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Cell Groups Reveal Structure of Stimulus Space

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  • Carina Curto
  • Vladimir Itskov

Abstract

An important task of the brain is to represent the outside world. It is unclear how the brain may do this, however, as it can only rely on neural responses and has no independent access to external stimuli in order to “decode” what those responses mean. We investigate what can be learned about a space of stimuli using only the action potentials (spikes) of cells with stereotyped—but unknown—receptive fields. Using hippocampal place cells as a model system, we show that one can (1) extract global features of the environment and (2) construct an accurate representation of space, up to an overall scale factor, that can be used to track the animal's position. Unlike previous approaches to reconstructing position from place cell activity, this information is derived without knowing place fields or any other functions relating neural responses to position. We find that simply knowing which groups of cells fire together reveals a surprising amount of structure in the underlying stimulus space; this may enable the brain to construct its own internal representations.Author Summary: We construct our understanding of the world solely from neuronal activity generated in our brains. How do we do this? Many studies have investigated how neural activity is related to outside stimuli, and maps of these relationships (often called receptive fields) are routinely computed from data collected in neuroscience experiments. Yet how the brain can understand the meaning of this activity, without the dictionary provided by these maps, remains a mystery. We tackle this fundamental question in the context of hippocampal place cells—i.e., neurons in rodent hippocampus whose activity is strongly correlated to the animal's position in space. We find that the structure of stimulus space can be revealed by exploiting relationships between groups of cofiring neurons in response to different stimuli. We provide a ‘proof of principle’ by demonstrating constructively how the topology of space and the animal's position in an environment can be derived purely from the action potentials fired by hippocampal place cells. In this way, the brain may be able to build up structured representations of stimulus spaces that are then used to represent external stimuli.

Suggested Citation

  • Carina Curto & Vladimir Itskov, 2008. "Cell Groups Reveal Structure of Stimulus Space," PLOS Computational Biology, Public Library of Science, vol. 4(10), pages 1-13, October.
  • Handle: RePEc:plo:pcbi00:1000205
    DOI: 10.1371/journal.pcbi.1000205
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    References listed on IDEAS

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    Cited by:

    1. Sudhamayee, K. & Krishna, M. Gopal & Manimaran, P., 2023. "Simplicial network analysis on EEG signals," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    2. Samir Chowdhury & Bowen Dai & Facundo Mémoli, 2018. "The importance of forgetting: Limiting memory improves recovery of topological characteristics from neural data," PLOS ONE, Public Library of Science, vol. 13(9), pages 1-20, September.
    3. Y Dabaghian & F Mémoli & L Frank & G Carlsson, 2012. "A Topological Paradigm for Hippocampal Spatial Map Formation Using Persistent Homology," PLOS Computational Biology, Public Library of Science, vol. 8(8), pages 1-14, August.
    4. Mamiko Arai & Vicky Brandt & Yuri Dabaghian, 2014. "The Effects of Theta Precession on Spatial Learning and Simplicial Complex Dynamics in a Topological Model of the Hippocampal Spatial Map," PLOS Computational Biology, Public Library of Science, vol. 10(6), pages 1-14, June.
    5. Williams, Robert, 2018. "Strongly maximal intersection-complete neural codes on grids are convex," Applied Mathematics and Computation, Elsevier, vol. 336(C), pages 162-175.

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