Cited by 391Memory and Neural MechanismsSpatial Cognition and NavigationNeural dynamics and brain function

The hippocampus as a cognitive graph.

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Muller, R U, Stead, M, Pach, J·1996·The Journal of general physiology

Abstract

A theory of cognitive mapping is developed that depends only on accepted properties of hippocampal function, namely, long-term potentiation, the place cell phenomenon, and the associative or recurrent connections made among CA3 pyramidal cells. It is proposed that the distance between the firing fields of connected pairs of CA3 place cells is encoded as synaptic resistance (reciprocal synaptic strength). The encoding occurs because pairs of cells with coincident or overlapping fields will tend to fire together in time, thereby causing a decrease in synaptic resistance via long-term potentiation; in contrast, cells with widely separated fields will tend never to fire together, causing no change or perhaps (via long-term depression) an increase in synaptic resistance. A network whose connection pattern mimics that of CA3 and whose connection weights are proportional to synaptic resistance can be formally treated as a weighted, directed graph. In such a graph, a "node" is assigned to each CA3 cell and two nodes are connected by a "directed edge" if and only if the two corresponding cells are connected by a synapse. Weighted, directed graphs can be searched for an optimal path between any pair of nodes with standard algorithms. Here, we are interested in finding the path along which the sum of the synaptic resistances from one cell to another is minimal. Since each cell is a place cell, such a path also corresponds to a path in two-dimensional space. Our basic finding is that minimizing the sum of the synaptic resistances along a path in neural space yields the shortest (optimal) path in unobstructed two-dimensional space, so long as the connectivity of the network is great enough. In addition to being able to find geodesics in unobstructed space, the same network enables solutions to the "detour" and "shortcut" problems, in which it is necessary to find an optimal path around a newly introduced barrier and to take a shorter path through a hole opened up in a preexisting barrier, respectively. We argue that the ability to solve such problems qualifies the proposed hippocampal object as a cognitive map. Graph theory thus provides a sort of existence proof demonstrating that the hippocampus contains the necessary information to function as a map, in the sense postulated by others (O'Keefe, J., and L. Nadel. 1978. The Hippocampus as a Cognitive Map. Clarendon Press, Oxford, UK). It is also possible that the cognitive mapping functions of the hippocampus are carried out by parallel graph searching algorithms implemented as neural processes. This possibility has the great attraction that the hippocampus could then operate in much the same way to find paths in general problem space; it would only be necessary for pyramidal cells to exhibit a strong nonpositional firing correlate.

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  • A number of neurobiologically inspired, fully mechanistic computational models of navigational behavior have been developed to account for the ability of animals relying on allocentric frameworks to perform path planning without resorting to mentalistic explanations.

    “A number of neurobiologically inspired, fully mechanistic computational models of navigational behavior have been developed to account for the ability of animals relying on allocentric frameworks to perform path planning, without the need to resort to “mentalistic” explanations”

    From Spatial Cognition in Teleost Fish: Strategies and Mechanisms (2021) · cites this paper as [92]

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Authors
Muller, R. U., Stead, M., & Pach, J.
Affiliations
State University of New York (US)
Venue
The Journal of general physiology
Published
1996-06-01
Volume
107
Issue
6
Pages
663-694
ISSN
  • 0022-1295 (ISSN-L)
  • 1540-7748
OpenAlex
W2102984289
Cited by
391
References
7
Citations by year
2026: 11 · 2025: 10 · 2024: 23 · 2023: 12 · 2022: 7 · 2021: 12 · 2020: 37 · 2019: 24 · 2018: 11 · 2017: 10 · 2016: 10 · 2015: 6 · 2014: 12 · 2013: 18 · 2012: 10
FWCI
2.60
Type
journal article
Language
en
Open access
Locations
  • The Journal of General Physiology (publishedVersion)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by-nc-sa)
  • PubMed Central (publishedVersion, cc-by-nc-sa)
  • PubMed (publishedVersion)
  • Infoscience (Ecole Polytechnique Fédérale de Lausanne) (submittedVersion)
  • Infoscience (Ecole Polytechnique Fédérale de Lausanne) (submittedVersion, cc-by-nc-nd)
Funders
  • National Institutes of Health (5r01ns014497-16)
  • National Institute of Neurological Disorders and Stroke (NS14497, NS 20686, R01NS020686)
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
  • Physical Sciences › Engineering › Automotive Engineering › Spatial Cognition and Navigation
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
Keywords
hippocampus, cognitive maps, place cells, CA3 pyramidal cells, long-term potentiation, long-term depression, weighted directed graphs, shortest path, geodesics, spatial navigation, recurrent connectivity, associative memory, problem space search, artificial neural networks
MeSH terms
Animals, Brain Mapping, Cognition, Hippocampus, Humans, Models, Neurological, Nerve Net, Neural Pathways, Synapses

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