AIMS Neuroscience, 2016, 3(2): 181-202. doi: 10.3934/Neuroscience.2016.2.181 Research article Topical Section

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A Buffer Model Account of Behavioral and ERP Patterns in the Von Restorff Paradigm

Siri-Maria Kamp, Melissa Lehman, Kenneth J. Malmberg, Emanuel Donchin

1 Department of Psychology, Saarland University, Campus, Building A2.4., Room 2.23, 66123 Saarbrücken, Germany;
2 Department of Psychology, College of Arts and Sciences, Lynn University, Boca Raton, FL, USA;
3 Department of Psychology, University of South Florida, Tampa, FL, USA.

Received: , Accepted: , Published:

Topical Section: Advances in Memory Theories

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We combined a mechanistic model of episodic encoding with theories on the functional significance of two event-related potential (ERP) components to develop an integrated account for the Von Restorff effect, which refers to the enhanced recall probability for an item that deviates in some feature from other items in its study list. The buffer model of Lehman and Malmberg (2009, 2013) can account for this effect such that items encountered during encoding enter an episodic buffer where they are actively rehearsed. When a deviant item is encountered, in order to re-allocate encoding resources towards this item the buffer is emptied from its prior content, a process labeled “compartmentalization”. Based on theories on their functional significance, the P300 component of the ERP may co-occur with this hypothesized compartmentalization process, while the frontal slow wave may index rehearsal. We derived predictions from this integrated model for output patterns in free recall, systematic variance in ERP components, as well as associations between the two types of measures in a dataset of 45 participants who studied and freely recalled lists of the Von Restorff type. Our major predictions were confirmed and the behavioral and physiological results were consistent with the predictions derived from the model. These findings demonstrate that constraining mechanistic models of episodic memory with brain activity patterns and generating predictions for relationships between brain activity and behavior can lead to novel insights into the relationship between the brain, the mind, and behavior.

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Copyright Info: © 2016, Siri-Maria Kamp, et al., licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution Licese (http://creativecommons.org/licenses/by/4.0)

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