Cortical Dynamics Underlying Seizure Mapping and Control

In one-third of epilepsy patients, antiepileptic drugs do not effectively control seizures, leaving resective surgery as the primary treatment option. In the absence of discrete focal lesions, long-term outcome after surgery is modest and often associated with side effects. In many cases, surgery cannot be performed due to the lack of a discrete region generating seizures. For these reasons, new therapeutic technologies have been developed to treat drug-resistant epilepsy with electrical stimulation. These devices are promising, but the efficacy of first-generation implants has been limited. The work in this thesis aims to advance current approaches to seizure monitoring and control by developing better hardware and building the foundational knowledge behind the cortical dynamics underlying seizure generation, propagation and neural stimulation. In this thesis, I first develop new technologies that sample local field potentials on the cortical surface with high spatial and temporal resolutions. These devices capture complex spatiotemporal patterns of epileptiform activity that are not detected on current clinical electrodes. By adding stimulation functionalities to these arrays, we position them as an ideal candidate for responsive, therapeutic neurostimulation. Next, I explore the effect of direct electrical stimulation in the cortex by recording responses with high spatial resolution on the surface and within the cortical laminae. The findings detail the capabilities and limitations of electrical stimulation as a means of modulating seizures. Finally, I use the same three-dimensional recording paradigm in feline neocortex to investigate the genesis and propagation of epileptiform activity in an isolated, chemically-induced epilepsy model. These experiments demonstrate that important circuit elements involved in seizure propagation are found deeper in the cortex and are not reflected in surface recordings. My investigations also present potential stimulation strategies to more effectively disrupt the spread of seizures in the neocortex. It is my hope that the results of this work will inform future technologies to better detect and prevent seizures, ultimately improving the lives of drug-resistant epilepsy patients through the next generation of implantable devices

Intracranial EEG fluctuates over months after implanting electrodes in human brain.

OBJECTIVE: Implanting subdural and penetrating electrodes in the brain causes acute trauma and inflammation that affect intracranial electroencephalographic (iEEG) recordings. This behavior and its potential impact on clinical decision-making and algorithms for implanted devices have not been assessed in detail. In this study we aim to characterize the temporal and spatial variability of continuous, prolonged human iEEG recordings. APPROACH: Intracranial electroencephalography from 15 patients with drug-refractory epilepsy, each implanted with 16 subdural electrodes and continuously monitored for an average of 18 months, was included in this study. Time and spectral domain features were computed each day for each channel for the duration of each patient\u27s recording. Metrics to capture post-implantation feature changes and inflexion points were computed on group and individual levels. A linear mixed model was used to characterize transient group-level changes in feature values post-implantation and independent linear models were used to describe individual variability. MAIN RESULTS: A significant decline in features important to seizure detection and prediction algorithms (mean line length, energy, and half-wave), as well as mean power in the Berger and high gamma bands, was observed in many patients over 100 d following implantation. In addition, spatial variability across electrodes declines post-implantation following a similar timeframe. All selected features decreased by 14-50% in the initial 75 d of recording on the group level, and at least one feature demonstrated this pattern in 13 of the 15 patients. Our findings indicate that iEEG signal features demonstrate increased variability following implantation, most notably in the weeks immediately post-implant. SIGNIFICANCE: These findings suggest that conclusions drawn from iEEG, both clinically and for research, should account for spatiotemporal signal variability and that properly assessing the iEEG in patients, depending upon the application, may require extended monitoring

Bioresorbable silicon electronics for transient spatiotemporal mapping of electrical activity from the cerebral cortex.

Bioresorbable silicon electronics technology offers unprecedented opportunities to deploy advanced implantable monitoring systems that eliminate risks, cost and discomfort associated with surgical extraction. Applications include postoperative monitoring and transient physiologic recording after percutaneous or minimally invasive placement of vascular, cardiac, orthopaedic, neural or other devices. We present an embodiment of these materials in both passive and actively addressed arrays of bioresorbable silicon electrodes with multiplexing capabilities, which record in vivo electrophysiological signals from the cortical surface and the subgaleal space. The devices detect normal physiologic and epileptiform activity, both in acute and chronic recordings. Comparative studies show sensor performance comparable to standard clinical systems and reduced tissue reactivity relative to conventional clinical electrocorticography (ECoG) electrodes. This technology offers general applicability in neural interfaces, with additional potential utility in treatment of disorders where transient monitoring and modulation of physiologic function, implant integrity and tissue recovery or regeneration are required