The entorhinal cortex (EC) is a vital structure in the mammalian brain, implicated in the processes of learning and memory, and a possible site for the generation of seizures in temporal lobe epilepsy. Neurones in the EC are constantly bombarded with inhibitory and excitatory neurotransmitter. This background activity is thought to exert significant control on the excitability and function of neurones in cortical networks, with changes in the levels and proportion of background inhibition (IBg) and excitation (EBg) driving rhythmic oscillations in membrane potential, and even underlying the generation of epileptic seizures.

In the early hours of the morning several years ago I awoke with paramedics leaning over me. In a state of confusion, my first conscious decision was to enter my music production studio while they attempted to lead me to the ambulance. Music was important to me even in a disorientated post-ictal state (an altered state of consciousness following a seizure). Two weeks later I awoke with paramedics standing over me again. I had started to experience multiple seizures. During the previous weeks, I also experienced numerous incidents of memory loss when delivering presentations at work, feelings of being returned to the room following an absence of consciousness and suffering from temporal disorientation. I also experienced multiple episodes of déjà vu, aromas that were difficult to identify, visual distortions and waves of euphoria like momentary intoxication of an unknown origin. These experiences began to increase in frequency until my first tonic-clinic seizure. Following medical tests, I was diagnosed with epilepsy. It was a confusing period with no history of epilepsy in my family and no physiological causes could be identified. I viewed epilepsy as an overwhelming authority, it takes control of your life and asserts its power upon you, forcibly changing your reality in an instant. When I saw the EEG readouts from my tests I noticed how similar they were to sound waves. As an electronic musician, this project is being used as an artistic and cathartic opportunity to creatively transform the power of epilepsy and reassert my personal identity upon it. Symbolically reclaiming personal control and creatively transforming the psychological perception of personal power that is lost through the experience of epilepsy. Transforming it from an internal destructive force into an external and creative activity in my life. Capturing the cultural and emotional experiences of epilepsy and transforming them into cinematic electronic soundscapes using research and musical experimentation with EEG epilepsy signals. It is an existential exploration, the results will be tangible, accessible and reasonable in the transformation of the EEG epilepsy recordings from the uncontrollable unconscious into the creative conscious. This project will apply transposition, mathematics, research and creative exploration to map epilepsy EEG events into computer synthesized soundscapes, transforming the passive nature of diagnoses and treatment into a proactive and creative process. This thesis shares an individual's research and experiences of epilepsy with a community that have an interest in transforming the passive sufferer into a creatively active and articulate patient. Professor Dan Lloyd (Thomas C. Brownell) Professor of Philosophy at Trinity College states that: “It is observed that fMRI (Brain) activity is more similar to music than it is to language ... ” Lloyd D. (2011). If, as Lloyd suggests, brain activity is more like music than language then what might epilepsy be saying or possibly singing during these events? What are the audible timbres of these events? Researchers such as Wu et al, Psyche et al, Chafe and Parvizi have previously interpreted EEG data of epilepsy EEG events to aid medical research, but it is not exploring the emotional timbre of epilepsy from a patient’s perspective. The previous research derived musical notes from EEG signals to trigger MIDI instruments and modulate non-epilepsy related audio sources for medical identification purposes. This project examines the possible timbres derived directly from the EEG data to explore and creatively describe the emotional and physical experience from a patient’s perspective. This thesis presents the personal experience of epilepsy, the development of electroencephalography (EEG), the sociocultural history of epilepsy. the sonification and musification of EEG data, plus the concepts involved in the design of timbre and sound effect. For this project, a bespoke granular synthesizer called ‘The Oblique-Granizer’ (programmed with Cycling74's MAXMSP) has been constructed that employs EEG signals, converted to digital audio, to synthesize timbres that explore the description of human experience and emotions related to epilepsy. This thesis includes research that has been carried out into mathematical algorithms to generate musical notes and melodic information in electronic music compositions using EEG epilepsy seizure activity. The aim is to take back personal control by creatively transforming the EEG data and my psychological perception of epilepsy into electronic soundscapes and sonic textures through exploration of sonification and musification techniques.

Neurodevelopmental disorders (ND) present a significant burden on society as over 5% of the US population is diagnosed with a ND. While environmental and biological factors have been associated with some cases of NDs, many still have unknown etiology. Strong comorbidities of NDs have been shown suggesting common biological processes of disease development. Sequencing technologies have allowed for the unprecedented identification of new candidate genes associated with NDs and many genes have been linked to multiple NDs. Developing robust methods to functionally validate these candidates is a critical next step for aiding patients with NDs. Using the zebrafish (Danio rerio), we characterized the developmental requirement of epilepsy candidate genes in the context of gene knockdown (KD). We demonstrated three different larval responses to pentylenetetrazol (PTZ) (hyperactive, hypoactive, or the same as control). We characterized the two genes resulting in a hyperactive response, Zinc Finger Homeobox 3 (ZFHX3) and Spectrin Repeat Domain Containing Nuclear Envelope Protein 1 (SYNE1), in greater detail. ZFHX3 is expressed in distinct brain regions during development and shows strong expression along nerve fiber tracts. SYNE1 shows broad expression during development that is enriched in the brain. Using CRISPR/Cas9 we generated a predicted null SYNE1 allele and recapitulated the seizure sensitivity phenotype in mutant larvae. Using a 60-hour behavioral assay we also demonstrate a generalized daytime hyperactivity in SYNE1 mutants. Our studies confirm ZFHX3 and SYNE1 as strong candidates for further study in epilepsy and suggest a role for SYNE1 in multiple NDs such as autism and attention-deficit/hyperactivity disorder.

Repeated focal electrical stimulation of the brain results in kindling, the development of generalized seizures that progress in length and severity as more seizures are elicited. Barnes et al. (2001) paired one context (CS+) with kindling stimulation of the amygdala, and another context (CS-) with sham stimulation. They found conditioned anticipatory fear responses in the CS+, a conditioned place aversion to the CS+, and more intense convulsions in the CS+ than in the CS- in a probe trial. The present experiment was an attempt to replicate the findings, and to extend them by recording electroencephalographs (EEG). As well, I tested for conditioned effects on afterdischarge threshold (ADT). Rats received 45 pairings in each context before a conditioned place preference/aversion test, to determine whether the stimulation and seizures were rewarding or punishing. After more pairings, rats received suprathreshold stimulation in each context (switch test). Ictal measures in this test included afterdischarge duration, clonus duration, latency to clonus, class of convulsion, and falls. After more pairings, ADT was measured in each context. I partially replicated the findings of Barnes et al., in that conditioned anticipatory responses and conditioned place aversion were found. However, there were no conditioned effects on any ictal measures, including ADT. I conclude that conditioning is unlikely to play a major role in epileptogenesis.

Epilepsy is a nervous system disorder which affects approximately 1% of the world's population. Nearly 25% of people who have epilepsy are resistant to traditional treatments such as medication and are not candidates for surgery [32]. A new form of treatment has emerged that attempts to disrupt epileptic activity in the brain by electrically stimulating neural tissue. However, the nature of this treatment requires that it is able to accurately predict the onset of a seizure in order to time the intervention correctly. Recent studies suggest that EEG recordings may be generated by a low dimensional nonlinear process [35] [36] [6]. This paper will investigate nonlinearity tests, as well as the use of methods from the theory of nonlinear dynamical systems in the prediction of seizures or seizure like events (SLEs) from complex time series. To do this data is generated from a nonlinear dynamical system with a stochastic time dependent parameter, which attempts to emulate the different states of an epileptic brain. Two kinds of nonlinearity tests were used in simulations, one which specifies a model in the alternative hypothesis (Keenans test) and one which simply states that the process is `not linear' (Surrogate data test). The tests were applied to the generated data, as well as a short EEG recording from a person with epilepsy and a simple nonstationary example. Both tests were able to correctly identify the model as nonlinear, neither test identified the EEG data as nonlinear and there were contradicting results when the tests were applied to nonstationary data. Estimates of the correlation dimension and Lyapunov exponent were then used to classify the preictal state of the model data. Correlation dimensions showed the best ability to classify states, so they were used in the prediction algorithm. The results of the simulation was that the correlation dimension was able to successfully predict half of the SLEs, however there was an alarmingly high false prediction rate. These results suggest that even though a complicated model may fit the data better, when dealing with prediction it is usually best to use a simple model. A simpler approach with better understood statistical properties may be able to improve on the prediction of SLEs as well as reduce the computational cost of performing them.

Epilepsy is a nervous system disorder which affects approximately 1% of the world's population. Nearly 25% of people who have epilepsy are resistant to traditional treatments such as medication and are not candidates for surgery [32]. A new form of treatment has emerged that attempts to disrupt epileptic activity in the brain by electrically stimulating neural tissue. However, the nature of this treatment requires that it is able to accurately predict the onset of a seizure in order to time the intervention correctly. Recent studies suggest that EEG recordings may be generated by a low dimensional nonlinear process [35] [36] [6]. This paper will investigate nonlinearity tests, as well as the use of methods from the theory of nonlinear dynamical systems in the prediction of seizures or seizure like events (SLEs) from complex time series. To do this data is generated from a nonlinear dynamical system with a stochastic time dependent parameter, which attempts to emulate the different states of an epileptic brain. Two kinds of nonlinearity tests were used in simulations, one which specifies a model in the alternative hypothesis (Keenans test) and one which simply states that the process is `not linear' (Surrogate data test). The tests were applied to the generated data, as well as a short EEG recording from a person with epilepsy and a simple nonstationary example. Both tests were able to correctly identify the model as nonlinear, neither test identified the EEG data as nonlinear and there were contradicting results when the tests were applied to nonstationary data. Estimates of the correlation dimension and Lyapunov exponent were then used to classify the preictal state of the model data. Correlation dimensions showed the best ability to classify states, so they were used in the prediction algorithm. The results of the simulation was that the correlation dimension was able to successfully predict half of the SLEs, however there was an alarmingly high false prediction rate. These results suggest that even though a complicated model may fit the data better, when dealing with prediction it is usually best to use a simple model. A simpler approach with better understood statistical properties may be able to improve on the prediction of SLEs as well as reduce the computational cost of performing them.

Repeated focal electrical stimulation of the brain results in kindling, the development of generalized seizures that progress in length and severity as more seizures are elicited. Barnes et al. (2001) paired one context (CS+) with kindling stimulation of the amygdala, and another context (CS-) with sham stimulation. They found conditioned anticipatory fear responses in the CS+, a conditioned place aversion to the CS+, and more intense convulsions in the CS+ than in the CS- in a probe trial. The present experiment was an attempt to replicate the findings, and to extend them by recording electroencephalographs (EEG). As well, I tested for conditioned effects on afterdischarge threshold (ADT). Rats received 45 pairings in each context before a conditioned place preference/aversion test, to determine whether the stimulation and seizures were rewarding or punishing. After more pairings, rats received suprathreshold stimulation in each context (switch test). Ictal measures in this test included afterdischarge duration, clonus duration, latency to clonus, class of convulsion, and falls. After more pairings, ADT was measured in each context. I partially replicated the findings of Barnes et al., in that conditioned anticipatory responses and conditioned place aversion were found. However, there were no conditioned effects on any ictal measures, including ADT. I conclude that conditioning is unlikely to play a major role in epileptogenesis.

The way that emotions are processed in the brain has been widely debated. The two leading hypotheses are the cognitive appraisal viewpoint (Lazarus, 1982) and the affective primacy hypothesis (Zajonc, 1980). The former argues that higher cortical structures are needed to evaluate affective stimuli whereas the latter asserts that humans can use information only processed at the subcortical level to influence behavior. The current study tested the presence of this subcortical pathway by using an affective priming task developed by Murphy and Zajonc (1993). Happy and angry faces were presented for 4 ms before the presentation of a neutral stimulus (Chinese Ideograph) that participants were asked to rate based on how much they liked each one. Individuals do not report conscious awareness of primes presented at this suboptimal speed. In a young adult sample, participants rated ideographs preceded by happy primes significantly higher than those preceded by angry primes. Also, the priming effect was only observed in participants who reported a high positive mood. Next, when primes were presented in the left or right hemifield priming was only found in the right hemifield, and was driven by increased ratings for ideographs preceded by happy primes. Patients with epilepsy who have undergone a temporal lobectomy provide a unique opportunity to study emotional processing. In this procedure, not only is the seizure focus (typically the hippocampus) removed, but the amygdala and surrounding areas of the mesial temporal lobe are removed as well. Nine patients post right temporal lobectomy and three patients post left temporal lobectomy completed the study and did not show an effect of priming. However, 21 pre-surgical epilepsy patients were found to give higher liking ratings to ideographs preceded by angry primes as compared to those preceded by happy primes. Overall, these results support the affective primacy hypothesis however they also suggest that patients with temporal lobe dysfunction may process emotional stimuli differentially from controls. In this population, ideographs preceded by angry primes were rated as more liked than those preceded by happy primes. Directions for future studies to clarify the role of the amygdala in emotional processing are discussed. / text

The purpose of this study was to identify clinical and demographic predictors of seizure recurrence in medically-treated patients with epilepsy. Innovus Invision™ Data Mart insurance claims from January 1, 2007 to September 30, 2010 were retrospectively analyzed. Patients aged 18-64 years with a primary or secondary diagnosis of epilepsy and >1 prescription claim for an antiepileptic drug (AED) pre-index were included. The primary outcome was incidence of seizures defined as an occurrence of an emergency room visit, ambulance service use or hospitalization with a primary or secondary diagnosis of epilepsy during the 1-year follow-up period. Predictor variables included antiepileptic drug (AED) adherence (Proportion of Days Covered ≥ 80 %), general comorbidity (Charlson’s Comorbidity Index ≥ 1), any mental health comorbidity, evidence of a prior seizure, type of epilepsy diagnosis (intractable versus non-intractable), presence of AED-interacting medications and any bioequivalent AED switch. The covariates included age, gender and geographic region of residence. The overall incidence of post-index seizures in the 1-year follow-up period for all four monotherapy cohorts combined was 5.3 % (n=166/3140), but was higher for the Keppra®/levetiracetam cohort (7.9%; n=88/1114) compared to the other cohorts [Lamictal®/lamotrigine (3.9%; n=45/1143), Trileptal®/oxcarbazepine (4.0%; n=18/456) and Topamax®/topiramate (3.5%; n=15/427)]. The combined cohort analysis demonstrated that pre-index seizures (odds ratio [OR] = 4.28; 95% CI, 2.81-6.53), any mental health comorbidity ([OR] = 3.41; 95% CI, 2.10-5.54), Charlson comorbidity Index ≥1 ([OR] = 2.88; 95% CI, 1.96-4.24) and monotherapy with Keppra®/levetiracetam ([OR] = 1.54; 95% CI, 1.03-2.31) were significant predictors of seizure recurrence. Among covariates, only geographic region was a significant predictor, with patients residing in the Northeast U.S. having higher odds of post-index seizure ([OR] = 1.92; 95% CI, 1.19-3.10), while controlling for clinical, medication and demographic characteristics. A bioequivalent AED switch, type of epilepsy diagnosis, AED adherence and the presence of interacting medications were not significant predictors of seizure recurrence in the combined cohort (p>0.05). Results indicate that epilepsy patients with comorbid conditions (both mental and somatic diseases), as well as patients who may have initially been unstable (with previous seizure occurrences) were more likely to experience seizures during the follow-up period. / text

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