Review
Tracking the flow of hippocampal computation: Pattern separation, pattern completion, and attractor dynamics

https://doi.org/10.1016/j.nlm.2015.10.008Get rights and content

Highlights

  • Experiments testing classic computational theories of hippocampus are reviewed.

  • LEC and MEC provided conflicting inputs to hippocampus.

  • DG performed pattern separation and CA3 performed pattern completion.

  • Possible contributions to hippocampus-dependent memory are discussed.

Abstract

Classic computational theories of the mnemonic functions of the hippocampus ascribe the processes of pattern separation to the dentate gyrus (DG) and pattern completion to the CA3 region. Until the last decade, the large majority of single-unit studies of the hippocampus in behaving animals were from the CA1 region. The lack of data from the DG, CA3, and the entorhinal inputs to the hippocampus severely hampered the ability to test these theories with neurophysiological techniques. The past ten years have seen a major increase in the recordings from the CA3 region and the medial entorhinal cortex (MEC), with an increasing (but still limited) number of experiments from the lateral entorhinal cortex (LEC) and DG. This paper reviews a series of studies in a local–global cue mismatch (double-rotation) experiment in which recordings were made from cells in the anterior thalamus, MEC, LEC, DG, CA3, and CA1 regions. Compared to the standard cue environment, the change in the DG representation of the cue-mismatch environment was greater than the changes in its entorhinal inputs, providing support for the theory of pattern separation in the DG. In contrast, the change in the CA3 representation of the cue-mismatch environment was less than the changes in its entorhinal and DG inputs, providing support for a pattern completion/error correction function of CA3. The results are interpreted in terms of continuous attractor network models of the hippocampus and the relationship of these models to pattern separation and pattern completion theories. Whereas DG may perform an automatic pattern separation function, the attractor dynamics of CA3 allow it to perform a pattern separation or pattern completion function, depending on the nature of its inputs and the relative strength of the internal attractor dynamics.

Introduction

Although most computational theories of the mnemonic functions of the hippocampus have focused on the CA3 and dentate gyrus (DG) regions, the large majority of single-unit studies of the hippocampus have been recordings from the CA1 region. This emphasis on CA1 is understandable for both functional and practical reasons. CA1 is the region that primarily transmits the output of DG/CA3 processing to the rest of the cerebrum (Witter & Amaral, 2004). Thus, it can serve as a functional readout of the information provided by the hippocampus to other brain areas that are involved in hippocampus-dependent cognition and behavior. Moreover, CA1 is the first cell layer encountered in the rodent hippocampus when an electrode is advanced from the dorsal surface of the brain, and it is by far the easiest layer of the hippocampus to record large ensembles of well-isolated units.

Although recordings from CA1 can illuminate the types of information and representations being sent to other brain regions, these recordings in isolation can inform little about the nature of the information processing that occurs within the hippocampal circuitry. For example, one may know that CA1 place cells form independent spatial representations of two distinct environments (Bostock, Muller, & Kubie, 1991). However, this knowledge alone tells us little about the computational processing that creates these two representations, and whether that processing occurs within CA1, in upstream hippocampal regions like DG or CA3, or even in regions entirely afferent to the hippocampus. To understand the neural computations of the hippocampus, it is necessary to understand the information represented in hippocampal inputs, in its internal processing stages, and in its outputs, as well as the transformations that occur as information is processed through these circuits.

This article will review a series of studies from our lab over the past decade in which we recorded the activity of hippocampal input regions and output regions, as well as the intrahippocampal processing in the DG and CA3 regions. To induce controlled, parametric changes to the animal’s environment, we used a “double rotation” manipulation, in which the local reference frame of the behavioral track was placed in varying degrees of conflict with the global reference frame of the laboratory environment (Knierim, 2002, Shapiro et al., 1997). We investigated how neural populations in the hippocampal system responded to these alterations in order to deduce the neural representations and computations associated with the different regions. In particular, we addressed the questions of whether we can interpret (1) DG responses as evidence for its proposed role of performing pattern separation on its inputs and (2) CA3 responses as evidence for its proposed role of performing pattern completion (or the related concepts of error correction and generalization) on its inputs. We begin with a brief history of the computational theories of pattern separation and completion.

Section snippets

Classic theories of DG function: Pattern separation in DG vs. pattern completion in CA3

The most prominent theory of DG function is the pattern separation theory (Kesner et al., 2000, McNaughton and Morris, 1987, McNaughton and Nadel, 1990, Rolls and Treves, 1998, Yassa and Stark, 2011), which originated in David Marr’s theory of the cerebellum (Marr, 1969). Marr proposed that the cerebellar granule layer created a very sparse representation of incoming sensorimotor input by an expansion recoding strategy; that is, highly overlapping representations encoded by populations of

Double rotation experiments

With these considerations in mind, we will now review a series of neurophysiological recording experiments from hippocampal afferent regions (the MEC, LEC, and anterior thalamus), intrahippocampal regions (DG and CA3), and the hippocampal output layer (CA1). In these experiments, rats ran clockwise on a circular track (Knierim, 2002) (Fig. 3). The track was divided into 4 quadrants, each with a distinct visual and tactile texture. The track was centered in a room with a circular, black curtain

Final comments and caveats

With this review we hope to have demonstrated how a series of experimental studies from our laboratory over the past decade have provided direct, physiological evidence in favor of classic models of hippocampal computation and its relationship to memory. We have taken the approach from the computational literature that the concepts of pattern separation and pattern completion can only be studied directly in terms of input–output transformations of neural representations (McClelland and Goddard,

Acknowledgments

We thank I. Lee, D. Yoganarasimha, F. Savelli, and G. Rao for help in data collection for some of the figures shown in this manuscript. The experiments reviewed here were supported by Public Health Service grants NS039456 and MH094146 and by the Johns Hopkins University Brain Sciences Institute. The funding agency had no role in the design, data collection, analysis, or writing of the paper.

References (83)

  • B.L. McNaughton et al.

    Hippocampal synaptic enhancement and information storage within a distributed memory system

    Trends in Neuroscience

    (1987)
  • T. Nakashiba et al.

    Young dentate granule cells mediate pattern separation, whereas old granule cells facilitate pattern completion

    Cell

    (2012)
  • J.P. Neunuebel et al.

    CA3 retrieves coherent representations from degraded input: Direct evidence for CA3 pattern completion and dentate gyrus pattern separation

    Neuron

    (2014)
  • E.T. Rolls et al.

    A computational theory of hippocampal function, and empirical tests of the theory

    Progress in Neurobiology

    (2006)
  • M.P. Witter et al.

    Hippocampal formation

  • M.A. Yassa et al.

    Pattern separation in the hippocampus

    Trends in Neurosciences

    (2011)
  • K.G. Akers et al.

    Hippocampal neurogenesis regulates forgetting during adulthood and infancy

    Science

    (2014)
  • A. Bakker et al.

    Pattern separation in the human hippocampal CA3 and dentate gyrus

    Science

    (2008)
  • H.T. Blair

    A thalamocortical circuit for computing directional heading in the rat

    Advances in Neural Information Processing Systems

    (1996)
  • E. Bostock et al.

    Experience-dependent modifications of hippocampal place cell firing

    Hippocampus

    (1991)
  • V.H. Brun et al.

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

    Hippocampus

    (2008)
  • D.A. Caruana et al.

    New insights into the regulation of synaptic plasticity from an unexpected place: Hippocampal area CA2

    Learning & Memory

    (2012)
  • L.L. Colgin et al.

    Frequency of gamma oscillations routes flow of information in the hippocampus

    Nature

    (2009)
  • L.L. Colgin et al.

    Attractor-map versus autoassociation based attractor dynamics in the hippocampal network

    Journal of Neurophysiology

    (2010)
  • S.S. Deshmukh et al.

    Representation of non-spatial and spatial information in the lateral entorhinal cortex

    Frontiers in Behavioral Neuroscience

    (2011)
  • S.S. Deshmukh et al.

    Theta modulation in the medial and the lateral entorhinal cortex

    Journal of Neurophysiology

    (2010)
  • P.E. Gilbert et al.

    Dissociating hippocampal subregions: Double dissociation between dentate gyrus and CA1

    Hippocampus

    (2001)
  • T. Hafting et al.

    Hippocampus-independent phase precession in entorhinal grid cells

    Nature

    (2008)
  • T. Hafting et al.

    Microstructure of a spatial map in the entorhinal cortex

    Nature

    (2005)
  • E.L. Hargreaves et al.

    Major dissociation between medial and lateral entorhinal input to dorsal hippocampus

    Science

    (2005)
  • E.L. Hargreaves et al.

    Cohesiveness of spatial and directional representations recorded from neural ensembles in the anterior thalamus, parasubiculum, medial entorhinal cortex, and hippocampus

    Hippocampus

    (2007)
  • Hasselmo, M. E. (2005). The role of hippocampal regions CA3 and CA1 in matching entorhinal input with retrieval of...
  • M.E. Hasselmo et al.

    A proposed function for hippocampal theta rhythm: Separate phases of encoding and retrieval enhance reversal of prior learning

    Neural Computation

    (2002)
  • F.L. Hitti et al.

    The hippocampal CA2 region is essential for social memory

    Nature

    (2014)
  • K.M. Igarashi et al.

    Coordination of entorhinal–hippocampal ensemble activity during associative learning

    Nature

    (2014)
  • R.P. Kesner et al.

    The role of postnatal neurogenesis in supporting remote memory and spatial metric processing

    Hippocampus

    (2014)
  • J.J. Knierim

    Dynamic interactions between local surface cues, distal landmarks, and intrinsic circuitry in hippocampal place cells

    Journal of Neuroscience

    (2002)
  • J.J. Knierim

    Hippocampal remapping: Implications for spatial learning and navigation

  • J.J. Knierim et al.

    Place cells, head direction cells, and the learning of landmark stability

    The Journal of Neuroscience

    (1995)
  • J.J. Knierim et al.

    Interactions between idiothetic cues and external landmarks in the control of place cells and head direction cells

    Journal of Neurophysiology

    (1998)
  • J.J. Knierim et al.

    Functional correlates of the lateral and medial entorhinal cortex: Objects, path integration and local–global reference frames

    Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences

    (2013)
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