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Improve understanding of the correlation between surface EEG and implanted EEG recordings
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| ECOG and EEG Sensor | Study subjects are neurosurgical patients with medically refractory epilepsy who will have implanted with intracranial ECoG electrodes. The electrodes will be used during a period of inpatient monitoring to identify resectable seizure foci. |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| EEG | Device | EEG will be collected with Brain Product's VAMP-16 channel EEG Monitor using the accompanying software. (Website with further specifications and product details: https://www.brainproducts.com/productdetails.php?id=15) |
| Measure | Description | Time Frame |
|---|---|---|
| Electrocardiogram (EEG) change before, during, and after anesthesia. | Patient subjective level of consciousness during and after anesthesia administration will be assessed using response to verbal stimuli, response via button press, reported subjective level of consciousness, and/or response to memory tests (i.e. demonstration of explicit memory recall). Around loss and recovery of consciousness time points (e.g. induction or emergence from anesthesia or when patient falls asleep or wakes up during 24 hour postoperative time points) level of consciousness will be assessed in brief intervals (seconds) until patient no longer responds or begins to respond. Data collected before, after, and during seizure activity if a patient loses consciousness or has diminished consciousness may also be compared. | Up to 48 hours. Specific time points are dependent on patient clinical events. |
| Measure | Description | Time Frame |
|---|---|---|
| Electrocardiogram (EEG) change during any changes in consciousness. | Scalp and cortical electrical activity collected using EEG and ECOG arrays respectively will be analyzed using standard frequency-derived measures (e.g. spectrograms, Fourier analysis), nonlinear dynamical analyses (e.g. correlation dimension, entropy), network dynamics (e.g. connectivity matrices, path length), and/or machine learning. These measures will include all of the data collected from the start of the implant procedure until 24 hours after the implant procedure has ended. Data collected before, after, and during seizure activity if a patient loses consciousness or has diminished consciousness may also be compared. Reports will included characterization of electrophysiological activity before, during, and after variations in behavioral and subjectively reported consciousness. |
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Inclusion Criteria:
Exclusion Criteria:
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Stanford Health Care and Clinics
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| Name | Affiliation | Role |
|---|---|---|
| David Drover, MD | Stanford University | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Stanford University | Stanford | California | 94305 | United States |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 17236792 | Background | Hashiguchi K, Morioka T, Yoshida F, Miyagi Y, Nagata S, Sakata A, Sasaki T. Correlation between scalp-recorded electroencephalographic and electrocorticographic activities during ictal period. Seizure. 2007 Apr;16(3):238-47. doi: 10.1016/j.seizure.2006.12.010. Epub 2007 Jan 19. | |
| 23684007 | Background | Asano E, Brown EC, Juhasz C. How to establish causality in epilepsy surgery. Brain Dev. 2013 Sep;35(8):706-20. doi: 10.1016/j.braindev.2013.04.004. Epub 2013 May 15. |
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| ID | Term |
|---|---|
| D004569 | Electroencephalography |
| ID | Term |
|---|---|
| D003943 | Diagnostic Techniques, Neurological |
| D019937 | Diagnostic Techniques and Procedures |
| D003933 | Diagnosis |
| D004568 | Electrodiagnosis |
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| ECOG | Device | ECOG will be collected with Nihon Kohden acquisition System and accompanying software and depth electrodes. |
|
| Up to 48 hours. Specific time points are dependent on patient clinical events. |
| Electrocardiogram (EEG) change during any seizures. | Scalp and cortical electrical activity collected using EEG and ECOG arrays respectively will be analyzed using standard frequency-derived measures (e.g. spectrograms, Fourier analysis), nonlinear dynamical analyses (e.g. correlation dimension, entropy), network dynamics (e.g. connectivity matrices, path length), and/or machine learning. Data collected before, after, and during seizure activity if a patient loses consciousness or has diminished consciousness may also be compared. Reports will include characterization and comparison of EEG and ECOG electrophysiological activity and analyses during consciousness transitions and significant time points. | Up to 48 hours. Specific time points are dependent on patient clinical events. |
| 27020798 | Background | Smith EH, Liou JY, Davis TS, Merricks EM, Kellis SS, Weiss SA, Greger B, House PA, McKhann GM 2nd, Goodman RR, Emerson RG, Bateman LM, Trevelyan AJ, Schevon CA. The ictal wavefront is the spatiotemporal source of discharges during spontaneous human seizures. Nat Commun. 2016 Mar 29;7:11098. doi: 10.1038/ncomms11098. |
| 27324839 | Background | Ramantani G, Maillard L, Koessler L. Correlation of invasive EEG and scalp EEG. Seizure. 2016 Oct;41:196-200. doi: 10.1016/j.seizure.2016.05.018. Epub 2016 Jun 10. |
| 28044337 | Background | Hajat Z, Ahmad N, Andrzejowski J. The role and limitations of EEG-based depth of anaesthesia monitoring in theatres and intensive care. Anaesthesia. 2017 Jan;72 Suppl 1:38-47. doi: 10.1111/anae.13739. |
| 28786839 | Background | Fahy BG, Chau DF. The Technology of Processed Electroencephalogram Monitoring Devices for Assessment of Depth of Anesthesia. Anesth Analg. 2018 Jan;126(1):111-117. doi: 10.1213/ANE.0000000000002331. |
| 26275092 | Background | Purdon PL, Sampson A, Pavone KJ, Brown EN. Clinical Electroencephalography for Anesthesiologists: Part I: Background and Basic Signatures. Anesthesiology. 2015 Oct;123(4):937-60. doi: 10.1097/ALN.0000000000000841. |