We’ve all come to believe that as people get older, they inevitably lose their mental abilities, from speeded responses to the infamous inability to remember names. Occasionally, researchers challenge this set of assumptions, showing that age changes in everything from brain volume to higher-level intellectual skills are preserved in some people well into the 80s, 90s, and beyond. However, the considered wisdom is certainly on the side of aging bringing with it mental decline.
Now, the considered wisdom may be changing. University of Tübingen linguist Michael Ramscar and his colleagues (2014) systematically compared computer simulations with human performance data on aging in areas such as memory for names, ability to learn novel associations, and even speed of responses. Their basic argument is that as you get older, your storehouse of knowledge and experience continue to grow exponentially. As a result, it takes you longer to sift through all that information when you’re trying to recall one specific item. Like a crowded file drawer, each item becomes more difficult to pull out compared to a drawer that’s nearly empty.
Let’s start with the case of people’s names, always a sore spot for people with memory complaints. According to Ramscar and his co-authors, the reason you would have more trouble remembering the name of someone you meet when you’re 50 than you did when you were 30 is due to the sheer number of people you’ve met over that 2 decade period. Over your lifetime, by extrapolation, it would be statistically impossible for you to remember the many thousands more people you’ve met. Therefore, forgetting one person’s name, or even 10 or 20, doesn’t mean your mind is shot.
There’s another reason it’s becoming harder for everyone to remember names. As Ramscar and his group point out, names are just getting harder to remember, period. 100 years ago, there were only a limited number of first names. Today, almost anything can be a name, from a fruit to a season to an emotion. This means that keeping track of someone’s name requires a great deal more effort when the only names you had to remember were “John,” “Mary,” and maybe the occasional “Jeffrey” or “Linda.”
Older people, therefore, are not just struggling with remember more people’s names, but more names, period. They also have a longer history of forming associations to words that are now names with referents that aren’t people (such as “Apple” for a name instead of a fruit).
Similarly, the ability to learn new paired-associates, a frequent lab test of learning, can be more difficult for older adults because they have acquired so many more associations throughout their lives that have to be broken in one of these lab tasks. For example, you might be shown the pair “Jacket-Frame” in a learning trial. Then in the test trial, when you’re shown the word “Jacket,” you need to remember that it was paired with “Frame.” However, older adults have a long history of associating the word “jacket” to lots of different things, people, and experiences (such as jacket-knife, or jacket-coat, or even jacket-down). It’s not that they can’t learn new associations, but that they’ll take just that much longer than a younger, naïve subject would, to forget the ones they’ve formed earlier in life.
The situation in associational learning is very much the same as might happen to you when you’re used to going the same way to your neighborhood coffee shop. When the sidewalk closes due to construction, you have to go a different way. However, because that habit is so well-formed, there will invariably be days when you head out taking the old, familiar path before realizing your way is blocked. As Mick Jagger so aptly expressed, “Old Habits Die Hard.” They're not impossible, just hard, to stamp out. In a lab situation, the older person looks mentally incapacitated next to the young participants who have fewer associational bonds to forget.
You get the idea. It’s the new learning you do throughout life that makes your mind seem to be functioning less efficiently as you get older. Ramscar and colleagues also develop an elegant argument about the accumulation of vocabulary words throughout life to show how, statistically, the more information we stock in our heads, the slower we may become at any one given task. They take as an analogy the fact that normally developing infants are sensitive to the sounds of all different languages until they learn their own native vocabulary. It’s learning that shapes the infant’s sensitivity, causing some abilities to be lost. We would never argue, however, that “cognitive decline begins in infancy” (p. 11).
Letter classification is another task commonly used to demonstrate slower mental processing for older adults. You’re shown a series of 2 letters from a set of 5, presented in uppercase or lowercase, and asked to decide in each case if the pair of letters are the same. Older adults take longer on this task, according to the Ramscar study, because they’ve formed more paired-letter associations throughout their lives. For example, if you’re seeing the letters “A and r” vs. “A and q,” you might take a hair longer on the A-r pair if you’re older because that pair brings up an association that a younger person doesn’t have, namely that Ar is actually a 2-letter words acceptable to use in Scrabble. As you get older, you also learn more abbreviations which, in like fashion, could pop into your head at the same moment when you’re faced with making this lexical decision. It’s not a long hesitation, but long enough to show up as significant when we’re talking about differences on the order of a few milliseconds.
Word fluency tasks are another sphere in which age differences are supposedly etched in stone. However, here too, Ramscar and the team analyze the problem from a probabilistic standpoint to question what we thought we knew about the aging process. In a word fluency task, you need to come up with as many words as possible in a given amount of time that start with the same letter (with no duplicates). When prompted with the cue to come up with all animals name that you can starting with the letter B, you will generate more possible animal names when you’re older than you would’ve when you were younger because you know so many more names. Unusual names such as “meercat” and “lemur” might come to mind but then need editing out because they’re not “B” names. Yes, you might think of “bonobo,” but only after you’ve sifted out these other irrelevant options.
As if these analyses weren’t convincing enough on logical, if not statistical terms, there are a few more nails that the authors put in the age-is-all-decline coffin. The most novel one to me was their finding that the larger the sample in a given study of aging and ability (such as word fluency), the larger the age differences. Having 20 people per age group produces more robust age differences than having several hundred. This puzzle led the authors to ask “How can sample size influence performance on a test as simple as naming words beginning with F?” (p. 33). The answer, they believe, has to do with the realities of research and the recruitment of participants. The more people you need to recruit for your study, the wider you may cast your net, and fail to rule out some of the health problems that make the smaller sample a “purer” one in terms of the problems that can interefere with cognitive performance.
Another reason a researcher may show larger age effects in smaller samples is that the research assistants actually do a better job in testing when they have fewer people to test. Studies in psychology depend on the ability of the research assistants to carry out faithfully the study’s procedures. Although research assistants have to be well-trained no matter what the field, there’s more room for error in psychology studies than in studies in which the results of a chemical reaction need to be recorded.
Studies on aging can also be influenced by the belief systems held by both researchers and participants. Young adult researchers are aware that they’re testing older adults who, by virtue of their physical appearance, might strike them as less able. This communicates an unconscious expectation that influences the performance of the participants. Not by a lot, perhaps, but by those precious few milliseconds that can really add up from trial to trial. Participants themselves may be influenced by what they think is true about aging and mental abilities. Furthermore, because many of them are retired, they're getting less daily stimulation which could cause some of their neurons to fire a bit more slowly than when they were more actively engaged.
I still remember when I was conducting my dissertation research on memory in older adults that many of them announced before we’d even started that they were sure their memory was failing them. In one of my early studies, I showed that older adults were more affected by the debilitating kind of test anxiety than were younger adults. We now know that memory beliefs, and particularly people’s identities regarding their memory, can influence their performance. Getting older in a society that’s constantly reinforcing the view of aging and mental decline can only make a given memory task exponentially harder for you than for someone who's still in what most people consider the prime of mental life.
The Ramscar study goes a long way toward countering that view. Let’s hope that it’s soon replaced by a more optimistic view that respects the growing wisdom that you can accumulate over your lifetime.
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Copyright Susan Krauss Whitbourne, Ph.D. 2014
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 (2014) 5–42 DOI: 10.1111/tops.12078