Multi-scale analysis of neural activity in humans: Implications for micro-scale electrocorticography

Spencer Kellis, Larry Sorensen, Felix Darvas, Conor Sayres, Kevin O'Neill, Richard B. Brown, Paul House, Jeff Ojemann, Bradley Greger

Research output: Contribution to journalArticlepeer-review

62 Scopus citations

Abstract

Objective: Electrocorticography grids have been used to study and diagnose neural pathophysiology for over 50 years, and recently have been used for various neural prosthetic applications. Here we provide evidence that micro-scale electrodes are better suited for studying cortical pathology and function, and for implementing neural prostheses. Methods: This work compares dynamics in space, time, and frequency of cortical field potentials recorded by three types of electrodes: electrocorticographic (ECoG) electrodes, non-penetrating micro-ECoG (μECoG) electrodes that use microelectrodes and have tighter interelectrode spacing; and penetrating microelectrodes (MEA) that penetrate the cortex to record single- or multiunit activity (SUA or MUA) and local field potentials (LFP). Results: While the finest spatial scales are found in LFPs recorded intracortically, we found that LFP recorded from μECoG electrodes demonstrate scales of linear similarity (i.e., correlation, coherence, and phase) closer to the intracortical electrodes than the clinical ECoG electrodes. Conclusions: We conclude that LFPs can be recorded intracortically and epicortically at finer scales than clinical ECoG electrodes are capable of capturing. Significance: Recorded with appropriately scaled electrodes and grids, field potentials expose a more detailed representation of cortical network activity, enabling advanced analyses of cortical pathology and demanding applications such as brain-computer interfaces.

Original languageEnglish (US)
Pages (from-to)591-601
Number of pages11
JournalClinical Neurophysiology
Volume127
Issue number1
DOIs
StatePublished - Jan 1 2016
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2015 International Federation of Clinical Neurophysiology.

Keywords

  • Brain computer interface (BCI)
  • Human cerebral cortex
  • Micro-electrocorticography grid
  • Neural engineering
  • Neural microtechnology

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