Variability in encoding precision accounts for visual short-term memory limitations

Abstract

It is commonly believed that visual short-term memory (VSTM) consists of a fixed number of "slots" in which items can be stored. An alternative theory in which memory resource is a continuous quantity distributed over all items seems to be refuted by the appearance of guessing in human responses. Here, we introduce a model in which resource is not only continuous but also variable across items and trials, causing random fluctuations in encoding precision. We tested this model against previous models using two VSTM paradigms and two feature dimensions. Our model accurately accounts for all aspects of the data, including apparent guessing, and outperforms slot models in formal model comparison. At the neural level, variability in precision might correspond to variability in neural population gain and doubly stochastic stimulus representation. Our results suggest that VSTM resource is continuous and variable rather than discrete and fixed and might explain why subjective experience of VSTM is not all or none.T homas Chamberlin famously warned scientists against entertaining only a single hypothesis, for such a modus operandi might lead to undue attachment and "a pressing of the facts to make them fit the theory" (ref. 1, p. 840). For half a century, the study of short-term memory limitations has been dominated by a single hypothesis, namely that a fixed number of items can be held in memory and any excess items are discarded (2-5). The alternative notion that short-term memory resource is a continuous quantity distributed over all items, with a lower amount per item translating into lower encoding precision, has enjoyed some success (6-8), but has been unable to account for the finding that humans often seem to make a random guess when asked to report the identity of one of a set of remembered items, especially when many items are present (9). Specifically, if resource were evenly distributed across items (6, 10), observers would never guess. Thus, at present, no viable continuous-resource model exists.Here, we propose a more sophisticated continuous-resource model, the variable-precision (VP) model, in which the amount of resource an item receives, and thus its encoding precision, varies randomly across items and trials and on average decreases with set size. Resource might correspond to the gain of a neural population pattern of activity encoding a memorized feature. When gain is higher, a stimulus is encoded with higher precision (11,12). Variability in gain across items and trials is consistent with observations of single-neuron firing rate variability (13-15) and attentional fluctuations (16, 17).We tested the VP model against three alternative models (Fig. 1). According to the classic item-limit (IL) model (4), a fixed number of items is kept in memory, and memorized items are recalled perfectly. In the equal-precision (EP) model (6, 10), a continuous resource is evenly distributed across all items. The slots-plus-averaging (SA) model (9) acknowledges the presence of noise but combines it with the notion of ...

Interference and memory capacity limitations.

“…Participants' memory thus seems to be capacity-limited as predicted by a slot-model. In this and the following literature, fixed and limited capacities have thus been used as diagnostic of slotlike memory representations vs. continuous resource-like representations, often based on sophisticated mathematical analyses (e.g., van den Berg et al, 2012;Rouder et al, 2008; W. Zhang & Luck, 2008).…”

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“…Several computational models already exist for visual WM (Bays, 2014;Matthey, Bays, & Dayan, 2015;Swan & Wyble, 2014;van den Berg, Shin, Chou, George, & Ma, 2012). We recently proposed a computational model of attention to items in verbal WM (Oberauer, 2013;Oberauer, Souza, Druey, & Gade, 2013) that explains the effects of switching attention between items in WM and of swapping entire memory sets into and out of WM.…”

Why some colors appear more memorable than others: A model combining categories and particulars in color working memory.

“…After a short delay period, participants report the hue value of one of the study objects on a con-4 tinuous response scale, a hue circle (usually with 180 exemplars) comprising all the hues utilized in the study. Response variability -measured as angular deviation between selected and true hues-differs between trials and by condition, motivating inferences concerning the structure of visual working memory (Anderson & Awh, 2012;Bays, Catalao, & Husain, 2009;Bays, Wu, & Husain, 2011;Emrich & Ferber, 2011;Fougnie & Alvarez, 2011;Fougnie, Asplund, & Marois, 2010;Fougnie, Suchow, & Alvarez, 2012;Gold et al, 2010;van den Berg, Shin, Chou, George, & Ma, 2012;Wilken & Ma, 2004;Zhang & Luck, 2011;2009;.…”