Model of working memory based on negative derivative feedback (Lim and Goldman, 2013)

We proposed a model of working memory in which recurrent synaptic interactions provide a corrective feedback that enables persistent activity to be maintained stably for prolonged durations. When recurrent excitatory and inhibitory inputs to memory neurons were balanced in strength and offset in time, drifts in activity triggered a corrective signal that counteracted memory decay. Circuits containing this mechanism temporally integrated their inputs, generated the irregular neural firing observed during persistent activity and were robust against common perturbations that severely disrupted previous models of short-term memory storage.

Model Type: Realistic Network; Synapse

Model Concept(s): Working memory

Simulation Environment: MATLAB

Implementer(s): Lim, Sukbin


Lim S, Goldman MS. (2013). Balanced cortical microcircuitry for maintaining information in working memory. Nature neuroscience. 16 [PubMed]

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