Precision of working memory for visual motion sequences and transparent motion surfaces

Abstract

Recent studies investigating working memory for location, colour and orientation support a dynamic resource model. We examined whether this might also apply to motion, using random dot kinematograms (RDKs) presented sequentially or simultaneously. Mean precision for motion direction declined as sequence length increased, with precision being lower for earlier RDKs. Two alternative models of working memory were compared specifically to distinguish between the contributions of different sources of error that corrupt memory (Zhang & Luck (2008) vs. Bays et al (2009)). The latter provided a significantly better fit for the data, revealing that decrease in memory precision for earlier items is explained by an increase in interference from other items in a sequence, rather than random guessing or a temporal decay of information. Misbinding feature attributes is an important source of error in working memory. Precision of memory for motion direction decreased when two RDKs were presented simultaneously as transparent surfaces, compared to sequential RDKs. However, precision was enhanced when one motion surface was prioritized, demonstrating that selective attention can improve recall precision. These results are consistent with a resource model that can be used as a general conceptual framework for understanding working memory across a range of visual features.

Alterations in visual cortical activation and connectivity with prefrontal cortex during working memory updating in major depressive disorder

“…Such relationship, along with the impaired behavioral performance, suggests that depressive mood state and ruminative processing style may have reduced the ability to inhibit obsolete material which then interfered with the ability to focus on the relevant material (see below). This interpretation is consistent with the effects of stimulus competition and interference on working memory integrity demonstrated in previous behavioral studies (Bays et al, 2011, Gorgoraptis et al, 2011, Zokaei et al, 2011). Another possibility is the disruption of task-related signal from the prefrontal cortex.…”

Attention as foraging for information and value

“…This could be due to poor retention or poor acquisition. Although retention is generally considered to have a capacity of 4 or more items (Snyder and Kingstone, 2000; Gilchrist et al, 2001), a variable-precision account of working memory retention might predict refixations, particularly when combined with temporal decay (Bays and Husain, 2008; Zokaei et al, 2011). A more straightforward explanation of refixation is that participants only acquire a limited amount of information about each target as they fixate it.…”

Changing concepts of working memory

“…The delayed-estimation technique has now been used to study memory of a range of visual features, including color, orientation and motion direction 8–10,15,16,18–21 . Rather than exhibiting the abrupt, step decline that would be expected on reaching a capacity limit of a fixed number of items 5 , in every case, recall variability has been shown to gradually and continuously increase as set size increases (Fig.…”

“…Rather than being limited to a fixed storage resolution, a growing body of evidence indicates that memory resources can be unevenly distributed so that prioritized items are stored with enhanced precision compared to other objects. Voluntary control over resource allocation has been demonstrated by studies in which one stimulus in a memory array is indicated as more likely to be selected for test, resulting in a robust gain in recall precision for the cued stimulus 10,18,26 . Critically, this recall advantage appears to come with a corresponding cost to other stimuli in memory, which are recalled with less precision 10,11,26 .…”