to further evaluate this question.
While the anatomy of the mouse brain is similar in many ways to the human
brain, it should be noted that murine hippocampal commissures have differing anatomical
characteristics and connectivity in comparison to those in humans. Although the VHC is
reduced in humans, the dorsal hippocampal commissure (DHC) is well developed and
represents a sizable fiber tract connecting the right and left hippocampi via fornix
attachments (Gloor et al., 1993). A transgenic mouse model was selected for this study,
and therefore the VHC was selected as the primary stimulation target. However, DHC
stimulation may be more successful if this work is to be successfully translated into
human studies.
In conclusion, the Q54 model of epilepsy exhibits chronic spontaneous seizures at
a reliable and sustainable high incidence that is maintained over several days and
characterized by increased power in frequency bands in the range of 1-300 Hz. LFS at a
frequency of 3Hz significantly reduces seizure frequency, but the effect is not immediate,
supporting that underlying mechanisms of action may be complex and long lasting. The
fundamental goal of this study was to evaluate the effect of low frequency deep brain stimulation applied to the ventral hippocampal commissures on seizure activity, which
was found to be significantly inhibitory. The present study is unique in its design and
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provides evidence to support a new method for the application of deep brain stimulation in the treatment of epileptic seizures. Future studies into the mechanisms of action are required in order to guide the selection of optimal LFS parameters for the successful suppression of epileptic seizures in humans.
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fourier transform of the signals seline (BL), pre-seizure (PS), and seline (BL), pre-seizure ght electroencephalogram (EEG), and significant difference from EEG and Low (1-15 Hz), Gamma (25-80 High (100-200 Hz) and Low er was calculated using the fast ing three key activity periods: ba uding neck electromyogarm (EMG), ri fference from DPE BL (p<0.01); ** = Table 3.1—Signal power in frequency bands: Table 3.1—Signal power in frequency obtained from three channels incl Very High (200-300Hz) frequency band pow hippocampal deep electrode (DPE) dur seizure (SZ). (* = significant di DPE for respective bands during SZ (p<0.05))
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A
B
Figure 3.1—Surgical targets: A) ventral hippocampal commissure stimulation electrode target, and B) bilateral hippocampal recording electrode targets (modified from (Paxinos and Franklin, 2001a)).
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EEG REC STIM
Figure 3.2—Surgical implantation: Four EEG skull screws, one stimulating electrode, and a pair of bilateral hippocampal deep electrodes were implanted into Q54 transgenic mice (modified from (Paxinos and Franklin, 2001a)).
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A B C
D
Figure 3.3—Q54 model seizures: A-C) Q54 mice exhibited motor seizures as previously described (Kearney et al., 2001). D) During chronic electrical recordings, electrode implanted mice were video monitored from above to confirm occurrence of motor seizures.
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A
B
C
D
E
F
Figure 3.4—Chronic recording: Six-channel recordings were maintained for 24 hours a
day over entire experimental protocol. Typical recording including A) Hippocampus, B)
EMG, C) Right EEG, D) Left EEG, E) Frontal EEG, and F) Parietal EEG, is shown, with
seizure (boxed) as identified by high frequency components across all channels as well as
by motor seizure activity seen in video monitoring (Scale: 50µV, 2.5s).
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Figure 3.5—Daily Seizure Frequency: Average seizure frequency over all animals
(n=6) during baseline data was found to be 14.6 ± 1 seizures/hr. Seizure frequency was slightly greater during the daytime hours (6am-6pm), 14.9±1 seizures/hr, versus 13.8±1 seizures/hr during the nighttime hours (6pm-6am), although this result was not found to be statistically significant (data is presented here as mean seizure frequency ± SEM).
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A B
Figure 3.6—Signal frequency analysis: Frequency bands were analyzed from wideband
(0.3-300Hz) EMG (top trace), EEG (middle trace), and hippocampal (bottom trace) recordings over 10s segments: Baseline (BL, -60s start, not shown), A) Pre-seizure (PS, -
10s start), and B) Seizure (SZ, 0s start) periods. Scales: 10s and 50uV (all).
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A. EMG B. DPE 0 4 40
200 Hz 500 Hz 200 Hz 500 Hz
Figure 3.7—Very high frequency band spectral density during seizure: Fast Fourier
transform was calculated during seizure activity for A) EMG and B) deep electrode
(DPE). Deep electrode had consistently larger energy, 29.9±0.4V2, than EMG,
8.8±0.1V2, when integrated over the very high frequency band (200 – 300 Hz).
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DPE Power during Activity States
4.5
4 to 3.5 3 2.5 BL 2 Normalized Baseline 1.5 PS 1 SZ Power 0.5 0 Low Gamma High Very High Frequency Band
Figure 3.8—Changes in DPE signal power over frequency bands: Signal power was calculated from spectral density over frequency bands of interest: low (1-15 Hz), gamma
(25-80 Hz), high (100-200 Hz), and very high (200-300 Hz) during three time periods: baseline (BL), pre-seizure (PS), and during seizure (SZ). Seizure activity had a significantly higher power for all frequency bands (p<0.05).
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3 Hz
Figure 3.9—Low Frequency Stimulation (LFS) protocol: LFS (3 Hz) was applied for a period of four days immediately following a four day period without stimulation, baseline
(BL), and preceding an additional four days of recording without stimulation, recovery
(R). Seizures were counted per hour over a period of four hours, 9am – 12pm, each day.
Mean seizure frequency (seizures/hour) ± SEM is shown over all experimental days
(n=6).
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A
B
C
D
E
F
Figure 3.10—Stimulation during chronic recording: Six-channel recordings during
periods of cycling stimulation. Channels of A) hippocampus DPE, B) EMG, C)
stimulation indicator, D) Left EEG, E) Right EEG, and F) Parietal EEG, are shown, with
seizure (boxed) as identified by high frequency components across all channels as well as
by motor seizure activity seen in video monitoring. Stimulus artifacts from square wave
pulses (dotted line) are easily identifiable over recordings, with the exception of right
EEG (Scale: 50µV, 5s).
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* *
Figure 3.11—Effect of Low Frequency Stimulation (LFS) on seizure frequency: Mean seizure frequency ± SEM over four day baseline (BL), 3 Hz stimulation (3Hz), and recovery (R) periods is shown for all animals (n = 6, d = 4, h = 4, m = 96). Overall, animals experienced a decrease in average seizure frequency during the period of applied LFS, which persisted during recovery (* = significant decrease from baseline, p<0.05).
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Figure 3.12—Effect of stimulation state on seizure frequency: No significant difference in the mean percent of total seizures per hour (n=6, h=4, d=4) was found between on and off states over four days of 3Hz low frequency stimulation.
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Chapter 4: A Novel Multi-pronged Electrode for Deep Brain Stimulation of White Matter
4.1 ABSTRACT
Purpose: To design an electrode for the activation of axonal-rich areas of the central nervous system for the application of deep brain stimulation in the treatment of neurological disorders such as epilepsy. Design goals were to minimize damage while maintaining the ability to activate over 50% of axons in the target area, in our case the ventral hippocampal commissural (VHC) fibers. Methods: Finite element model was constructed using Maxwell 3-D Software (Ansoft, LLC., Pittsburg, PA). Electrode diameter was reduced to less than 50 µm by the use of fine wires, rather than several large contacts on a single large diameter electrode shaft. In addition, contact size and shape was evaluated to determine the most effective size that would allow maximal activation while minimizing current density related damage to surrounding tissue.
Computer models were used to evaluate design parameters followed by the construction of several prototypes that were evaluated and tested in vivo. Results: Four thin wire electrode contacts achieved sufficient activation of target area (1mm3). Electrode
induced tissue damage was minimized through reduction of contact and lead diameter by
use of fine wires. A proposed “safe” charge density limit of 100µC/cm2 was met by
increasing contact length, and reducing current injection by increasing contacts from one
to four. Multi-pronged, flexible contacts allowed sufficient dispersion of contacts for maximal axonal activation within the target volume. Electrode prototypes (n=5) demonstrated low impedance measurements (6.63±1.7 KΩ @ 1 KHz) and were able to evoke hippocampal population spikes (≥0.5 mV) in vivo via stimulation (100 µs, 400 µA,
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cathodic square wave) delivered to the VHC. Conclusion: Fine-wire electrodes are a
promising alternative to the current FDA approved designs, especially for the stimulation
of small, white matter tracts.
4.2 INTRODUCTION
More than three million Americans are affected by epilepsy, a neurological
disorder characterized by the presence of seizures, the uncontrolled excitation of large
neuronal ensembles. Seizures vary in their effect on the individual depending on the
areas of the brain involved and the disease state of the patient. Some epilepsy syndromes
can be successfully treated medically through the administration of anti-epileptic drugs
(AEDs), however many patients remain untreatable and rely on surgical resection of a
brain tissue for seizure cessation.
One potential alternative therapy for medically intractable epilepsies is deep brain
stimulation (DBS). DBS is a surgical treatment involving the implantation of one or more
electrodes into the central nervous system in order to deliver electrical impulses to
specific target regions of the brain. Although the mechanisms are not clearly understood,
because DBS has a direct effect on brain activity in a controlled manner and it has
become a recognized therapy for several neurological disorders including the treatment of
Parkinson’s deisase (PD) (Obesco et al., 2001), essential tremor (Benabid et al., 1996), and dystonia (Vidailhet et al., 2005). The Food and Drug Administration (FDA)
approved DBS as a treatment for PD and essential tremor in 1997 (Halpern et al., 2007),
and dystonia in 2003 (Yu and Neimat, 2008). More recently, DBS therapy has been
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applied to other neurological conditions including depression (Mayberg et al., 2005),
obsessive-compulsive disorder (Gabriels et al., 2003), and epilepsy (Hodaie et al., 2002).
Many forms of epilepsy involve the temporal lobe, including the hippocampus, a
commonly studied and well-documented portion of the brain responsible for relational
learning and memory. The highly laminar structure of the hippocampus renders it
especially useful for research purposes (Carlson, 2004). Signals in the hippocampus are
transmitted from the dentate gyrus to CA3 via mossy fiber axons and then to CA1
through Schaffer Collaterals. In many studies, a stimulating electrode placed into the area containing Schaffer collateral axons, or even further upstream such as into the ventral hippocampal commissural axons, can be used to evoke pyramidal cell population spikes within the hippocampus. Recording electrodes placed into the CA1 or CA3 regions of the hippocampus are utilized to record neural activity for future data analysis.
Previously, we demonstrated that low frequency stimulation applied to white matter tracts, in particular the ventral hippocampal commissural (VHC) fibers (Figure 4.1), was
successful in reducing seizure frequency in seizure prone mice (Kile et al., 2008b).
Unfortunately, the only DBS electrodes currently approved by the FDA are the
Medtronic 3387 and 3389 (Medtronic Inc., Minneapolis, MN), both with a shaft at least 9
mm in length and 1.27 mm in diameter (Figure 4.2). An electrode of this size is simply
too large and bulky for implantation into the VHC without inducing significant damage
and/or activation of surrounding brain tissue. For direct, localized activation of the VHC,
a smaller electrode design is needed, preferably one that minimizes damage to the axonal
fiber tracts within the small target region of activation.
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The electrical stimulation of biological tissue with a metal electrode requires the
flow of ionic charge into the biological tissue, known as charge injection. Charge
injection is composed of two primary mechanisms: capacitive and faradaic. Capacitive
charge injection is the charging or discharging of the ions in the tissue fluid in response to
the changes in electrostatic charge on the metal surface which forming the Helmholtz
electrode double layer. Conversely, faradaic mechanisms of charge injection involve the
electron transfer across the electrode-tissue interface resulting in the oxidation or
reduction of chemical species in the surrounding tissue medium. Some faradaic reactions
are reversible, but others are not. Irreversible faradaic charge injection reactions
introduce new chemical species into the surrounding solution and should be minimized in
chronically implanted devices. This has a negative effect on the surrounding tissue, leading to an enhancement foreign body reaction to the implant. This enhanced foreign body reaction causes both increased encapsulation formation around the electrode as well as increased cell death and axonal degeneration in the nervous tissue surround.
Encapsulation of the electrode creates an insulation barrier, requiring even more current to activate the same population of neurons, thus establishing a negative feedback cycle of
CNS damage.
The limit at which electrode materials can no longer restrict irreversible mechanisms for a given current injection is known as the “reversible charge injection limit” and expressed as a charge or current density (Robblee and Rose, 1990). Reversible charge injection limit is primarily affected by the electrode (material, shape, and size), chemical composition of the electrolyte or tissue medium, and the stimulation waveform
(pulse magnitude, duration, polarity, bias, and frequency).
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Long term DBS therapy requires a steady and reliable delivery of stimulation with
minimal impact on surrounding tissue. The goal of this study was to design and evaluate
a novel DBS electrode to stimulate small axon-rich regions of the brain for the treatment
of epileptic seizures. Our hypothesis was that a multi-pronged thin wired electrode could
sufficiently activate the target stimulation area, VHC, while minimizing damage to the
surrounding axonal populations. The best design would limit tissue encapsulation and
assist in the delivery of current to axonal populations thus minimizing current needed for
sufficient activation, keeping current density well within charge injection limits.
4.3 METHODS
4.3.1 Bioelectric field model
A finite element model (FEM) of the DBS electrode prototype and brain interface
was constructed using Maxwell 3-D 12.0 (Ansoft Corporation, Pittsburg, PA). The active
electrode contact was used as the voltage boundary condition for monopolar stimulation,
while the outer surface of the volume conductor was grounded. For this model we
assumed a homogenous and isotropic bulk tissue medium to represent the mouse brain in
the shape of a square with a 1,000 mm3 total volume. Properties of the homogenous brain tissue medium were modeled as saline with a conductance of 2.0 S/m (Cooper,
1946). The electrode was constructed as a 30-sided tungsten (18.2 MS/m) polyhedron with a 17.5 µm radius. Insulation was added as an additional 30-sided polyhedron shell of polyimide (0.0 S/m) with a width of 8.5 µm to create a final electrode diameter of 50
µm (Figure 4.3). Voltage and current density distributions were examined as several
variables of the model were changed, including the shape of the electrode contact and
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conducting material. To examine voltage distributions in the conducting volume
generated by multiple wires, several electrode configurations were examined.
4.3.2 Electrode materials and construction
A multi-pronged stimulating electrode as illustrated in Figure 4.4 was designed in
order to diffuse current density during deep brain stimulation. Because the target area is
approximately one cubic millimeter in volume, the construction of the electrode must be
extremely accurate. In order to achieve the desired stiffness at such a small diameter, four
sections of tungsten wire (99.95% Tungsten CS HML 0.002” size, California Fine Wire
Company, Grover Beach, CA) approximately 4 cm in length were entwined using Loctite
and allowed to disperse 1mm from the stimulating tip. The opposite tip of the electrode
was first stripped of insulation using a pair of hot tweezers set to high and then spot
welded between two 2 mm x 2 mm squares of stainless steel using an UNITEK 125 watt-
seconds pressure welder (UNITEK 125, Miyachi Unitek Corporation, Monrovia, CA) set
to low range, 2% energy, and a pressure of 030. The stainless steel and tungsten
electrode combination was then enclosed in a gold clip (E3630 Electrical Socket Contact,
Plastics One, Roanoke, VA). To insure that the electrode remained intact during surgery,
it was then surrounded by a 0.7cm length of heat shrink wrap (1/16 x 0.5” Heat Shrink
FP116K-R50-ND) and subjected to a heat gun for a duration of two seconds. Electrode
construction was achieved using standard electrical construction equipment (soldering iron, multimeter, etc.). Examples of the electrode prototype constructed are shown in
Figure 4.4.
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4.3.3 Impedance measurements
Electrode prototypes (n = 4) were evaluated with a Potentiostat and Frequency
Response Analyzer (Solartron Analytical, Hampshire, UK) in combination with Zplot
Application Software (Solartron Analytical, Hampshire, UK) to determine electrode
impedance. Measurements were taken in phosphate buffered saline with a Calomel
reference electrode and a large stainless steel plate ground electrode. Each electrode was
evaluated a minimum of three times and resultant data was averaged.
4.3.4 Axonal stimulation by electrode prototypes
Experiments were performed on the C57BL/6J (B6) (Jackson Laboratories,
Stock# 000664) mice (n = 3). Both male and female mice were used in experiments, but
their age was limited to a window of 2-4 months. All animals were housed in
microisolator cages maintained in a veterinarian monitored animal care facility. All
animal protocols were reviewed and approved by the Institutional Animal Care and Use
Committee of Case Western Reserve University.
Stimulation of axonal, white matter tracts by electrode prototypes was tested in
vivo by recording orthodromic field potentials with an epoxy-insulated tungsten microelectrode (Cat.No.577400, 12MOhms, A-M Systems, Carlsborg, WA) from the hippocampus of isoflurane anesthetized mice (n = 3). CA1 pyramidal cell population spikes (PSs) were evoked using a cathodic stimulus pulse (100 μsec, 10–350 μA, 0.05–
0.1 Hz) delivered to the ventral hippocampal commissural fibers (orthodromic) by each monopolar prototype. All electrode prototypes (n = 3) evoked a PS ≥1.0 mV to ensure consistent viability between experiments.
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All signals were amplified with a Differential AC Amplifier (Model 1700, A-M
Systems, Carlsborg, WA), and recorded onto a personal computer using a 16-Channel
PowerLab Data Acquisition System (Model ML795, ADInsturments, Colorado Springs,
CO). Stimulation current was applied with a Digital Stimulus Isolator (Model 2300, A-M
Systems, Carlsborg, WA). Off-line data analyses were performed in Chart Software
(V5.5.5, ADInsturments, Colorado Springs, CO).
The brain was removed from mice immediately following in vivo testing. Mice
were decapitated under isoflourane anesthesia. The brain was rapidly removed and
sectioned twice, removing the cerebellum and the olfactory bulb. The brain was then
immediately fixed in 10% formalin and later embedded in agar. Over 50 coronal slices
(100 μm thick) were cut from each animal. Cresyl violet stain was applied to mark Nissel
bodies. Final sections were viewed with a light microscope and captured with digital
imaging software.
4.3.5 Data analysis
Measurements throughout this text are expressed as mean ± standard deviation
(SD) or mean ± standard error of the mean (SEM), with n indicating the number of items
evaluated per test group in each study. Results obtained were evaluated using statistical
analysis methods including analysis of variance (ANOVA) and Student’s t-test, with a
significance level, p < 0.05. Statistical analysis was performed using Minitab 15
(Minitab Inc., State College, PA).
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4.4 RESULTS
4.4.1 Bioelectric field model
To determine the necessary boundary distance required to simulate monopolar
stimulation, the effect on the voltage drop from the current source was evaluated as the
size of the volume conductor was increased, with the model sink located on the outer
boundary of the volume conductor (Figure 4.5). From the mouse brain atlas, a typical
mouse brain volume can be estimated to be about 1,500 mm3 (Paxinos and Franklin,
2001b). To validate the choice of 1,000 mm3 volume for the model, 5, 10, 50, and 150
mm sided cubes were evaluated to determine the effect of changing the sink distance on
the steady-state voltage profile. Figure 4.5 B and C show the voltage profiles along the
y-axis and z-axis respectively. From these values, percent error was calculated to
evaluate the effect of assuming a shorter sink distance than 150 mm in our model (Figure
4.5, C and D). It was determined that reducing our conducting volume from 150 mm to
10 mm would only affect the steady-state voltage profile within 5% error. In addition, previous work has determined a 150 mm x 150 mm x 200 mm saline volume to be a sufficient model for peripheral nerve FINE simulations (Schiefer et al., 2008).
In order to determine the area of activation for a single electrode contact, current injection was applied at either an amplitude of 10µA or 100µA and current density
(A/m2) was evaluated along three axes stemming from the center of the electrode contact
point (0,0,0). A current density of 50 A/m2 was deemed sufficient for axonal activation
as demonstrated by Warman et. al. (Warman et al., 1992). Table 4.1 summarizes the
findings the distance in each direction (X, Y, and Z) at which the limit of activation (50
A/m2) is reached, and provides an estimated percentage of target activation. The 10µA
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current amplitude activated a spherical volume of approximately 0.13 mm radius, while
the larger, 100µA current amplitude activated a spherical volume of approximately 0.39
mm radius. These spherical volumes of activation equated to approximately 25% and
80% of the desired target volume of activation.
To determine the safety of these current injections, charge density (µC/cm2) was calculated for the given electrode geometry and current injections (cathodic, 100µs duration). Safe charge density limits for nervous system tissue have been recommended as low as 150 µC/cm2 (Brummer and Turner, 1977) or as high as 350 µC/cm2 (Rose and
Robblee, 1990). Given that typical platinum electrodes should not be pushed too far past
74 µC/cm2, to avoid irreversible and damaging reactions at the electrode surface, charge
density safety ranges were established as “safe” (<100µC/cm2), “warning” (100-
150µC/cm2), “dangerous” (150-350µC/cm2), or “highly dangerous” (>350µC/cm2). For the original electrode contact design, current injection of 10µA for 100µs results in a
“warning” charge density of 104µC/cm2, while current injection of 100µA for 100µs
results in a “highly dangerous” charge density of 1,039µC/cm2 (Table 4.2). In order to
achieve a large activation area, while maintaining a charge density level in the “safe”
region, electrode contact shape modifications were considered.
Charge density is determined by surface area, and a given increase in surface area
for the same applied current injection will cause a reduction in charge density at the
electrode surface. The simplest way to increase the surface area of the electrode contact
was to strip a greater amount of insulation from the lead wire. To assess the amount of
insulation removal needed, model adjustments were evaluated with insulation stripped
from the end (SE) or from the middle (SM) of the wire. As also shown in Table 4.2, SE
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configurations effectively reduce charge density by an acceptable amount. For a 100µA
current injection, SM is only safe at lengths greater than 0.01cm. This type of
modification would also require capping off the ends of the wire and a significant amount
of added work. For safe, sufficient activation of the target area, a larger electrode contact
is required, and can be achieved by the simple stripping of insulation from our leads at
the electrode contact end. Current density profiles for SE and SM lengths (0.001, 0.0025,
0.005, and 0.01 cm) are shown in Figures 4.6 and 4.7 respectively. These figures reveal the presence of high current density regions, or “hot spots”, along the electrode contact.
These areas could be particularly damaging to the surrounding tissue. To evaluate the severity of these “hot spots”, current density profiles along the electrode edge were plotted (Figure 4.8). Current density was measured along the electrode surface as shown by the black arrow in Figure 4.8B, with (0,0) located a the point where the exposed contact edge meets insulated wire. Further support of SE contact dseign is demonstrated in Figure 4.8A, where the SM current density peaks are considerably larger than the SE contacts of the same length due to the loss of surface area at the end that is now insulated for the SM design. Regardless, both contacts exhibit a dramatic >80% decrease in peak current density as length increase from 0.001 to 0.01cm, as shown in Figure 4.8 C & D.
Additionally, multiple contacts can be utilized to distribute current charge provided an identical current injection is required for sufficient target activation. Figure
4.9 shows three configurations for four electrode contacts in three planes within the target activation volume. Configuration three, where contacts are separated in both the X-Y plane and the Z-Y plane achieves the greatest volume of activation of approximately 77%
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of target area when all four contacts receive a combined current injection of 100µA
(Table 4.3).
4.4.2 Electrode construction and evaluation
Five prototype electrodes were constructed as described in the methods above
(Figure 4.4). Impendence measurements were conducted as also described, and are shown in Figure 4.10. While a significant capacitive component was indicated by increasing resistance with decreasing frequency, 1 KHz resistance measures were reasonable with an average value of 6.63±1.7 KΩ. Electrodes tested in the mouse brain in vivo were able to evoke a hippocampal population spikes ≥0.5mV when a cathodic stimulus pulse (100 μsec, 10–350 μA, 0.05–0.1 Hz) was delivered to the ventral hippocampal commisures (Figure 4.11, A). Figure 4.11 also shows a comparable population spike evoked by the same current injection into the VHC with a tungsten monopolar electrode.
4.5 DISCUSSION
The fundamental goal of this study was to develop and evaluate a novel electrode
design for deep brain stimulation of white matter tracts. Several studies have characterized the effects of DBS electric fields on underlying neural tissue (McIntyre et
al., 2004a; Miocinovic et al., 2006; McIntyre et al., 2007). The only available DBS
electrodes currently approved by the FDA are the Medtronic 3387 and 3389 (Medtronic
Inc., Minneapolis, MN). Both of these models are identical in principle, with one
notable difference in the distance between stimulating contacts (0.5 or 1.5mm). Several
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problems have been reported with this electrode model including lead breakage, and a significant foreign body reaction (FBR) (Oh et al., 2002). In addition, encapsulation, often 500 µm thick, by a FBR limits the volume of tissue activated. As modeled by
Butson and collegues, a cathodic square wave stimulus pulse with a 120µs pulse width and an amplitude of 4V would normally activate an area greater than 150mm3, but when
the electrode is encapsulated by a typical FBR, the same activation area shrinks to less
than 50mm3 (Butson et al., 2006) Furthermore, if we wish to stimulate small fiber tracts
without damaging a significant number of axons forming vital connections within the
CNS, a smaller stimulation electrode is needed. Thus there is a need for the creation of a
DBS electrode that minimizes neuronal damage and implant-induced encapsulation,
while allowing for substantial activation of the target tissue volume. The goal of this
study was to design and evaluate a novel DBS electrode to stimulate small axon-rich
regions of the brain for the treatment of epileptic seizures.
Deep brain electrodes are surrounded by a range of gray and white matter
structures, resulting in an inhomogenous and anisotropic environment that will have an
effect on the shape of the resultant electric field as well as the neural response to
stimulation (McIntyre et al., 2004b; Sotiropoulos and Steinmetz, 2007). A recent
modeling study has shown that the size and shape of the volume of tissue activated by
stimulation applied to the subthalamic nucleus (STN) is reduced by about half when an
isotropic medium is adjusted to account for the anisotropic properties of brain tissue
(Butson et al., 2007). However, our model is limited to a single white matter region, the
ventral hippocampal commissures, and less anisotropic than the STN model. In addition,
DBS electrodes are often surrounded by a high resistance encapsulation sheath that also
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limits the region of activation (Butson et al., 2006). In our case, our electrodes have a
diameter of 0.050 mm, which is significantly smaller than typical DBS electrodes, for
example Medtronic models 3387 and 3389 (Medtronic Inc., Minneapolis, MN) have a
1.27mm diameter (Butson et al., 2006; Rossi et al., 2007), such that one benefit of our
design is to minimize the resultant tissue encapsulation of the electrode contacts.
Therefore, our assumption of isotropic medium is acceptable, with the understanding that
our estimated field of axonal activation is likely to be somewhat smaller than our results
show here.
Our electrode prototype design was determined by the results of our model study.
Evaluation of volume of tissue activated indicates that 100µA is sufficient. This is not
surprising as previous studies have shown a monopolar stimulation (100uA, 200us) has can activate axons within 0.5 to 1.0mm away from an electrode contact (Rattay, 1990).
The main concern with such current amplitudes for stimulation is the resultant charge
injection as determined by the electrode contact surface area. Charge densities need to be
minimized to prevent nervous tissue damage. It is also important to note that the standard
material used for electrical devices implanted into the central nervous system is platinum,
which has a charge density limit of 74µc/cm2. So in addition to overall health, material
property requirements also support that charge density should be minimized, and multiple
electrode contacts is one possible solution. In addition, charge density can be further
minimized by changing the electrode contact shape. By stripping away more insulation,
the electrode contact length can be extended allowing for a greater surface area and thus a
decrease in charge density.
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Electrode prototype construction was modeled after final design template (Figure
4.4). Electrode impedance measurements of 6.63±1.7KΩ at 1KHz are comparable to
Medtronic DBS electrode values of 2-4 KΩ at 1KHz (Butson et al., 2006). Futhermore,
these prototypes were able to evoke population spikes in the hippocampus in vivo, when
a cathodic stimulus pulse (100 μsec, 10–350 μA, 0.05–0.1 Hz) was applied to the ventral hippocampal commisures.
Certainly, the successful design of a multi-pronged electrode will require extensive experimentation and numerous amendments. However, its creation will represent a new step towards more effective treatments for epilepsy. The future of deep brain stimulation promises many new technological advancements that will greatly
enhance patient care. Further design improvements include the development of a more
compact method to connect the electrical circuits of the four electrodes so that the
diameter of the creation allows for its insertion through a cannula. Such improvements
would make possible the eventual chronic implantation of multi-pronged electrodes in the
human brain.
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Current Injection (µA) Measure +X +Y -Z Distance Activated (mm) 0.130 0.130 0.135 10 % Activated (of 0.5mm) 26 26 27 Distance Activated (mm) 0.385 0.385 0.405 100 % Activated (of 0.5mm) 77 77 81
Table 4.1— Effect of current injection on activation of target area: Current injection of
10µA or 100µA activates approximately 25 to 80 percent respectively, of target area
(1mm3) respectively, when mapped in +X, +Y, and -Z directions from the center of the electrode contact surface (0, 0, 0).
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Geometry Length Contact Area 10 uA, 100 uA, Change (cm) (cm^2) 100us 100us S.End (no change) 0.0000 9.6211E-06 104 1039 S.End 0.0025 3.7110E-05 27 269 S.End 0.0050 6.4599E-05 15 155 S.End 0.0100 1.1958E-04 8 84 S.Middle 0.0025 2.7489E-05 36 364 S.Middle 0.0050 5.4978E-05 18 182 S.Middle 0.0100 1.0996E-04 9 91
Table 4.2— Effect of electrode geometry on current density: levels of resultant charge
injections (µC/cm2) are colored coded as follows: green = safe (<100µC/cm2), yellow = warning (100-150µC/cm2), orange = dangerous (150-350µC/cm2), red = highly dangerous (>350µC/cm2).
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Estimated Configuration % Activation 1 26.4 2 62.6 3 77.1
Table 4.3—Effect of configuration on activation of target area: Estimated percent of activation is given for each configuration (Figure 4.8).
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Resistance ±STD Frequency (KOhm) (KOhm) 10 KHz 2.07 0.7 1 KHz 6.63 1.7 100 Hz 29.04 6.6 10 Hz 130.89 28.4 1 Hz 275.59 66.1
Table 4.4—Electrode prototype impedance measurements: Electrodes demonstrated acceptable (6.63±1.7 KΩ) impedance measurements at 1 KHz (n=5).
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DBS Target
xx
Figure 4.1—Deep Brain Stimulation (DBS) target: Electrode design was intended for axon-rich stimulation of the ventral hippocampal commissural fibers and corpus callosum (red box) (modified from (Paxinos and Franklin, 2001b)).
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Figure 4.2—Medtronic DBS electrodes: Models 3387 and 3389 (Medtronic, 2006).
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A
a ≈ 50 µm b = 17.5 µm c = 8.5 µm
B C
Figure 4.3—Bioelectric field model design: Electrode design including: A) double polyhedron model of insulated wire end, B) injected current (10µA, 100µA, or 400µA) out of electrode wire, and C) current sink/ground set to external surface of saline cube volume conductor, or “mouse head”. Key dimensions of electrode contact surface are given as a) total electrode diameter ≈ 50 µm, b) conducting wire radius = 17.5 µm, and c) polyimide insulating layer radius = 8.5 µm.
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A
B C
Figure 4.4—Electrode prototype fabrication: A) multi-pronged stimulating electrode construction design. Four pieces of tungsten wire (California Fine Wire Company
99.95% Tungsten CS HML 0.002” size) approximately 4 cm in length were joined with cyanoacrylate apart from 0.1cm stimulating tips. The opposite end was spot welded between two 2 mm x 2 mm squares of stainless steel and enclosed in a gold clip (Plastics
One E3630 Electrical Socket Contact, 0.8cm). An external 0.7cm length of heat shrink wrap (1/16 x 0.5” Heat Shrink FP116K-R50-ND) was applied for stability. B) electrode prototypes, C) separation of electrode tips during insertion of prototype into agarose gel from a stereotaxically immobilized syringe cannula (scale is 400µm).
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A
Voltage Drop in Y+ Direction Voltage Drop in -Z Direction B 0.7 C 0.7
0.6 0.6
0.5 0.5
0.4 (5mm)^3 0.4 (5mm)^3 (10mm)^3 (10mm)^3 (50mm)^3 (50mm)^3 0.3 0.3
Voltage [V] Voltage (150mm)^3 [V] Voltage (150mm)^3
0.2 0.2
0.1 0.1
0 0
0 0 03 .04 07 09 0.1 12 15 03 .04 07 09 0.1 12 15 0.01 0.02 0. 0 0.05 0.06 0. 0.08 0. 0.11 0. 0.13 0.14 0. 0.01 0.02 0. 0 0.05 0.06 0. 0.08 0. 0.11 0. 0.13 0.14 0. Distance [mm] Distance [mm] Voltage Drop (Y) Dependance on Sink Distance Voltage Drop (Z) Dependance on Sink Distance 100 100 90 D E 90 80 80
70 70
60 60 5 vs 150 50 10 vs 150 5 vs 150 50 10 vs 150 % Error 50 vs 150
% Error 50 vs 150 40 40
30 30
20 20
10 10
0 0 0 2 6 1 4 8 6 3 4 2 6 5 0 . 1 1 . 3 . 0 2 4 6 2 4 6 8 2 8 .3 2 4 6 8 4 2 4 6 8 . 0 . . 0.2 0 .32 . 0.4 .48 0 0.1 .1 .1 .1 0.2 .2 0 .3 0. 4 .4 0.5 0 0.04 0.0 0.08 0.12 0 0.16 0 0.22 0.24 0.2 0.28 0 0 0.36 0.38 0.4 0.44 0.4 0 0.0 0.0 0.0 0.08 0 0 0 0.1 0.2 0.24 0.26 0 0 0.3 0.3 0.3 0. 0.4 0.4 0 Distance [mm] Distance [mm]
Figure 4.5—Model validation: A) Steady-state voltage profile following 100uA current
injection. Voltage profile was determined while varying the sink distance: 5mm, 10mm,
50mm, and 150mm from the center of the electrode contact positioned at (0, 0, 0). The
effect of changing sink distance on voltage drop is plotted in either B) positive y-axis
direction, or C) negative z-axis direction. Percent error was calculated when compared
with 150 mm sink distance in the same planes, D) y-axis, and E) z-axis.
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0.001 cm 0.0025 cm
A B
0.005 cm 0.01 cm
C D
Figure 4.6—Stripped end (SE) current density profiles: Current density profiles are shown for increasing lengths of stripped wire: A) 0.001 cm, B) 0.0025 cm, C)0.005 cm, and D) 0.01 cm (scale from dark blue to red, is 1,000 - 100,000 A/m2 respectively).
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0.001 cm 0.0025 cm
A B
0.005 cm 0.01 cm
C D
Figure 4.7— Stripped middle (SM) current density profiles: Current density profiles are shown for increasing lengths of stripped wire: A) 0.001 cm, B) 0.0025 cm, C)0.005 cm, and D) 0.01 cm (scale from dark blue to red, is 1,000 - 100,000 A/m2 respectively).
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A
B
C D
Figure 4.8—Current density along electrode edge: Current density profiles are shown along the edge of the striped electrode contact (as shown in B, inset): A) both SM (A-D, increasing lengths) and SE (A-D, increasing lengths), C) SE only, and D) SM only.
Current density peaks decrease with increasing electrode length for both SM and SE, although overall SM profiles are considerably larger than SE profiles for same electrode lengths.
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A B C
1
2
3
Figure 4.9—Electrode contact configurations: Current density profiles for there
different configurations (1-3) are shown in rows of images above. Three different planes
are show for each configuration in columns: A) Z-X plane, B) Z-Y plane, and C) X-Y
plane. As noted in the following scale, activation threshold of 50 A/m2 is green (scale
evenly spaced from blue to green to red, is 0 A/m2 to 50 A/m2 to 100 A/m2 respectively).
Target activation volume is indicated by square.
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Electrode Impedance
400.00 350.00 300.00 250.00
200.00 150.00 100.00
Resistance (KOhm) Resistance 50.00 0.00 1Hz 10Hz 100Hz 1kHz 10kHz
Log Frequency (Hz)
Figure 4.10—Electrode prototype impedance: Electrode impedance measurements
(n=5) demonstrate decreasing resistance with increasing frequency. 1kHz frequency sweeps resulted in an average resistance of 6+.63±1.7KΩ.
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A Prototype
1mV, 10ms B Control
0.5mV, 5ms
Figure 4.11—Evoked population spike: Electrode prototypes successfully evoked hippocampal population spikes in vivo (A), comparable to control tungsten electrodes
(B).
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Chapter 5: Conclusions and Future Directions
5.1 FULFILLMENT OF THESIS OBJECTIVES
The work presented in this thesis is a multidisciplinary study on the analysis and control of seizure activity utilizing a recently developed murine model of epilepsy. The objectives of this research were: (i.) to characterize in vitro epileptiform activity in Q54 mice, (ii.) to characterize and evaluate the efficacy of low frequency deep brain stimulation as a seizure therapy in Q54 mice, and (iii.) to design and evaluate a novel deep brain stimulation electrode for axon-rich areas of the central nervous system.
Several studies were conducted to investigate these objectives. Details of each study, as well as their results and conclusions are summarized within their respective objective in the following text. Future directions of this work are also identified.
------5.1.1 Objective I: To characterize in vitro epileptiform activity in Q54 mice. ------
Cellular network activity of the hippocampus in Q54 mice displaying spontaneous seizures due to a gain-of-function mutation of the Scn2a sodium channel gene was investigated in vitro. Extacellular recordings were obtained from CA1 and CA3 pyramidal neurons in hippocampal slices prepared from Q54 transgenic and nontransgenic littermates (WT) under physiologic conditions as well as during periods of orthodromic stimulation of the Schaffer collaterals. Cerebral spinal fluid samples were analyzed and cresyl violet histology of the hippocampus was conducted. Increased spontaneous extracellular activity was found in both CA1 and CA3 regions of Q54
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hippocampal slices. Q54 slices also demonstrated significantly greater spontaneous and afterdischarge activity as well as population spike amplitude and duration following tetanic stimulus in comparison to WT slices. Frequency analysis of tetanically stimulated recordings indicated high-frequency components (100 and 200 Hz) unique to Q45 slices.
Analysis of cresyl violet histology supports healthy Q54 slices up to 10 weeks, while Q54 cerebral spinal fluid shows elevated osmolarity. Evidence for hyperexcitability and increased synaptic efficacy in Q54 mice was found by observing spontaneous activity as well as evoked activity. Response to tetanic stimulation included unique high-frequency oscillations, and resulted in an increased population spike amplitude and duration.
Histological assessment shows equivalent neuronal development in both experimental groups. The data support the hypothesis that modified Scn2a channels in Q54 mice result in network hyperexcitability of the hippocampus necessary for the development and maintenance of temporal lobe seizures.
------5.1.2 Objective II: To characterize and evaluate the efficacy of low frequency deep brain stimulation as a seizure therapy in Q54 mice. ------
In this objective, chronic recordings from Q54 mice that display spontaneous seizures because of a gain-of-function mutation of the Scn2a sodium channel gene were investigated, and the efficacy of low frequency deep brain stimulation (DBS) for seizure control was evaluated. EEG, EMG, and hippocampal deep electrodes were implanted into Q54 mice expressing an epileptic phenotype (n = 6). Chronic six channel recordings
(wideband, 2KHz sampling rate) were stored 24 hours a day for more than 12 days. LFS
(3Hz, square wave, biphasic, 100µs, 400µA) was applied to ventral hippocampal commissural fibers (VHC) in alternating five minute cycles (on or off) 24 hours a day for
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a period of four days. Frequency analysis of spontaneous seizures indicated a significant and unique increase in signal power recorded from hippocampal deep electrodes over all frequency bands. LFS (3Hz) resulted in a significant reduction in seizure frequency
(p<0.05) when applied to the VHC of epileptic Q54 mice (n = 6), but seizure frequency was not directly affected by stimulation state (on or off). Analysis of seizure activity in
Q54 mice reveals a robust and well maintained seizure frequency over several days with seizures that are characterized by increased power in all frequency bands. LFS at a frequency of 3Hz significantly reduces seizure frequency in the Q54 model.
Furthermore, the presence of LFS does not seem to have a direct and immediate effect on seizure frequency, supporting that mechanisms of action are more complex, such as long term depression.
------5.1.3 Objective III: To design and evaluate a novel deep brain stimulation electrode for axon-rich areas of the central nervous system. ------
An electrode for deep brain stimulation of axonal-rich areas of the central nervous system in the treatment of neurological disorders was designed and evaluated. A finite element model was constructed using Maxwell 3-D Software (Ansoft, LLC., Pittsburg,
PA), and contact size and shape was evaluated to determine the most effective size that would allow maximal activation while minimizing current density related damage to surrounding tissue. Electrode diameter was reduced to less than 50 µm by the use of fine wires, rather than several large contacts on a single large diameter electrode shaft. In addition, several prototypes were evaluated and tested in vivo. Four thin wire electrode contacts were found to be sufficient for the activation of a 1mm3 target area. Electrode
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contacts were improved by increasing length, and locating contacts away from the end of
the electrode. Multi-pronged, flexible contacts allowed sufficient dispersion of contacts,
yet separation distance was unpredictable. Electrode prototypes (n=5) demonstrated
acceptable impedance measurements (6.63±1.7 KΩ @ 1 KHz) and were able to evoke
hippocapmal population spikes (>0.5 mV) in vivo via stimulation (100 µs, 400 µA, cathodic square wave) delivered to the VHC.
5.2 FUTURE DIRECTIONS
The work presented in this thesis contributes to a greater understanding of
epilepsy animal models, the characteristics and mechanisms of epileptiform activity in
vitro and in vivo, as well as the effectiveness of low frequency DBS therapy for seizure
suppression.
The work presented in chapter two describes the network activity of Q54 model
of epilepsy in the hippocampal slice preparation. Future studies are needed to understand additional brain regions involved in the development of seizures in the Q54 model and the order of their involvement as seizures progress from focal to generalized.
Identification of the sequence of pathways within the brain that are involved in the
development and maintenance of seizures would greatly enhance our understanding the
progression of epilepsy disorders and give insight into potential new therapeutic
strategies.
The work presented in chapter three evaluates seizure suppression by LFS applied
to the VHC in the Q54 model of epilepsy. Although promising, stimulus induced
reduction in seizure frequency needs to be substantial to compensate for the invasive
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nature of the implanted therapeutic device. Further work is required to establish ideal parameters for stimulation that will maximize seizure reduction, including stimulus pulse waveform as well as stimulation cycling times. While the Q54 mouse line exhibited robust seizures, it would be interesting to evaluate LFS of VHC in a model of epilepsy that has been utilized for other LFS studies. This would allow for a more direct comparison of alternate stimulation protocols.
In terms of stimulation protocol, the number of days examined for baseline, stimulation, and recovery could be expanded. An extension of the stimulation duration would be useful for determining the maximal affect of VHC LFS on seizure reduction.
Seizure frequency was continuing to decrease each day in some animals and may have decreased even further given more time. Recovery did not return to baseline values in most mice, suggesting a lasting effect. It would be helpful to determine the length of this effect, and this could easily be done by collecting data over additional days during the recovery period. Baseline data should also be collected for the entire protocol duration in several animals to serve as control and evaluate the seizure frequency in animals that do not receive stimulation. Finally, human or primate studies would be helpful to evaluate the effectiveness of ventral hippocampal commissural stimulation given the slight differences from murine neurophysiology.
Work presented in chapter two also demonstrated an increase in high frequency oscillations associated with seizure activity. Recent work by Bragin et. al. suggests that seizures in TLE are marked by the presence of interictal “fast ripples”, high frequency oscillations (~360Hz, 25ms duration) that are found within the hippocampus and ipsilateral to seizure foci (Bragin et al., 1999). Effect of LFS on “fast ripples” could be
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evaluated to build on our understanding of the mechanisms of DBS on neuronal network
activity.
The work presented in chapter four describes a novel electrode design for DBS therapy applied to white matter tracts in the brain. The fine-wire electrode design investigated presents a promising alternative to the current FDA approved designs, especially for the stimulation of small, white matter tracts. However, to compensate for brain plasticity, insertion of fine wires for stimulation of a large area of white matter tracts may be improved by the addition of a thin, tissue anchor which allows flexibility of wires, but prevents them from being “pushed out” of the brain by typical foreign body reaction mechanisms. Also, a removable cannula for insertion would be beneficial for providing a stiff guide over long distances given the inclination of flexible fine wires to be misdirected from their targets. Both of these improvements would allow for both initial and long term stability of implantation for accurate activation of small areas deep within the brain.
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