"Help me up!" New research: Even at 60, your brain is still alive

Written by: Hao Jing:

Editor: Kou Jianchao

Layout: Bai Ruobing

"I'm old and my brain doesn't work as well as before."

In the past, most people firmly believed that the reactions of the elderly were slower than those of the young.

A large number of scientific studies have also shown that there is a negative correlation between thinking speed (the speed at which the brain thinks about problems) and age. That is, in a variety of cognitive tasks and environments, the thinking speed of the elderly tends to be slower than that of the young.

However, is this true?

(Source: Pixabay)

Recently, a research team from the Institute of Psychology at Heidelberg University in Germany found that although our reaction time begins to slow down at the age of 20, this slowdown is due to increases in decision caution and slower non-decisional processes, rather than differences in thinking speed.

The difference in thinking speed only appears after about 60 years of age.

This research therefore challenges the commonly held view on the relationship between age and thinking speed.

The related research paper, titled "Mental speed is high until age 60 as revealed by analysis of over a million participants", was published in the journal Nature Human Behaviour.

Are old people slow in thinking? Wrong

Why do we always think that older people have slow brains?

This is actually due to the fact that most of the research in recent years on the correlation between age and thinking speed has been done.

In previous studies, scientists' conclusions on the relationship between age and thinking speed were mainly based on using the subjects' average reaction times (RTs) in primary cognitive tasks (such as comparing two letters) as a measure of the basic speed of information processing.

(Source: Pixabay)

However, this approach has two obvious disadvantages:

1. Using mean RTs alone does not exploit the full information contained in the empirical RT distribution and ignores accuracy data that can also be obtained from experimental paradigms.

In other words, this method only draws conclusions from a single result. For example, in real life, when we compare the deliciousness of crayfish in two restaurants, "the crayfish in this restaurant is big, so it tastes good; the crayfish in that restaurant is small, so it tastes bad." We only focus on the size of the crayfish but ignore other factors that affect the taste of the crayfish (such as cooking methods, the freshness of the crayfish, etc.), and the conclusion we draw has certain limitations.

2. Far from being a pure measure of thinking speed, average RTs represent the sum of different cognitive processes.

For example, the speed-accuracy trade-off (i.e., differences in response caution affect both speed and accuracy of responses) and the time spent on encoding and motor processes, although they are unrelated to thought speed, can have a strong influence on mean RTs.

Therefore, the extent to which average RTs reflect thinking speed is still debatable.

Furthermore, sample sizes have also been small in most studies over the past two decades, which is particularly problematic for individual differences research that seeks to improve reliability with larger samples.

To improve the accuracy of the study, the researchers used deep learning to apply the Bayesian diffusion model (DM) to a large sample (including 1.2 million participants aged 10-80 years) to extract interpretable cognitive parameters from the raw response time data.

The researchers found that thinking speed, decision-making caution, and non-decision components (encoding and motor reaction time) influenced average RTs across age groups.

A three-pronged approach to controlling your brain

So, what is the specific impact?

First, it is the speed of thinking, which is what we usually call the speed of brain reaction.

Studies have shown that people's thinking speed remains stable until the age of 60. From around 60 years old, the thinking speed tends to decline at an accelerated rate, and this decline will continue until the age of 80.

So, by the time you are 60, you are still thinking at the same speed as you did at 20. (Is that why the retirement age is 60?)

Secondly, it is decision-making prudence. Decision-making prudence represents the degree of caution we use when making decisions and whether we will consider the consequences of the decisions we make.

The study showed that decision-making caution decreases between the ages of 10 and 20, and then increases quasi-linearly until the age of 65.

This result suggests that college-age individuals are the least cautious in their responses and are more willing to trade off between accuracy and speed.

Furthermore, a trend toward increasing decision-making caution becomes evident in early adulthood, which explains why, in adulthood, the speed of mean RTs begins to correlate with increasing age.

Finally, there is non-decision time, which is the time required for encoding and motor response.

Studies have shown that non-decision-making time tends to decrease from the age of 10-15 years, and then increases quasi-linearly until the age of 80 years.

Thus, age differences in decision caution and non-decision time were strongly associated with the patterns found for RTs, suggesting that these factors may have a significant impact on mean levels of RTs across the life course.

Figure | Thinking speed is a function of age, experimental conditions, and demographic variables. Age differences in drift rate were analyzed separately according to gender, education level, and experimental conditions. (Source: The paper)

In addition, the researchers observed a clear nonlinear relationship between drift rate, an indicator of thinking speed, and age, which was significantly different from the association suggested by mean RTs and more informative than age differences found in previous DM studies.

limitation

The researchers say that the different age-related patterns of DM parameters become more plausible in the context of literature linking changes in cognitive abilities to changes in their neurophysiological basis.

Compared with previous cognitive aging studies, this study has several advantages, the most prominent of which are:

(1) A large sample size, allowing for detailed age-related analyses;

(2) Using Bayesian diffusion models, we decompose the different components of the decision-making process in a robust and theoretically justified way.

However, the researchers said, "We must note some limitations of this study."

These include the fact that the study’s data came from only one specific type of decision-making task, and whether the age differences and trends in the study represent internal developmental processes (after all, people are constantly changing and don’t grow according to set patterns). These are all open questions.

But the researchers anticipated this, and they believe that while these analyses are beyond the scope of this paper, they may be of value in future work.

In short, this study overturns our traditional understanding of the concept that at least before the age of 60, our brains remain "young" and can still "function".

So, how many more years do you think you can fight?

References:
https://www.nature.com/articles/s41562-021-01282-7

Source: Academic Headlines