Ramscar et al (2014)1 claim that Cognitive Aging is “a myth” because slowing of all decisions is a key behavioural marker of mental changes in old age2 but occurs only because accumulation of information over a lifetime slows retrieval of data to support any decision. This feel-good news that slowing of decisions on all tasks is not a defining symptom of progressive failure but an honourable distinction of an age-stocked mind has eagerly excited the media (Telegraph; Guardian; BBC World Service , New York Times), but not researchers on cognitive aging.
The Ramscar model seems to derive from the earlier Homer Simpson model: “Every time I learn something new it pushes something out”. The Simpson model makes no prediction for decision speed because it posits finite data capacity beyond which no increment, and so no further slowing, can occur. In this respect it is more elegant than the Ramscar model which makes no allowance for stabilisation or even shrinking of the data store by data attrition (forgetting) or displacement.
The Simpson model is also parsimonious because it makes no predictions for age-related change, leaving open whether other factors such as biological changes affect retrieval and so decision times. The Ramscar model is actually also age-neutral and can only account for age-related changes in data retrieval speed by an extra assumption that brain neurophysiology, and so efficiency, remain unchanged throughout the lifespan until, and unless gross pathologies such as dementias intervene. In fact diffuse progressive brain changes indexed by global losses of neural tissue and marked by white matter lesions begin in young adulthood, accelerate throughout the rest of life and affect decision times earlier and more severely than memory or other mental abilities3,4,5. In terms of present medical knowledge these changes are considered “normal” or “usual” slowly progressive age-related changes not necessarily symptomatic of gross pathologies. The silence of the Simpson model on this issue is judicious.
The Ramscar model is supported by ingenious analyses of the statistical properties of linguistic data-sets to support the idea that larger sets require longer search times. The nearest to any explanation of why age also slows performance on very simple non-verbal tasks is the claim that all tasks require participants to interpret instructions which becomes slower to retrieve as general knowledge of the world and, in particular, vocabulary increases. It is hard to accept this as an explanation for marked age-slowing in even the simplest possible tasks such as responding with one finger to one signal lamp. Or as an explanation for why the old, though perhaps initially handicapped by misunderstanding of simple tasks, continue to be slower even when practised beyond the point at which they can improve.
Because the Ramscar model is actually age-neutral it is over-modest to only apply it to age-related cognitive slowing. It is far more general because its only premise is that the more information any system, including the brain, holds the longer it must take to retrieve any data from it. The claim that old brains inevitably contain more information than young brains is not necessary. It is also contentious because it requires an extra assumption that all the information that our brains ever process is permanently recorded and becomes progressively less inaccessible only because mental congestion increases. So if we compare the speed with which people of any age can distinguish words of different categories or words from non-words or, indeed, make decisions of any kind, those who have larger vocabularies and more knowledge of the world must be slower. In fact the opposite is the case. Perhaps Ramscar et al elide this point because of their need to counter a quite different objection that old people generally have only equal or even lower scores on vocabulary tests than the young. Ramscar et al insist that vocabulary tests cannot be appropriate measures because they are biased towards low frequency words and so do not accurately assess older people who know more rare words that are not tested. It is questionable whether most older people actually do know more rare words than most young adults, but scores on vocabulary tests are not the only, or the best comparison. For instance, people of any age whose brains are so stuffed with words that they can produce more names of animals within a fixed time also produce words in other categories correspondingly faster and more accurately. This does not support the Ramscar hypothesis that words are retrieved more slowly from a large vocabulary. This is not a problem for the elegantly simple Simpson model.
To argue that stuffed minds are the sole cause of “the myth” of cognitive aging, the Ramscar model must also account for other marked individual differences in decision speed such as those indexed by scores on intelligence tests. People with higher intelligence test scores have larger vocabularies and stores of information about the world than those with lower scores. They nevertheless generate categories of words much faster, more accurately and more completely than lower scorers do, and are also faster at making all other kinds of decisions about the world6,7. My unpublished results show that, when all of these variables are entered as joint predictors of their performance, individuals’ intelligence test scores predict more of the variance between them on verbal category generation tasks than either their ages or their vocabulary test scores. Further, non-verbal intelligence test scores account for more than 90% of specifically age-related variance in decision times on simple letter/letter coding tasks.8 Here, once again, the judiciously scholarly non-commitment of the Simpson model is an advantage.
In conclusion: unlike the Simpson model, which was arguably first empirically tested seventy years ago9 and still offers a touching insight into the human condition, the Ramscar model may be intended only as a provocation and to stimulate discussion. The boundary between provocation and exasperation is narrow, and is shifted by the experiences and intellectual commitments of an audience. Auden’s useful phrase “Clever-Silly” comes irresistibly to mind, but this must be inadvertent fall-out from an elderly brain overstuffed by failure to assimilate the vast literature on cognitive aging. Ramscar and his associates clearly do not suffer this handicap but I hope that their good natures may allow them to forgive the lapse.
- Ramscar, M., Hendrix, P., Shaoul, C., Milin,P. & Bayen, H., (2014) The myth of Cognitive Decline: Non-Linear Dynamics of Lifelong Learning. Topics in Cognitive Science, 1-38
- Salthouse, T. A. (1985). A cognitive theory of aging.
- Rabbitt, P., Mogapi, O., Scott, M., Thacker, N., Lowe, C., Horan, M., … & Lunn, D. (2007). Effects of global atrophy, white matter lesions, and cerebral blood flow on age-related changes in speed, memory, intelligence, vocabulary, and frontal function. Neuropsychology, 21(6), 684.
- Ylikoski, R., Ylikoski, A., Erkinjuntti, T., Sulkava, R., Raininko, R., & Tilvis, R. (1993). White matter changes in healthy elderly persons correlate with attention and speed of mental processing. Archives of Neurology, 50(8), 818.
- Rabbitt, P., Scott, M., Lunn, M., Thacker, N., Lowe, C., Pendleton, N., … & Jackson, A. (2007). White matter lesions account for all age-related declines in speed but not in intelligence. Neuropsychology, 21(3), 363.
- Danthiir, V., Roberts, R. D., Schulze, R., & Wilhelm, O. (2004). Mental speed.Handbook of understanding and measuring intelligence, 27-46.
- Deary, I. J., & Stough, C. (1996). Intelligence and inspection time: Achievements, prospects, and problems. American Psychologist, 51(6), 599.
- Rabbitt, P., & Anderson, M. (2006). of Cognitive Abilities. Lifespan Cognition: Mechanisms of Change, 331.
- Melton, A. W., & Irwin, J. M. (1940). The influence of degree of interpolated learning on retroactive inhibition and the overt transfer of specific responses.The American Journal of Psychology, 53(2), 173-203.