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

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.

Keywords: deep source imaging; hippocampus; magnetoencephalography (MEG); review; simulation and empirical evidence.

Figure 1

Flux transformer (pick up coils). (A) Magnetometer; (B) First-order planar gradiometer (C) First-order axial gradiometer. (D) Signal-to-noise ratio (y-axis with arbitrary units) of MEG sensors as a function of the length of the baseline of the flux transformer pick up coils (x-axis). (A–C) is reproduced with permission from Hämäläinen et al. (1993). (D) is adapted from Vrba and Robinson (2001).

Figure 2

MEG measures of human hippocampal theta oscillations (4–8 Hz) during spatial navigation and its behavioral correlates. Upper: Group image (N = 18) of main effect of environmental novelty in the time window of 1.25–2.25 s during virtual spatial navigation in the right hippocampus revealed by beamforming analyses and the time frequency representations (TFRs) of the virtual sensor placed in the peak voxel of right hippocampus in new and familiar environment. The black squares on the TFRs indicate more theta power during 1.25–2.25 s in the new (1st training set) vs. familiar (2nd training set) environment. Lower: Theta power in the first training set (new environment) in the right hippocampal region shown in the upper left panel plotted against averaged path lengths (arbitrary units) in the first or second training set in the navigation task. This figure is reproduced with permission from Pu et al. (2017).

Figure 3

Simultaneously recorded magnetoencephalogram (MEG; black trace) and hippocampus depth electroencephalogram (EEG; red trace) from a pre-surgery patient. Theta oscillations recorded by MEG and those recorded by the depth electrode are correlated without any phase delay. This figure is reproduced with permission from Korczyn et al. (2013).