Quantifying Microscale Interictal Activity from High-Resolution Cortical Recordings in Patients with Epilepsy

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2024

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Abstract

The clinical tools used to record from the brain for diagnosis and surgical planning in patients with drug resistant epilepsy have undergone little to no innovation over the past several decades. In contrast, the academic research community has made significant progress in neural interfacing technologies, including novel developments in materials, fabrication methods, recording hardware, data visualization, and signal processing. One key development has been the increase in spatial resolution of neural recording arrays, enabling the acquisition of localized high-frequency neural activity from many individual recording sites. Such tools have been used to conduct essential neuroscience experiments in animal models and are the basis of brain-computer interface technology for humans. However, these high-resolution neural interfaces have not been clinical translated for epilepsy diagnosis and surgical planning, in part because the advantages of high-resolution arrays for acquiring clinically relevant epileptic biomarkers have been insufficiently studied. This dissertation addresses this gap by evaluating interictal activity recorded intraoperatively from high-resolution, thin-film cortical arrays in patients with epilepsy. I conducted intraoperative recordings from patients with epilepsy using micro-electrocorticographic (µECoG) arrays made of a liquid crystal polymer thin-film (LCP-TF) substrate with small gold recording contacts (200 µm diameter). The LCP-TF arrays are compelling candidates for clinical translation of high-resolution neural technology given their in vivo longevity, flexible and smooth surfaces which minimize tissue damage, inert chemical properties, and large-scale manufacturability with thin-film fabrication techniques. Furthermore, the LCP-TF µECoG arrays record not only at high spatial resolution but also with large coverage of the cortex – a necessary feature for clinically mapping epileptic foci which many other microelectrode arrays do not provide. In this work, we demonstrate how LCP-TF µECoG arrays broadly map epileptic cortex with microscale precision and test the hypothesis that high-resolution, broad-coverage cortical recordings capture microscale spatiotemporal patterns of interictal biomarkers of epileptic tissue which are poorly acquired by clinical standard macrocontact arrays. This dissertation reports novel methods for high-resolution array design, data acquisition hardware testing, and intraoperative neural recordings. In collaboration with clinicians and a larger research team, I used these methods to collect a unique dataset of high-resolution, intraoperative recordings from broad areas of cortex in patients with epilepsy. This includes recordings from a hybrid array I designed which has densely spaced microcontacts alongside clinical scale macrocontacts, enabling simultaneous recordings at both spatial scales. From this data, I identified previously described interictal biomarkers of epileptic tissue, including microseizures (µSZs), high-frequency oscillations (HFOs), and interictal discharges (IDs). Leveraging new and established signal processing methods, I analyzed the microscale spatiotemporal dynamics of these interictal events and evaluated the potential added value of microarrays for capturing interictal activity as compared to clinical standard macrocontacts. I concluded that LCP-TF microelectrode arrays successfully captured microscale spatial features of clinically relevant interictal biomarkers during epilepsy surgery. Specifically, I found that HFOs most often occurred within a millimeter radius of tissue, and that densely spaced microcontacts captured more HFOs than macrocontact arrays. In collaboration with James Sun at New York University, we identified µSZs in our intraoperative recordings and showed that they were specific to patients with epilepsy and required dense microcontact arrays to be detected. I found that IDs were often localized to sub-centimeter areas of cortex which could be missed by centimeter-spaced clinical macrocontact arrays and showed that our high-resolution microarrays can track microscale patterns of ID propagation. Finally, I also report methods that I have developed to screen high-channel count amplifier chips (Intan Technologies) for analog-to-digital conversion errors which produce artifacts in the acquired signal. Ensuring low-noise recordings from high-channel count acquisition systems is essential to recording low-amplitude, high-frequency neural activity and establishing high-resolution recording technology as a robust clinical diagnostic tool. In summary, this dissertation provides compelling evidence for the utility of neural interfaces with high spatial resolution and broad coverage for capturing the wealth of interictal epileptic activity in the human brain, with the potential to improve clinical methods for intracranial mapping of epileptic foci in patients with drug resistant epilepsies.

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Barth, Katrina (2024). Quantifying Microscale Interictal Activity from High-Resolution Cortical Recordings in Patients with Epilepsy. Dissertation, Duke University. Retrieved from https://hdl.handle.net/10161/31962.

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