Abstract

The encoding of information in spike phase relative to local field potential (LFP) oscillations offers several theoretical advantages over equivalent firing rate codes. One notable example is provided by place and grid cells in the rodent hippocampal formation, which exhibit phase precession—firing at progressively earlier phases of the 6–12 Hz movement‐related theta rhythm as their spatial firing fields are traversed. It is often assumed that such phase coding relies on a high amplitude baseline oscillation with relatively constant frequency. However, sustained oscillations with fixed frequency are generally absent in LFP and spike train recordings from the human brain. Hence, we examine phase coding relative to LFP signals with broadband low‐frequency (2–20 Hz) power but without regular rhythmicity. We simulate a population of grid cells that exhibit phase precession against a baseline oscillation recorded from depth electrodes in human hippocampus. We show that this allows grid cell firing patterns to multiplex information about location, running speed and movement direction, alongside an arbitrary fourth variable encoded in LFP frequency. This is of particular importance given recent demonstrations that movement direction, which is essential for path integration, cannot be recovered from head direction cell firing rates. In addition, we investigate how firing phase might reduce errors in decoded location, including those arising from differences in firing rate across grid fields. Finally, we describe analytical methods that can identify phase coding in the absence of high amplitude LFP oscillations with approximately constant frequency, as in single unit recordings from the human brain and consistent with recent data from the flying bat. We note that these methods could also be used to detect phase coding outside of the spatial domain, and that multi‐unit activity can substitute for the LFP signal. In summary, we demonstrate that the computational advantages offered by phase coding are not contingent on, and can be detected without, regular rhythmicity in neural activity.

Highlights

  • In the central nervous system, phase coding refers to the encoding of information in the phase of neuronal activity with respect to an ongoing oscillation in the local field potential (LFP)

  • Using LFP recordings from depth electrodes in the hippocampal formation of pre-surgical epilepsy patients performing a spatial memory task (Bush et al, 2017), we demonstrate that phase precession in simulated grid cells can be robustly maintained in the absence of any clear peak in the LFP power spectra or spike train temporal auto-correlogram, consistent with recent data from flying bats (Eliav et al, 2018)

  • Using intracranial LFP recordings from the human hippocampus, we aim to demonstrate that a robust phase code can be maintained in the absence of a prominent baseline oscillation with relatively fixed frequency; and to examine the functional advantages offered by phase coding over and above a pure rate code

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Summary

| INTRODUCTION

In the central nervous system, phase coding refers to the encoding of information in the phase of neuronal activity with respect to an ongoing oscillation in the local field potential (LFP). The best known example of phase coding comes from place and grid cells in the rodent hippocampal formation, whose firing phase relative to the ongoing 6–12 Hz movement related theta oscillation advances progressively as their spatial firing fields are traversed (Hafting, Fyhn, Bonnevie, Moser, & Moser, 2008; O'Keefe & Recce, 1993) This theta phase precession is independent of both running speed (Geisler et al, 2010; Geisler, Robbe, Zugaro, Sirota, & Buzsáki, 2007) and heading direction (Climer, Newman, & Hasselmo, 2013; Huxter, Burgess, & O'Keefe, 2003; Jeewajee et al, 2014), ensuring that firing phase provides more spatial information than spike rate alone (Jensen & Lisman, 2000). We demonstrate that phase coding in grid cells is not contingent on sustained rhythmicity in neural activity and offers several computational advantages over a pure rate code

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