Age and the overstuffed mind

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.


  1. 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
  2. Salthouse, T. A. (1985). A cognitive theory of aging.
  3. 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. Neuropsychology21(6), 684.
  4. 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 Neurology50(8), 818.
  5. 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. Neuropsychology21(3), 363.
  6. Danthiir, V., Roberts, R. D., Schulze, R., & Wilhelm, O. (2004). Mental speed.Handbook of understanding and measuring intelligence, 27-46.
  7. Deary, I. J., & Stough, C. (1996). Intelligence and inspection time: Achievements, prospects, and problems. American Psychologist51(6), 599.
  8. Rabbitt, P., & Anderson, M. (2006). of Cognitive Abilities. Lifespan Cognition: Mechanisms of Change, 331.
  9. 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 Psychology53(2), 173-203.

About Gray Rabbitt

Grumpy gerontologist
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9 Responses to Age and the overstuffed mind

  1. Simon W Davis says:

    Excellent, witty critique! I also enjoyed the provocation in this paper, and I’m always a fan of overturning biases in the ageing literature, but it is difficult to connect the results of this paper with anything before it. Striking premise, but many flaws. More intelligent observers than i have also noticed that one of the assumptions of the Ramscar model–that lexical search is serial–is deeply at odds with both psycholinguistics as well as the knowledge that the cortex is a massively parallelized machine.
    A paper with a similar ‘positive ageing’ feeling to it, but more neurobiologically-minded focus is Rosalyn Moran’s study in PLoS Computational Biology, which also came out last month. However, in this instance it is the age-related change in brain patterns (not cognition) that is in question, specifically the shift in activity from sensory to executive regions. Moran uses DCM of MEG to put forth an efficiency explanation for this pattern. Would be interested in your take!

    • pmar76 says:

      Thank you for your kind words. You are, of course, precisely on the ball in regard to the assumption that lexical search is serial. Thank you aalso for the cue to Rosalyn Moran. I shall read her paper with inbterest.

  2. Pingback: Cognitive Ageing or Cognitive Decline? An FAQ | The Importance of Being Wrong

  3. pmar76 says:

    Reply to Ramscar Group piingback:

    I regret that problems at learning how to blog have delayed my posting both the Ramscar Group (RG) response to my first ever blog and this reply. I am also sorry that RG feel that I have misinterpreted their article. I do not think that I have.

    RG begin cryptically: “Our article claimed that Cognitive Decline is a Myth. Cognitive Ageing is a Fact”. I am reassured that I have spent my working life studying a “fact” but surprised by news that all of the negative changes in cognitive performance that my colleagues and I have measured are “mythical”.

    We can only assess cognitive changes by measuring peoples’ performance on laboratory tasks or at their real life skills or professions. Sadly, when we do this we find that all of us perform less well as we age. Documenting these negative changes is useful because it is only by describing precisely what is going wrong that we may find ways to make things better. Refusal to use the word “decline” to describe negative change seems unhelpful superstition.

    Since age-related declines in performance cognitive tasks are documented by a vast literature RG cannot claim that they do not exist. They must rather mean that if we choose to make the special assumptions on which they base their simple model we will conclude that our measurements have been inappropriate. These assumptions are: (1) We incrementally gain knowledge throughout our lives. (2) The more knowledge we gain the less rapidly we can retrieve and use it to make decisions (3). So older people only seem to have declined because our tests and observations have not measured their greater “hidden” acquired knowledge of the world and have only assessed them on tasks with which this knowledge interferes.

    We are all free to use any assumptions we please to describe hypothetical information accumulation systems. To show that our models account for observed reality is much more useful and difficult. Tellingly the RG model makes no mention of forgetting or capacity limitation but envisages a perfectly non-degrading system whose performance changes only as accumulating information slows retrieval. To apply this model to human brains, we must prove that these are also systems that do not forget and that also suffer no functional degradation during a (healthy) lifespan. If brains do degrade, we must ask if this explains none, some, most or all of the declines in cognitive performance that are universally observed. So, to maintain their position RG have to argue that there is no evidence for age-related brain changes that impair cognitive performance. This is what they do.

    I think that RG are directly contradicted by copious evidence on brain ageing. The references that RG selectively cite to counter this point are not, in fact, evidence for lifelong brain integrity. They are observations of local brain plasticity showing that if particular tasks or skills (e.g. juggling1, or taxi and bus route learning etc2,3 etc) are intensively practised, the specific brain areas that support them can show gains in neuronal connectivity and local volume. These changes can last for 2 years1 are most evident in youth and become increasingly less marked in old age. This is not evidence that our brains do not degrade with age nor that they are continuously self-repairing. A vast and convincing literature shows that gross losses of brain tissue and proliferations of white matter lesions in the entire brain occur throughout adult life and accelerate in old age4 when their faster progress becomes measurable over periods as short as 12 months. Longitudinal scanning with concurrent cognitive testing shows that these changes accompany and predict progressive declines in performance on cognitive tasks eg.5,6,7,8,9. Gross brain changes in healthy brains are distinct from patterns of changes experienced in dementias 8 do not repair themselves and are clearly associated with – sorry but there is no other phrase for it – both general and specific cognitive declines. Indeed, because patterns of age related brain changes vary between individuals the hottest current topic in current cognitive gerontology is the relation between individual differences in patterns of brain changes and corresponding patterns of cognitive losses.10

    The RG paper does not deal with forgetting or errors of information retrieval. It predicts only for a single behavioural performance measure i.e. decision speed. I think that that the fact that age-slowing occurs even on the simplest possible tasks such as responding with one finger to one signal lamp, and persists even to practise asymptotes is difficult for the RG model. RG challenge this by inviting me to devise a model that considers all of the myriads of other things than pressing keys that we learn to do with our fingers as our lives progress. This is disingenuous. Of course anyone can devise an abstract model using RG’s assumption that any learned activity will slow performance of any similar activity. It is far more interesting to model the reality that teaching people to type or play the piano or to do countless things with their fingers does not impair their simple reaction times – and may very likely improve them. Unlike most humans over many millennia RG do not seem to have twigged that learning to do something new makes us better, rather than worse at doing other similar things. Perhaps RG can be excused because psychologists only recently began to formally explore this phenomenon (about a hundred years ago). We call it “generalisation”. A brief Google search on this word will find scores of ingenious experiments illustrating that learning a new thing can make you faster, not slower, at doing other things.

    RG have another shot for me in their locker: A study in which older adults solved mental arithmetic problems faster than the young 11. This twice misses any target. First, if general information clogging means that older people have difficulty with instructions on all tasks surely they should also become slower on mental arithmetic? Second, why am I supposed to be banjaxed by any finding that performance on any task improves with age ? (no nasty “decline” then!). I am not, because I can still do (some) mental arithmetic faster than my children or grand-children because, when I was little, ferocious nuns drilled me on multiplication tables. My undrilled offspring have the sluggish insouciance of people who have always had calculators to hand. I note that the authors of the study that RG cite 11 emphasise this precise point (see their Discussion lines 8-13).

    I also do not feel crushed by RG’s direct personal accusation that I “do not know what intelligence is”. I can only say that whenever I doubt that I still do I again read John Duncan’s 12 excellent book and am comforted. Again RG do not take my actual point: people who can solve non-trivial problems faster than the rest of us (and so gain higher scores on intelligence tests) not only learn more words and more things about the world than the rest of us but, even with all this extra information in their brains, make decisions about words, light flashes and everything else significantly faster than we can.

    I will not blog again about the RG paper or post their further comments and my responses to them in this blog. Writing this reply has made me feel like a deeply bored Touareg besieger of Fort Zinderneuf in “Beau Geste” 13 where, as soon as defenders were shot, their corpses were re-inserted to man the battlements yet again. I am conscious of RG’s cleverness and extraordinary persistence, and also of their courtesy but, for me, this correspondence has not been, in the Lord Buddha’s phrase, “an exercise tending to edification”. Much worse than this, it is no fun at all. So I warmly wish RG well and formally end this exchange.


    1.Boyke, J., Driemeyer, J., Gaser, C., Büchel, C., & May, A. (2008). Training-induced brain structure changes in the elderly. The Journal of neuroscience,28, 7031-7035.
    2.Maguire, E. A., Gadian, D. G., Johnsrude, I. S., Good, C. D., Ashburner, J., Frackowiak, R. S., & Frith, C. D. (2000). Navigation-related structural change in the hippocampi of taxi drivers. Proceedings of the National Academy of Sciences, 97, 4398-4403.
    3. Maguire, E. A., Woollett, K., & Spiers, H. J. (2006). London taxi drivers and bus drivers: a structural MRI and neuropsychological analysis. Hippocampus,16(, 1091-1101.
    4. de Groot, J. C., Oudkerk, M., Gijn, J. V., Hofman, A., Jolles, J., & Breteler, M. M. (2000). Cerebral white matter lesions and cognitive function: the Rotterdam Scan Study. Annals of neurology, 47(2), 145-151.
    5. Rusinek, H., De Santi, S., Frid, D., Tsui, W. H., Tarshish, C. Y., Convit, A., & de Leon, M. J. (2003). Regional Brain Atrophy Rate Predicts Future Cognitive Decline: 6-year Longitudinal MR Imaging Study of Normal Aging1. Radiology,229(3), 691-696.
    6. Tisserand, D. J., Visser, P. J., Van Boxtel, M. P. J., & Jolles, J. (2000). The relation between global and limbic brain volumes on MRI and cognitive performance in healthy individuals across the age range. Neurobiology of aging,21(4), 569-576.
    7. Raz, Naftali; Rodrigue, Karen M.; Kennedy, Kristen M.; Acker, James D. Vascular health and longitudinal changes in brain and cognition in middle-aged and older adults.Neuropsychology, Vol 21(2), Mar 2007, 149-157. doi: 10.1037/0894-4105.21.2.149
    8. Schmidt, R., Ropele, S., Enzinger, C., Petrovic, K., Smith, S., Schmidt, H., … & Fazekas, F. (2005). White matter lesion progression, brain atrophy, and cognitive decline: the Austrian stroke prevention study. Annals of neurology,58(4), 610-616
    9. Sluimer, J. D., van der Flier, W. M., Karas, G. B., Fox, N. C., Scheltens, P., Barkhof, F., & Vrenken, H. (2008). Whole-Brain atrophy rate and cognitive decline: Longitudinal MR study of memory clinic patients1. Radiology, 248(2), 590-598.
    10. Raz, N., & Rodrigue, K. M. (2006). Differential aging of the brain: patterns, cognitive correlates and modifiers. Neuroscience & Biobehavioral Reviews,30(6), 730-748.
    11. Klessinger, N., Szczerbinski, M., & Varley, R. (2012). The role of number words: the phonological length effect in multidigit addition. Memory & cognition,40(8), 1289-1302.

    12. Duncan, J. (2010). How intelligence happens. Yale University Press.
    13. Beau Geste (1939) film after PC Wren’s book, “Beau Geste” director William A Wellman

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  6. Marji says:

    My experience: When I retired (for the 4th time) I went from a stressed Exec. Coord. to an artist. I discovered I could ‘let go’ of all those years (45) of keeping everyone and everything in line. That not everything is important. What a relief for me. However, it concerned my children (6 of them). I’m still very active with projects and fun, but on my time and by my choice. I’m accomplishing so much more and enjoying doing it. All those years, I kept most of those ‘plates on sticks’ in my head. I now keep a calendar. And I say ‘No’ a lot. Talking with friends my age and older who retired from busy, stressful work express a similar experience. It takes about 2 years out to realize that one can ‘let go’ of the extraneous. I hope you all can include this type of ‘forgetfulness’ as you’re doing all of your research/publishing.

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