Abstract
A series of experiments examined short-term recognition memory for trios of briefly presented, synthetic human faces derived from three real human faces. The stimuli were a graded series of faces, which differed by varying known amounts from the face of the average female. Faces based on each of the three real faces were transformed so as to lie along orthogonal axes in a 3-D face space. Experiment 1 showed that the synthetic faces’ perceptual similarity structure strongly influenced recognition memory. Results were fit by a noisy exemplar model (NEMO) of perceptual recognition memory (Kahana & Sekuler, 2002). The fits revealed that recognition memory was influenced both by the similarity of the probe to the series items and by the similarities among the series items themselves. Nonmetric multidimensional scaling (MDS) showed that the faces’ perceptual representations largely preserved the 3-D space in which the face stimuli were arrayed. NEMO gave a better account of the results when similarity was defined as perceptual MDS similarity, rather than as the physical proximity of one face to another. Experiment 2 confirmed the importance of within-list homogeneity directly, without mediation of a model. We discuss the affinities and differences between visual memory for synthetic faces and memory for simpler stimuli.
Article PDF
Similar content being viewed by others
References
Ashby, F. G., &Ell, S. W. (2001). The neurobiology of human category learning.Trends in Cognitive Sciences,5, 204–210.
Ashby, F. G., &Maddox, W. T. (1998). Stimulus categorization. In A. A. J. Marley (Ed.),Choice, decision, and measurement: Essays in honor of R. Duncan Luce (pp. 251–301). Mahwah, NJ: Erlbaum.
Brainard, D. H. (1997). The Psychophysics Toolbox.Spatial Vision,10, 443–446.
Brunswik, E., &Reiter, L. (1937). Eindruckscharaktere schematisierter Gesichter.Zeitschrift für Psychologie,142, 67–134.
Clark, S. E., &Gronlund, S. D. (1996). Global matching models of recognition memory: How the models match the data.Psychonomic Bulletin & Review,3, 37–60.
Diamantaras, K. I., &Kung, S. Y. (1996).Principal component neural networks. New York: Wiley.
Dryden, I. L., &Mardia, V. (1998).Statistical shape analysis. New York: Wiley.
Duchaine, B. C., &Weidenfeld, A. (2003). An evaluation of two commonly used tests of unfamiliar face recognition.Neuropsychologia,41, 713–720.
Ekman, P., &Friesen, W. V. (1975).Unmasking the face: A guide to recognizing emotions from facial cues. Englewood Cliffs, NJ: Prentice-Hall.
Ennis, D. M. (1988). Confusable and discriminable stimuli: Comment on Nosofsky (1986) and Shepard (1986).Journal of Experimental Psychology: General,117, 408–411.
Ennis, D. M., Mullen, K., Frijters, J. E. R., &Tindall, J. (1989). Decision conflicts: Within-trial resampling in Richardson’s method of triads.British Journal of Mathematical & Statistical Psychology,42, 265–269.
Gallegos, D. R., &Tranel, D. (2005). Positive facial affect facilitates identification of famous faces.Brain & Language,93, 338–348.
Gauthier, I., Skudlarski, P., Gore, J. C., &Anderson, A. W. (2000). Expertise for cars and birds recruits brain areas involved in face recognition.Nature Neuroscience,3, 191–197.
Gold, J., Bennett, P. J., &Sekuler, A. B. (1999). Signal but not noise changes with perceptual learning.Nature,402, 176–178.
Goldstein, A. G., &Chance, J. E. (1971). Visual recognition memory for complex configurations.Perception & Psychophysics,9, 237–241.
Goren, D., &Wilson, H. R. (2006). Quantifying facial expression recognition across viewing conditions.Vision Research,46, 1253–1262.
Grill-Spector, K., Knouf, N., &Kanwisher, N. (2004). The fusiform face area subserves face perception, not generic within-category identification.Nature Neuroscience,7, 555–562.
Gronlund, S. D. (2004). Sequential lineups: Shift in criterion or decision strategy?Journal of Applied Psychology,89, 362–368.
Hole, G. J. (1996). Decay and interference effects in visuospatial shortterm memory.Perception,25, 53–64.
Humphreys, M. S., Pike, R., Bain, J. D., &Tehan, G. (1989). Global matching: A comparison of the SAM, Minerva II, Matrix, and TODAM models.Journal of Mathematical Psychology,33, 36–67.
Hwang, G., Jacobs, J., Geller, A., Danker, J., Sekuler, R., &Kahana, M. J. (2005). EEG correlates of subvocal rehearsal in working memory.Behavioral & Brain Function,1, 20.
Isaacowitz, D., Wadlinger, H., Goren, D., &Wilson, H. (2006). Selective preference in visual fixation away from negative images in old age? An eye tracking study.Psychology & Aging,21, 40–48.
Johansson, M., Mecklinger, A., &Treese, A.-C. (2004). Recognition memory for emotional and neutral faces: An event-related potential study.Journal of Cognitive Neuroscience,16, 1840–1853.
Johnstone, A. B., &Williams, C. (1997). Do distinctive faces come from outer space? An investigation of the status of a multidimensional face-space.Visual Cognition,4, 59–67.
Joseph, J. E., &Gathers, A. D. (2002). Natural and manufactured objects activate the fusiform face area.NeuroReport,13, 935–938.
Kahana, M. J., &Sekuler, R. (2002). Recognizing spatial patterns: A noisy exemplar approach.Vision Research,42, 2177–2192.
Kahana, M. J., Zhou, F., Geller, A. S., &Sekuler, R. (2007). Lure similarity affects visual episodic recognition: Detailed tests of a noisy exemplar model.Memory & Cognition,35, 1222–1232.
Kaufmann, J. M., &Schweinberger, S. R. (2004). Expression influences the recognition of familiar faces.Perception,33, 399–408.
Klein, I., Paradis, A. L., Poline, J. B., Kosslyn, S. M., &Le Bihan, D. (2000). Transient activity in the human calcarine cortex during visualmental imagery: An event-related fMRI study.Journal of Cognitive Neuroscience,12(Suppl. 2), 15–23.
Kosslyn, S., Thompson, W. L., Kim, I. J., &Alpert, N. M. (1995). Topographical representations of mental images in primary visual cortex.Nature,378, 496–498.
Lee, K., Byatt, G., &Rhodes, G. (2000). Caricature effects, distinctiveness, and identification: Testing the face-space hypothesis.Psychological Science,11, 379–385.
Lehky, S. R. (2000). Fine discrimination of faces can be performed rapidly.Journal of Cognitive Neuroscience,12, 848–855.
Lindsay, R. C., Lea, J. A., Nosworthy, G. J., Fulford, J. A., Hector, J., LeVan, V., &Seabrook, C. (1991). Biased lineups: Sequential presentation reduces the problem.Journal of Applied Psychology,76, 796–802.
Loffler, G., Gordon, G. E., Wilkinson, F., Goren, D., &Wilson, H. R. (2005). Configural masking of faces: Evidence for high-level interactions in face perception.Vision Research,45, 2287–2297.
Loffler, G., Yourganov, G., Wilkinson, F., &Wilson, H. R. (2005). fMRI evidence for the neural representation of faces.Nature Neuroscience,8, 1386–1391.
Loftus, G. R., &Masson, M. E. J. (1994). Using confidence intervals in within-subject designs.Psychonomic Bulletin & Review,1, 476–490.
Magnussen, S., &Greenlee, M. W. (1999). The psychophysics of perceptual memory.Psychological Research,62, 81–92.
McKinley, S. C., &Nosofsky, R. M. (1996). Selective attention and the formation of linear decision boundaries.Journal of Experimental Psychology: Human Perception & Performance,22, 294–317.
Mitchell, M. (1996).An introduction to genetic algorithms. Cambridge, MA: MIT Press.
Näsänen, R. (1999). Spatial frequency bandwidth used in the recognition of facial images.Vision Research,39, 3824–3833.
Nosofsky, R. M. (1984). Choice, similarity, and the context theory of classification.Journal of Experimental Psychology: Learning, Memory, & Cognition,10, 104–114.
Nosofsky, R. M. (1986). Attention, similarity, and the identification-categorization relationship.Journal of Experimental Psychology: General,115, 39–57.
Nosofsky, R. M. (1991). Tests of an exemplar model for relating perceptual classification and recognition memory.Journal of Experimental Psychology: Human Perception & Performance,17, 3–27.
Nosofsky, R. M. (1992). Exemplar-based approach to relating categorization, identification, and recognition. In F. G. Ashby (Ed.),Multidimensional models of perception and cognition (pp. 363–394). Hillsdale, NJ: Erlbaum.
Nosofsky, R. M., &Kantner, J. (2006). Exemplar similarity, study list homogeneity, and short-term perceptual recognition.Memory & Cognition,34, 112–124.
Pelli, D. G. (1997). The VideoToolbox software for visual psychophysics: Transforming numbers into movies.Spatial Vision,10, 437–442.
Pelli, D. G., Robson, J. G., &Wilkins, A. J. (1988). Designing a new letter chart for measuring contrast sensitivity.Clinical Vision Sciences,2, 187–199.
Peters, R. J., Gabbiani, F., &Koch, C. (2003). Human visual object categorization can be described by models with low memory capacity.Vision Research,43, 2265–2280.
Phillips, W. A. (1974). On the distinction between sensory storage and short-term visual memory.Perception & Psychophysics,16, 283–290.
Phillips, W. A. (1983). Short-term visual memory.Philosophical Transactions of the Royal Society of London: Series B,302, 295–309.
Phillips, W. A., &Christie, D. F. M. (1977). Components of visual memory.Quarterly Journal of Experimental Psychology,29, 117–133.
Principle, J. C., Euliano, N. R., &Lefebvre, W. C. (2000).Neural and adaptive systems. New York: Wiley.
Riesenhuber, M., Jarudi, I., Gilad, S., &Sinha, P. (2004). Face processing in humans is compatible with a simple shape-based model of vision.Proceedings of the Royal Society of London: Series B,271, S448-S450.
Romney, A. K., Brewer, D. D., &Batchelder, W. H. (1993). Predicting clustering from semantic structure.Psychological Science,4, 28–34.
Sadr, J., Jarudi, I., &Sinha, P. (2003). The role of eyebrows in face recognition.Perception,32, 285–293.
Sigala, N., Gabbiani, F., &Logothetis, N. K. (2002). Visual categorization and object representation in monkeys and humans.Journal of Cognitive Neuroscience,14, 187–198.
Steblay, N., Dysart, J., Fulero, S., &Lindsay, R. C. (2001). Eyewitness accuracy rates in sequential and simultaneous lineup presentations: A meta-analytic comparison.Law & Human Behavior,25, 459–473.
Torgerson, W. S. (1958).Theory and methods of scaling. New York: Wiley.
Turtle, J., Lindsay, R. C., &Wells, G. L. (2003). Best practice recommendations for eyewitness evidence procedures: New ideas for the oldest way to solve a case.Canadian Journal of Police & Security Services,1, 5–18.
Valentine, T. (1991). A unified account of the effects of distinctiveness, inversion, and race in face recognition.Quarterly Journal of Experimental Psychology,43A, 161–204.
Valentine, T., &Bruce, V. (1986). The effects of distinctiveness in recognising and classifying faces.Perception,15, 525–535.
Valentine, T., &Endo, M. (1992). Towards an exemplar model of face processing: The effects of race and distinctiveness.Quarterly Journal of Experimental Psychology,44A, 671–703.
Visscher, K., Kaplan, E., Kahana, M. J., &Sekuler, R. (2006). Auditory short-term memory behaves like visual short-term memory.Public Library of Science Biology,5, e56.
Weller, S. C., &Romney, A. K. (1988).Systematic data collection (Vol. 10). Newbury Park, CA: Sage.
Wexler, K. N., &Romney, A. K. (1972). Individual variations in cognitive structures. In A. K. Romney, R. M. Shepard, & M. Nerlove (Eds.),Multidimensional scaling: Theory and applications in the behavioral sciences (2nd ed., pp. 73–92). New York: Seminar Press.
Wilson, H. R., Loffler, G., &Wilkinson, F. (2002). Synthetic faces, face cubes, and the geometry of face space.Vision Research,42, 2909–2923.
Yotsumoto, Y., Kahana, M. J., Wilson, H. R., &Sekuler, R. (2004).Preliminary studies of recognition memory for synthetic faces (Tech. Rep. 2004-3). Waltham, MA: Brandeis University, Visual Cognition Laboratory, Volen Center for Complex Systems.
Zhou, F., Kahana, M. J., &Sekuler, R. (2004). Short-term episodic memory for visual textures: A roving probe gathers some memory.Psychological Science,153, 112–118.
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Yotsumoto, Y., Kahana, M.J., Wilson, H.R. et al. Recognition memory for realistic synthetic faces. Memory & Cognition 35, 1233–1244 (2007). https://doi.org/10.3758/BF03193597
Received:
Accepted:
Issue Date:
DOI: https://doi.org/10.3758/BF03193597