Cognitive tasks and human ambulatory electrocorticography using the RNS System

Abstract

Background Electrocorticography studies are typically conducted in patients undergoing video EEG monitoring, but these studies are subject to confounds such as the effects of pain, recent anesthesia, analgesics, drug changes, antibiotics, and implant effects. New Method Techniques were developed to obtain electrocorticographic (ECoG) data from freely moving subjects performing navigational tasks using the RNS® System (NeuroPace, Inc., Mountain View, CA), a brain-responsive neurostimulation medical device used to treat focal onset epilepsy, and to align data from the RNS System with cognitive task events with high precision. These subjects had not had recent surgery, and were therefore not confounded by the perioperative variables that affect video EEG studies. Results Task synchronization using the synchronization marker technique provides a quantitative measure of clock uncertainty, and can align data to task events with less than 4ms of uncertainty. Hippocampal ECoG activity was found to change immediately before an incorrect response to a math problem compared to hippocampal activity before a correct response. In addition, subjects were found to have variable but significant changes in theta band power in the hippocampus during navigation compared to when subjects were not navigating. We found that there is theta-gamma phase-amplitude coupling in the right hippocampus while subjects stand still during a navigation task. Comparison with Existing Methods An alignment technique described in this study improves the upper bound on task-ECoG alignment uncertainty from approximately 30ms to under 4ms. The RNS System is one of the first platforms capable of providing untethered ambulatory ECoG recording in humans, allowing for the study of real world instead of virtual navigation. Compared to intracranial video EEG studies, studies using the RNS System platform are not subject to confounds caused by the drugs and recent surgery inherent to the perioperative environment. Furthermore, these subjects provide the opportunity to record from the same electrodes over the course of many years. Conclusions The RNS System enables us to study human navigation with unprecedented clarity. While RNS System patients have fewer electrodes implanted than video EEG patients, the lack of external artifact and confounds from recent surgery make this system a useful tool to further human electrophysiology research.

Functionally distinct high and low theta oscillations in the human hippocampus

“…Two recent studies measured human hippocampal oscillations from people walking in the physical world and reported high-theta oscillations (e.g., 7,8 ; but see ref. 55 ). These results were interpreted to suggest that virtual navigation relies on a fundamentally different, lower-frequency oscillatory network state compared with real-world navigation 9 .…”

Functionally distinct high and low theta oscillations in the human hippocampus

“…A key result from our work is showing that high-theta oscillations appear in the human hippocampus during movement in virtual reality. Two recent studies measured human hippocampal oscillations from people walking in the physical world and reported high-theta oscillations (Bohbot et al, 2017; Aghajan et al, 2016; but see Meisenhelter et al, 2018). These results were interpreted to suggest that virtual navigation relies on a fundamentally different, lower-frequency oscillatory network state compared to real-world navigation (Yassa, 2018); however, it should be noted that at least one of the studies that previously showed high-theta oscillations in real-world navigation showed examples of these patterns at relatively posterior locations (Bohbot et al, 2017).…”

Modulation of human intracranial theta oscillations during freely moving spatial navigation and memory

“…A custom-made Electromagnet was externally placed on the head over the position of the underlying implanted RNS System and was used to trigger data storage and simultaneously generated a visible light signal detected by the motion capture system that was then used to then synchronize iEEG and behavioral movement data. Due to variable, and uncontrollable, delays in the magnet signal ( < 500ms) 27 , the synchronization between behavior and neural data only allowed for analyses that required lower temporal precisions (e.g., phase of the experiments such as encoding/retrieval rather than trialbased analyses).…”