A model of episodic memory: Mental time travel along encoded trajectories using grid cells
Introduction
Episodic memory includes the capacity to internally re-experience the sequence of events that occurred at particular places and times, in what has been termed “mental time travel” (Eichenbaum and Cohen, 2001, Tulving, 2001, Tulving, 2002). Episodic memory includes the capacity to mentally retrace trajectories through previously visited locations, including re-experiencing specific stimuli encountered on this trajectory, and the relative timing of events. For example, you can probably remember the route you followed when you left your home this morning, with a memory of the locations you visited and the time you spent in individual locations. You can use this memory to remember where you parked the car, who you saw on your trip, or where you left your car keys. This aspect of episodic memory requires some means by which neurons can code continuous trajectories through space with time intervals representing the original episode. This also requires some means for encoding the location and time of specific events or stimuli encountered along this trajectory.
Physiological data shows that hippocampal activity during REM sleep can replay the relative time intervals of spiking activity evoked by different spatial locations during waking (Louie & Wilson, 2001), indicating the capacity to replay spatiotemporal trajectories with the same time scale as actual behavior. Other experiments also show that spiking activity in the hippocampal formation can maintain information about the relative timing of events (Berger et al., 1983, Deadwyler and Hampson, 2006, Hoehler and Thompson, 1980).
Lesion data suggests that encoding and retrieval of previously experienced episodic trajectories involves the entorhinal cortex and hippocampus. In humans, lesions of these structures cause profound impairments of episodic memory, tested both qualitatively and with quantitative measures in verbal memory tasks (Corkin, 1984, Eichenbaum and Cohen, 2003, Graf et al., 1984, Rempel-Clower et al., 1996, Scoville and Milner, 1957). Impairments in formation of object-location associations occur with right hippocampal or parahippocampal lesions (Bohbot et al., 2000, Bohbot et al., 1998, Milner et al., 1997, Stepankova et al., 2004). In rats, hippocampal manipulations impair performance in tasks that can be solved using episodic retrieval of specific recent trajectories, including the 8-arm radial maze (Bunce, Sabolek, & Chrobak, 2004), delayed spatial alternation (Ennaceur, Neave, & Aggleton, 1996), the Morris water maze with new platform location on each day (Buresova et al., 1986, Steele and Morris, 1999) and a task testing a sequence of spatial locations (Lee, Jerman, & Kesner, 2005). Spatial memory is also impaired by lesions of the entorhinal cortex (Steffenach, Witter, Moser, & Moser, 2005) and postsubiculum (Taube, Kesslak, & Cotman, 1992). Learning of spatial trajectories may be a special case of a general capacity for learning sequences within the hippocampus (Eichenbaum, Dudchenko, Wood, Shapiro, & Tanila, 1999), including the sequential order of sensory stimuli (Agster et al., 2002, Fortin et al., 2002, Kesner et al., 2002, Kesner and Novak, 1982).
Many previous models of hippocampal function focus on its role in spatial navigation to goals (Burgess et al., 1997, Foster et al., 2000, Touretzky and Redish, 1996, Trullier and Meyer, 2000), but not on episodic retrieval of specific trajectories. Most previous hippocampal models that focus on encoding and retrieval of sequences (Hasselmo and Eichenbaum, 2005, Jensen and Lisman, 1996a, Jensen and Lisman, 1996b, Levy, 1996, McNaughton and Morris, 1987, Minai and Levy, 1993, Redish and Touretzky, 1998, Treves and Rolls, 1994, Tsodyks et al., 1996, Wallenstein and Hasselmo, 1997, Zilli and Hasselmo, 2008c) focus on encoding associations between discrete sequential states (items or locations). However, recent data on grid cell firing in the entorhinal cortex (Barry et al., 2007, Hafting et al., 2005, Moser and Moser, 2008, Sargolini et al., 2006) suggests a different approach (Hasselmo, 2008b) in which each individual state (place) is associated with an action (the velocity coded by speed-modulated head direction cells).
This model of the episodic encoding and retrieval of trajectories can use either of two main classes of grid cell models. One class of models generates grid cells based on interference patterns (Burgess, 2008, Burgess et al., 2007). This model could use mechanisms of membrane potential oscillations shown in entorhinal neurons (Alonso and Llinas, 1989, Giocomo and Hasselmo, 2008a, Giocomo and Hasselmo, 2008b, Giocomo et al., 2007, Hasselmo et al., 2007), or could use mechanisms of stable persistent spiking (Egorov et al., 2002, Fransén et al., 2006, Hasselmo, 2008a, Tahvildari et al., 2007). The other class of models uses attractor dynamics to generate grid cell activity (Fuhs and Touretzky, 2006, McNaughton et al., 2006). The first type of model is used here, but either or both types of models could be used, because both models update grid cell position with a velocity signal from head direction cells. As shown here, a circuit mechanism using grid cells provides a substrate for encoding and retrieval of trajectories defined on continuous dimensions of space and time.
Section snippets
Model of trajectory encoding and retrieval
The model presented here will consider encoding and retrieval of a trajectory of movement through the environment by an agent over time. The agent could be a human being or other mammal. The circuit model of encoding and retrieval is summarized in Fig. 1. The physiological data used to justify the model has primarily been obtained from the rat, including data on entorhinal grid cells (Fyhn et al., 2007, Hafting et al., 2005, Moser and Moser, 2008), head direction cells in structures such as
Results
As shown in the figures, the model described here performs encoding and retrieval of complex spatial trajectories. Fig. 4 illustrates the basic components of the trajectory retrieval, which includes head direction cell activity (4A), grid cell phase (4B), and place cell activity (4C). In the figure, the actual trajectory run by the rat is shown in gray. This trajectory is from experimental data obtained in the Moser laboratory (Hafting et al., 2005). The rat forages along a meandering
Discussion
The model presented here uses grid cells, place cells, head direction cells and a set of context-dependent cells termed arc length cells to encode and retrieve neural activity associated with specific spatiotemporal trajectories through the environment. During encoding, external input drives head direction activity that drives entorhinal grid cell and hippocampal cell activity. Synaptic modification strengthens connections between hippocampal place cells and head direction cells. During
Acknowledgments
Research supported by Silvio O. Conte Center grant NIMH MH71702, NIMH R01 60013, NIMH R01 MH61492, NSF Science of Learning Center CELEST SBE 0354378.
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