Literature DB >> 25740875

The cost of misremembering: Inferring the loss function in visual working memory.

Chris R Sims1.   

Abstract

Visual working memory (VWM) is a highly limited storage system. A basic consequence of this fact is that visual memories cannot perfectly encode or represent the veridical structure of the world. However, in natural tasks, some memory errors might be more costly than others. This raises the intriguing possibility that the nature of memory error reflects the costs of committing different kinds of errors. Many existing theories assume that visual memories are noise-corrupted versions of afferent perceptual signals. However, this additive noise assumption oversimplifies the problem. Implicit in the behavioral phenomena of visual working memory is the concept of a loss function: a mathematical entity that describes the relative cost to the organism of making different types of memory errors. An optimally efficient memory system is one that minimizes the expected loss according to a particular loss function, while subject to a constraint on memory capacity. This paper describes a novel theoretical framework for characterizing visual working memory in terms of its implicit loss function. Using inverse decision theory, the empirical loss function is estimated from the results of a standard delayed recall visual memory experiment. These results are compared to the predicted behavior of a visual working memory system that is optimally efficient for a previously identified natural task, gaze correction following saccadic error. Finally, the approach is compared to alternative models of visual working memory, and shown to offer a superior account of the empirical data across a range of experimental datasets.
© 2015 ARVO.

Entities:  

Keywords:  Bayesian decision theory; information theory; loss function; visual working memory

Mesh:

Year:  2015        PMID: 25740875     DOI: 10.1167/15.3.2

Source DB:  PubMed          Journal:  J Vis        ISSN: 1534-7362            Impact factor:   2.240


  11 in total

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2.  Visual short-term memory for oriented, colored objects.

Authors:  Hongsup Shin; Wei Ji Ma
Journal:  J Vis       Date:  2017-08-01       Impact factor: 2.240

3.  Decision theory, motor planning, and visual memory: deciding where to reach when memory errors are costly.

Authors:  Rachel A Lerch; Chris R Sims
Journal:  Exp Brain Res       Date:  2016-01-28       Impact factor: 1.972

4.  Optimal attentional allocation in the presence of capacity constraints in uncued and cued visual search.

Authors:  Christopher J Bates; Robert A Jacobs
Journal:  J Vis       Date:  2021-05-03       Impact factor: 2.240

5.  The virtual loss function in the summary perception of motion and its limited adjustability.

Authors:  Tianyuan Teng; Sheng Li; Hang Zhang
Journal:  J Vis       Date:  2021-05-03       Impact factor: 2.240

6.  Cognitive Control as a Multivariate Optimization Problem.

Authors:  Harrison Ritz; Xiamin Leng; Amitai Shenhav
Journal:  J Cogn Neurosci       Date:  2022-03-05       Impact factor: 3.225

7.  The evolution of lossy compression.

Authors:  Sarah E Marzen; Simon DeDeo
Journal:  J R Soc Interface       Date:  2017-05       Impact factor: 4.118

8.  Internal but not external noise frees working memory resources.

Authors:  Ivan Tomić; Paul M Bays
Journal:  PLoS Comput Biol       Date:  2018-10-15       Impact factor: 4.475

9.  A resource-rational theory of set size effects in human visual working memory.

Authors:  Ronald van den Berg; Wei Ji Ma
Journal:  Elife       Date:  2018-08-07       Impact factor: 8.140

10.  Strategic allocation of working memory resource.

Authors:  Aspen H Yoo; Zuzanna Klyszejko; Clayton E Curtis; Wei Ji Ma
Journal:  Sci Rep       Date:  2018-11-01       Impact factor: 4.379

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