After observers see an object or pattern, their visual memory of what they have seen decays slowly over time. Nearly all current theories of vision assume that decay of short-term memory occurs because visual representations are progressively and randomly corrupted as time passes. We tested this assumption using psychophysical noise-masking methods, and we found that visual memory decays in a completely deterministic fashion. This surprising finding challenges current ideas about visual memory and sets a goal for future memory research: to characterize the deterministic “forgetting function” that describes how memories decay over time.
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References
1.
BurgessA.E.ColborneB. (1988). Visual signal detection IV: Observer inconsistency. Journal of the Optical Society of America A, 5, 617–627.
2.
BurgessA.E.WagnerR.F.JenningsR.J.BarlowH.B. (1981). Efficiency of human visual signal discrimination. Science, 214, 93–94.
3.
CornelissenF.W.GreenleeM.W. (2000). Visual memory for random block patterns defined by luminance and color contrast. Vision Research, 40, 287–299.
4.
DurlachN.I.BraidaL.D. (1969). Intensity perception: I. Preliminary theory of intensity resolution. Journal of the Acoustical Society of America, 46, 372–383.
5.
EfronB.TibshiraniR. (1993). An introduction to the bootstrap. New York: Chapman & Hall.
6.
GoldJ.M.BennettP.J.SekulerA.B. (1999). Signal but not noise changes with perceptual learning. Nature, 402, 176–178.
GreenD.M.SwetsJ.A. (1966). Signal detection theory and psychophysics. New York: John Wiley and Sons.
10.
HarveyL.D. (1986). Visual memory: What is remembered?InKlixF.HagendorfH.(Eds.), Human memory and cognitive capabilities (Vol. 1, pp.173–187). The Hague, The Netherlands: Elsevier Science.
11.
InuiT. (1988). Properties of human visual memory for block patterns. Biological Cybernetics, 59, 179–187.
12.
KennedyF. (1898). On the experimental investigation of memory. Psychological Review, 5, 477–499.
13.
KinchlaR.A.SmyzerF. (1967). A diffusion model of perceptual memory. Perception & Psychophysics, 2, 219–229.
14.
LamingD.ScheiwillerP. (1985). Retention in perceptual memory: A review of models and data. Perception & Psychophysics, 37, 189–197.
15.
LeeB.HarrisJ. (1996). Contrast transfer characteristics of visual short-term memory. Vision Research, 36, 2159–2166.
16.
LeggeG.KerstenD.BurgessA.E. (1987). Contrast discrimination in noise. Journal of the Optical Society of America A, 4, 391–406.
17.
LuZ.L.DosherB.A. (1999). Characterizing human perceptual inefficiencies with equivalent internal noise. Journal of the Optical Society of America A, 16, 764–778.
18.
MagnussenS.GreenleeM.W. (1999). The psychophysics of perceptual memory. Psychological Research, 62, 81–92.
19.
PelliD.G. (1990). The quantum efficiency of vision. InBlakemoreC.(Ed.), Vision: Coding and efficiency (pp.3–24). Cambridge, England: Cambridge University Press.
20.
PelliD.G.FarellB. (1999). Why use noise?Journal of the Optical Society of America A, 16, 647–653.
21.
SakaiK.InuiT. (2002). A feature-segmentation model of short-term visual memory. Perception, 31, 579–589.
22.
SperlingG. (1960). The information available in brief visual presentations. Psychological Monographs: General and Applied, 74(11), 1–29.
23.
SpiegelM.F.GreenD.M. (1981). Two procedures for estimating internal noise. Journal of the Acoustical Society of America, 70, 69–73.
24.
StiglerS.M. (1978). Some forgotten work on memory. Journal of Experimental Psychology: Human Learning and Memory, 4(1), 1–4.
25.
TjanB.S.BrajeW.L.LeggeG.E.KerstenD. (1995). Human efficiency for recognizing 3-d objects in luminance noise. Vision Research, 35, 3053–3069.
26.
TolhurstD.J.MovshonJ.A.ThompsonI.D. (1981). The dependence of response amplitude and variance of cat visual cortical neurones on stimulus contrast. Experimental Brain Research, 41, 414–419.
