Non-invasive Investigation of Human Hippocampal Rhythms Using Magnetoencephalography: A Review.

Yi Pu,Douglas O Cheyne,Brian R Cornwell,Blake W Johnson

doi:10.3389/fnins.2018.00273

Abstract

Hippocampal rhythms are believed to support crucial cognitive processes including memory, navigation, and language. Due to the location of the hippocampus deep in the brain, studying hippocampal rhythms using non-invasive magnetoencephalography (MEG) recordings has generally been assumed to be methodologically challenging. However, with the advent of whole-head MEG systems in the 1990s and development of advanced source localization techniques, simulation and empirical studies have provided evidence that human hippocampal signals can be sensed by MEG and reliably reconstructed by source localization algorithms. This paper systematically reviews simulation studies and empirical evidence of the current capacities and limitations of MEG “deep source imaging” of the human hippocampus. Overall, these studies confirm that MEG provides a unique avenue to investigate human hippocampal rhythms in cognition, and can bridge the gap between animal studies and human hippocampal research, as well as elucidate the functional role and the behavioral correlates of human hippocampal oscillations.

Highlights

The hippocampus is an important brain region for various cognitive processes, including spatial navigation (O’Keefe and Nadel, 1978; Buzsaki and Moser, 2013), memory (Horner and Doeller, 2017), and language comprehension (Piai et al, 2016)
The results indicate that MEG can tell us where the hippocampal region is responsible for a certain cognitive process, but can tell us the specific neural mechanism and timing of this process (Dalal et al, 2008; Moses et al, 2011)
The principal neurons of the hippocampus are uniformly aligned with their dendrites in parallel in the same direction perpendicular to the hippocampal surface (Lorente de No, 1947), such that the intracellular currents produced by synchronization of those neurons should be detectable by MEG (Murakami and Okada, 2006)

Summary

Introduction

The hippocampus is an important brain region for various cognitive processes, including spatial navigation (O’Keefe and Nadel, 1978; Buzsaki and Moser, 2013), memory (Horner and Doeller, 2017), and language comprehension (Piai et al, 2016). Detailed simulations of deep brain areas, such as the hippocampus, the amygdala, and thalamus were carried out by Attal et al (Attal et al, 2007, 2012; Attal and Schwartz, 2013) based on realistic anatomical and electrophysiological models to explore the detectability by MEG for these deep sources, and to compare the performance of different depth weighted minimum norm inverse operators (one depth weighted MNE and two noise-normalized depth weighted MNE algorithms).

Results

Conclusion