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Attention, working memory, and phenomenal experience of WM content: memory levels determined by different types of top-down modulation.

Jane Jacob, Christianne Jacobs, Juha Silvanto

Frontiers in Psychology October 19, 2015 DOI: 10.3389/fpsyg.2015.01603 (opens in new tab)

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AI-extracted from the abstract
Characteristics Theoretical or philosophical paper Peer reviewed
Keywords Working memory Consciousness Top-down attention Phenomenal experience Memory state
Key points Argues that attentional enhancement of a working memory representation is not sufficient for phenomenal consciousness; a second top-down mechanism, suppression of incoming visual input via inhibition of early visual cortex, is also required. Proposes three memory levels based on the top-down control involved: nonattended nonconscious, attended phenomenally nonconscious, and attended phenomenally conscious.

Abstract

What is the role of top-down attentional modulation in consciously accessing working memory (WM) content? In influential WM models, information can exist in different states, determined by allocation of attention; placing the original memory representation in the center of focused attention gives rise to conscious access. Here we discuss various lines of evidence indicating that such attentional modulation is not sufficient for memory content to be phenomenally experienced. We propose that, in addition to attentional modulation of the memory representation, another type of top-down modulation is required: suppression of all incoming visual information, via inhibition of early visual cortex. In this view, there are three distinct memory levels, as a function of the top-down control associated with them: (1) Nonattended, nonconscious associated with no attentional modulation; (2) attended, phenomenally nonconscious memory, associated with attentional enhancement of the actual memory trace; (3) attended, phenomenally conscious memory content, associated with enhancement of the memory trace and top-down suppression of all incoming visual input.

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