Detecting and characterizing high-frequency oscillations in epilepsy: a case study of big data analysis

abstract: We develop a framework to uncover and analyse dynamical anomalies from massive, nonlinear and non-stationary time series data. The framework consists of three steps: preprocessing of massive datasets to eliminate erroneous data segments, application of the empirical mode decomposition and Hilbert transform paradigm to obtain the fundamental components embedded in the time series at distinct time scales, and statistical/scaling analysis of the components. As a case study, we apply our framework to detecting and characterizing high-frequency oscillations (HFOs) from a big database of rat electroencephalogram recordings. We find a striking phenomenon: HFOs exhibit on–off intermittency that can be quantified by algebraic scaling laws. Our framework can be generalized to big data-related problems in other fields such as large-scale sensor data and seismic data analysis.The final version of this article, as published in Royal Society Open Science, can be viewed online at: http://rsos.royalsocietypublishing.org/content/4/1/16074

Development and application of inhibitory luminopsins for the treatment of epilepsy

Optogenetics has shown great promise as a direct neuromodulatory tool for halting seizure activity in various animal models of epilepsy. However, light delivery into the brain is still a major practical challenge that needs to be addressed before future clinical translation is feasible. Not only does light delivery into the brain require surgically implanted hardware that can be both invasive and restrictive, but it is also difficult to illuminate large or complicated structures in the brain due to light scatter and attenuation. We have bypassed the challenges of external light delivery by directly coupling a bioluminescent light source (a genetically encoded Renilla luciferase) to an inhibitory opsin (Natronomonas halorhodopsin) as a single fusion protein, which we term an inhibitory luminopsin (iLMO). iLMOs were developed and characterized in vitro and in vivo using intracellular recordings, multielectrode arrays, and behavioral testing. iLMO2 was shown to generate hyperpolarizing outward currents in response to both external light and luciferase substrate, which was sufficient to suppress action potential firing and synchronous bursting activity in vitro. iLMO2 was further shown to suppress single-unit firing rate and local field potentials in the hippocampus of anesthetized and awake animals. Finally, expression of iLMO was scaled up to multiple structures of the basal ganglia to modulate rotational behavior of freely moving animals in a hardware-independent fashion. iLMO2 was further utilized to acutely suppress focal epileptic discharges induced by intracerebral injection of bicuculline and generalized seizures resulting from systemic administration of pentylenetetrazol. Inhibitory luminopsins have enabled the possibility of optogenetic inhibition of neural activity in a non-invasive and hardware-independent fashion. This work increases the versatility, scalability, and practicality of utilizing optogenetic approaches for halting seizure activity in vivo.Ph.D

Analysis of seizure EEG in kindled epileptic rats

Using wavelet analysis we have detected the presence of chirps in seizure EEG signals recorded from kindled epileptic rats. Seizures were induced by electrical stimulation of the amygdala and the EEG signals recorded from the amygdala were analyzed using a continuous wavelet transform. A time -frequency representation of the wavelet power spectrum revealed that during seizure the EEG signal is characterized by a chirp-like waveform whose frequency changes with time from the onset of seizure to its completion. Similar chirp-like timefrequency profiles have been observed in newborn and adult patients undergoing epileptic seizures. The global wavelet spectrum depicting the variation of power with frequency showed two dominant frequencies with the largest amounts of power during seizure. Our results indicate that a kindling paradigm in rats can be used as an animal model of human temporal lobe epilepsy to detect seizures by identifying chirp-like time -frequency variations in the EEG signal

Doctor of Philosophy

dissertationIn the past few decades, a revolution in our understanding of brain function has occurred based on demonstrations that astrocytes play critical roles in synaptic physiology. These findings led to the concept of the "tripartite synapse," which redefines the synapse to be comprised of not only the pre- and postsynaptic neuronal elements, but also the astrocyte processes that interact with them. Likewise, temporal lobe epilepsy (TLE) is a seizure disorder that affects the structure and function of networks of both neurons and astrocytes. One of the hallmark findings in TLE is the profound change in astrocyte structure and gene expression, a process called astrogliosis, throughout the brain regions involved in seizure generation. Using a well-established rat model of TLE, our lab recently demonstrated that astrocytes begin to express kainate receptor subunits during the development of TLE, and this increased expression persists throughout chronic epilepsy, suggesting that this pathway may play a role in the development of hyperexcitable circuits. However, the functional consequences of changes in reactive astrocytes and their impact on tripartite synapse function are not known. To facilitate imaging experiments at the tripartite synapse, I developed a novel genetic tool that uses a fluorescent reporter system to label astrocytes with tdTomato and neurons with Cerulean. This plasmid also includes the genetically encoded calcium-indicating protein, Lck-GCaMP6f, enabling the monitoring of calcium transients in the fine processes of all transfected cells. I expressed this novel tool in the rat brain with in utero electroporation and characterized expression throughout development using immunohistochemistry for markers of astrocytes and neurons. I demonstrated the utility of this tool to investigate functional subcellular Ca2+ signals in both astrocytes and neurons. This tool was used in experiments that showed that Ca2+ signaling is altered during the development of temporal lobe epilepsy in the rat kainic acid-induced model of status epilepticus. Spontaneous Ca2+ events in the processes of reactive astrocytes exhibited longer interevent intervals and longer duration of events compared to astrocytes from healthy tissue. I also found that increased protein expression of kainate receptors translated to functional expression of kainate receptors on a subset of reactive astrocytes following kainic acid-induced SE, suggesting a pathway that may be involved in pathological neuron-glial signaling contributing to the development of epilepsy. Taken together, these results indicate that alterations in Ca2+ signaling in astrocytes during the development of TLE may have important consequences on function at the tripartite synapse. This dissertation lays the groundwork for future studies in the tripartite synapse and points to a novel pathway that may be involved in pathological neuron-astrocyte signaling that contributes to hyperexcitability during epileptogenesis

Seizure prediction : ready for a new era

Acknowledgements: The authors acknowledge colleagues in the international seizure prediction group for valuable discussions. L.K. acknowledges funding support from the National Health and Medical Research Council (APP1130468) and the James S. McDonnell Foundation (220020419) and acknowledges the contribution of Dean R. Freestone at the University of Melbourne, Australia, to the creation of Fig. 3.Peer reviewedPostprin