The notion of attractor networks is the leading hypothesis for how associative memories are stored and recalled. A defining/nanatomical feature of such networks is excitatory recurrent connections. These ‘‘attract’’ the firing pattern of the network to/na stored pattern, even when the external input is incomplete (pattern completion). The CA3 region of the hippocampus has/nbeen postulated to be such an attractor network; however, the experimental evidence has been ambiguous, leading to the/nsuggestion ...
The notion of attractor networks is the leading hypothesis for how associative memories are stored and recalled. A defining/nanatomical feature of such networks is excitatory recurrent connections. These ‘‘attract’’ the firing pattern of the network to/na stored pattern, even when the external input is incomplete (pattern completion). The CA3 region of the hippocampus has/nbeen postulated to be such an attractor network; however, the experimental evidence has been ambiguous, leading to the/nsuggestion that CA3 is not an attractor network. In order to resolve this controversy and to better understand how CA3/nfunctions, we simulated CA3 and its input structures. In our simulation, we could reproduce critical experimental results and/nestablish the criteria for identifying attractor properties. Notably, under conditions in which there is continuous input, the/noutput should be ‘‘attracted’’ to a stored pattern. However, contrary to previous expectations, as a pattern is gradually/n‘‘morphed’’ from one stored pattern to another, a sharp transition between output patterns is not expected. The observed/nfiring patterns of CA3 meet these criteria and can be quantitatively accounted for by our model. Notably, as morphing/nproceeds, the activity pattern in the dentate gyrus changes; in contrast, the activity pattern in the downstream CA3 network/nis attracted to a stored pattern and thus undergoes little change. We furthermore show that other aspects of the observed/nfiring patterns can be explained by learning that occurs during behavioral testing. The CA3 thus displays both the learning/nand recall signatures of an attractor network. These observations, taken together with existing anatomical and behavioral/nevidence, make the strong case that CA3 constructs associative memories based on attractor dynamics.
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