Browsing by Author "Trumpis, Michael"

Now showing 1 - 2 of 2
  • Thumbnail Image
    ItemOpen Access
    Intraoperative microseizure detection using a high-density micro-electrocorticography electrode array.
    (Brain communications, 2022-01) Sun, James; Barth, Katrina; Qiao, Shaoyu; Chiang, Chia-Han; Wang, Charles; Rahimpour, Shervin; Trumpis, Michael; Duraivel, Suseendrakumar; Dubey, Agrita; Wingel, Katie E; Rachinskiy, Iakov; Voinas, Alex E; Ferrentino, Breonna; Southwell, Derek G; Haglund, Michael M; Friedman, Allan H; Lad, Shivanand P; Doyle, Werner K; Solzbacher, Florian; Cogan, Gregory; Sinha, Saurabh R; Devore, Sasha; Devinsky, Orrin; Friedman, Daniel; Pesaran, Bijan; Viventi, Jonathan
    One-third of epilepsy patients suffer from medication-resistant seizures. While surgery to remove epileptogenic tissue helps some patients, 30-70% of patients continue to experience seizures following resection. Surgical outcomes may be improved with more accurate localization of epileptogenic tissue. We have previously developed novel thin-film, subdural electrode arrays with hundreds of microelectrodes over a 100-1000 mm2 area to enable high-resolution mapping of neural activity. Here, we used these high-density arrays to study microscale properties of human epileptiform activity. We performed intraoperative micro-electrocorticographic recordings in nine patients with epilepsy. In addition, we recorded from four patients with movement disorders undergoing deep brain stimulator implantation as non-epileptic controls. A board-certified epileptologist identified microseizures, which resembled electrographic seizures normally observed with clinical macroelectrodes. Recordings in epileptic patients had a significantly higher microseizure rate (2.01 events/min) than recordings in non-epileptic subjects (0.01 events/min; permutation test, P = 0.0068). Using spatial averaging to simulate recordings from larger electrode contacts, we found that the number of detected microseizures decreased rapidly with increasing contact diameter and decreasing contact density. In cases in which microseizures were spatially distributed across multiple channels, the approximate onset region was identified. Our results suggest that micro-electrocorticographic electrode arrays with a high density of contacts and large coverage are essential for capturing microseizures in epilepsy patients and may be beneficial for localizing epileptogenic tissue to plan surgery or target brain stimulation.
  • Thumbnail Image
    ItemOpen Access
    Quantifying High Dimensional Recordings of Neural Surface Potentials
    (2018) Trumpis, Michael

    Chronically reliable neural implants are needed to provide long lasting, high fidelity interfaces for clinical use and for basic science. Minimally invasive implants, such as micro-electrocorticographic arrays (µECoG), have been proposed in this field to minimize immune response and glial scarring reactions and promote long-term recording stability. µECoG electrodes record field potential from the surface of the pia or dura. Because of their low sensitivity to direct neuronal discharges, the neural "output" of µECoG electrodes is ambiguous. In addition, the correct sampling resolution for µECoG arrays is not precisely known, due to incomplete knowledge of the spatial correlation of surface potential. This dissertation proposes and validates µECoG characterization metrics to assist in comparing the quality of recording output between novel and reference devices, and to enable longitudinal quality tracking in chronic implants. Among this methodology is a model of spatial field variation that sheds new light on spatial bandwidth, and the prediction and denoising capabilities from correlated sampling.

    In the first section of this dissertation, the rat auditory cortex model is introduced as the in vivo validation target for subsequent work. A comprehensive set of metrics, sensitive to spatial and temporal variation, are developed to summarize the background and evoked response µECoG signal. µECoG is validated as accurately reflecting auditory physiology in the acute setting, and is shown to record consistent signal in implants for 30-60 days. The second section applies these signal validation techniques to demonstrate the compatibility of neural recordings from two fundamentally different amplification technologies: a high impedance voltage amplifier and a transimpedance amplifier. The third section is a thorough investigation of recordings from µECoG arrays implanted chronically for over one year. The quantification methodologies are adapted to longitudinal quality tracking and are compared to the common status indicator of electrode impedance. The fourth section explores the problem of spatial sampling in µECoG by directly quantifying the efficiency of predicting unsampled field potential under various spatial bandwidth and noise conditions.

    This set of results in acute and chronic settings provides a robust confirmation of some simple but reliable metrics of µECoG recordings. The use of these statistics in ongoing device validation work should provide nuanced and multivariate accounting of the strengths and weaknesses of neural interfaces. However, future work is required to improve sensitivity to finer scale spatio-temporal features of surface potential fields.