Attention, Perception, & Psychophysics

, Volume 76, Issue 7, pp 2015–2030 | Cite as

Understanding age-related reductions in visual working memory capacity: Examining the stages of change detection

  • Philip C. Ko
  • Bryant Duda
  • Erin Hussey
  • Emily Mason
  • Robert J. Molitor
  • Geoffrey F. Woodman
  • Brandon A. Ally


Visual working memory (VWM) capacity is reduced in older adults. Research has shown age-related impairments to VWM encoding, but aging is likely to affect multiple stages of VWM. In the present study, we recorded the event-related potentials (ERPs) of younger and older adults during VWM maintenance and retrieval. We measured encoding-stage processing with the P1 component, maintenance-stage processing with the contralateral delay activity (CDA), and retrieval-stage processing by comparing the activity for old and new items (old–new effect). Older adults showed lower behavioral capacity estimates (K) than did younger adults, but surprisingly, their P1 components and CDAs were comparable to those of younger adults. This remarkable dissociation between neural activity and behavior in the older adults indicated that the P1 and CDA did not accurately assess their VWM capacity. However, the neural activity evoked during VWM retrieval yielded results that helped clarify the age-related differences. During retrieval, younger adults showed early old–new effects in frontal and occipital areas and a late central–parietal old–new effect, whereas older adults showed a late right-lateralized parietal old–new effect. The younger adults’ early old–new effects strongly resembled an index of perceptual fluency, suggesting that perceptual implicit memory was activated. The activation of implicit memory could have facilitated the younger adults’ behavior, and the lack of these early effects in older adults may suggest that they have much lower-resolution memory than do younger adults. From these data, we speculated that younger and older adults store the same number of items in VWM, but that younger adults store a higher-resolution representation than do older adults.


Visual working memory Aging Event-related potentials (ERP) 


Author Note

This research was supported by National Institute on Aging Grant Nos. K23AG031925 and R01AG0347 to B.A.A., and F32AG044076 to P.C.K.

Supplementary material

13414_2013_585_Fig6_ESM.jpg (105 kb)
Supplementary Figure 1

(JPEG 104 kb)

13414_2013_585_MOESM1_ESM.tif (3.4 mb)
High resolution image (TIFF 3.44 mb)
13414_2013_585_Fig7_ESM.jpg (101 kb)
Supplementary Figure 2

(JPEG 100 kb)

13414_2013_585_MOESM2_ESM.tif (29.5 mb)
High resolution image (TIFF 29.4 mb)
13414_2013_585_MOESM3_ESM.docx (88 kb)
ESM 1 (DOCX 88 kb)


  1. Adjutant General’s Office. (1944). Army individual test battery: Manual of directions and scoring. Washington, DC: War Department.Google Scholar
  2. Ally, B. A., & Budson, A. E. (2007). The worth of pictures: Using high density event-related potentials to understand the memorial power of pictures and the dynamics of recognition memory. NeuroImage, 35, 378–395. doi: 10.1016/j.neuroimage.2006.11.023 PubMedCrossRefPubMedCentralGoogle Scholar
  3. Ally, B. A., McKeever, J. D., Waring, J. D., & Budson, A. E. (2009). Preserved frontal memorial processing for pictures in patients with mild cognitive impairment. Neuropsychologia, 47, 2044–2055. doi: 10.1016/j.neuropsychologia.2009.03.015 PubMedCrossRefPubMedCentralGoogle Scholar
  4. Ally, B. A., Simons, J. S., McKeever, J. D., Peers, P. V., & Budson, A. E. (2008a). Parietal contributions to recollection: Electrophysiological evidence from aging and patients with parietal lesions. Neuropsychologia, 46, 1800–1812. doi: 10.1016/j.neuropsychologia.2008.02.026 PubMedCrossRefPubMedCentralGoogle Scholar
  5. Ally, B. A., Waring, J. D., Beth, E. H., McKeever, J. D., Milberg, W. P., & Budson, A. E. (2008b). Aging memory for pictures: Using high-density event-related potentials to understand the effect of aging on the picture superiority effect. Neuropsychologia, 46, 679–689. doi: 10.1016/j.neuropsychologia.2007.09.011 PubMedCrossRefPubMedCentralGoogle Scholar
  6. Alter, A. L., & Oppenheimer, D. M. (2009). Uniting the tribes of fluency to form a metacognitive nation. Personality and Social Psychology Review, 13, 219–235. doi: 10.1177/1088868309341564 PubMedCrossRefGoogle Scholar
  7. Awh, E., Barton, B., & Vogel, E. K. (2007). Visual working memory represents a fixed number of items regardless of complexity. Psychological Science, 18, 622–628. doi: 10.1111/j.1467-9280.2007.01949.x PubMedCrossRefGoogle Scholar
  8. Awh, E., & Jonides, J. (2001). Overlapping mechanisms of attention and spatial working memory. Trends in Cognitive Sciences, 5, 119–126. doi: 10.1016/S1364-6613(00)01593-X PubMedCrossRefGoogle Scholar
  9. Bays, P. M., & Husain, M. (2008). Dynamic shifts of limited working memory resources in human vision. Science, 321, 851–854. doi: 10.1126/science.1158023 PubMedCrossRefPubMedCentralGoogle Scholar
  10. Bledowski, C., Kaiser, J., Wibral, M., Yildiz-Erzberger, K., & Rahm, B. (2012). Separable neural bases for subprocesses of recognition in working memory. Cerebral Cortex, 22, 1950–1958. doi: 10.1093/cercor/bhr276 PubMedCrossRefGoogle Scholar
  11. Brockmole, J. R., Parra, M. A., Della Sala, S., & Logie, R. H. (2008). Do binding deficits account for age-related decline in visual working memory? Psychonomic Bulletin & Review, 15, 543–547. doi: 10.3758/PBR.15.3.543 CrossRefGoogle Scholar
  12. Brown, L. A., & Brockmole, J. R. (2010). The role of attention in binding visual features in working memory: Evidence from cognitive ageing. Quarterly Journal of Experimental Psychology, 63, 2067–2079. doi: 10.1080/17470211003721675 CrossRefGoogle Scholar
  13. Budson, A. E., Droller, D. B., Dodson, C. S., Schacter, D. L., Rugg, M. D., Holcomb, P. J., & Daffner, K. R. (2005). Electrophysiological dissociation of picture versus word encoding: The distinctiveness heuristic as a retrieval orientation. Journal of Cognitive Neuroscience, 17, 1181–1193. doi: 10.1162/0898929055002517 PubMedCrossRefGoogle Scholar
  14. Ciaramelli, E., Rosenbaum, R. S., Solcz, S., Levine, B., & Moscovitch, M. (2010). Mental space travel: Damage to posterior parietal cortex prevents egocentric navigation and reexperiencing of remote spatial memories. Journal of Experimental Psychology: Learning, Memory, and Cognition, 36, 619–634. doi: 10.1037/a0019181 PubMedGoogle Scholar
  15. Cowan, N. (2001). The magical number 4 in short-term memory: A reconsideration of mental storage capacity. Behavioral and Brain Sciences, 24, 87–114. doi: 10.1017/S0140525X01003922. disc. 114–185.PubMedCrossRefGoogle Scholar
  16. Cowan, N., Naveh-Benjamin, M., Kilb, A., & Saults, J. S. (2006). Life-span development of visual working memory: When is feature binding difficult? Developmental Psychology, 42, 1089–1102. doi: 10.1037/0012-1649.42.6.1089 PubMedCrossRefPubMedCentralGoogle Scholar
  17. Curran, T., DeBuse, C., Woroch, B., & Hirshman, E. (2006). Combined pharmacological and electrophysiological dissociation of familiarity and recollection. Journal of Neuroscience, 26, 1979–1985. doi: 10.1523/JNEUROSCI.5370-05.2006 PubMedCrossRefGoogle Scholar
  18. Danker, J. F., Hwang, G. M., Gauthier, L., Geller, A., Kahana, M. J., & Sekuler, R. (2008). Characterizing the ERP old–new effect in a short-term memory task. Psychophysiology, 45, 784–793. doi: 10.1111/j.1469-8986.2008.00672.x PubMedCrossRefPubMedCentralGoogle Scholar
  19. Daselaar, S. M., Fleck, M. S., Dobbins, I. G., Madden, D. J., & Cabeza, R. (2006). Effects of healthy aging on hippocampal and rhinal memory functions: An event-related fMRI study. Cerebral Cortex, 16, 1771–1782. doi: 10.1093/cercor/bhj112 PubMedCrossRefPubMedCentralGoogle Scholar
  20. Dien, J. (1998). Addressing misallocation of variance in principal components analysis of event-related potentials. Brain Topography, 11, 43–55.PubMedCrossRefGoogle Scholar
  21. Donchin, E., & Coles, M. G. H. (1988). Is the P300 component a manifestation of context updating? Behavioral and Brain Sciences, 11, 357–374.CrossRefGoogle Scholar
  22. Drew, T., Horowitz, T. S., & Vogel, E. K. (2013). Swapping or dropping? Electrophysiological measures of difficulty during multiple object tracking. Cognition, 126, 213–223. doi: 10.1016/j.cognition.2012.10.003 PubMedCrossRefPubMedCentralGoogle Scholar
  23. Fleischman, D. A. (2007). Repetition priming in aging and Alzheimer’s disease: An integrative review and future directions. Cortex, 43, 889–897.PubMedCrossRefGoogle Scholar
  24. Folstein, M. F., Folstein, S. E., & McHugh, P. R. (1975). “Mini Mental State”: A practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research, 12, 189–198. doi: 10.1016/0022-3956(75)90026-6 PubMedCrossRefGoogle Scholar
  25. Fukuda, K., Awh, E., & Vogel, E. K. (2010). Discrete capacity limits in visual working memory. Current Opinion in Neurobiology, 20, 177–182. doi: 10.1016/j.conb.2010.03.005 PubMedCrossRefPubMedCentralGoogle Scholar
  26. Gao, Z., Yin, J., Xu, H., Shui, R., & Shen, M. (2011). Tracking object number or information load in visual working memory: Revisiting the cognitive implication of contralateral delay activity. Biological Psychology, 87, 296–302. doi: 10.1016/j.biopsycho.2011.03.013 PubMedCrossRefGoogle Scholar
  27. Gazzaley, A., Clapp, W., Kelley, J., McEvoy, K., Knight, R. T., & D’Esposito, M. (2008). Age-related top-down suppression deficit in the early stages of cortical visual memory processing. Proceedings of the National Academy of Sciences, 105, 13122–13126. doi: 10.1073/pnas.0806074105 CrossRefGoogle Scholar
  28. Hasher, L., & Zacks, R. T. (1988). Working memory, comprehension, and aging: A review and a new view. In G. H. Bower (Ed.), The psychology of learning and motivation: Advances in research and theory (Vol. 22, pp. 193–225). San Diego, CA: Academic Press. doi: 10.1016/S0079-7421(08)60041-9 Google Scholar
  29. Howard, M. W., Bessette-Symons, B., Zhang, Y., & Hoyer, W. J. (2006). Aging selectively impairs recollection in recognition memory for pictures: Evidence from modeling and receiver operating characteristic curves. Psychology and Aging, 21, 96–106. doi: 10.1037/0882-7974.21.1.96 PubMedCrossRefPubMedCentralGoogle Scholar
  30. Hyun, J.-S., Woodman, G. F., Vogel, E. K., Hollingworth, A., & Luck, S. J. (2009). The comparison of visual working memory representations with perceptual inputs. Journal of Experimental Psychology: Human Perception and Performance, 35, 1140–1160. doi: 10.1037/a0015019 PubMedPubMedCentralGoogle Scholar
  31. Ikkai, A., McCollough, A. W., & Vogel, E. K. (2010). Contralateral delay activity provides a neural measure of the number of representations in visual working memory. Journal of Neurophysiology, 103, 1963–1968. doi: 10.1152/jn.00978.2009 PubMedCrossRefPubMedCentralGoogle Scholar
  32. Jacoby, L. L., & Dallas, M. (1981). On the relationship between autobiographical memory and perceptual learning. Journal of Experimental Psychology: General, 110, 306–340. doi: 10.1037/0096-3445.110.3.306 CrossRefGoogle Scholar
  33. Jacoby, L. L., & Whitehouse, K. (1989). An illusion of memory: False recognition influenced by unconscious perception. Journal of Experimental Psychology: General, 118, 126–135. doi: 10.1037/0096-3445.118.2.126 CrossRefGoogle Scholar
  34. Jiang, Y., Haxby, J. V., Martin, A., Ungerleider, L. G., & Parasuraman, R. (2000). Complementary neural mechanisms for tracking items in human working memory. Science, 287, 643–646. doi: 10.1126/science.287.5453.643 PubMedCrossRefGoogle Scholar
  35. Johnson, J., Spencer, J., Luck, S., & Schöner, G. (2009). A dynamic neural field model of visual working memory and change detection. Psychological Science, 20, 568–577.PubMedCrossRefPubMedCentralGoogle Scholar
  36. Jost, K., Bryck, R. L., Vogel, E. K., & Mayr, U. (2011). Are old adults just like low working memory young adults? Filtering efficiency and age differences in visual working memory. Cerebral Cortex, 21, 1147–1154. doi: 10.1093/cercor/bhq185 PubMedCrossRefGoogle Scholar
  37. Ko, P. C., Duda, B., Hussey, E., & Ally, B. A. (2013). Electrophysiological distinctions between recognition memory with and without awareness. Neuropsychologia, 51, 642–655.PubMedCrossRefPubMedCentralGoogle Scholar
  38. Kurilla, B. P., & Gonsalves, B. D. (2012). An ERP investigation into the strategic regulation of the fluency heuristic during recognition memory. Brain Research, 1442, 36–46. doi: 10.1016/j.brainres.2011.12.060 PubMedCrossRefPubMedCentralGoogle Scholar
  39. Leynes, P. A., & Zish, K. (2012). Event-related potential (ERP) evidence for fluency-based recognition memory. Neuropsychologia, 50, 3240–3249. doi: 10.1016/j.neuropsychologia.2012.10.004 CrossRefGoogle Scholar
  40. Lins, O. G., Picton, T. W., Berg, P., & Scherg, M. (1993). Ocular artifacts in EEG and event-related potentials I: Scalp topography. Brain Topography, 6, 51–63.PubMedCrossRefGoogle Scholar
  41. Luria, R., Sessa, P., Gotler, A., Jolicœur, P., & Dell’Acqua, R. (2009). Visual short-term memory capacity for simple and complex objects. Journal of Cognitive Neuroscience, 22, 496–512. doi: 10.1162/jocn.2009.21214 CrossRefGoogle Scholar
  42. Luria, R., & Vogel, E. K. (2011). Shape and color conjunction stimuli are represented as bound objects in visual working memory. Neuropsychologia, 49, 1632–1639. doi: 10.1016/j.neuropsychologia.2010.11.031 PubMedCrossRefPubMedCentralGoogle Scholar
  43. Mack, W. J., Freed, D. M., Williams, B. W., & Henderson, V. W. (1992). Boston Naming Test: Shortened versions for use in Alzheimer’s disease. Journal of Gerontology, 47, 154–P158.CrossRefGoogle Scholar
  44. Magen, H., Emmanouil, T.-A., McMains, S. A., Kastner, S., & Treisman, A. (2009). Attentional demands predict short-term memory load response in posterior parietal cortex. Neuropsychologia, 47, 1790–1798. doi: 10.1016/j.neuropsychologia.2009.02.015 PubMedCrossRefPubMedCentralGoogle Scholar
  45. Mathes, B., Schmiedt, J., Schmiedt-Fehr, C., Pantelis, C., & Basar-Eroglu, C. (2012). New rather than old? For working memory tasks with abstract patterns the P3 and the single-trial delta response are larger for modified than identical probe stimuli. Psychophysiology, 49, 920–932.PubMedCrossRefGoogle Scholar
  46. Monsch, A. U., Bondi, M. W., Butters, N., Salmon, D. P., Katzman, R., & Thal, L. J. (1992). Comparisons of verbal fluency tasks in the detection of dementia of the Alzheimer type. Archives of Neurology, 49, 1253–1258.PubMedCrossRefGoogle Scholar
  47. Morris, J. C., Heyman, A., Mohs, R. C., Hughes, J. P., van Belle, G., Fillenbaum, G., & Clark, C. (1989). The Consortium to Establish a Registry for Alzheimer’s Disease (CERAD): Part I. Clinical and neuropsychological assessment of Alzheimer’s disease. Neurology, 39, 1159–1165.PubMedCrossRefGoogle Scholar
  48. Naveh-Benjamin, M. (2000). Adult age differences in memory performance: Tests of an associative deficit hypothesis. Journal of Experimental Psychology: Learning, Memory, and Cognition, 26, 1170–1187. doi: 10.1037/0278-7393.26.5.1170 PubMedGoogle Scholar
  49. Nessler, D., Mecklinger, A., & Penney, T. B. (2005). Perceptual fluency, semantic familiarity and recognition-related familiarity: An electrophysiological exploration. Cognitive Brain Research, 22, 265–288. doi: 10.1016/j.cogbrainres.2004.03.023 PubMedCrossRefGoogle Scholar
  50. Noack, H., Lövdén, M., & Lindenberger, U. (2012). Normal aging increases discriminal dispersion in visuospatial short-term memory. Psychology and Aging, 27, 627–637. doi: 10.1037/a0027251 PubMedCrossRefGoogle Scholar
  51. Nobre, A. C., Coull, J. T., Maquet, P., Frith, C. D., Vandenberghe, R., & Mesulam, M. M. (2004). Orienting attention to locations in perceptual versus mental representations. Journal of Cognitive Neuroscience, 16, 363–373. doi: 10.1162/089892904322926700 PubMedCrossRefGoogle Scholar
  52. Öztekin, I., Davachi, L., & McElree, B. (2010). Are representations in working memory distinct from representations in long-term memory? Neural evidence in support of a single store. Psychological Science, 21, 1123–1133. doi: 10.1177/0956797610376651 PubMedCrossRefPubMedCentralGoogle Scholar
  53. Öztekin, I., McElree, B., Staresina, B. P., & Davachi, L. (2009). Working memory retrieval: Contributions of the left prefrontal cortex, the left posterior parietal cortex, and the hippocampus. Journal of Cognitive Neuroscience, 21, 581–593. doi: 10.1162/jocn.2008.21016 PubMedCrossRefPubMedCentralGoogle Scholar
  54. Parra, M. A., Abrahams, S., Logie, R. H., & Della Sala, S. (2009). Age and binding within-dimension features in visual short-term memory. Neuroscience Letters, 449, 1–5. doi: 10.1016/j.neulet.2008.10.069 PubMedCrossRefGoogle Scholar
  55. Rajaram, S., & Geraci, L. (2000). Conceptual fluency selectively influences knowing. Journal of Experimental Psychology: Learning, Memory, and Cognition, 26, 1070–1074. doi: 10.1037/0278-7393.26.4.1070 PubMedGoogle Scholar
  56. Reuter-Lorenz, P. A., & Sylvester, C.-Y. C. (2005). The cognitive neuroscience of working memory and aging. In R. Cabeza, L. Nyberg, & D. Park (Eds.), Cognitive neuroscience of aging: Linking cognitive and cerebral aging (pp. 186–217). New York, NY: Oxford University Press.Google Scholar
  57. Rugg, M. D., & Curran, T. (2007). Event-related potentials and recognition memory. Trends in Cognitive Sciences, 11, 251–257. doi: 10.1016/j.tics.2007.04.004 PubMedCrossRefGoogle Scholar
  58. Rugg, M. D., Mark, R. E., Walla, P., Schloerscheidt, A. M., Birch, C. S., & Allan, K. (1998). Dissociation of the neural correlates of implicit and explicit memory. Nature, 392, 595–598. doi: 10.1038/33396 PubMedCrossRefGoogle Scholar
  59. Ryals, A. J., Yadon, C. A., Nomi, J. S., & Cleary, A. M. (2011). When word identification fails: ERP correlates of recognition without identification and of word identification failure. Neuropsychologia, 49, 3224–3237. doi: 10.1016/j.neuropsychologia.2011.07.027 PubMedCrossRefGoogle Scholar
  60. Sander, M. C., Werkle-Bergner, M., & Lindenberger, U. (2011). Contralateral delay activity reveals life-span age differences in top-down modulation of working memory contents. Cerebral Cortex, 21, 2809–2819. doi: 10.1093/cercor/bhr076 PubMedCrossRefGoogle Scholar
  61. Simons, J. S., Peers, P. V., Mazuz, Y. S., Berryhill, M. E., & Olson, I. R. (2010). Dissociation between memory accuracy and memory confidence following bilateral parietal lesions. Cerebral Cortex, 20, 479–485. doi: 10.1093/cercor/bhp116 PubMedCrossRefPubMedCentralGoogle Scholar
  62. Soldan, A., Hilton, H. J., Cooper, L. A., & Stern, Y. (2009). Priming of familiar and unfamiliar visual objects over delays in young and older adults. Psychology and Aging, 24, 93–104. doi: 10.1037/a0014136 PubMedCrossRefPubMedCentralGoogle Scholar
  63. Vaughan, L., & Hartman, M. (2009). Aging and visual short-term memory: Effects of object type and information load. Aging, Neuropsychology, and Cognition, 17, 35–54. doi: 10.1080/13825580903009063 CrossRefGoogle Scholar
  64. Vogel, E. K., & Machizawa, M. G. (2004). Neural activity predicts individual differences in visual working memory capacity. Nature, 428, 748–751. doi: 10.1038/nature02447 PubMedCrossRefGoogle Scholar
  65. Vogel, E. K., McCollough, A. W., & Machizawa, M. G. (2005). Neural measures reveal individual differences in controlling access to working memory. Nature, 438, 500–503. doi: 10.1038/nature04171 PubMedCrossRefGoogle Scholar
  66. Voss, J. L., Lucas, H. D., & Paller, K. A. (2010). Conceptual priming and familiarity: Different expressions of memory during recognition testing with distinct neurophysiological correlates. Journal of Cognitive Neuroscience, 22, 2638–2651. doi: 10.1162/jocn.2009.21341 PubMedCrossRefGoogle Scholar
  67. Voss, J. L., Lucas, H. D., & Paller, K. A. (2012). More than a feeling: Pervasive influences of memory without awareness of retrieval. Cognitive Neuroscience, 3, 193–207. doi: 10.1080/17588928.2012.674935 PubMedCrossRefGoogle Scholar
  68. Voss, J. L., & Paller, K. A. (2009). An electrophysiological signature of unconscious recognition memory. Nature Neuroscience, 12, 349–355. doi: 10.1038/nn.2260 PubMedCrossRefPubMedCentralGoogle Scholar
  69. Warbrick, T., Arrubla, J., Boers, F., Neuner, I., & Shah, N. J. (2013). Attention to detail: Why considering task demands is essential for single-trial analysis of BOLD correlates of the visual P1 and N1. Journal of Cognitive Neuroscience. doi: 10.1162/jocn_a_00490. Advance online publication.PubMedGoogle Scholar
  70. Wheeler, M. E., & Treisman, A. M. (2002). Binding in short-term visual memory. Journal of Experimental Psychology: General, 131, 48–64. doi: 10.1037/0096-3445.131.1.48 CrossRefGoogle Scholar
  71. Woodman, G. F. (2010). A brief introduction to the use of event-related potentials in studies of perception and attention. Attention, Perception, & Psychophysics, 72, 2031–2046. doi: 10.3758/BF03196680 CrossRefGoogle Scholar
  72. Woodman, G. F., Vecera, S. P., & Luck, S. J. (2003). Perceptual organization influences visual working memory. Psychonomic Bulletin & Review, 10, 80–87. doi: 10.3758/BF03196470 CrossRefGoogle Scholar
  73. Woodruff, C. C., Hayama, H. R., & Rugg, M. D. (2006). Electrophysiological dissociation of the neural correlates of recollection and familiarity. Brain Research, 1100, 125–135. doi: 10.1016/j.brainres.2006.05.019 PubMedCrossRefGoogle Scholar
  74. Woollams, A. M., Taylor, J. R., Karayanidis, F., & Henson, R. N. (2008). Event-related potentials associated with masked priming of test cues reveal multiple potential contributions to recognition memory. Journal of Cognitive Neuroscience, 20, 1114–1129. doi: 10.1162/jocn.2008.20076 PubMedCrossRefGoogle Scholar
  75. Xu, Y., & Chun, M. M. (2006). Dissociable neural mechanisms supporting visual short-term memory for objects. Nature, 440, 91–95. doi: 10.1038/nature04262 PubMedCrossRefGoogle Scholar
  76. Xu, Y., & Chun, M. M. (2009). Selecting and perceiving multiple visual objects. Trends in Cognitive Sciences, 13, 167–174. doi: 10.1016/j.tics.2009.01.008 PubMedCrossRefPubMedCentralGoogle Scholar
  77. Yonelinas, A. P. (2002). The nature of recollection and familiarity: A review of 30 years of research. Journal of Memory and Language, 46, 441–517. doi: 10.1006/jmla.2002.2864 CrossRefGoogle Scholar
  78. Yonelinas, A. P., Aly, M., Wang, W.-C., & Koen, J. D. (2010). Recollection and familiarity: Examining controversial assumptions and new directions. Hippocampus, 20, 1178–1194. doi: 10.1002/hipo.20864 PubMedCrossRefGoogle Scholar
  79. Yonelinas, A. P., Widaman, K., Mungas, D., Reed, B., Weiner, M. W., & Chui, H. C. (2007). Memory in the aging brain: Doubly dissociating the contribution of the hippocampus and entorhinal cortex. Hippocampus, 17, 1134–1140. doi: 10.1002/hipo.20341 PubMedCrossRefPubMedCentralGoogle Scholar
  80. Zhang, W., & Luck, S. (2008). Discrete fixed-resolution representations in visual working memory. Nature, 453, 233–235. doi: 10.1038/nature06860 PubMedCrossRefPubMedCentralGoogle Scholar

Copyright information

© Psychonomic Society, Inc. 2013

Authors and Affiliations

  • Philip C. Ko
    • 1
    • 4
  • Bryant Duda
    • 1
  • Erin Hussey
    • 1
  • Emily Mason
    • 1
  • Robert J. Molitor
    • 1
  • Geoffrey F. Woodman
    • 2
  • Brandon A. Ally
    • 1
    • 3
  1. 1.Department of NeurologyVanderbilt UniversityNashvilleUSA
  2. 2.Department of PsychologyVanderbilt UniversityNashvilleUSA
  3. 3.Departments of Psychology and PsychiatryVanderbilt UniversityNashvilleUSA
  4. 4.Department of NeurologyVanderbilt UniversityNashvilleUSA

Personalised recommendations