CNS ORAL PRESENTATIONS involved in visuomotor control and network integration of striatothala- mocortical circuits appear to predict DBS response. These findings shed a light on the mechanism of action of DBS and L-DOPA and may help serve as useful treatment response biomarkers. STEREOTACTIC AND FUNCTIONAL NEUROSURGERY RESIDENT AWARD 148 A Fully Implantable Brain Machine Interface for Volitional Hand Grasp Restoration in Cervical Quadriplegia Iahn Cajigas, MD, PhD; Noeline W Prins, PhD; Sebastian Gallo; Jasim A. Naeem, BS; Santiago Guerra; Brandon Parks, BS; Anne Palermo, PT; Audrey Wilson; Letitia Fisher, BA; Steven Vanni, DO, DC; Michael E. Ivan, MD, MBS; Abhishek Prasad, PhD; Jonathan R. Jagid, MD INTRODUCTION: Neural interface research has been strongly motivated by the need to restore communication and control to the estimated 5.3 million people in the US population which currently suffer from some form of paralysis. We recently enrolled a patient with a chronic traumatic cervical spinal cord injury (C5 ASIA A) to undergo placement of a brain machine interface aimed at restoring unilateral upper distal extremity function (ClinicalTrials.gov NCT02564419). The objective of this study was to evaluate the safety and efficacy of a fully implanted brain machine interface consisting of the Medtronic PC + S and the Bioness H200 hand rehabilitation orthosis for the functional restoration of hand grasp in a patient with cervical quadriplegia. METHODS: A computer task was developed to engage the subject in thinking of either hand movement or rest while electrocorticographic (ECoG) activity was recorded. “Open-loop” trials were used to train various classifiers for predicting “move” or “rest” states based on observa- tions of the ECoG activity. In “closed-loop” experiments, the decoded desired hand state was used to drive functional electrical stimulation of the dominant hand utilizing the Bioness H200 orthosis. Functional performance was measured by a modified Jebson Taylor Hand Function (JTHF) test and range of motion. RESULTS: Movement intent information was decoded with an online accuracy of 88.2% with a tree bagging classifier over 21 sessions. Functional improvement was observed in reduction of the average time to perform subtasks within the JTHF test. CONCLUSION: Our results demonstrate that a fully implanted brain machine interface can be safely implanted and used to reliably decode movement intent from motor cortex allowing for volitional control of hand grasp in a laboratory setting. Further work will aim to allow use of the device in a home setting, a critical step for the widespread use of these approaches to restore motor function in patients living with paralysis. 149 Tackling Big Data in Human Intracranial Electroencephalography Recordings Patrick J. Karas, MD; John F. Magnotti, PhD; Zhengjia Wang; Daniel Yoshor, MD; Michael S. Beauchamp, PhD INTRODUCTION: Intracranial electrode recordings (ECoG [electrocorticography], sEEG [stereoelectroencephalography], and iEEG [intracranial electroencephalography]) are increasingly common across neurosurgery. Intracranial recordings during epilepsy monitoring, awake craniotomy, and deep brain stimulation are revolutionizing our under- standing of basic brain function, providing access to direct recordings from human neurons. However analyzing this data is daunting. Hundreds of electrodes, each recording thousands of measurements each second, record for hours, days, or weeks. The resulting datasets easily reach hundreds of gigabytes in size, with trillions of datapoints representing a scale of data difficult to tackle. Presently, most labs write custom in-house code to analyze these datasets, making peer review of results next to impossible and exacerbating a reproducibility crisis. We present a software package, RAVE (R Analysis and Visualization of iEEG), equipped with dimension reduction techniques to allow users to more easily analyze giant iEEG datasets. METHODS: RAVE is written in R using the Shiny package, enabling it to run from any web browser. Data is notch-filtered then wavelet trans- formed to obtain power and phase components. Both common average and bipolar re-referencing are supported. Data is then temporally down- sampled, maintaining high frequency information but vastly reduces the size of datasets. Power and phase information is then interactively displayed across single or multiple electrodes. RESULTS: RAVE is a freely available software package with a growing user base, available at https://github.com/beauchamplab/rave/ tree/master#rave. Inclusion of a preprocessing pipeline, signal decompo- sition, dimension reduction, and graphical display of iEEG data achieves our goals of standardizing data analysis, allowing users with limited programming background to analyze iEEG data, and increased trans- parency of published results. CONCLUSION: We have developed a dimension reduction, analysis, and visualization pipeline in RAVE that allows users to take large complex datasets and easily create publication quality images in a rigorous, transparent, and easily shareable way. 150 Thalamic Arousal Network Disturbances in Temporal Lobe Epilepsy and Improvement After Surgery Hernán F. J. González, MS; Srijata Chakravorti, BS; Sarah E. Goodale, BE; Kanupriya Gupta, BA; Daniel O. Claassen, MD, MS; Benoit M. Dawant, PhD; Victoria L. Morgan, PhD; Dario J. Englot, MD, PhD INTRODUCTION: The effects of temporal lobe epilepsy (TLE) on subcortical arousal structures remain incompletely understood. Here we evaluate thalamic arousal network functional connectivity in TLE and examine changes after epilepsy surgery. METHODS: We examined 26 adult TLE patients and 26 matched control participants and used resting-state functional magnetic resonance imaging (fMRI) to measure functional connectivity between the thalamus (entire thalamus and 19 bilateral thalamic nuclei) and both neocortex and brainstem ascending reticular activating system (ARAS) nuclei. Postoperative imaging was completed for 19 patients > 1 yr after surgery and compared to preoperative baseline. RESULTS: Before surgery, TLE patients demonstrated abnormal thalamo-occipital functional connectivity, losing the normal negative CLINICAL NEUROSURGERY VOLUME 66 | NUMBER 1 | SEPTEMBER 2019 | 43 Downloaded from https://academic.oup.com/neurosurgery/article/66/Supplement_1/nyz310_150/5551687 by guest on 14 September 2021