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Transferring Cognitive Tasks Between Brain Imaging Modalities: Implications for Task Design and Results Interpretation in fMRI Studies
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Cognitive tasks and human ambulatory electrocorticography using the RNS System.

Stephen Meisenhelter1, Markus E Testorf2, Mark A Gorenstein3

  • 1School of Graduate and Advanced Studies, Dartmouth College, Hanover, NH 03755, United States.

Journal of Neuroscience Methods
|September 30, 2018
PubMed
Summary

New methods using the RNS® System allow electrocorticography (ECoG) studies in freely moving subjects, reducing confounds from surgery and medication for clearer human navigation research.

Keywords:
Ambulatory ECoGCognitionECoGElectrocorticographyEpilepsyMemoryNavigationRNS System

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Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Medical Devices

Background:

  • Electrocorticography (ECoG) studies are often confounded by perioperative variables like pain, anesthesia, and medications.
  • Traditional video EEG monitoring limits the ability to study freely moving subjects during cognitive tasks.

Purpose of the Study:

  • To develop and validate techniques for obtaining high-precision ECoG data from freely moving subjects using the RNS® System.
  • To enable the study of human navigation and cognitive processes without perioperative confounds.

Main Methods:

  • Utilized the RNS® System for untethered, ambulatory ECoG recordings in subjects performing navigational tasks.
  • Developed a task synchronization technique for precise alignment of ECoG data with cognitive events, achieving <4 ms uncertainty.

Main Results:

  • Demonstrated immediate changes in hippocampal ECoG activity preceding incorrect responses in a math task.
  • Observed significant theta band power changes in the hippocampus during navigation.
  • Identified theta-gamma phase-amplitude coupling in the right hippocampus during static navigation tasks.

Conclusions:

  • The RNS® System facilitates high-clarity studies of human navigation and electrophysiology.
  • Improved task-ECoG alignment accuracy (<4 ms) overcomes limitations of previous methods (approx. 30 ms).
  • This approach minimizes confounds from recent surgery and medication, offering a valuable tool for human electrophysiology research.