Are the effects of memory and attention on perception synergistic, antagonistic, or independent? Tested separately, memory and attention have been shown to affect the accuracy of orientation judgements. When multiple stimuli are presented sequentially versus simultaneously, error variance is reduced. When a target is validly cued, precision is increased. What if they are manipulated together? We combined memory and attention manipulations in an orientation judgement task to answer this question. Two circular gratings were presented sequentially or simultaneously. On some trials a brief luminance cue preceded the stimuli. Participants were cued to report the orientation of one of the two gratings by rotating a response grating. We replicated the finding that error variance is reduced on sequential trials. Critically, we found interacting effects of memory and attention. Valid cueing reduced the median, absolute error only when two stimuli appeared together and improved it to the level of performance on uncued sequential trials, whereas invalid cueing always increased error. This effect was not mediated by cue predictiveness; however, predictive cues reduced the standard deviation of the error distribution, whereas nonpredictive cues reduced “guessing”. Our results suggest that, when the demand on memory is greater than a single stimulus, attention is a bottom-up process that prioritizes stimuli for consolidation. Thus attention and memory are synergistic.
Anton-ErxlebenK., & CarrascoM. (2013). Attentional enhancement of spatial resolution: Linking behavioural and neurophysiological evidence. Nature Reviews: Neuroscience, 14, 188–200. doi:10.1038/nrn3443
3.
Baddeley, A., Eysenck, M. W., & Anderson, M. C. (2009). Memory. East Sussex: Psychology Press.
4.
BaldassiS., & BurrD. C. (2000). Feature-based integration of orientation signals in visual search. Vision Research, 40, 1293–1300. doi:10.1016/s0042-6989(00)00029-8
5.
BenjafieldJ. G., SmilekD., & KingstoneA. (2010). The varieties of attention. In Cognition (5th ed., pp. 85–119). Ontario: Oxford University Press.
6.
CameronE. L., TaiJ. C., & CarrascoM. (2002). Covert attention affects the psychometric function of contrast sensitivity. Vision Research, 42, 949–967. doi:10.1016/s0042-6989(02)00039-1
7.
CarrascoM. (2011). Visual attention: The past 25 years. Vision Research, 51, 1484–1525. doi:10.1016/j.visres.2011.04.012
8.
DosherB. A., & LuZ-L. (2000). Noise exclusion in spatial attention. Psychological Science, 11, 139–146. doi:10.1111/1467-9280.00229
9.
DrollJ. A., AbbeyC. K., & EcksteinM. P. (2009). Learning cue validity through performance feedback. Journal of Vision, 9, 1–22. doi:10.1167/9.2.18
10.
DrukerM., & AndersonB. (2010). Spatial probability aids visual stimulus discrimination. Frontiers in Human Neuroscience, 4, 1–10. doi:10.3389/fnhum.2010.00063
11.
EnnsJ. T., & BrodeurD. A. (1989). A developmental study of covert orienting to peripheral visual cues. Journal of Experimental Child Psychology, 48, 171–189. doi:10.1016/0022-0965(89)90001-5
12.
EriksenC. W., & YehY. Y. (1985). Allocation of attention in the visual field. Journal of Experimental Psychology: Human Perception and Performance, 11, 583–597. doi:10.1037/0096-1523.11.5.583
13.
FiserJ., & AslinR. N. (2001). Unsupervised statistical learning of higher-order spatial structures from visual scenes. Psychological Science, 12, 499–504. doi:10.1111/1467-9280.00392
14.
FoxJ., FriendlyM., & MonetteG. (2014). heplots: Visualizing tests in multivariate linear models. R package version 1.0–12: http://CRAN.R-project.org/package=heplots
15.
GorardS. (2005). Revisiting a 90-year-old debate: The advantages of the mean deviation. The British Journal of Educational Studies, 53, 417–430. doi:10.1111/j.1467-8527.2005.00304.x
16.
HothornT., BretzF., & WestfallP. (2008). Simultaneous inference in general parametric models. Biometrical Journal, 50, 346–363. doi:10.1002/bimj.200810425
17.
JiangY. V., SwallowK. M., RosenbaumG. M., & HerzigC. (2013). Rapid acquisition but slow extinction of an attentional bias in space. Journal of Experimental Psychology: Human Perception and Performance, 39, 87–99. doi:10.1167/12.9.392
18.
JohnsonD. N., & YantisS. (1995). Allocating visual attention: Tests of a two-process model. Journal of Experimental Psychology: Human Perception and Performance, 21, 1376–1390. doi:10.1037/0096-1523.21.6.1376
19.
JolicoeurP., & Dell'AcquaR. (1998). The demonstration of short-term consolidation. Cognitive Psychology, 36, 138–202. doi: 10.1006/cogp.1998.0684
20.
JonidesJ. (1980). Towards a model of the mind's eye's movement. Canadian Journal of Psychology, 34, 103–112. doi:10.1006/cogp.1998.0684
21.
LiuT., & BeckerM. W. (2013). Serial consolidation of orientation information into visual short-term memory. Psychological Science, 24, 1044–1050. doi:10.1037/e502412013-872
22.
MaW. J., HusainM., & BaysP. M. (2014). Changing concepts of working memory. Nature Neuroscience, 17, 347–356. doi:10.1038/nn.3655
23.
MurrayA. M., NobreA. C., ClarkI. A., CravoA. M., & StokesM. G. (2013). Attention restores discrete items to visual short-term memory. Psychological Science, 24, 550–556. doi:10.1177/0956797612457782
24.
PackW., KleinS. A., & CarneyT. (2014). Bias corrected double judgment accuracy during spatial attention cueing: Unmasked stimuli with non-predictive and semi-predictive cues. Vision Research, 105, 213–225. doi:10.1016/j.visres.2014.07.017.
25.
Palmer, J. (1994). Set-size effects in visual search: The effect of attention is independent of the stimulus for simple tasks. Vision Research, 34(13), 1703–1721.
26.
PerruchetP., & PactonS. (2006). Implicit learning and statistical learning: Two approaches, one phenomenon. Trends in Cognitive Sciences, 10, 233–238. doi:10.1016/j.tics.2006.03.006
27.
PierceJ. W. (2007). PsychoPy - Psychophysics software in Python. Journal of Neuroscience Methods, 162, 8–13. doi:10.1016/j.jneumeth.2006.11.017
28.
PinheiroJ., BatesD., DebRoyS., SarkarD., & R Core Team. (2014). nlme: Linear and nonlinear mixed effects models. R package version 3.1–117: http://CRAN.R-project.org/package=nlme
29.
PosnerM. I. (1980). Orienting of attention. Quarterly Journal of Experimental Psychology, 32, 3–25. doi:10.1080/00335558008248231
30.
PosnerM. I., SnyderC. R., & DavidsonB. J. (1980). Attention and the detection of signals. Journal of Experimental Psychology: General, 109, 160–174. doi:10.1037/0096-3445.109.2.160
31.
PrinzmetalW., AmiriH., AllenK., & EdwardsT. (1998). Phenomenology of attention: 1. Color, location, orientation, and spatial frequency. Journal of Experimental Psychology: Human Perception and Performance, 24, 261–282. doi:10.1037/0096-1523.24.1.261
32.
PrinzmetalW., NwachukuI., BodanskiL., BlumenfeldL., & ShimizuN. (1997). Phenomenology of attention: 2. Brightness and contrast. Consciousness and Cognition, 6, 372–412. doi:10.1006/ccog.1997.0313
33.
SaffranJ. R., AslinR. N., & NewportE. L. (1996). Statistical learning by 8-month-old infants. Science, 274, 1926–1928. doi:10.1126/science.274.5294.1926
34.
SergentC., WyartV., Babo-RebeloM., CohenL., NaccacheL., & Tallon-BaudryC. (2013). Cuing attention after the stimulus is gone can retrospectively trigger conscious perception. Current Biology, 23, 150–155. doi:10.1016/j.cub.2012.11.047
35.
ShiuL., & PashlerH. (1994). Negligible effect of spatial precuing on identification of single digits. Journal of Experimental Psychology: Human Perception and Performance, 20, 1037–1054. doi:10.1037/0096-1523.20.5.1037
36.
Shiu, L. P., & Pashler, H. (1995). Spatial attention and vernier acuity. Vision Research, 35(3), 337–343.
37.
SolomonJ. A., NilliL., & MorganM. J. (1997). Contrast discrimination function: Spatial cuing effects. Journal of the Optical Society of America A, 14, 2443–2448. doi:10.1364/josaa.14.002443
38.
Turk-BrowneN. B. (2012). Statistical learning and its consequences. In DoddM. D. & FlowersJ. H. (Eds.), The influence of attention, learning, and motivation on visual search (pp. 117–146). New York: Springer Science+Business Media.
39.
Turk-Browne, N. B., Scholl, B. J., Chun, M. M., & Johnson, M. K. (2009). Neural evidence of statistical learning: Efficient detection of visual regularities without awareness. Journal of Cognitive Neuroscience, 21(10), 1934–1945.
40.
van den BergR., AwhE., & MaW. J. (2014). Factorial comparison of working memory models. Psychology Review, 121, 124–149. doi:10.1037/a0035234
41.
van den BergR., ShinH., ChouW. C., GeorgeR., & MaW. J. (2012). Variability in encoding precision accounts for visual short-term memory limitations. Proceedings of the National Academy of Science USA, 109, 8780–5. doi:10.1073/pnas.1117465109
42.
WickhamH. (2009). ggplot2: Elegant graphics for data analysis. New York: Springer New York.
43.
WilkenP., & MaW. J. (2004). A detection theory account of change detection. Journal of Vision, 4, 1120–1135. doi:10.1167/4.12.11
44.
YehY-Y., YangC-T., & ChiuY-C. (2005). Binding or prioritization: The role of selective attention in visual short-term memory. Visual Cognition, 12, 759–799. doi:10.1080/13506280444000490
45.
ZhangW., & LuckS. J. (2008). Discrete fixed-resolution representations in visual working memory. Nature, 453, 233–235. doi:10.1037/e527342012-120
