Comparing Child and Adult Brains: How to Account for Performance Differences?

Wednesday, March 3, 2010

In an ideal world, we’d be able to study maturational brain changes by scanning a group of adults, a group of children, and comparing the brain images. Unfortunately, there are complications.



One complication is that these studies usually require doing some kind of task in the scanner, and children usually have lower accuracy and longer reaction times on this task. These differences, especially reaction time differences, can have a significant effect on brain activation. (Activation is averaged over seconds, so the longer your reaction time, the higher the brain activation, simply because you spend more time on the task). So how do we know what differences are due to actual brain maturation and what differences are due to poor performance inside the scanner?

In a 2002 study, Schlaggar and colleagues addressed the issue of performance differences by comparing only those children and adults that performed similarly on the task. They were interested in word processing in children (aged 7-10) and adults (age 18-35). In their experiment, participants saw single words on a screen and had to say a response word based on a cue (for example, a rhyming word, or the opposite word).

Instead of comparing all adults and all children, Schlaggar and colleagues divided the participants into two subgroups. The top scoring children and lower scoring adults to formed a Performance matched subgroup, where the children’s performance did not differ significantly from adults. The rest formed a Performance Non-matched subgroup, where there were clear differences in accuracy and response time between adults and children.

Schlaggar and colleagues looked at several regions of interest in the left frontal and left extrastriate regions, all traditional language and word processing areas. When there were differences between age groups, the children almost always had greater activation.

But the interesting results occur when you compare the subgroups. Some regions showed differences in the Non-Matched subgroup that disappeared when you look at the Performance Matched groups, suggesting that the brain differences here were due to performance differences inside the scanner.

Other regions, however showed differences between children and adults in both the Performance Matched and the Performance Non-matched subgroups. In these regions, one can safely assume that there’s more to these differences than simple in scanner performance.

What does this tell us? For one thing, it tells us that in-scanner performance differences between children and adults should not be ignored. There were several “developmental” differences here that disappeared as soon as you controlled for in-scanner performance. On the other hand, there do appear to be differences that remain even when you have children and adults that perform equally.

A few things to think about with this study. First, it’s admirable that the authors control for performance, but doing so also introduces opposite selection biases in children and adults. You have to wonder what population of children would perform as well as adults almost twice their age, and conversely, what population of adults would perform at the level of 7-10 year olds. Is it fair to compare these two groups and generalize these comparisons to the entire population?

Second, what does it mean to control for in-scanner performance? If we treat it as a confounding factor and control for it, we’re assuming that performance differences on this word generation task are irrelevant to the process we’re studying. However, that can’t be completely true. We’re interested in word processing differences between children and adults, so if we look for children and adults that perform similarly on a word generation task, we’re filtering out some of the differences that we set out to study.

Third, it might be helpful, as mentioned in BJ Casey’s commentary on the study, to differentiate between differences from maturation alone and differences due to skill level. In a field such as reading, this might be hard to tease apart. While children’s brains mature between ages 7 and 18, they also undergo thousands of hours of reading instruction that introduce changes in the brain. When we study reading acquisition in children, therefore, we should think about kind of brain changes we’re interested in, and that will affect the comparisons and analyses we do.

Schlaggar BL, Brown TT, Lugar HM, Visscher KM, Miezin FM, & Petersen SE (2002). Functional neuroanatomical differences between adults and school-age children in the processing of single words. Science (New York, N.Y.), 296 (5572), 1476-9 PMID: 12029136

Casey, B. (2002). NEUROSCIENCE: Windows into the Human Brain Science, 296 (5572), 1408-1409 DOI: 10.1126/science.1072684

6 comments:

Peta Jinnath Andersen March 5, 2010 at 9:30 AM  

It's strange reading about this, because I kind of participated in a study like this at college. One of the requirements of the psych course I took was to complete 10 hours of guinea-pigging.

Several of the studies I did were repeating existing work, though, as they were higher level BSc. kids or first year grad students.

Joanna March 6, 2010 at 11:59 AM  

I wonder about the validity of the measurements used. Activation is measured by time. What about intensity?

Some years ago I worked with eight boys, nine years old, who were considered Attention Deficit children. It was my job to keep them occupied and interested away from the classroom so the teacher could teach for a few hours free of their disturbing behavior.

I took the boys to the empty gymnasium, sat on a pillow and read them Kipling. The boys literally climbed the walls. They ran up the walls as far as they could. They played Tarzan on the hanging ropes. They leaped, jumped, rolled and ran.

BUT... they heard and registered every word I read. While they were active they shouted answers to my questions and made great comments on Mowgli, Kaa, Shere Kahn and Bagheera.

I concluded that far from being attention deficit they were attention enhanced!

So I wonder about using intensity as an additional measurement in brain studies.

Joanna Poppink
http://www.eatingdisorderrecovery.com

Livia March 6, 2010 at 12:08 PM  

Joanna -- Actually, activation is measured in intensity, not time. Reaction time only becomes an issue because each measurement takes 2 seconds, so we can only compare the intensity in 2 second chunks. But with normal imaging parameters, we don't have the temporal resolution to look at intensity over shorter periods of time than that. Hope that made sense...

Anonymous,  March 15, 2010 at 11:23 AM  

Have you read Russ Poldrack's paper, "Imaging Plasticity"? Great treatment of some of the issues (and possible workarounds--including performance-matched control groups instead of age-matched) in trying to tease out maturation vs. learning vs. group effects.

It was in Neuroimage either 2000 or 2001.

Priya

Anonymous,  March 15, 2010 at 11:25 AM  

http://www.ncbi.nlm.nih.gov/pubmed/10875897

Stephanie,  March 16, 2010 at 7:26 AM  

So I realize I am a little behind the conversation here, but I think Joanna raises an interesting point regarding attention deficit. It is a condition about which there is a great deal more to learn, but some clarity is emerging from the research. One detail that I find interesting is that contrary to popular belief, children with ADD can focus. Their difficulty lies in regulating their focus. So when they have to focus on a task that may be less interesting for them, or drags on too long, or is simply too difficult they space out. All children do this to a certain degree, but in kids with ADD this normal behavior interferes with their ability to participate in typical learning. That interpretation does happen to fit in nicely with descriptions of other "abnormal" behaviors. For instance, as discussed here in this forum, all children reverse letters, but dyslexics do so for a longer time in development or face a real cognitive barrier to moving on to a stage where they do not reverse letters.

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