Article published in:
Phonological and Phonetic Considerations of Lexical Processing
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

| Eberhard Karls Universität Tübingen
| Eberhard Karls Universität Tübingen
| University College London
| Eberhard Karls Universität Tübingen
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.
Published online: 01 October 2015
https://doi.org/10.1075/bct.80.08ram
References
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. CrossrefGoogle Scholar
Anderson, J.R.
(1974) Retrieval of propositional information from long-term memory. Cognitive Psychology, 6(4), 451–474. CrossrefGoogle Scholar
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. CrossrefGoogle Scholar
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. CrossrefGoogle Scholar
Baayen,R.H.
(2001) Word frequency distributions. Amsterdam: Kluwer. CrossrefGoogle Scholar
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. CrossrefGoogle Scholar
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. CrossrefGoogle Scholar
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. CrossrefGoogle Scholar
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. CrossrefGoogle Scholar
Box, G.E., & Draper, N.R.
(1987) Empirical model-building and response surfaces. John Wiley & Sons.Google Scholar
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. CrossrefGoogle Scholar
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. CrossrefGoogle Scholar
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. CrossrefGoogle Scholar
Brink, S.
(2014) An aging brain is still pretty smart [Web log article]. Retrieved fromNational Geographic, http://​news​.nationalgeographic​.com​/news​/2014​/01​/140128​-aging​-brain​-memory​-cognitive​-decline​-neurology/Google Scholar
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. CrossrefGoogle Scholar
(1979) Dendritic growth in the aged human brain and failure of growth in senile dementia. Science, 206, 854–856. CrossrefGoogle Scholar
Burke, S., & Barnes, C.
(2006) Neural plasticity in the aging brain. Nature Reviews Neuro science, 7(1), 30–40. CrossrefGoogle Scholar
Carey, B.
(2014) The older mind may just be a fuller mind [Web log article]. Retrieved fromThe New York Times, http://​newoldage​.blogs​.nytimes​.com​/2014​/01​/27​/the​-older​-mind​-may​-just​-be​-a​-fuller​-mindGoogle Scholar
Chrysikou, E.G., Weber, M.J., & Thompson-Schill, S.L.
(2013) A matched filter hypothesis for cognitive control. Neuropsychologia, S0028–3932(13), 00379–5.Google Scholar
Danks, D.
(2003) Equilibria of the rescorla-wagner model. Journal of Mathematical Psychology, 47(2), 109–121. CrossrefGoogle Scholar
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. CrossrefGoogle Scholar
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. CrossrefGoogle Scholar
Davies, M.
(2012) Expanding horizons in historical linguistics with the 400 million word Corpus of historical American English. Corpora, 7, 121–157. CrossrefGoogle Scholar
(2009) The 385+ million word corpus of contemporary American English (1990–present). International Journal of Corpus Linguistics, 14, 159–190. CrossrefGoogle Scholar
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. CrossrefGoogle Scholar
(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. CrossrefGoogle Scholar
Deary, I.J.. et al.
(2009) Age-associated cognitive decline. British Medical Bulletin, 92, 135–152. CrossrefGoogle Scholar
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. CrossrefGoogle Scholar
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. CrossrefGoogle Scholar
Driemeyer, J., Boyke, J., Gaser, C., Büchel, C., & May, A.
(2008) Changes in gray matter induced by learning – revisited. PLoS One, 3(7), e2669. CrossrefGoogle Scholar
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. CrossrefGoogle Scholar
Dweck, C.S.
(1999) Self-theories: Their role in motivation, personality and development. Philadelphia: Psychology Press.Google Scholar
Dweck, C.S., & Leggett, E.L.
(1988) A social-cognitive approach to motivation and personality. Psychological Review, 95(2), 256. CrossrefGoogle Scholar
Dweck, C.S.
(2006) Mindset: The new psychology of success. New York:Random House.Google Scholar
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. CrossrefGoogle Scholar
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. CrossrefGoogle Scholar
Flynn,J.R.
(1987) Massive IQ gains in 14 nations: What IQ tests really measure. Psychological Bulletin, 101, 171–191. CrossrefGoogle Scholar
Friederici, A.D.
(2011) The brain basis of language processing: From structure to function. Physiological Reviews, 91(4), 1357–1392. CrossrefGoogle Scholar
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. CrossrefGoogle Scholar
(1993) Critical issues in the analysis of dendritic extent in aging humans, primates, and rodents. Neurobiology of Aging, 14, 649–654. CrossrefGoogle Scholar
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. CrossrefGoogle Scholar
Hart, B. & Risley, T.T.
(1995) Meaningful differences in the everyday experience of young American children. Brookes Publishing.Google Scholar
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. CrossrefGoogle Scholar
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. CrossrefGoogle Scholar
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. CrossrefGoogle Scholar
Kriegeskorte, N., & Kievit, R.A.
(2013) Representational geometry: Integrating cognition, computation, and the brain. Trends in Cognitive Science, 17(8), 401–412. CrossrefGoogle Scholar
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. CrossrefGoogle Scholar
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. CrossrefGoogle Scholar
Kruschke, J.K.
(2003) Attention in learning. Current Directions in Psychological Science, 12,171–175. CrossrefGoogle Scholar
Lynn, R.
(1982) IQ in Japan and the United States shows a growing disparity. Nature, 297(5863), 222–223. CrossrefGoogle Scholar
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. CrossrefGoogle Scholar
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. CrossrefGoogle Scholar
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. CrossrefGoogle Scholar
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. CrossrefGoogle Scholar
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. CrossrefGoogle Scholar
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. CrossrefGoogle Scholar
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.Google Scholar
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. CrossrefGoogle Scholar
Park, D.C., & Reuter-Lorenz, P.
(2009) The adaptive brain: aging and neurocognitive scaffolding. Annual Review of Psychology, 60, 173. CrossrefGoogle Scholar
Pascual-Leone, A., Amedi, A., Fregni, F., & Merabet, L.B.
(2005) The plastic human brain cortex. Annual Review of Neuroscience, 28, 377–401. CrossrefGoogle Scholar
Pereira, A.F., Smith, L.B., & Yu, C.
(2014) A bottom-up view of toddler word learning. Psychonomic Bulletin & Review, 21(1), 178–185. CrossrefGoogle Scholar
Rabbitt, P.
(2014) Age and the overstuffed mind [Web log article]. Retrieved fromOutlook from the Hutch: A blog on aging and the mind, http://​pmar76​.wordpress​.com​/2014​/02​/06​/age​-and​-the​-overstuffed​-mind/
Ramscar, A.
(2014) What happens to our minds and memories in healthy aging? [Web log article]. Retrieved from The importance of being wrong, http://​ramscar​.wordpress​.com​/2014​/01​/19​/what​-happens​-to​-our​-minds​-and​-memories​-in​-healthy​-aging/
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. CrossrefGoogle Scholar
Ramscar, M., & Gitcho, N.
(2007) Developmental change and the nature of learning in childhood. Trends in Cognitive Science, 11(7), 274–279. CrossrefGoogle Scholar
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. CrossrefGoogle Scholar
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. CrossrefGoogle Scholar
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. CrossrefGoogle Scholar
Ramscar, M., Dye, M., & Klein, J.
(2013a) Children value informativity over logic in word learning. Psychological Science, 24(6), 1017–1023. CrossrefGoogle Scholar
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. CrossrefGoogle Scholar
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. CrossrefGoogle Scholar
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. CrossrefGoogle Scholar
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. CrossrefGoogle Scholar
(2010) Individual differences, aging, and IQ in twochoice tasks. Cognitive Psychology, 60, 127–157. CrossrefGoogle Scholar
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. CrossrefGoogle Scholar
Rescorla,R.A.
(1968) Probability of shock in the presence and absence of CS in fear conditioning. Journal of Comparative Physiology, 66, 1–5.Google Scholar
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.Google Scholar
Rescorla, R.A.
(1988) Pavlovian conditioning: It’s not what you think it is. American Psychologist, 43, 151–160. CrossrefGoogle Scholar
Rizzuto, D.S., & Kahana, M.J.
(2001) An autoassociative neural network model of paired-associate learning. Neural Computation, 13(9), 2075–2092. CrossrefGoogle Scholar
Salthouse, T.A.
(2009) When does age-related cognitive decline begin? Neurobiology of Aging, 30, 507–514. CrossrefGoogle Scholar
Salthouse.T.A.
(2011) Consequences of age-related cognitive declines. Annual Review of Psychology, 63, 5.1–5.26.Google Scholar
Schaie, K.W.
(1977) Quasi-experimental research designs in the psychology of aging. Handbook of the Psychology of Aging, 1, 39–69.Google Scholar
(1974) Translations in gerontology-from lab to life. Intellectual functioning. The American Psychologist, 29(11), 802. CrossrefGoogle Scholar
(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. CrossrefGoogle Scholar
(1959) Cross-sectional methods in the study of psychological aspects of aging. Journal of Gerontology, 14(2), 208–215. CrossrefGoogle Scholar
(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. CrossrefGoogle Scholar
Scholz, J., Klein, M.C., Behrens, T.E., & Johansen-Berg, H.
(2009) Training induces changes in white-matter architecture. Nature Neuroscience, 12, 1370–1371. CrossrefGoogle Scholar
Schultz, W.
(2006) Behavioral theories and the neurophysiology of reward. Annual Review of Psychology, 57, 87–115. CrossrefGoogle Scholar
Schultz, W., Dayan, P., & Montague, P.R.
(1997) A neural substrate of prediction and reward. Science, 275(5306), 1593–1599. CrossrefGoogle Scholar
Schurz, M., Sturm, D., Richlan, F., Kronbichler, M., Ladurner, G., & WimmerH.
(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. CrossrefGoogle Scholar
Shimamura, A.P.
(2000) The role of the prefrontal cortex in dynamic filtering. Psychobiology, 28, 207–218.Google Scholar
Singh-Manoux, A.. et al.
(2012) Timing of onset of cognitive decline: Results from Whitehall II prospective cohort study. British Medical Journal, 344, d7622. CrossrefGoogle Scholar
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. CrossrefGoogle Scholar
Steele, C.M.
(1997) A threat in the air: How stereotypes shape intellectual identity and performance. American Psychologist, 52(6), 613–629. CrossrefGoogle Scholar
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. CrossrefGoogle Scholar
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. CrossrefGoogle Scholar
Weisleder, A., & Fernald, A.
(2013) Talking to children matters: Early language experience strengthens processing and builds vocabulary. Psychological Science, 24(11), 2143–2152. CrossrefGoogle Scholar
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. CrossrefGoogle Scholar
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. CrossrefGoogle Scholar
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. CrossrefGoogle Scholar
Zucker, R.S.
(1999) Calcium-andactivity-dependentsynapticplasticity. Current Opinion in Neurobiology, 9, 305–313. CrossrefGoogle Scholar
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. CrossrefGoogle Scholar