Here's a new abstract:
Reward processing is a central component of learning and decision making. Functional magnetic resonance imaging (fMRI) has contributed essentially to our understanding of reward processing in humans. The strength of reward-related brain responses might prove as a valuable marker for, or correlate of, individual preferences or personality traits. An essential prerequisite for this is a sufficient reliability of individual measures of reward-related brain signals. We therefore determined test-retest reliabilities of BOLD responses to reward prediction, reward receipt and reward prediction errors in the ventral striatum and the orbitofrontal cortex in 25 subjects undergoing three different simple reward paradigms (retest interval 7-13 days). Although on a group level the paradigms consistently led to significant activations of the relevant brain areas in two sessions, across subject retest reliabilities were only poor to fair (with intraclass correlation coefficients (ICC) of -.15 to .44). ICCs for motor activations were considerably higher (ICC .32 to .73). Our results reveal the methodological difficulties behind across-subject correlations in fMRI research on reward processing. These results demonstrate the need for studies that address methods to optimize the retest reliability of fMRI.
Hat tip goes to the excellent Vaughn Bell. Here are related criticisms. Here is a related paper, possibly gated for you, "Is There a Method for Neuroeconomics?"
fMRI is always fraught with reliability issues. The data is really, really noisy and the magnitude of the BOLD signal changes from one trial to the next (which is why you look at changes in the BOLD rather than its magnitude to determine effect).
Another issue is this – BOLD is a proxy of neural activity because one assumes that when a brain region is going to be active, it will need energy in the form of ATP brought by the bloodstream. This is correlated with neuronal firing, but isn’t identical. For instance, a paper in Science about a year ago (? maybe Nature?) showed that when a certain type of picture is displayed, neural activity increases in visual cortex and the BOLD signal rises. Now you put the subject in a situation where it thinks it will view the picture, but randomly doesn’t. The BOLD signal changes, but neuronal activity doesn’t. So perhaps the BOLD signal is something about the brain predicting where it will need energy?
Which is not to say that fMRI is a poor tool, it just needs to be interpreted judiciously. For instance, I haven’t read the paper above but it’s possible that the reason that you see poor within-subject correlations are because once blood has rushed to that area, there’s some lingering ATP (energy) so it won’t need to more anytime soon? Whereas within groups, this effect is washed away.
Anyway, there’s more to neuroeconomics – imho, in my interpretation of the field – than just fMRI work, although that’s as always the sexiest (a common lament). There’s work that examines the effect of things like testosterone and oxytocin, animal models look at the effects of neurotransmitters like dopamine, etc. fMRI is great because we can do a lot on human subjects with it…but to really understand decision processes, we’re probably going to have to do most of it in animals first.
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