Extensive work in computational modeling has highlighted the advantages for employing sparse yet distributed data representation and storage Kanerva (1998), properties that extend to neuronal networks encoding mnemonic information (memory traces or engrams). While neurons that participate in an engram are distributed across multiple brain regions, within each region, the cellular sparsity of the mnemonic representation appears to be quite fixed. Although technological advances have enabled significant progress in identifying and manipulating engrams, relatively little is known about the region-dependent microcircuit rules governing the cellular sparsity of an engram. Here we review recent studies examining the mechanisms that help shape engram architecture and examine how these processes may regulate memory function. We speculate that countervailing forces in local microcircuits contribute to the generation and maintenance of engrams and discuss emerging questions regarding how engrams are formed, stored and used.

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Persistent URL dx.doi.org/10.1016/j.conb.2018.10.013, hdl.handle.net/1765/112046
Journal Current Opinion in Neurobiology
Rao-Ruiz, P, Yu, J. (Julia), Kushner, S.A, & Josselyn, S.A. (2019). Neuronal competition: microcircuit mechanisms define the sparsity of the engram. Current Opinion in Neurobiology (Vol. 54, pp. 163–170). doi:10.1016/j.conb.2018.10.013