Academic journal article Attention, Perception and Psychophysics

Catching a Glimpse of Working Memory: Top-Down Capture as a Tool for Measuring the Content of the Mind

Academic journal article Attention, Perception and Psychophysics

Catching a Glimpse of Working Memory: Top-Down Capture as a Tool for Measuring the Content of the Mind

Article excerpt

Published online: 25 September 2012

© Psychonomic Society, Inc. 2012

Abstract This article outlines a methodology for probing working memory (WM) content in high-level cognitive tasks (e.g., decision making, problem solving, and memory retrieval) by capitalizing on attentional and oculomotor biases evidenced in top-down capture paradigms. This method would be of great use, as it could measure the information resident in WM at any point in a task and, hence, track information use over time as tasks dynamically evolve. Above and beyond providing a measure of information occupancy in WM, such a method would benefit from sensitivity to the specific activation levels of individual items in WM. This article additionally forwards a novel fusion of standard free recall and visual search paradigms in an effort to assess the sensitivity of eye movements in top-down capture, on which this new measurement technique relies, to item-specific memory activation (ISMA). The results demonstrate eye movement sensitivity to ISMA in some, but not all, cases.

Keywords Attention and memory .Working memory . Eye movements . Top-down capture

Attempts to understand information use through time in high-level cognitive tasks, such as decision making or problem solving, face an empirical challenge in determining how the various inputs and outputs of the task are utilized over time. Traditionally, overt report of a person's final output has been used as the primary measure for investigating the processes underlying performance in such domains. Although overt report has supported a wealth of insight, it is ill-suited for addressing issues regarding the temporal dynamics unfolding within a task. The primary reason for this insufficiency is that overt report is highly disruptive to ongoing cognitive dynamics.

For instance, consider a cued recall task such as medical diagnosis. The items relevant to this task are the patient's symptom states and the diagnoses that are retrieved on the basis of these inputs. Understanding the temporal dynamics of this task requires understanding how and when these items are placed into (and become displaced from) working memory (WM). As the task unfolds, each item in memory (i.e., symptoms, and diagnoses once they are recalled) possesses a particular amount of memory activation. In order to understand the temporal dynamics of this task, we would like to measure the evolution of these activations throughout the task.

Methods for examining the dynamic utilization of information over time would benefit from four characteristics. First, such techniques should show minimal interference to the contents of WM and their utilization in the task. Second, it would be possible to deploy the measure within (and potentially throughout) the task as it unfolds. Third, the measure would be item-specific, in that it would allow measurement at the level of individual items, rather than simply the engagement of generalized processing as measured in neuroscience (e.g., fMRI, EEG, MEG). Finally, the measure would be of superior usefulness if it were sensitive not only to items being in or out of WM, but to their current levels of activation in memory, as well. At present, no methodology satisfying these criteria exists.

Interestingly, the literature on top-down capture, demonstrating a tight coupling between attentional processes and the contents of WM, suggests a solution (Downing, 2000; Huang & Pashler, 2007; Moores, Laiti, & Chelazzi, 2003; Olivers, 2009; Olivers, Meijer, & Theeuwes, 2006; Soto, Heinke, Humphreys, & Blanco, 2005; Soto & Humphreys, 2007). Such work by Soto et al. (2005) and by Soto and Humphreys (2007) has suggested that attention is automatically captured by the contents of WM when matching items reappear in search arrays (but see Woodman & Luck, 2007, for a demonstration in which WM content was used strategically). Of particular importance for the present method, Soto et al. …

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