Abstract
Visual perception can be affected by training mental representations. However, it remains unclear if training procedures can also affect the quality of mental representations. To investigate if training enhances the fidelity of mental representations retrieved from visual long-term memory (VLTM), we used a task including object-color associations with a continuous response-space. We tested 15 participants in a training group and 15 participants in a control group. Training consisted of six training runs executed on 3 consecutive days. Before and after training, we assessed accessibility and fidelity of mental representations in VLTM and of single objects in visual short-term memory (VSTM). Not only accessibility to mental representation but also their fidelity increased across training and transferred to novel object-color associations in VLTM and VSTM after training. At the end of the training, fidelity of VLTM representations were virtually identical to fidelity of VSTM representations. We conclude that training object-color associations does not only improve the accessibility of VLTM representations, but also their fidelity based on perceptual plasticity of the visual system.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Notes
Model-free analyses were repeated with means of absolute response errors for every participant (instead of medians). All statistical decisions were identical to those based on medians of absolute response errors, with the exception of an additional main effect session, F(1, 28) = 6.66, p = .015, ηp2 = .19, in the 2 × 2 mixed measures ANOVA for the VLTM data with the within-subject factor session (pre-training vs. post-training) and the between-subject factor group (training vs. control).
References
Allred, S. R., & Flombaum, J. I. (2014). Relating color working memory and color perception. Trends in Cognitive Sciences, 18(11), 562–565. https://doi.org/10.1016/j.tics.2014.06.002.
Amar-Halpert, R., Laor-Maayany, R., Nemni, S., Rosenblatt, J. D., & Censor, N. (2017). Memory reactivation improves visual perception. Nature Neuroscience, 20(10), 1325–1328. https://doi.org/10.1038/nn.4629.
Baddeley, A. D., & Hitch, G. J. (2017). Is the levels of processing effect language-limited? Journal of Memory and Language, 92, 1–13. https://doi.org/10.1016/j.jml.2016.05.001.
Bae, G.-Y., Olkkonen, M., Allred, S. R., Wilson, C., & Flombaum, J. I. (2014). Stimulus-specific variability in color working memory with delayed estimation. Journal of Vision, 14(4), 7–7. https://doi.org/10.1167/14.4.7.
Bae, G.-Y., Olkkonen, M., Allred, S. R., & Flombaum, J. I. (2015). Why some colors appear more memorable than others: a model combining categories and particulars in color working memory. Journal of Experimental Psychology: General, 144(4), 744–763. https://doi.org/10.1037/xge0000076.
Bennett, R. G., & Westheimer, G. (1991). The effect of training on visual alignment discrimination and grating resolution. Perception & Psychophysics, 49(6), 541–546. https://doi.org/10.3758/BF03212188.
Brady, T. F., Konkle, T., Gill, J., Oliva, A., & Alvarez, G. A. (2013). Visual long-term memory has the same limit on fidelity as visual working memory. Psychological Science, 24(6), 981–990. https://doi.org/10.1177/0956797612465439.
Brainard, D. H. (1997). The psychophysics toolbox. Spatial Vision, 10(4), 433–436. https://doi.org/10.1163/156856897X00357.
Brodeur, M. B., Dionne-Dostie, E., Montreuil, T., & Lepage, M. (2010). The bank of standardized stimuli (BOSS), a new set of 480 normative photos of objects to be used as visual stimuli in cognitive research. PLoS One, 5(5), e10773. https://doi.org/10.1371/journal.pone.0010773.
Burke, S. N., & Barnes, C. A. (2006). Neural plasticity in the ageing brain. Nature Reviews Neuroscience, 7(1), 30–40. https://doi.org/10.1038/nrn1809.
Buschkuehl, M., Jaeggi, S. M., Mueller, S. T., Shah, P., & Jonides, J. (2017). Training change detection leads to substantial task-specific improvement. Journal of Cognitive Enhancement, 1, 419–433. https://doi.org/10.1007/s41465-017-0055-y.
Dosher, B. A., & Lu, Z.-L. (1998). Perceptual learning reflects external noise filtering and internal noise reduction through channel reweighting. Proceedings of the National Academy of Sciences, 95(23), 13988–13993. https://doi.org/10.1073/pnas.95.23.13988.
Dosher, B. A., & Lu, Z.-L. (2017). Visual perceptual learning and models. Annual Review of Vision Science, 3, 343–363. https://doi.org/10.1146/annurev-vision-102016-061249.
Fan, J. E., Hutchinson, J. B., & Turk-Browne, N. B. (2016). When past is present: substitutions of long-term memory for sensory evidence in perceptual judgments. Journal of Vision, 16(8), 1. https://doi.org/10.1167/16.8.1.
Fiorentini, A., & Berardi, N. (1980). Perceptual learning specific for orientation and spacial frequency. Nature, 287, 43–44.
Fiorentini, A., & Berardi, N. (1981). Learning in grating waveform discrimination: specificity for orientation and spatial frequency. Vision Research, 21(7), 1149–1158. https://doi.org/10.1016/0042-6989(81)90017-1.
Fougnie, D., Suchow, J. W., & Alvarez, G. A. (2012). Variability in the quality of visual working memory. Nature Communications, 3, 1229. https://doi.org/10.1038/ncomms2237.
Goldstone, R. L. (1998). Perceptual learning. Annual Review of Psychology, 49, 585–612.
Grady, C. L., & Craik, F. I. M. (2000). Changes in memory processing with age. Current Opinion in Neuro Biology, 10, 224–231. https://doi.org/10.1093/ejil/chq032.
Karni, A., & Bertini, G. (1997). Learning plasticity. Current Opinion in Neuro Biology, 7, 530–535.
Knoblauch, K., Vital-Durand, F., & Barbur, J. L. (2001). Variation of chromatic sensitivity across the life span. Vision Research, 41(1), 23–36. https://doi.org/10.1016/S0042-6989(00)00205-4.
Konkle, T., Brady, T. F., Alvarez, G. A., & Oliva, A. (2010). Conceptual distinctiveness supports detailed visual long-term memory for real-world objects. Journal of Experimental Psychology: General, 139(3), 558–578. https://doi.org/10.1037/a0019165.
Kosslyn, S. M., Alpert, N. M., Thompson, W. L., Maljkovic, V., Weise, S. B., Chabris, C. F., et al. (1993). Visual mental imagery activates topographically organized visual cortex: PET investigations. Journal of Cognitive Neuroscience, 5(3), 263–287. https://doi.org/10.1162/jocn.1993.5.3.263.
Leys, C., Ley, C., Klein, O., Bernard, P., & Licata, L. (2013). Detecting outliers: do not use standard deviation around the mean, use absolute deviation around the median. Journal of Experimental Social Psychology, 49(4), 764–766. https://doi.org/10.1016/j.jesp.2013.03.013.
Mast, F. W., Tartaglia, E. M., & Herzog, M. H. (2012). New percepts via mental imagery? Frontiers in Psychology, 3, 360. https://doi.org/10.3389/fpsyg.2012.00360.
Mednick, S., Nakayama, K., & Stickgold, R. (2003). Sleep-dependent learning: a nap is as good as a night. Nature Neuroscience, 6(7), 697–698. https://doi.org/10.1038/nn1078.
Meier, B., Rey-Mermet, A., Rothen, N., & Graf, P. (2013). Recognition memory across the lifespan: the impact of word frequency and study-test interval on estimates of familiarity and recollection. Frontiers in Psychology, 4, 1–15. https://doi.org/10.3389/fpsyg.2013.00787.
Owsley, C. (2011). Aging and vision. Vision Research, 51(13), 1610–1622. https://doi.org/10.1016/j.visres.2010.10.020.
Owsley, C. (2016). Vision and aging. Annual Review of Vision Science, 2, 255–271. https://doi.org/10.1146/annurev-vision-111815-114550.
Özgen, E., & Davies, I. R. L. (2002). Acquisition of categorical color perception: a perceptual learning approach to the linguistic relativity hypothesis. Journal of Experimental Psychology: General, 131(4), 477–493. https://doi.org/10.1037//0096-3445.131.4.477.
Paramei, G. V. (2012). Color discrimination across four life decades assessed by the Cambridge colour test. Journal of the Optical Society of America A, 29(2), A290–A297. https://doi.org/10.1364/JOSAA.29.00A290.
Park, D. C., & Reuter-Lorenz, P. (2009). The adaptive brain: aging and neurocognitive scaffolding. Annual Review of Psychology, 60(1), 173–196. https://doi.org/10.1146/annurev.psych.59.103006.093656.
Pearson, J., Clifford, C. W. G., & Tong, F. (2008). The functional impact of mental imagery on conscious perception. Current Biology, 18(13), 982–986. https://doi.org/10.1016/j.cub.2008.05.048.
Pearson, J., Naselaris, T., Holmes, E. A., & Kosslyn, S. M. (2015). Mental imagery: functional mechanisms and clinical applications. Trends in Cognitive Sciences, 19(10), 590–602. https://doi.org/10.1016/j.tics.2015.08.003.
Pelli, D. G. (1997). The VideoToolbox software for visual psychophysics: transforming numbers into movies. Spatial Vision, 10(4), 437–442. https://doi.org/10.1163/156856897X00366.
Prinzmetal, W., Amiri, H., Allen, K., & Edwards, T. (1998). Phenomenology of attention: I. color, location, orientation, and spatial frequency. Journal of Experimental Psychology: Human Perception and Performance, 24(1), 261–282. https://doi.org/10.1037/0096-1523.24.1.261.
Rademaker, R. L., & Pearson, J. (2012). Training visual imagery: improvements of metacognition, but not imagery strength. Frontiers in Psychology, 3, 224. https://doi.org/10.3389/fpsyg.2012.00224.
Rajaram, S. (1996). Perceptual effects on remembering: recollective processes in picture recognition memory. Journal of Experimental Psychology. Learning, Memory, and Cognition, 22(2), 365–377.
Rasch, B., & Born, J. (2013). About sleep’s role in memory. Physiological Reviews, 93, 681–766. https://doi.org/10.1152/Physrev.00032.2012.
Schoups, A. A., Vogels, R., & Orban, G. A. (1995). Human perceptual learning in identifying the oblique orientation: Retinotopy, orientation specificity and monocularity. The Journal of Physiology, 483(3), 797–810. https://doi.org/10.1113/jphysiol.1995.sp020623.
Schoups, A. A., Vogels, R., Qian, N., & Orban, G. (2001). Practising orientation identification improves orientation coding in V1 neurons. Nature, 412(6846), 549–553. https://doi.org/10.1038/35087601.
Souza, A. S., & Skóra, Z. (2017). The interplay of language and visual perception in working memory. Cognition, 166, 277–297. https://doi.org/10.1016/j.cognition.2017.05.038.
Suchow, J. W., Brady, T. F., Fougnie, D., & Alvarez, G. A. (2013). Modeling visual working memory with the MemToolbox. Journal of Vision, 13(10), 9. https://doi.org/10.1167/13.10.9.
Sutterer, D. W., & Awh, E. (2016). Retrieval practice enhances the accessibility but not the quality of memory. Psychonomic Bulletin and Review, 23(3), 831–841. https://doi.org/10.3758/s13423-015-0937-x.
Tartaglia, E. M., Bamert, L., Mast, F. W., & Herzog, M. H. (2009). Human perceptual learning by mental imagery. Current Biology, 19(24), 2081–2085. https://doi.org/10.1016/j.cub.2009.10.060.
Thurston, C., & Dobkins, K. (2007). Stimulus-specific perceptual learning for chromatic, but not luminance, contrast detection. Journal of Vision, 7(9), 469–469.
van den Berg, R., Shin, H., Chou, W.-C., George, R., & Ma, W. J. (2012). Variability in encoding precision accounts for visual short-term memory limitations. Proceedings of the National Academy of Sciences, 109(22), 8780–8785. https://doi.org/10.1073/pnas.1117465109.
Vingrys, A. J., & King-Smith, P. E. (1988). A quantitative scoring technique for panel tests of color vision. Investigative Ophthalmology and Visual Science, 29(1), 50–63.
Watanabe, T., & Sasaki, Y. (2015). Perceptual learning: toward a comprehensive theory. Annual Review of Psychology, 66(1), 197–221. https://doi.org/10.1146/annurev-psych-010814-015214.
Wesemann, W., Schiefer, U., & Bach, M. (2010). Neue DIN-Normen zur Sehschärfebestimmung. Ophthalmologe, 107(9), 821–826. https://doi.org/10.1007/s00347-010-2228-2.
Wilken, P., & Ma, W. J. (2004). A detection theory account of change detection. Journal of Vision, 4(12), 11. https://doi.org/10.1167/4.12.11.
Witzel, C., & Franklin, A. (2014). Do focal colors look particularly “colorful”? Journal of the Optical Society of America A, 31(4), A365–A374. https://doi.org/10.1364/JOSAA.31.00A365.
Xie, W., & Zhang, W. (2017). Negative emotion enhances mnemonic precision and subjective feelings of remembering in visual long-term memory. Cognition, 166, 73–83. https://doi.org/10.1016/j.cognition.2017.05.025.
Xie, W., & Zhang, W. (2018). Mood-dependent retrieval in visual long-term memory: dissociable effects on retrieval probability and mnemonic precision. Cognition and Emotion, 32(4), 674–690. https://doi.org/10.1080/02699931.2017.1340261.
Zeki, S., Watson, J. D. G., Lueck, C. J., Friston, K. J., Kennard, C., & Frackowiak, R. S. J. (1991). A direct demonstration of functional specialization in human visual cortex. The Journal of Neuroscience, 11(3), 641–649.
Zhang, W., & Luck, S. J. (2008). Discrete fixed-resolution representations in visual working memory. Nature, 453, 233–235. https://doi.org/10.1038/Nature06860.
Acknowledgements
The authors thank Christoph Witzel for advice on color rendering. Further, the authors thank Geoffrey Ward, Jerry Fisher, and Christa von Dach for their helpful comments on a previous version of this article during a summer school, and Esther Brill and Sophie Ankner for data acquisition.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of Interest
The authors declare that they have no competing interests.
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
This work was supported by the Swiss National Science Foundation (Grant Number: PZ00P1_154954).
Electronic supplementary material
Supplementary Figure 1
(PDF 81 kb)
Rights and permissions
About this article
Cite this article
Ovalle Fresa, R., Rothen, N. Training Enhances Fidelity of Color Representations in Visual Long-Term Memory. J Cogn Enhanc 3, 315–327 (2019). https://doi.org/10.1007/s41465-019-00121-y
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s41465-019-00121-y