Part of
Phonological and Phonetic Considerations of Lexical ProcessingEdited by Gonia Jarema and Gary Libben
[Benjamins Current Topics 80] 2015
► pp. 199–230
Edited by Gonia Jarema and Gary Libben
[Benjamins Current Topics 80] 2015
► pp. 199–230
Learning is not decline
The mental lexicon as a window into cognition across the lifespan
As otherwise healthy adults age, their performance on cognitive tests tends to decline. This change is traditionally taken as evidence that cognitive processing is subject to significant declines in healthy aging. We examine this claim, showing current theories over-estimate the evidence in support of it, and demonstrating that when properly evaluated, the empirical record often indicates that the opposite is true.
To explain the disparity between the evidence and current theories, we show how the models of learning assumed in aging research are incapable of capturing even the most basic of empirical facts of “associative” learning, and lend themselves to spurious discoveries of “cognitive decline.” Once a more accurate model of learning is introduced, we demonstrate that far from declining, the accuracy of older adults lexical processing appears to improve continuously across the lifespan. We further identify other measures on which performance does not decline with age, and show how these different patterns of performance fit within an overall framework of learning.
Finally, we consider the implications of our demonstrations of continuous and consistent learning performance throughout adulthood for our understanding of the changes in underlying brain morphology that occur during the course of cognitive development across the lifespan.
References (102)
Alemán-Gómez, Y., Janssen, J., Schnack, H., Balaban, E., Pina-Camacho, L., Alfaro-Almagro, F., & Desco, M. (2013). The Human cerebral cortex flattens during adolescence. The Journal of Neuroscience, 33(38), 15004–15010. 
Anderson, J.R. (1974). Retrieval of propositional information from long-term memory. Cognitive Psychology, 6(4), 451–474.
Arnon, I., & Ramscar, M. (2012). Granularity and the acquisition of grammatical gender: How order of acquisition affects what gets learned. Cognition, 122(3), 292–305.
Baayen, R.H., Davidson, D.J., & Bates, D.M. (2008). Mixed-effects modeling with crossed random effects for subjects and items. Journal of Memory and Language, 59(4), 390–412.
Baayen, R.H. (2001). Word frequency distributions. Amsterdam: Kluwer.
Baayen, R.H., Milin, P., Đurđević, D.F., Hendrix, P., & Marelli, M. (2011). An amorphous model for morphological processing in visual comprehension based on naive discriminative learning. Psychological Review, 118(3), 438–482.
Baayen, R.H., Hendrix, P., & Ramscar, M. (2013). Sidestepping the combinatorial explosion: Towards a processing model based on discriminative learning. Language and Speech, 56, 329–347.
Baayen, R.H., Feldman, L.B., & Schreuder, R. (2006). Morphological influences on the recog-nition of monosyllabic monomorphemic words. Journal of Memory and Language, 55(2), 290–313.
Bion, R.A., Borovsky, A., & Fernald, A. (2013). Fast mapping, slow learning: Disambiguation of novel word–object mappings in relation to vocabulary learning at 18, 24, and 30months. Cognition, 126(1), 39–53.
Box, G.E., & Draper, N.R. (1987). Empirical model-building and response surfaces. John Wiley & Sons.
Borovsky, A., Elman, J.L., & Fernald, A. (2012). Knowing a lot for one’s age: Vocabulary skill and not age is associated with anticipatory incremental sentence interpretation in children and adults. Journal of Experimental Child Psychology, 112(4), 417–436.
Boyke, J., Driemeyer, J., Gaser, C., Buchel, C., & May, A. (2008). Training-induced brain structure changes in the elderly. Journal of Neuroscience, 28, 7031–7035.
Bruno, J.L., Zumberge, A., Manis, F.R., Lu, Z.-L., & Goldman, J.G. (2008). Sensitivity to orthographic familiarity in the occipito-temporal region. Neuroimage, 39, 1988–2001.
Brink, S. (2014). An aging brain is still pretty smart [Web log article]. Retrieved fromNational Geographic, [URL]
Buell, S.J., & Coleman, P.D. (1981). Quantitative evidence for selective dendritic growth in normal human aging but not in senile dementia. Brain Research, 214, 23–41.
. (1979). Dendritic growth in the aged human brain and failure of growth in senile dementia. Science, 206, 854–856.
Burke, S., & Barnes, C. (2006). Neural plasticity in the aging brain. Nature Reviews Neuro science, 7(1), 30–40.
Carey, B. (2014). The older mind may just be a fuller mind [Web log article]. Retrieved fromThe New York Times, [URL]
Chrysikou, E.G., Weber, M.J., & Thompson-Schill, S.L. (2013). A matched filter hypothesis for cognitive control. Neuropsychologia, S0028–3932(13), 00379–5.
Danks, D. (2003). Equilibria of the rescorla-wagner model. Journal of Mathematical Psychology, 47(2), 109–121.
Daw, N.D., Courville, A.C., & Dayan, P. (2008). Semi-rational models of conditioning: The case of trial order. InN. Chater & M. Oaksford(Eds.), The probabilistic mind. Oxford: Oxford University Press.
Daw, N.D., Gershman, S.J., Seymour, B., Dayan, P., & Dolan, R.J. (2011). Model-based influences on humans’ choices and striatal prediction errors. Neuron, 69(6), 1204–1215.
Davies, M. (2012) Expanding horizons in historical linguistics with the 400 million word Corpus of historical American English. Corpora, 7, 121–157.
. (2009). The 385+ million word corpus of contemporary American English (1990–present). International Journal of Corpus Linguistics, 14, 159–190.
Davis, T., Love, B.C., & Preston, A.R. (2012a). Learning the Exception to the Rule: Model-based fMRI reveals specialized representations for surprising category members. Cerebral Cortex, 22, 260–273.
. (2012b). Striatal and hippocampal entropy and recogni-tion signals in category learning: Simultaneous processes revealed by model-based fMRI. Journal of Experimental Psychology: Learning, Memory, and Cognition, 38, 821–839.
Deary, I.J. et al. (2009). Age-associated cognitive decline. British Medical Bulletin, 92, 135–152.
des Rosiers, G., & Ivison, D. (1986). Paired-associate learning: Normative data for differences between high and low associate word pairs. Journal of Clinical Experimental Neuropsychology, 8, 637–642.
Draganski, B., Gaser, C., Busch, V., Schuierer, G., Bogdahn, U., & May, A. (2004). Neuroplasticity: Changes in grey matter induced by training. Nature, 427(6972), 311–312.
Driemeyer, J., Boyke, J., Gaser, C., Büchel, C., & May, A. (2008). Changes in gray matter induced by learning – revisited. PLoS One, 3(7), e2669.
Dweck, C.S., Davidson, W., Nelson, S., & Enna, B. (1978). Sex differences in learned helplessness: II. The contingencies of evaluative feedback in the classroom and III. An experimental analysis. Developmental psychology, 14(3), 268.
Dweck, C.S. (1999). Self-theories: Their role in motivation, personality and development. Philadelphia: Psychology Press.
Dweck, C.S., & Leggett, E.L. (1988). A social-cognitive approach to motivation and personality. Psychological Review, 95(2), 256.
Dweck, C.S. (2006). Mindset: The new psychology of success. New York:Random House.
Fernald, A., Marchman, V.A., & Weisleder, A. (2012). SES differences in language processing skill and vocabulary are evident at 18 months. Developmental Science, 16(2), 234–248.
Fernald, A., & Marchman, V.A. (2012). Individual differences in lexical processing at 18 months predict vocabulary growth in typically developing and late‐talking toddlers. Child Development, 83(1), 203–222.
Flynn, J.R. (1987). Massive IQ gains in 14 nations: What IQ tests really measure. Psychological Bulletin, 101, 171–191.
Friederici, A.D. (2011). The brain basis of language processing: From structure to function. Physiological Reviews, 91(4), 1357–1392.
Flood, D.G. (1991). Region-specific stability of dendritic extent in normal human aging and regression in Alzheimer’s disease. II. Subiculum. Brain Research, 540, 83–95.
. (1993). Critical issues in the analysis of dendritic extent in aging humans, primates, and rodents. Neurobiology of Aging, 14, 649–654.
Gureckis, T.M., & Love, B.C. (2010). Direct associations or transformations of an internal state? Exploring the mechanism underlying sequential learning behavior. Cognitive Science, 34, 10–50.
Hart, B. & Risley, T.T. (1995). Meaningful differences in the everyday experience of young American children. Brookes Publishing.
Hess, T.M., Auman, C., Colcombe, S.J., & Rahhal, T.A. (2003). The impact of stereotype threat on age differences in memory performance. The Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 58(1), P3–P11.
Hess, T.M., & Hinson, J.T. (2006). Age-related variation in the influences of aging stereotypes on memory in adulthood. Psychology and Aging, 21(3), 621.
Hess, T.M., Hinson, J.T., & Hodges, E.A. (2009). Moderators of and mechanisms underlying stereotype threat effects on older adults’ memory performance. Experimental Aging Research, 35(2), 153–177.
Kriegeskorte, N., & Kievit, R.A. (2013). Representational geometry: Integrating cognition, computation, and the brain. Trends in Cognitive Science, 17(8), 401–412.
Kronbichler, M., Bergmann, J., Hutzler, F., Staffen, W., Mair, A., & Ladurner, G. (2007). Taxi vs. Taksi: Orthographic word recognition in the left ventral occipitotemporal cortex. Journal of Cognitive Neuroscience, 19, 1584–1594.
Kronbichler, M., Hutzler, F., Wimmer, H., Mair, A., Staffen, W., & Ladurner, G. (2004). The visual word form area and the frequency with which words are encountered: evidence from a parametric fMRI study. Neuroimage, 21, 946–953.
Kruschke, J.K. (2003). Attention in learning. Current Directions in Psychological Science, 12,171–175.
Lynn, R. (1982). IQ in Japan and the United States shows a growing disparity. Nature, 297(5863), 222–223.
Mack, M.L., Preston, A.R., & Love, B.C. (2013). Decoding the Brain’s algorithm for categorization from its neural implementation. Current Biology, 23, 2023–2027.
Mangels, J.A., Good, C., Whiteman, R.C., Maniscalco, B., & Dweck, C.S. (2012). Emotion blocks the path to learning under stereotype threat. Social Cognitive and Affective Neuroscience, 7(2), 230–241.
Mano, Q.R., Humphries, C., Desai, R.H., Seidenberg, M.S., Osmon, D.C., Stengel, B.C., & Binder, J.R. (2013). The role of left occipitotemporal cortex in reading: Reconciling stimulus, task, and lexicality effects. Cerebral Cortex, 23(4), 988–1001.
Merrill, D.A., Chiba, A.A., & Tuszynski, M.H. (2001). Conservation of neuronal number and size in the entorhinal cortex of behaviorally characterized aged rats. The Journal of Comparative Neurology, 438, 445–456.
Morris, R.G, Moser, E.I., Riedel, G., Martin, S.J., Sandin, J., Day, M., & O’Carroll, C. (2003). Elements of a neurobiological theory of the hippocampus: The role of activity-dependent synaptic plasticity in memory. Philosophical Transactions of the Royal Society B: Biological Sciences, 358, 773–786.
Nelson, D.L., Dyrdal, G.M., & Goodmon, L.B. (2005). What is preexisting strength? Predicting free association probabilities, similarity ratings, and cued recall probabilities. Psychonomic Bulletin & Review, 12(4), 711–719.
Nusbaum, H.C. (1985). A Stochastic account of the relationship between Lexical Density and Word Frequency. Indiana University, Research on Speech Perception, Progress Report #11.
O’Donnell, C., Nolan, M.F., & van Rossum, M.C. (2011). Dendritic spine dynamics regulate the long-term stability of synaptic plasticity. The Journal of Neuroscience, 31(45), 16142–16156.
Park, D.C., & Reuter-Lorenz, P. (2009). The adaptive brain: aging and neurocognitive scaffolding. Annual Review of Psychology, 60, 173.
Pascual-Leone, A., Amedi, A., Fregni, F., & Merabet, L.B. (2005). The plastic human brain cortex. Annual Review of Neuroscience, 28, 377–401.
Pereira, A.F., Smith, L.B., & Yu, C. (2014). A bottom-up view of toddler word learning. Psychonomic Bulletin & Review, 21(1), 178–185.
Rabbitt, P. (2014). Age and the overstuffed mind [Web log article]. Retrieved fromOutlook from the Hutch: A blog on aging and the mind, [URL]
Ramscar, A. (2014). What happens to our minds and memories in healthy aging? [Web log article]. Retrieved from The importance of being wrong, [URL]
Ramscar, M., Hendrix, P., Shaoul, C., Milin, P., & Baayen, H. (2014). The myth of cognitive decline: Non-linear dynamics of lifelong learning. Topics in Cognitive Science, 6, 5–42.
Ramscar, M., & Gitcho, N. (2007). Developmental change and the nature of learning in childhood. Trends in Cognitive Science, 11(7), 274–279.
Ramscar, M., & Yarlett, D. (2007). Linguistic self-correction in the absence of feedback: A new approach to the logical problem of language acquisition. Cognitive Science, 31, 927–960.
Ramscar, M.J.A., Yarlett, D.G., Dye, M.W., Denny, K., & Thorpe, K. (2010). The effects of Feature-Label-Order and their implications for symbolic learning. Cognitive Science, 34(6), 909–957.
Ramscar, M., Dye, M., Popick, H.M., & O’Donnell-McCarthy, F. (2011). The enigma of number: Why children find the meanings of even small number words hard to learn and how we can help them do better. PLoS ONE, 6(7): e22501.
Ramscar, M., Dye, M., & Klein, J. (2013a). Children value informativity over logic in word learning. Psychological Science, 24(6), 1017–1023.
Ramscar, M., Dye, M., Gustafson, J.W., & Klein, J. (2013b). Dual routes to cognitive flexibility: Learning and response conflict resolution in the dimensional change card sort task. Child Development, 84(4), 1308–1323.
Ramscar, M., Dye, M., & McCauley, S. (2013c). Error and expectation in language learning: The curious absence of ‘mouses’ in adult speech. Language, 89(4), 760–793.
Rapp, P.R., & Gallagher, M. (1996). Preserved neuron number in the hippocampus of aged rats with spatial learning deficits. Proceedings of the National Academy of Sciences USA, 93, 9926–9930.
Ratcliff, R., Thapar, A., & McKoon, G. (2011). Effects of aging and IQ on item and associative memory. Journal of Experimental Psychology: General, 140(3), 464–487.
. (2010). Individual differences, aging, and IQ in twochoice tasks. Cognitive Psychology, 60, 127–157.
Rattan, A., Good, C., & Dweck, C.S. (2012). “It’ s ok – not everyone can be good at math”: Instructors with an entity theory comfort (and demotivate) students. Journal of Experimental Social Psychology, 48(3), 731–737.
Rescorla, R.A. (1968). Probability of shock in the presence and absence of CS in fear conditioning. Journal of Comparative Physiology, 66, 1–5.
Rescorla, R.A., & Wagner, A.R. (1972). A theory of Pavlovian conditioning: Variations in the effectiveness of reinforcement and nonreinforcement. InA.H. Black & W.F. Prokasy(Eds.), Classical conditioning II: Current research and theory (pp. 64–99). New York: Crofts.
Rescorla, R.A. (1988). Pavlovian conditioning: It’s not what you think it is. American Psychologist, 43, 151–160.
Rizzuto, D.S., & Kahana, M.J. (2001). An autoassociative neural network model of paired-associate learning. Neural Computation, 13(9), 2075–2092.
Salthouse, T.A. (2009). When does age-related cognitive decline begin? Neurobiology of Aging, 30, 507–514.
Salthouse. T.A. (2011). Consequences of age-related cognitive declines. Annual Review of Psychology, 63, 5.1–5.26.
Schaie, K.W. (1977). Quasi-experimental research designs in the psychology of aging. Handbook of the Psychology of Aging, 1, 39–69.
. (1974). Translations in gerontology-from lab to life. Intellectual functioning. The American Psychologist, 29(11), 802.
. (1973). Methodological problems in descriptive developmental research on adulthood and aging. InJ.R. Nesselroade & H.W. Reese(Eds.), Life-span developmental psychology: Methodological issues (pp. 253–280). New York: Academic Press.
. (1959). Cross-sectional methods in the study of psychological aspects of aging. Journal of Gerontology, 14(2), 208–215.
. (1988). Internal validity threats in studies of adult cognitive development. InM.L. Howe & C.J. Brainerd(Eds.), Cognitive development in adulthood: Progress in cognitive development research (pp. 241–272). New York: Springer-Verlag.
Scholz, J., Klein, M.C., Behrens, T.E., & Johansen-Berg, H. (2009). Training induces changes in white-matter architecture. Nature Neuroscience, 12, 1370–1371.
Schultz, W. (2006). Behavioral theories and the neurophysiology of reward. Annual Review of Psychology, 57, 87–115.
Schultz, W., Dayan, P., & Montague, P.R. (1997). A neural substrate of prediction and reward. Science, 275(5306), 1593–1599.
Schurz, M., Sturm, D., Richlan, F., Kronbichler, M., Ladurner, G., & Wimmer H. (2010). A dual-route perspective on brain activation in response to visual words: Evidence for a length by lexicality interaction in the visual word form area (VWFA). Neuroimage, 49, 2649–2661.
Shimamura, A.P. (2000). The role of the prefrontal cortex in dynamic filtering. Psychobiology, 28, 207–218.
Singh-Manoux, A. et al. (2012). Timing of onset of cognitive decline: Results from Whitehall II prospective cohort study. British Medical Journal, 344, d7622.
Sowell, E.R., Peterson, B.S., Thompson, P.M., Welcome, S.E., Henkenius, A.L., & Toga, A.W. (2003). Mapping cortical change across the human lifespan. Nature Neuroscience, 6(3),309–415.
Steele, C.M. (1997). A threat in the air: How stereotypes shape intellectual identity and performance. American Psychologist, 52(6), 613–629.
Teasdale, T.W., & Owen, D.R. (2005). A long-term rise and recent decline in intelligence test performance: The Flynn Effect in reverse. Personality and Individual Differences, 39(4), 837–843.
Turner, B.M., Forstmann, B.U., Wagenmakers, E.J., Brown, S.D., Sederberg, P.B., & Steyvers, M. (2013). A Bayesian framework for simultaneously modeling neural and behavioral data. Neuroimage, 72, 193–206.
Weisleder, A., & Fernald, A. (2013). Talking to children matters: Early language experience strengthens processing and builds vocabulary. Psychological Science, 24(11), 2143–2152.
Werker, J., & Tees, R. (1984). Cross-language speech perception: Evidence for perceptual reor-ganization during the first year of life. Infant Behavior and Development, 7, 49–63.
Yeager, D.S., & Dweck, C.S. (2012). Mindsets that promote resilience: When students believe that personal characteristics can be developed. Educational Psychologist, 47(4), 302–314.
Zatorre, R.J., Fields, R.D., & Johansen-Berg, H. (2012). Plasticity in gray and white: Neuro- imaging changes in brain structure during learning. Nature Neuroscience, 15(4), 528–536.
Zucker, R.S. (1999). Calcium-andactivity-dependentsynapticplasticity. Current Opinion in Neurobiology, 9, 305–313.
Zuo, Y., Lin, A., Chang, P., & Gan, W.B. (2005). Development of long-term dendritic spine stability in diverse regions of cerebral cortex. Neuron, 46, 181–189.