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The attentional blink reveals serial working memory encoding: Evidence from virtual and human event-related potentials

Craston, Patrick, Wyble, Brad, Chennu, Srivas, Bowman, Howard (2009) The attentional blink reveals serial working memory encoding: Evidence from virtual and human event-related potentials. Journal of Cognitive Neuroscience, 21 (3). pp. 550-566. ISSN 0898-929X. (doi:10.1162/jocn.2009.21036) (KAR id:23966)

Abstract

Observers often miss a second target (T2) if it follows an identified first target item (T1) within half a second in rapid serial visual presentation (RSVP), a finding termed the attentional blink. If two targets are presented in immediate succession, however, accuracy is excellent (Lag 1 sparing). The resource sharing hypothesis proposes a dynamic distribution of resources over a time span of up to 600 msec during the attentional blink. In contrast, the ST2 model argues that working memory encoding is serial during the attentional blink and that, due to joint consolidation, Lag 1 is the only case where resources are shared. Experiment 1 investigates the P3 ERP component evoked by targets in RSVP. The results suggest that, in this context, P3 amplitude is an indication of bottom.up strength rather than a measure of cognitive resource allocation. Experiment 2, employing a two-target paradigm, suggests that T1 consolidation is not affected by the presentation of T2 during the attentional blink. However, if targets are presented in immediate succession (Lag 1 sparing), they are jointly encoded into working memory. We use the ST2 model's neural network implementation, which replicates a range of behavioral results related to the attentional blink, to generate .virtual ERPs. by summing across activation traces. We compare virtual to human ERPs and show how the results suggest a serial nature of working memory encoding as implied by the ST2 model.

Item Type: Article
DOI/Identification number: 10.1162/jocn.2009.21036
Uncontrolled keywords: Attention: Visual, Event related potentials, Computational modeling, Memory: Working memory, EEG
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Srivas Chennu
Date Deposited: 29 Mar 2010 12:09 UTC
Last Modified: 16 Nov 2021 10:02 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/23966 (The current URI for this page, for reference purposes)

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