@ARTICLE{26583223_213552323_2017, 
	author = {Yury Markov and Natalia Tiurina and Yulia Stakina and Igor Utochkin}, 
	keywords = {, visual working memory, ensemble perceptionobject perception},
	title = {<p class="text">The Capacity and Precision of Visual Working Memory for Object and Ensembles</p>},
	journal = {Psychology. Journal of Higher School of Economics},
	year = {2017},
	volume = {14},
	number = {4},
	pages = {735-755},
	url = {https://psy-journal.hse.ru/en/2017-14-4/213552323.html},
	publisher = {},
	abstract = {Previous research has documented the limited capacity of visual working memory (VWM) for color objects set at 3-5 items. Another line of research has shown that multiple objects can be stored in a compressed form of ensemble. However, existing data is more likely to testify that VWM can store no more than two such compressed units. But the nature of this discrepancy can be methodological: VWM for ensembles was never tested using methods that are applied in the research of VWM for objects. Here we have tested the capacity and precision of VWM for objects and ensembles using two standard methods - change detection and continuous report with a mixture model. We found that VWM for both types of units showed the similar capacity and precision when critical psychophysical parameters, such as foveal density and area are controlled. We also showed that this quantitative similarity between objects and ensembles is provided by a mechanism that represents each ensemble as a holistic VWM chunk as efficiently as it represents any single object.},
	annote = {Previous research has documented the limited capacity of visual working memory (VWM) for color objects set at 3-5 items. Another line of research has shown that multiple objects can be stored in a compressed form of ensemble. However, existing data is more likely to testify that VWM can store no more than two such compressed units. But the nature of this discrepancy can be methodological: VWM for ensembles was never tested using methods that are applied in the research of VWM for objects. Here we have tested the capacity and precision of VWM for objects and ensembles using two standard methods - change detection and continuous report with a mixture model. We found that VWM for both types of units showed the similar capacity and precision when critical psychophysical parameters, such as foveal density and area are controlled. We also showed that this quantitative similarity between objects and ensembles is provided by a mechanism that represents each ensemble as a holistic VWM chunk as efficiently as it represents any single object.}
}