Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/2467
Appears in Collections:Psychology Journal Articles
Peer Review Status: Refereed
Title: A single-trace dual-process model of episodic memory: A novel computational account of familiarity and recollection
Author(s): Greve, Andrea
Donaldson, David
van Rossum, Mark C W
Contact Email: did1@stir.ac.uk
Keywords: episodic memory model
Hopfield network
recognition
recollection
familiarity
Issue Date: Feb-2010
Date Deposited: 14-Oct-2010
Citation: Greve A, Donaldson D & van Rossum MCW (2010) A single-trace dual-process model of episodic memory: A novel computational account of familiarity and recollection. Hippocampus, 20 (2), pp. 235-251. https://doi.org/10.1002/hipo.20606
Abstract: Dual-process theories of episodic memory state that retrieval is contingent on two independent processes: familiarity (providing a sense of oldness) and recollection (recovering events and their context). A variety of studies have reported distinct neural signatures for familiarity and recollection, supporting dual-process theory. One outstanding question is whether these signatures reflect the activation of distinct memory traces or the operation of different retrieval mechanisms on a single memory trace. We present a computational model that uses a single neuronal network to store memory traces, but two distinct and independent retrieval processes access the memory. The model is capable of performing familiarity and recollection-based discrimination between old and new patterns, demonstrating that dual-process models need not to rely on multiple independent memory traces, but can use a single trace. Importantly, our putative familiarity and recollection processes exhibit distinct characteristics analogous to those found in empirical data; they diverge in capacity and sensitivity to sparse and correlated patterns, exhibit distinct ROC curves, and account for performance on both item and associative recognition tests. The demonstration that a single-trace, dual-process model can account for a range of empirical findings highlights the importance of distinguishing between neuronal processes and the neuronal representations on which they operate.
DOI Link: 10.1002/hipo.20606
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