Dynamic Changes In EEG Coherence During Cardiac Arrest And Resuscitation In A Rodent Model That Mimics A Neuro-Intensive Care Unit (S42.001)

Objective: To better understand neurological phenomena during loss of consciousness surrounding cardiac arrest as well as after resuscitation and recovery, enabling better prognostication and opportunities to improve outcome. Background: Electroencephalogram (EEG) synchronization and coherence has been shown to 1) transiently rise during impending cardiac arrest and has been implicated in near-death experience, and 2) correlate with early recovery from CA in comatose patients. However, a detailed EEG-based time-frequency connectivity analysis during CA induction and the post-cardiopulmonary resuscitation (CPR) recovery period has not been performed. Design/Methods: In this study, male Wistar rats underwent 8 minutes of asphyxial CA followed by CPR. EEG coherence dynamics were analyzed during the minutes surrounding CA induction as well as at 4, 24, 48, and 72 hours following CPR. A rodent model using intracranial EEG electrodes facilitated the investigation of faster gamma frequencies of up to 150 Hz. Results: During impending CA, when EEG has almost reached electrocerebral silence, we found a large transient increase in coherence between the left and right frontal lobes in the beta and slow gamma EEG bands. Then, at 4 hours post-CPR, delta coherence increased and alpha coherence decreased, while at 24 hours post-CA beta coherence increased. Alpha, slow gamma, and ultra fast gamma (120–150 Hz) frequencies exhibited sustained changes in coherence following CA. Conclusions: Our findings indicate that rapid rises in EEG coherence can occur during impending cardiac arrest when the EEG has nearly reached electrocerebral silence. Moreoever, after CPR, acute and sustained EEG coherence dynamics, including sustained faster frequency changes, may allow us to predict the stage of recovery after brain injury in our preclinical model. To improve current quantitative EEG algorithms utilized in clinical practice, future studies will target faster frequency EEG coherence as a predictor of long-term outcome. Study Supported by: NIH KL2 grant (5KL2TR000147) to Y.A. via NCATS UL1 TR000153 NIH Trailblazer R21 grant (1R21EB024793-01) to Y.A. Disclosure: Dr. Akbari has nothing to disclose. Dr. Siu has nothing to disclose. Dr. Lee has nothing to disclose. Dr. Lee has nothing to disclose. Dr. Bazrafkan has nothing to disclose. Dr. Alcocer has nothing to disclose. Dr. Maki has nothing to disclose. Dr. Hosseini has nothing to disclose. Dr. Wilson has nothing to disclose. Dr. Lopour has nothing to disclose.