Supplemental Material for A Two-Phase Model of Resource Allocation in Visual Working Memory

2017 ◽  
Vol 43 (10) ◽  
pp. 1557-1566 ◽  
Author(s):  
Chaoxiong Ye ◽  
Zhonghua Hu ◽  
Hong Li ◽  
Tapani Ristaniemi ◽  
Qiang Liu ◽  
...  

2019 ◽  
Vol 85 (10) ◽  
pp. S208-S209
Author(s):  
Yijie Zhao ◽  
Xuemei Ran ◽  
Li Zhang ◽  
Ruyuan Zhang ◽  
Yixuan Ku

2009 ◽  
Vol 35 (5) ◽  
pp. 1359-1367 ◽  
Author(s):  
Brian Barton ◽  
Edward F. Ester ◽  
Edward Awh

2021 ◽  
Vol 17 (11) ◽  
pp. e1009544
Author(s):  
Yi-Jie Zhao ◽  
Tianye Ma ◽  
Li Zhang ◽  
Xuemei Ran ◽  
Ru-Yuan Zhang ◽  
...  

Working memory (WM) deficits have been widely documented in schizophrenia (SZ), and almost all existing studies attributed the deficits to decreased capacity as compared to healthy control (HC) subjects. Recent developments in WM research suggest that other components, such as precision, also mediate behavioral performance. It remains unclear how different WM components jointly contribute to deficits in schizophrenia. We measured the performance of 60 SZ (31 females) and 61 HC (29 females) in a classical delay-estimation visual working memory (VWM) task and evaluated several influential computational models proposed in basic science of VWM to disentangle the effect of various memory components. We show that the model assuming variable precision (VP) across items and trials is the best model to explain the performance of both groups. According to the VP model, SZ exhibited abnormally larger variability of allocating memory resources rather than resources or capacity per se. Finally, individual differences in the resource allocation variability predicted variation of symptom severity in PSZ, highlighting its functional relevance to schizophrenic pathology. This finding was further verified using distinct visual features and subject cohorts. These results provide an alternative view instead of the widely accepted decreased-capacity theory and highlight the key role of elevated resource allocation variability in generating atypical VWM behavior in schizophrenia. Our findings also shed new light on the utility of Bayesian observer models to characterize mechanisms of mental deficits in clinical neuroscience.


2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Christine Salahub ◽  
Holly A. Lockhart ◽  
Blaire Dube ◽  
Naseem Al-Aidroos ◽  
Stephen M. Emrich

AbstractVisual working memory is a brief, capacity-limited store of visual information that is involved in a large number of cognitive functions. To guide one’s behavior effectively, one must efficiently allocate these limited memory resources across memory items. Previous research has suggested that items are either stored in memory or completely blocked from memory access. However, recent behavioral work proposes that memory resources can be flexibly split across items based on their level of task importance. Here, we investigated the electrophysiological correlates of flexible resource allocation by manipulating the distribution of resources amongst systematically lateralized memory items. We examined the contralateral delay activity (CDA), a waveform typically associated with the number of items held in memory. Across three experiments, we found that, in addition to memory load, the CDA flexibly tracks memory resource allocation. This allocation occurred as early as attentional selection, as indicated by the N2pc. Additionally, CDA amplitude was better-described when fit with a continuous model predicted by load and resources together than when fit with either alone. Our findings show that electrophysiological markers of attentional selection and memory maintenance not only track memory load, but also the proportion of memory resources those items receive.


2019 ◽  
Author(s):  
Ronald van den Berg ◽  
Qijia Zou ◽  
Wei Ji Ma

ABSTRACTPrevious work has shown that humans distribute their visual working memory (VWM) resources flexibly across items: the higher the importance of an item, the better it is remembered. A related, but much less studied question is whether people also have control over the total amount of VWM resource allocated to a task. Here, we approach this question by testing whether increasing monetary incentives results in better overall VWM performance. In two experiments, subjects performed a delayed-estimation task on the Amazon Turk platform. In both experiments, four groups of subjects received a bonus payment based on their performance, with the maximum bonus ranging from $0 to $10 between groups. We found no effect of the amount of bonus on intrinsic motivation or on VWM performance in either experiment. These results suggest that resource allocation in visual working memory is insensitive to monetary reward, which has implications for resource-rational theories of VWM.


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