Tracking the Flow of Hippocampal Computation: Pattern Separation, Pattern Completion, and Attractor Dynamics

By James J. Knierim, Joshua P. Neunuebel. 2015

262 citations recorded by the source corpus.

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.

Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience

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Citations in the corpus

Re-evaluating circuit mechanisms underlying pattern separation (2019, neutral): “As the first stage in this pathway, the dentate gyrus is thought to separate entorhinal input patterns prior to memory storage in the hippocampus (Marr, 1971; McNaughton and Morris, 1987; Yassa and Stark, 2011; Schmidt et al., 2012; Knierim and Neunuebel, 2016; Rolls, 2016).”
In vivo imaging of dentate gyrus mossy cells in behaving mice (2017, background): “The mammalian hippocampus supports spatial information processing and episodic memory by routing information through its canonical trisynaptic circuit: from the dentate gyrus (DG) input node, to area CA3, and finally to the CA1 output node, with each subfield carrying out specialized computational o”
What Learning Systems do Intelligent Agents Need? Complementary Learning Systems Theory Updated. (2016, unknown): “, what happened) aspects of an event are thought to be processed primarily by parallel streams before converging in the hippocampus at the level of the DG/CA3 subregions [37].”
Physiological properties and behavioral correlates of hippocampal granule cells and mossy cells (2017, unknown): “Theoretical work, clinical imaging, and lesion experiments suggest that an important computational function of the hippocampal dentate gyrus (DG) is pattern separation (Marr, 1971; McNaughton and Morris, 1987; Treves and Rolls, 1994; Rolls and Kesner, 2006; Yassa and Stark, 2011; Myers and Scharfman”
Strong Evidence for Pattern Separation in Human Dentate Gyrus (2016, methodology): “…technique that is particularly appropriate given that this computation is defined at the level of the underlying representations (Treves and Rolls, 1994; McClelland et al., 1995; Norman and O’Reilly, 2003; Haynes and Rees, 2006; Davis and Poldrack, 2013; Haynes, 2015; Knierim and Neunuebel, 2016).”