Archive for the ‘Ageing’ Category


It’s a strange feeling. You scan what you think is a normal person, and have taken all precautions to make sure that there are no indications of medical complications. But once you look at the scans, there is something wrong with the brain you are looking at. As in this case, I scanned a person some while ago as part of my study of the brain in healthy ageing.

The finding is not as obvious as one should think. Why? Unless the lesions are so vivid that anybody can see it, training is required. Furthermore, research projects are not aimed at detecting or diagnosing pathology.



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Exercising your mind

runningbrain.jpgMany of us are doing crosswords, soduko or whatever kind of training to keep mentally in shape. However, it seems that at least some of the time we would be better off putting on our running shoes and start walking or running. According to a number of studies, mental health is strengthened by physical training. There are today also indications that running can delay the onset of degenerative disease such as Alzheimer’s (see here).

So although you can’t train your brain like a muscle — it doesn’t work that way — training what you normally think of as physical exercise actually helps your brain, too. A number of studies have focused on the effects on cognition and other behavioural measures, while more recent studies also focus on direct measurable effects on the brain’s structure and function. For example, in a study by Colcombe et al. (2003) physical exercise was found to reduce age-related brain decline. This can be shown both for gray and white matter:


LEFT: regions that are affected — i.e. shrink — during ageing. RIGHT: regions that show preservation as a function of better cardiovascular health (i.e. training).

So it should be a matter of just going out there and start running, right? Not so, according to a recent review by Kiraly and Kiraly. Reviewing the literature on mammalian and human research on this topic, the authors first note factors that have negative effects on the brain:

The cascade of cellular damages from oxidative stress, nitrosative stress and gluco-corticoid effects are cumulative and age related. (…) Lack of exercise and motility restrictions are associated with increased vulnerability from oxidative stress, nitrosative stress and glucocorticoid excesses, all of which precede amyloid deposition and are fundamental in the cascade of events resulting in neuronal degradation, especially in the hippocampi.

Contary to this, exercise has a postive influence on the brain:

Exercise training reduces oxidative stress, nitro-sative stress and improves neuroendocrine autoregulation which counteracts damages from stress- and age-related neuronal degeneration, brain ischemia and traumatic brain injury. People prone to chronic distress, brain ischemia, brain trauma, and the aged are at increased risk for neurodegenerative diseases such as Alzheimer’s. Exercise training may be a major protective factor but without clinical guidelines, its prescription and success with treatment adherence remain elusive.

I find that very last part very interesting. It’s obviously not just going out there and start running. You’d better do your training properly, and possibly with the help from a professional trainer.


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As we age, genes are expressed differently throughout our body. The most obvious examples are the hormonal changes seen in adolescence and in the menopause. In many models of how genes are expressed during older age, one of the prevalent models – the programmed ageing model – claims that ageing is caused by genetically programmed cell death. In other words, ageing is programmed into our cells – little blame is normally to be put on random or environmental factors.

Opposed to this model we have the normally less favoured stochastic model, which claims that random biological events play a significant role in ageing. In a recent report (PDF) (see also more extensive material here (PDF)) in Current Biology a team of researchers from the Max Planck Institute for Evolutionary Anthropology, headed by Mehmet Somel, present evidence supporting this model. Using an in-house method (called "age-correlated heterogeneity of expression", or ACHE) to assess heterogeneity of gene expression, they found that the expression becomes more heterogeneous as we age. And this goes not only for humans. Rats show the same pattern, too. They find that their results "are compatible with ACHE being an outcome of the accumulation of stochastic effects at the cellular level". In other words, something that is not programmed but due to other biological factors.

You can see this in the following figure from the article:


Explanation: "An example from the human brain data set B, the log-expression versus age plot for a probe set detecting the gene PIM-1, for which the ACHE test p-value was calculated as0.0002."
Looks like heterogeneity to me … although I'd like to see some more data, maybe on 100-200 subjects.

Note also from that article that the heterogeneity is different depending on where in the body we take the sample. What I find interesting is that the brain seems to be one of the organs where genes become most heterogeneous during ageing (see bar 2-5). This also goes for the rat hippocampus. Click the image to see a larger version:

Explanation: The heights of the bars indicate observed to expected ratios of the number of probe sets at different cutoffs within the ACHE test p-value distribution

But what is ACHE really a measure of? Here's the answer from Somel et al.:

Our results indicate that ACHE is a general — but weak — effect in the transcriptome.This is compatible with ACHE being the outcome of accumulating stochastic effects in the soma, such as cellular damage and mutations. These effects will influence each cell in a unique way so that expression variation among aging cells will be equalized at the tissue level. If somatic mutations mostly cause decreases in expression level, the overlap between ACHE and age- related decrease in expression levels can also be explained within this framework. ACHE supports the stochastic nature attributed to the aging process. It implies a weakening of expression regulation with age, contrary to previous observations and hypotheses based on measurements on a small number of gene.

While browsing around for links to this post, I found a great forthcoming publication (PDF) in Trends in Ecology and Evolution by Partridge and Gems. See also this nice yet brief post at Wikipedia about the ageing brain.


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What happens to the brain as we age? Today, we know that the brain as a whole becomes smaller, it atrophies. As the brain develops, we know from studies like the ones performed by Sowell et al. that regions such as the primary sensory and motor areas mature early in the lifespan, while areas such as the prefrontal cortex mature very late.

Now, tying the evidence from development and ageing together, we can see how the brain changes over the lifespan. This is, of course, only partly true. We can study people at different ages at one time to get an estimate of how large brains and regions are in age-, gender- and educationally comparable groups people. Such cohort studies have the drawback that they do not tell us anything about how the individual brain changes over time. For that we have longitudinal studies. These studies very clearly shows how the brain changes over a few years. Together, these studies show much the same picture: brain changes dramatically as we age. We can put this into a few points:

Neural ageing is region specific: If we look at different area of the brain, we can see that the regions differ in how they age. Some structures mature early and degenerate late. Others mature late and degenerate early.

Neural ageing is non-linear: Previous models of ageing used linear models to understand the changes occuring in the brain over age spans. More recent studies now demonstrate that non-linear models fit better to the data.

These points can be seen in the following images. They show the size of the hippocampus (top) and nucleus accumbens (bottom). This is to demonstrate three points: 1) that the changes according to age are non-linear; 2) that the changes are region specific, and; 3) that there is a great variability in the relative size of each structure.

Hippocampus ageing Nucleus Accumbens

Now to my main point. Can we assume that the individual differences are "stable", in the way that people with larger-than-mean hippocampi will always stay larger than the mean? Or is the opposite true; that there are very individual trajectories in how the brain develops and ages? IMO, whether one model is true and than other false has potential high impact on our treatment in different settings. This problem is illustrated by a figure by Terry Jernigan at our lab that I reproduce here. The example shows age changes in dorsolateral prefrontal cortex. The mean is shown as the green line. The other lines indicate hypothetical trajectories for individuals. In other words, the PfC may change in a very individual manner.

Age-related volume changes in the dlPfC

Think, for example, about teaching in schools. In a country such as Denmark, teaching is rather homogenous, the same curriculum is applied in every school, the same tests etc. And your belonging to one particular class is defined by your chronological age. As I see it, this is based on the assumption that our mental capacities follow the same trajectory: those with a good learning ability will always stay high, those who are low will stay low. As a mean approach, we use age as the least common demoninator to define your group belonging.

So the question arises here: what if it turns out that development (and ageing in general) is very individual, non-linear and not stable relative to the mean? What if a person with a large prefrontal cortex at age 8 will have a below mean size at age 14, and then end up by a larger structure at 25? Would this make it harder or easier to do teaching, training or other interventions with people? Does it mean that we should re-consider our (Danish/Scandinavian) ways of teaching and assigning kids into age-dependent classes? I'm just asking. Feel free to comment.


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Nikos LogothetisYesterday, Nikos Logothetis gave a great talk at the annual keynote lecture for the Copenhagen University Research Priority Area "Body and Mind". In the lecture, Logothetis touched upon several issues on the workings of the brain – from his perspective. But at the later Master-class where it was possible to have a one-to-one discussion with him, there was little doubt about Logothetis' view about how to understand the workings of the brain and mind. And especially how to study it with neuroimaging techniques.

BOLD fMRI, he claims, can tell us something about where in the brain something is happening. But other than that, it can tell us very little about what happens in that region. In other words, Logothetis is not fascinated by the current "blobology" (AKA neo-phrenology) that is seen in much of today's neuroimaging research papers. Logothetis argues that in order to say anything intelligible about brain function, we need to go beyond the current focus on where in the brain something is happening. We need to move towards integrating multiple imaging modalities in order to get a better picture of neural processes. Logothetis himself suggested and talked mostly about EEG and deep electrodes, and MEG, in combination with BOLD fMRI. But at the master class Logothetis also discussed the use of multiple MRI modalities such as the combination of perfusion MRI (Arterial Spin Labeing) and BOLD fMRI. But BOLD alone? No way!Multimodal approach to imaging ageing

To the right you can see the key slide from my talk at the Master class, positing the problem of combining measurements of perfusion and atrophy to BOLD fMRI measures, as co-variates. In ageing studies, we can see BOLD fMRI changes, but there is a question whether the well-known changes in brain perfusion and atrophy plays a role in chaning the BOLD signal. That was my question to Logothetis. Click on the image to see the full details.

Oh, and did I mention that Logothetis gives little for the current neo-phrenological thoughts about a 1:1 match between a cognitive function and a brain area? The brain doesn't work that way…


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A recent meta-analysis by Roberts, Walton and Viechtbauer published in Psychological Bulletin demonstrate that personality traits change over time. Some things that change over time includes our social interactions, they find, as well as our emotional stability. It would be most interesting to see how these findings relate to our normal sense of self, i.e. our feeling that we are the same person over time.

Here is the abstract:

Patterns of mean-level change in personality traits across the life course: a meta-analysis of longitudinal studies.

Roberts BW, Walton KE, Viechtbauer W in Psychol Bull. 2006 Jan ; 132(1): 1-25

The present study used meta-analytic techniques (number of samples = 92) to determine the patterns of mean-level change in personality traits across the life course. Results showed that people increase in measures of social dominance (a facet of extraversion), conscientiousness, and emotional stability, especially in young adulthood (age 20 to 40). In contrast, people increase on measures of social vitality (a 2nd facet of extraversion) and openness in adolescence but then decrease in both of these domains in old age. Agreeableness changed only in old age. Of the 6 trait categories, 4 demonstrated significant change in middle and old age. Gender and attrition had minimal effects on change, whereas longer studies and studies based on younger cohorts showed greater change. ((c) 2006 APA, all rights reserved).


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