PLoS Computational BiologyNeurosciencePeer-reviewed journal article
Atypically larger variability of resource allocation accounts for visual working memory deficits in schizophrenia
Yijie ZhaoiD, Tianye Ma, Xuemei Ran, Li Zhang, Ru‐Yuan ZhangiD, Yixuan KuiD
Abstract
Schizophrenia patients are known to have profound deficits in visual working memory (VWM), and almost all previous studies attribute the deficits to decreased memory capacity. This account, however, ignores the potential contributions of other VWM components (e.g., memory precision). Here, we measure the VWM performance of schizophrenia patients and healthy control subjects on two classical delay-estimation tasks. Moreover, we thoroughly evaluate several established computational models of VWM to compare the performance of the two groups. We find that the model assuming variable precision across items and trials is the best model to explain the performance of both groups. According to the variable-precision model, schizophrenia subjects exhibit abnormally larger variability of allocating memory resources rather than resources per se. These results invite a rethink of the widely accepted decreased-capacity theory and propose a new perspective on the diagnosis and rehabilitation of schizophrenia.
- Citations
- 18
- FWCI
- 1.97
- Field percentile
- top 14%
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