Experimental Brain Research

, Volume 234, Issue 6, pp 1589–1597 | Cite as

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

  • Rachel A. LerchEmail author
  • Chris R. Sims
Research Article


Limitations in visual working memory (VWM) have been extensively studied in psychophysical tasks, but not well understood in terms of how these memory limits translate to performance in more natural domains. For example, in reaching to grasp an object based on a spatial memory representation, overshooting the intended target may be more costly than undershooting, such as when reaching for a cup of hot coffee. The current body of literature lacks a detailed account of how the costs or consequences of memory error influence what we encode in visual memory and how we act on the basis of remembered information. Here, we study how externally imposed monetary costs influence behavior in a motor decision task that involves reach planning based on recalled information from VWM. We approach this from a decision theoretic perspective, viewing decisions of where to aim in relation to the utility of their outcomes given the uncertainty of memory representations. Our results indicate that subjects accounted for the uncertainty in their visual memory, showing a significant difference in their reach planning when monetary costs were imposed for memory errors. However, our findings indicate that subjects memory representations per se were not biased by the imposed costs, but rather subjects adopted a near-optimal post-mnemonic decision strategy in their motor planning.


Visuospatial memory Visual memory Decision making Motor planning 


  1. Bays PM (2014) Noise in neural populations accounts for errors in working memory. J Neuro-Sci 34(10):3632–3645Google Scholar
  2. Brouwer A-M, Knill DC (2007) The role of memory in visually guided reaching. J Vis 7(5):6CrossRefPubMedGoogle Scholar
  3. Brouwer A-M, Knill DC (2009) Humans use visual and remembered information about object location to plan pointing movements. J Vis 9(1):24CrossRefPubMedPubMedCentralGoogle Scholar
  4. Franconeri SL, Alvarez GA, Cavanagh P (2013) Flexible cognitive resources: competitive content maps for attention and memory. Trends Cogn Sci 17(3):134–141CrossRefPubMedGoogle Scholar
  5. Goldstone RL, Hendrickson AT (2010) Categorical perception. Wiley Interdiscip Rev Cogn Sci 1(1):69–78CrossRefPubMedGoogle Scholar
  6. Hayhoe MM, Shrivastava A, Mruczek R, Pelz JB (2003) Visual memory and motor planning in a natural task. J Vis 3(1):6CrossRefGoogle Scholar
  7. Hayhoe MM, Rothkopf CA (2011) Vision in the natural world. Wiley Interdiscip Rev Cogn Sci 2(2):158–166CrossRefPubMedGoogle Scholar
  8. Hollingworth A, Richard AM, Luck SJ (2008) Understanding the function of visual short-term memory: transsaccadic memory, object correspondence, and gaze correction. J Exp Psychol Gen 137(1):163CrossRefPubMedPubMedCentralGoogle Scholar
  9. Hudson TE, Wolfe U, Maloney LT (2012) Speeded reaching movements around invisible obstacles. P-LOS Computational BiologyGoogle Scholar
  10. Körding K (2007) Decision theory: what “should” the nervous system do? Science 318(5850):606–610CrossRefPubMedGoogle Scholar
  11. Luck SJ (2008) Visual short-term memory. In: Luck SJ, Hollingworth A (eds) Visual memory. Oxford University Press, Oxford, pp 43–85CrossRefGoogle Scholar
  12. Luck SJ, Vogel EK (2013) Visual working memory capacity: From psychophysics and neurobiology to individual differences. Trends Cogn Sci 17(8):391–400CrossRefPubMedPubMedCentralGoogle Scholar
  13. Lu Z-L, Dosher B (2014) Visual psychophysics: from laboratory to theory. MIT Press, MassachusettsGoogle Scholar
  14. Ma WJ, Husain M, Bays PM (2014) Changing concepts of working memory. Nat Neurosci 17(3):347–356CrossRefPubMedPubMedCentralGoogle Scholar
  15. Maloney LT, Zhang H (2010) Decision-theoretic models of visual perception and action. Vis Res 50(23):2362–2374CrossRefPubMedGoogle Scholar
  16. Orhan AE, Sims CR, Jacobs RA, Knill DC (2014) The adaptive nature of visual working memory. Curr Dir Psychol Sci 23(3):164–170CrossRefGoogle Scholar
  17. Richards W, Rubin JM (2015) Color vision: Representing material categories. Encyclopedia of Color Science and TechnologyGoogle Scholar
  18. Roberson D, Davies I, Davidoff J (2000) Color categories are not universal: replications and new evidence from a stone-age culture. J Exp Psychol Gen 129(3):369CrossRefPubMedGoogle Scholar
  19. Sims CR, Jacobs RA, Knill DC (2012) An ideal observer analysis of visual working memory. Psychol Rev 119(4):807CrossRefPubMedPubMedCentralGoogle Scholar
  20. Sims CR (2015) The cost of misremembering: Inferring the loss function in visual working memory. J Vis 15(3):2CrossRefPubMedGoogle Scholar
  21. Trommershäuser J, Maloney LT, Landy MS (2008) Decision making, movement planning and statistical decision theory. Trends Cogn Sci 12(8):291–297CrossRefPubMedGoogle Scholar
  22. Wolpert DM, Landy MS (2012) Motor control is decision-making. Curr Opin Neurobiol 22(6):996–1003CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.Applied Cognitive and Brain Sciences, Department of PsychologyDrexel UniversityPhiladelphiaUSA

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