A model of episodic memory: Mental time travel along encoded trajectories using grid cells

https://doi.org/10.1016/j.nlm.2009.07.005Get rights and content

Abstract

The definition of episodic memory includes the concept of mental time travel: the ability to re-experience a previously experienced trajectory through continuous dimensions of space and time, and to recall specific events or stimuli along this trajectory. Lesions of the hippocampus and entorhinal cortex impair human episodic memory function and impair rat performance in tasks that could be solved by retrieval of trajectories. Recent physiological data suggests a novel model for encoding and retrieval of trajectories, and for associating specific stimuli with specific positions along the trajectory. During encoding in the model, external input drives the activity of head direction cells. Entorhinal grid cells integrate the head direction input to update an internal representation of location, and drive hippocampal place cells. Trajectories are encoded by Hebbian modification of excitatory synaptic connections between hippocampal place cells and head direction cells driven by external action. Associations are also formed between hippocampal cells and sensory stimuli. During retrieval, a sensory input cue activates hippocampal cells that drive head direction activity via previously modified synapses. Persistent spiking of head direction cells maintains the direction and speed of the action, updating the activity of entorhinal grid cells that thereby further update place cell activity. Additional cells, termed arc length cells, provide coding of trajectory segments based on the one-dimensional arc length from the context of prior actions or states, overcoming ambiguity where the overlap of trajectory segments causes multiple head directions to be associated with one place. These mechanisms allow retrieval of complex, self-crossing trajectories as continuous curves through space and time.

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.

References (118)

  • M.E. Hasselmo et al.

    Mechanisms underlying working memory for novel information

    Trends in Cognitive Science

    (2006)
  • I. Lee et al.

    Gradual translocation of spatial correlates of neuronal firing in the hippocampus toward prospective reward locations

    Neuron

    (2006)
  • I. Lee et al.

    Disruption of delayed memory for a sequence of spatial locations following CA1- or CA3-lesions of the dorsal hippocampus

    Neurobiology of Learning and Memory

    (2005)
  • K. Louie et al.

    Temporally structured replay of awake hippocampal ensemble activity during rapid eye movement sleep

    Neuron

    (2001)
  • M.S. Matell et al.

    Cortico-striatal circuits and interval timing: Coincidence detection of oscillatory processes

    Brain Research Cognitive Brain Research

    (2004)
  • B.L. McNaughton et al.

    Hippocampal synaptic enhancement and information storage within a distributed memory system

    Trends in Neurosciences

    (1987)
  • P.E. Sharp et al.

    The anatomical and computational basis of the rat head-direction cell signal

    Trends in Neurosciences

    (2001)
  • P.E. Sharp et al.

    Movement-related correlates of single cell activity in the interpeduncular nucleus and habenula of the rat during a pellet-chasing task

    Behavioural Brain Research

    (2006)
  • H.A. Steffenach et al.

    Spatial memory in the rat requires the dorsolateral band of the entorhinal cortex

    Neuron

    (2005)
  • K. Stepankova et al.

    Object-location memory impairment in patients with thermal lesions to the right or left hippocampus

    Neuropsychologia

    (2004)
  • J.S. Taube

    Head direction cells and the neurophysiological basis for a sense of direction

    Progress in Neurobiology

    (1998)
  • K.L. Agster et al.

    The hippocampus and disambiguation of overlapping sequences

    Journal of Neuroscience

    (2002)
  • A. Alonso et al.

    Differential electroresponsiveness of stellate and pyramidal-like cells of medial entorhinal cortex layer II

    Journal of Neurophysiology

    (1993)
  • A. Alonso et al.

    Subthreshold Na-dependent theta-like rhythmicity in stellate cells of entorhinal cortex layer II

    Nature

    (1989)
  • C. Barry et al.

    Experience-dependent rescaling of entorhinal grids

    Nature Neuroscience

    (2007)
  • T.W. Berger et al.

    Single-unit analysis of different hippocampal cell types during classical conditioning of rabbit nictitating membrane response

    Journal of Neurophysiology

    (1983)
  • V.D. Bohbot et al.

    Memory deficits characterized by patterns of lesions to the hippocampus and parahippocampal cortex

    Annals of the New York Academy of Sciences

    (2000)
  • G.D. Brown et al.

    Oscillator-based memory for serial order

    Psychological Review

    (2000)
  • V.H. Brun et al.

    Progressive increase in grid scale from dorsal to ventral medial entorhinal cortex

    Hippocampus

    (2008)
  • J.G. Bunce et al.

    Intraseptal infusion of the cholinergic agonist carbachol impairs delayed-non-match-to-sample radial arm maze performance in the rat

    Hippocampus

    (2004)
  • O. Buresova et al.

    Differential effects of cholinergic blockade on performance of rats in the water tank navigation task and in a radial water maze

    Behavioral Neuroscience

    (1986)
  • N. Burgess

    Grid cells and theta as oscillatory interference. Theory and predictions

    Hippocampus

    (2008)
  • N. Burgess et al.

    An oscillatory interference model of grid cell firing

    Hippocampus

    (2007)
  • N. Burgess et al.

    Robotic and neuronal simulation of the hippocampus and rat navigation

    Philosophical Transactions of the Royal Society of London Series B – Biological Sciences

    (1997)
  • Burgess, N., Barry, C., Jeffery, K. J., & O’Keefe, J. (2005). A grid and place cell model of path integration utilizing...
  • M. Caballero-Bleda et al.

    Regional and laminar organization of projections from the presubiculum and parasubiculum to the entorhinal cortex: An anterograde tracing study in the rat

    Journal of Comparative Neurology

    (1993)
  • S. Corkin

    Lasting consequences of bilateral medial temporal lobectomy: Clinical course and experimental findings in H.M

    Seminars in Neurology

    (1984)
  • K. Diba et al.

    Forward and reverse hippocampal place-cell sequences during ripples

    Nature Neuroscience

    (2007)
  • C.T. Dickson et al.

    Properties and role of I(h) in the pacing of subthreshold oscillations in entorhinal cortex layer II neurons

    Journal of Neurophysiology

    (2000)
  • A.V. Egorov et al.

    Graded persistent activity in entorhinal cortex neurons

    Nature

    (2002)
  • H. Eichenbaum et al.

    From conditioning to conscious recollection: Memory systems of the brain

    (2001)
  • H. Eichenbaum et al.

    From conditioning to conscious recollection

    (2003)
  • H. Eichenbaum et al.

    Towards a functional organization of the medial temporal lobe memory system: Role of the parahippocampal and medial entorhinal cortical areas

    Hippocampus

    (2008)
  • A.D. Ekstrom et al.

    Cellular networks underlying human spatial navigation

    Nature

    (2003)
  • T.A. Engel et al.

    Subthreshold membrane-potential resonances shape spike-train patterns in the entorhinal cortex

    Journal of Neurophysiology

    (2008)
  • I. Erchova et al.

    Dynamics of rat entorhinal cortex layer II and III cells: Characteristics of membrane potential resonance at rest predict oscillation properties near threshold

    Journal of Physiology

    (2004)
  • N.J. Fortin et al.

    Critical role of the hippocampus in memory for sequences of events

    Nature Neuroscience

    (2002)
  • D.J. Foster et al.

    A model of hippocampally dependent navigation, using the temporal difference learning rule

    Hippocampus

    (2000)
  • D.J. Foster et al.

    Reverse replay of behavioural sequences in hippocampal place cells during the awake state

    Nature

    (2006)
  • M.C. Fuhs et al.

    A spin glass model of path integration in rat medial entorhinal cortex

    Journal of Neuroscience

    (2006)
  • Cited by (118)

    View all citing articles on Scopus
    View full text