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Authors: Katherine Goodman and John K. Bennett

Affiliation: University of Colorado Boulder, United States

Keyword(s): Serial Position Effect (SPE), Primacy, Recency, Hippocampus, Emergent Neural Network Simulation System, Leabra, Serial Recall, Working Memory.

Related Ontology Subjects/Areas/Topics: Agents ; Artificial Intelligence ; Bioinformatics ; Biomedical Engineering ; Enterprise Information Systems ; Information Systems Analysis and Specification ; Methodologies and Technologies ; Operational Research ; Simulation

Abstract: The Serial Position Effect (SPE) is a well-studied phenomenon in experimental psychology. SPE captures the idea that, when subjects are asked to recall list items, they are more likely to remember the first items and the last items, whether those items are numbers, non-words or elements of a story. Until recently, SPE has been generally considered to rely upon a two-store memory model, i.e., primacy (remembering initial items) and recency (remembering latter items) were thought to be the work of long term memory and short term memory, respectively. This paper reports the results of a basic hippocampus simulation study using the Leabra algorithm within the Emergent Neural Network Simulation System to model the SPE. Simulation results demonstrate that both primacy and recency of the SPE in a serial recall task can be replicated using only the hippocampus, suggesting that a one-store model of memory for this recall task is sufficient. It remains to be seen if this simulation mirrors the actual biological mechanism utilized. (More)

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Paper citation in several formats:
Goodman, K. and K. Bennett, J. (2014). Modeling the Serial Position Effect - Using the Emergent Neural Network Simulation System. In Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms (BIOSTEC 2014) - BIOINFORMATICS; ISBN 978-989-758-012-3; ISSN 2184-4305, SciTePress, pages 164-171. DOI: 10.5220/0004802701640171

@conference{bioinformatics14,
author={Katherine Goodman. and John {K. Bennett}.},
title={Modeling the Serial Position Effect - Using the Emergent Neural Network Simulation System},
booktitle={Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms (BIOSTEC 2014) - BIOINFORMATICS},
year={2014},
pages={164-171},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004802701640171},
isbn={978-989-758-012-3},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms (BIOSTEC 2014) - BIOINFORMATICS
TI - Modeling the Serial Position Effect - Using the Emergent Neural Network Simulation System
SN - 978-989-758-012-3
IS - 2184-4305
AU - Goodman, K.
AU - K. Bennett, J.
PY - 2014
SP - 164
EP - 171
DO - 10.5220/0004802701640171
PB - SciTePress