Coupling between gamma-band power and cerebral blood volume during recurrent acute neocortical seizures. Academic Article uri icon

Overview

abstract

  • Characterization of neural and hemodynamic biomarkers of epileptic activity that can be measured using non-invasive techniques is fundamental to the accurate identification of the epileptogenic zone (EZ) in the clinical setting. Recently, oscillations at gamma-band frequencies and above (>30 Hz) have been suggested to provide valuable localizing information of the EZ and track cortical activation associated with epileptogenic processes. Although a tight coupling between gamma-band activity and hemodynamic-based signals has been consistently demonstrated in non-pathological conditions, very little is known about whether such a relationship is maintained in epilepsy and the laminar etiology of these signals. Confirmation of this relationship may elucidate the underpinnings of perfusion-based signals in epilepsy and the potential value of localizing the EZ using hemodynamic correlates of pathological rhythms. Here, we use concurrent multi-depth electrophysiology and 2-dimensional optical imaging spectroscopy to examine the coupling between multi-band neural activity and cerebral blood volume (CBV) during recurrent acute focal neocortical seizures in the urethane-anesthetized rat. We show a powerful correlation between gamma-band power (25-90 Hz) and CBV across cortical laminae, in particular layer 5, and a close association between gamma measures and multi-unit activity (MUA). Our findings provide insights into the laminar electrophysiological basis of perfusion-based imaging signals in the epileptic state and may have implications for further research using non-invasive multi-modal techniques to localize epileptogenic tissue.

publication date

  • April 13, 2014

Research

keywords

  • Blood Volume
  • Cerebrovascular Circulation
  • Electroencephalography
  • Gamma Rhythm
  • Neocortex
  • Seizures

Identity

PubMed Central ID

  • PMC4077632

Scopus Document Identifier

  • 84901379588

Digital Object Identifier (DOI)

  • 10.1016/j.neuroimage.2014.04.014

PubMed ID

  • 24736180

Additional Document Info

volume

  • 97