Limitations of working memory (WM) capacity depend strongly on the cognitive resources that are available for maintaining WM contents in an activated state. Increasing the number of items to be maintained in WM was shown to reduce the precision of WM and to increase the variability of WM precision over time. Although WM precision was recently associated with neural codes particularly in early sensory cortex, we have so far no understanding of the neural bases underlying the variability of WM precision, and how WM precision is preserved under high load. To fill this gap, we combined human fMRI with computational modeling of behavioral performance in a delayed color-estimation WM task. Behavioral results replicate a reduction of WM precision and an increase of precision variability under high loads (5 Ͼ 3 Ͼ 1 colors). Load-dependent BOLD signals in primary visual cortex (V1) and superior intraparietal sulcus (IPS), measured during the WM task at 2-4 s after sample onset, were modulated by individual differences in load-related changes in the variability of WM precision. Although stronger load-related BOLD increase in superior IPS was related to lower increases in precision variability, thus stabilizing WM performance, the reverse was observed for V1. Finally, the detrimental effect of load on behavioral precision and precision variability was accompanied by a load-related decline in the accuracy of decoding the memory stimuli (colors) from left superior IPS. We suggest that the superior IPS may contribute to stabilizing visual WM performance by reducing the variability of memory precision in the face of higher load.
Mnemonic precision is an important aspect of visual working memory (WM). Here, we probed mechanisms that affect precision for spatial (size) and non-spatial (colour) features of an object, and whether these features are encoded and/or stored separately in WM. We probed precision at the feature-level—that is, whether different features of a single object are represented separately or together in WM—and the object-level—that is, whether different features across a set of sequentially presented objects are represented in the same or different WM stores. By manipulating whether stimuli were encoded by the left and/or right hemisphere, we gained further insights into how objects are represented in WM. At the feature-level, we tested whether recall fidelity for the two features of an object fluctuated in tandem from trial to trial. We observed no significant coupling under either central or lateralized encoding, supporting the claim of parallel feature channels at encoding. At the level of WM storage of a set of objects, we found asymmetric feature interference under central encoding, whereby an increase in colour load led to a decrease in size precision. When objects were encoded by a single hemisphere, however, we found largely independent feature stores. Precision for size was more resistant to interference from the size of another object under right-hemisphere encoding; by contrast, precision for colour did not differ across hemispheres, suggesting a more distributed WM store. These findings suggest that distinct features of a single object are represented separately but are then partially integrated during maintenance of a set of sequentially presented objects.
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