Phase coding of spatial representations in the human entorhinal cortex

Abstract

The grid-like activity pattern of cells in the mammalian entorhinal cortex provides an internal reference frame for allocentric self-localization. The same neurons maintain robust phase couplings with local field oscillations. We found that neurons of the human entorhinal cortex display consistent spatial and temporal phase locking between spikes and slow gamma band local field potentials (LFPs) during virtual navigation. The phase locking maintained an environment-specific map over time. The phase tuning of spikes to the slow gamma band LFP revealed spatially periodic phase grids with environment-dependent scaling and consistent alignment with the environment. Using a Bayesian decoding model, we could predict the avatar’s position with near perfect accuracy and, to a lesser extent, that of heading direction as well. These results imply that the phase of spikes relative to spatially modulated gamma oscillations encode allocentric spatial positions. We posit that a joint spatiotemporal phase code can implement the combined neural representation of space and time in the human entorhinal cortex.

Gated transformations from egocentric to allocentric reference frames involving retrosplenial cortex, entorhinal cortex, and hippocampus

“…Theta rhythmicity in human hippocampus has also been shown to increase near the boundaries of the environment (Stangl et al, 2021). Recordings indicate that spiking responses in human hippocampus show theta phase precession relative to the theta rhythm in the local field potential (Qasim et al, 2021) and entorhinal neurons show phase locking to gamma (Nadasdy et al, 2022). fMRI activity in humans demonstrates a six‐fold rotational symmetry in virtual worlds as predicted for grid cell responses (Doeller et al, 2010) which has also been observed in recordings of theta oscillations in the local field potential in the human entorhinal cortex (Maidenbaum et al, 2018).…”

Enhancing Perceptual, Attentional, and Working Memory Demands through Variable Practice Schedules: Insights from High-Density EEG Multi-Scale Analyses

“…The entorhinal cortex, more active in the random compared to the blocked condition, plays a critical role in spatial navigation and memory. It contains grid cells that encode spatial information in allocentric terms, offering a two-dimensional map-like representation of the environment (Fyhn et al 2004;Hafting et al 2005;Constantinidis and Klingberg 2016;Nau et al 2018;Nadasdy et al 2022). Additionally, the coding of distances extends beyond exact metric to categorical terms like above/below or right/left comparisons (Kosslyn et al 1992;Noordzij and Postma 2005;Baumann et al 2012).…”

Neurodynamical Computing at the Information Boundaries of Intelligent Systems

“…Neural oscillations are measured extracellularly as the net synaptic loop currents in the local volume [139,140] and the structure of prevalent frequency bands is highly conserved across mammals including humans [141][142][143]. Neuronal spike phase is measured as the relative alignment of spikes to oscillatory cycles and effectively constitutes a distinct spatiotemporal dimension of neural interaction that naturally supports sequence learning, generation, and chunking in biological [144][145][146][147][148][149][150][151][152] and artificial [153][154][155][156] systems. Because various lines of evidence indicate that neuronal spike phase and collective oscillations may be causally bidirectional [157][158][159][160][161][162], the discrete neural states organized by oscillatory cycles are candidate computational states.…”