Abstract
Navigation through space involves learning and representing relationships between past, current, and future locations. In mammals, this might rely on the hippocampal theta phase code, where in each cycle of the theta oscillation, spatial representations provided by neuronal sequences start behind the animal's true location and then sweep forward. However, the exact relationship between theta phase, represented position and true location remains unclear and even paradoxical. Here, we formalize previous notions of 'spatial' or 'temporal' theta sweeps that have appeared in the literature. We analyze single-cell and population variables in unit recordings from rat CA1 place cells and compare them to model simulations based on each of these schemes. We show that neither spatial nor temporal sweeps quantitatively accounts for how all relevant variables change with running speed. To reconcile these schemes with our observations, we introduce 'behavior-dependent' sweeps, in which theta sweep length and place field properties, such as size and phase precession, vary across the environment depending on the running speed characteristic of each location. These behavior-dependent spatial maps provide a structured heterogeneity that is essential for understanding the hippocampal code.
Highlights
Hippocampal place cells elevate their firing rates within circumscribed regions in the environment (‘place fields’) (O’Keefe and Dostrovsky, 1971)
Neuronal sequences during theta, the primary variable to be explained, it is linked to the activity of single place cells as follows
Each cell is considered to posses a ‘true place field’ (Sanders et al, 2015; Lisman and a Grace, 2005), which corresponds to the positions represented by the cell, i.e, a cell becomes active when the position represented by the population, r(t), falls within the cell’s true place field
Summary
Hippocampal place cells elevate their firing rates within circumscribed regions in the environment (‘place fields’) (O’Keefe and Dostrovsky, 1971). The position r(t) represented by the hippocampal population at time t appears to deviate from the physical location x(t) of the animal, sweeping from past to future positions during each theta cycle (Maurer et al, 2012; Gupta et al, 2012; Muessig et al, 2019; Kay et al, 2020; Zheng et al, 2021) This phenomenon suggests that beyond the representation of the current spatial location of an animal, the hippocampal theta code more generally encompasses representations of past, present and future events (Dragoi and Buzsáki, 2006; Cei et al, 2014; Terada et al, 2017). These studies indicate that the theta phase code plays a supporting role in a wide array of cognitive functions, such as sequential learning (Lisman and Idiart, 1995; Skaggs et al, 1996; Reifenstein et al, 2021), prediction (Lisman and Redish, 2009; Kay et al, 2020) and planning (Johnson and Redish, 2007; Erdem and Hasselmo, 2012; Bolding et al, 2020; Bush et al, 2015)
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