Effects of visual inputs on neural dynamics for coding of location and running speed in medial entorhinal cortex.

Holger Dannenberg,Pranav Nambiar,Michael E Hasselmo,Hallie Lazaro,Alec Hoyland

doi:10.7554/elife.62500

Abstract

Neuronal representations of spatial location and movement speed in the medial entorhinal cortex during the 'active' theta state of the brain are important for memory-guided navigation and rely on visual inputs. However, little is known about how visual inputs change neural dynamics as a function of running speed and time. By manipulating visual inputs in mice, we demonstrate that changes in spatial stability of grid cell firing correlate with changes in a proposed speed signal by local field potential theta frequency. In contrast, visual inputs do not alter the running speed-dependent gain in neuronal firing rates. Moreover, we provide evidence that sensory inputs other than visual inputs can support grid cell firing, though less accurately, in complete darkness. Finally, changes in spatial accuracy of grid cell firing on a 10 s time scale suggest that grid cell firing is a function of velocity signals integrated over past time.

Highlights

The spatially periodic firing of grid cells in the medial entorhinal cortex (MEC) (Fyhn et al, 2008; Fyhn et al, 2004; Hafting et al, 2005) is widely recognized as a neuronal correlate of memoryguided and/or self-motion-based spatial navigation (McNaughton et al, 2006)
We first studied if the absence of visual inputs during darkness changed the relationship between local field potential (LFP) theta frequency and running speed
Gray background highlights the interval of acceleration values between À5 cm/s2 and 5 cm/s2. (G) LFP theta frequency vs. running speed relationship based on the subset of time points where the running acceleration is near zero in the interval shown in F between À5 cm/s2 and 5 cm/s2. (H–L) Each data point shows the mean across all epochs of the same condition from 78 recording sessions from 14 mice. (H) LFP theta-frequency speed tuning curves for sequential 10 s blocks after the start of light and dark conditions

Summary

Introduction

The spatially periodic firing of grid cells in the medial entorhinal cortex (MEC) (Fyhn et al, 2008; Fyhn et al, 2004; Hafting et al, 2005) is widely recognized as a neuronal correlate of memoryguided and/or self-motion-based spatial navigation (McNaughton et al, 2006). Computational models of grid cells including attractor network models (Burak and Fiete, 2009; Fuhs and Touretzky, 2006), oscillatory interference models (Blair et al, 2008; Burgess, 2008; Burgess et al, 2007; Hasselmo, 2008; Zilli and Hasselmo, 2010), hybrid models of attractor networks and oscillatory interference (Bush and Burgess, 2014), and probabilistic learning models (Cheung, 2016) suggest that grid cells integrate running direction and traveled distance to maintain a spatially periodic firing pattern during path integration (Gil et al, 2018; Jacob et al, 2019). Two more recent studies on mice reported a rapid and nearly complete loss of spatially

Methods

Results

Conclusion