Archive for the ‘neuroimaging’ Category

How are values computed in the brain? Rewards can be as many things: the expectation when having just ordered your favourite dish; the child’s joy at Christmas Eve; the enjoyment of good music or the wonderful taste of strawberries.

But how does the brain process these many different kinds of rewards? Does it treat all types of rewards equally or does the brain distinguish between different kinds of rewards? Rewards can come in many different forms: from sex, social recognition, food when you’re hungry, or money. But it is still an open question whether the brain processes such rewards in different ways, or whether there is a “common currency” in the brain for all types of rewards.

Guillaume Sescousse and his colleagues in Lyon recently reported a study on how the brain reacts differently to money and sex. A group of men were scanned with functional MRI. While being tested, subjects played a game in which they sometimes reveiwed a reward. The reward could be money or it could be the sight of a lightly dressed woman. So there were two types of rewards. Money can be said to be an indirect reward, and the sexual images can be seen as more immediately rewarding (at least for most heterosexual men). But how did the brain process these rewards?

The researchers found that there were unique activations for both sex and money, but that there were also overlapping regions of activity. On one hand, for both types of reward was a general activation of what we often refer to as the brain’s reward system (ventral striatum, anterior insula, anterior cingulate cortex and midbrain; see figure 1). The brain thus uses the some structures to respond to both types of reward.

Regions of common activations

But there were also specific activations for erotic pictures and money. And this difference was primarily made in the brain’s prefrontal cortex, especially the orbitofrontal cortex (OfC). Here, it was found that monetary rewards engaged more anterior OfC regions, while erotic images activated more posterior OfC regions.

This could suggest that the brain also treats the two types of reward differently. The crux of this paper, however, is how one explains the difference. As noted, the researchers used two different kinds of reward, but they differ in several ways which I will try to summarize here:

  • Direct vs indirect
    • Money is indirectly rewarding, because money can not be ‘consumed’ in itself. They are rewarding to the extent they could be exchanged for other things. Erotic images are in themselves directly rewarding. Not because they symbolize sex, or the possibility of sex, but because they have an immediate rewarding effects.
  • Abstraction level
    • Another option is to say that erotic pictures and money differ in their level of abstraction: Erotic images are concrete, while money is an abstract reward.
  • Time interval
    • A final possibility is that there are differences in the time interval: Erotic images are immediately rewarding, while the money can only be converted into real value after a while (for example, after scanning, or after a few days where you spend the money). We already know that the frontopolar regions of the brain is among the regions that are most developed in humans compared to other primates, and is linked to our unique ability to think about the future, i.e. prospective memory and planning, and through this to use complex abstractions for rewards, including money.

Regions of distinct activations: orange = monetary rewards, green = sexual rewards

What the exact cause of this common currency as well as the separation between money and erotic pictures is still unclear and warrants further studies (which I am currently undertaking). The essential addition of this study is the separation between the posterior and anterior parts of the OFC in processing different kinds of rewards. By showing common and distinct regions, this study may resolve some of the ongoing debates in the decision neuroscience / neuroeconomic literature. But as always found in science, this study generates more questions than it resolves, and we can only hope that future studies can add to this knowledge.


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Where’s the voodoo?

I just love this title: Independence in ROI analysis: where is the voodoo? by Russel Poldrack and Jeanette Mumford. Lately, there has been much fuzz about so-called voodoo correlations in social neuroscience, and questions have been raised about the legitimacy of the claims put forward by Vul et al. (PDF of in press manuscript) and see criticism from Tania Singer and other colleagues here (PDF). Crucial to the criticism by Vul et al. is that the correlations between behavioural/social data and brain activation data show a correlation level that is highly improbable, or as Vul et al. put it:

Functional Magnetic Resonance Imaging studies of emotion, personality, and social cognition have drawn much attention in recent years, with high-profile studies frequently reporting extremely high (e.g., >.8) correlations between behavioral and self-report measures of personality or emotion and measures of brain activation.  We show that these correlations often exceed what is statistically possible assuming the (evidently rather limited) reliability of both fMRI and personality/emotion measures.  The implausibly high correlations are all the more puzzling because method sections rarely contain sufficient detail to ascertain how these correlations were obtained.

In the recent paper in SCAN, Poldrack and Mumford add to the criticism of Vul et al.:

We outline the problem of non-independence, and use a previously published dataset to examine the effects of non-independence. These analyses show that very strong correlations (exceeding 0.8) can occur even when the ROI is completely independent of the data being analyzed, suggesting that the claims of Vul et al. regarding the implausibility of these high correlations are incorrect.

I am not going to give you the details of the whole voodoo story here, since it has been covered nicely in the blogosphere. But what is interesting is that this discussion demonstrates just how easy it is to get pre-publication media and blogosphere coverage for researchers criticising brain research, much in the same vein as we saw in the case of criticism of neuroeconomics by Gul and Pesendorfer’s neo-conservative “A case agains mindless economics” (PDF), long before the article actually appeared… I guess in the end that as neuroscience and neuroimaging in particular becomes even more popular, it will always have the extremists of either side, saying either that it shows nothing/too much/fake information, or the wholesale version that lets people get away with anything, as long as they point to a brain…


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Emotional reactions may come in many forms and have different causes. But one of the main responses is the fear response, which has been shown to involved the amygdala. Different nuclei of the amygdala may contribute differentially to the fear response process.

One vital feature of emotion and amygdala is that emotional responses can be reduced, and eventually diminish. This is one of the basic mechanisms at play when we habituate to (or even extinguish) fearful stimuli. But is is also possible to reduce fear responses through more controlled processes, what has been termed cognitive emotion regulation. Such basic cognitive mechanisms underlie the psychological treatment of, e.g., phobias. In other words, there are two ways of reducing fear responses of the amygdala: 1) through habituation/extinction and 2) through cognitive (“rational”?) processing.

However, the exact neurobiological nature of these processes have been unknown. In a recent paper in Neuron, authored by Mauricio Delgado, and including prominent emotion researchers such as Joseph LeDoux, Elisabeth Phelps, looks at precicely this relationship. Using an emotion regulation strategy, the researchers compared the brain mechanisms (using fMRI) for conditioned fear regulation and for classic extinction.

From the methods section, one can read:

Each trial began with the presentation of a word cue, presented for 2 s, which instructed the participant on the type of trial. It was followed by either a blue or yellow square that served as a conditioned stimulus (CS) and was presented for 4 s. A mild shock to the wrist served as the unconditioned stimulus (US) and was administered during the last 200 ms for six of the CS trials. During one experimental session, a specific colored square (e.g., blue) was paired with the US, thus serving as the CS+, while the other square (e.g., yellow) served as the CS−. This contingency was counterbalanced across participants. The trial concluded with a 12 s intertrial interval.

When instructed to “attend,” participants were asked to view the stimulus and attend to their natural feelings regarding which CS was presented. In these Attend trials, for example, participants might focus on the fact that they may receive a shock (if the cue was followed by a CS+) or would never receive a shock (if the cue was followed by a CS−). When instructed to “reappraise,” participants were asked to view the CS and try to imagine something in nature that was calming, prompted by the color of the CS. During these Regulation trials, for example, participants could think of an image of the ocean or a blue sky when viewing the blue square, or they could think of the sunshine or a field of daffodils when viewing the yellow square.

During both cases of fear reduction, the amygdala (red in top image) activation level went from high to low, for both What the researchers found was that during extinction learning, the ventromedial prefrontal cortex (orange in top) showed a higher activity, and this was thought to cause the observed reduction in amygdala activation. In contrast, cognitive emotion control lead to a higher activation in the dorsolateral PfC (blue in top image).

So this is a very nice demonstration of two different mechanisms of emotion regulation. However, it stills seems open to me whether the two are overlapping or very different mechanisms. One way of assuming the relationship is that the dorsolateral PfC works through the ventromedial PfC on regulating the amygdala. However, it may also be possible that the dorsolateral PfC bypasses the ventromedial PfC altogether. By comparing the activation patterns of all three structures, the findings suggested that the dorsolateral PfC works on the amygdala through the ventromedial PfC. Or, as put by the authors:

Our results support a model in which the lateral PFC regions engaged by the online manipulation of information characteristic of cognitive emotion regulation strategies (for review see Ochsner and Gross, 2005) influences amygdala function through connections to vmPFC regions that are also thought to inhibit the amygdala during extinction (Milad and Quirk, 2002). These results are consistent with the suggestion that vmPFC may play a general regulatory role in diminishing fear across a range of paradigms (e.g., [Kim et al., 2003] and [Urry et al., 2006]).

The implications of these findings may be plenty, but a few immediately comes to mind: first, the identification of the dorsolateral PfC in controlling emotions may, in general, be used as a marker for emotional regulation in different psychological states. Lie detection may be one issue, and studies of implicit racism seem to suggest the same. Another interesting consequence is in the modelling of the phylogeny and ontogeny of emotion regulation in primates. The present results may suggest that the dorsolateral PfC role in emotion regulation has occurred later in primate evolution, and that it works through a more “ancient” ventromedial PfC basic regulation of the amygdala. It may even be possible that developmental studies can show that the later maturation of the dorsolateral PfC also corresponds to the development of emotional control. Finally, this idea may also serve as a good model for studying brain injury and the consequences of emotion regulation.


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I don’t know about you, but I often get fascinated by the mere visualization of brain imaging data. Aside with the neuroimaging blobologies, but looking at more detailed visualizations of brain parts and processes strike me as merely beautiful and fascinating. And, as the fascination of looking at a star may be deepened by knowing more about that exact star (e.g., it’s the leftovers from a supernova), knowing what you see in the image of the brain may provide more understanding of what we see, and why it looks just that way.

Just as with this cover image from a recent issue of Cerebral Cortex, in which the caption says:

Photomontage showing two consecutive coronal sections of an E12 mouse embryo after 24 hours of being in toto culture. After a CFDA injection into the rostro-medial telencephalic wall, labeled cells (green) migrate tangentially by the ventral telencephalon and reach the olfactory cortex, which is immunohistochemically stained against calretinin (red) and calbindin (pseudocolor orange). The blue color shows the DAPI unspecific staining of nuclei. Superimposed, the black and white figure shows an embryo head injected with the fluorescent tracer DiI (red).

Or, put more simple, it’s an image showing how cells migrate during embryonic development. The article can be found here.


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This really gets me freaked out! Martin says I’m just a grumpy old (?) man. So let me lie along the Neurocritic approach just for a minute, and just air my frustration:


Take a look at this image. It’s from a 2007 article in Science by Depue et al.

It’s supposed to show activation in the hippocampus and amygdala. Looks innocent, right? Let’s take a closer look.

Slice number 3 really provides the best errors:

I spent quite a while figuring the figues out. Did the yellow names indicate the blobs or where the structures actually are? For one thing, the blue blobs don’t fit into amygdala or hippocampus, but rather the entorhinal cortex. But let me comment on two big errors related to this slice.

First, the hippocampus is not present on this slice, so why put the name there? And why put it that lateral? This is really bothering. Do the researchers (and reviewers) really think that the hippocampus has anything to do here?

Second, the rightmost activation blob is centered in white matter. Hmm.. would that not give you the opportunity to speculate whether your coregistration was correct? I would. Related to this, let me just comment briefly on the two leftmost slices:

If you look at the blob, it really looks as if it fits better into the hippocampus. The entorhinal cortex is a thin slice with a whole different orientation. My guess: the hippocampus.

Next slide:

As before, I’m really curisous whether this is only a sign of poorly coregistered (and checked) fMRI images to the structural template brain. Or can it be just another example of why standard spatial normalization in this region is too problematic.

Guys, let’s face it: this is probably one of the bigger, non-spotted errors one can find in visualization of fMRI data. Does it help validate fMRI as a method? NO. How can this error be allowed? I have no idea. But would I trust ANY of the other spatial localizations in this article? NO WAY!

Get a grip, guys! Check your images, and get your medial temporal lobe your anatomy right!


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If you didn’t go the HBM meeting this year you might be interested in hearing that the organizing committee now has put up most of the keynote presentations – for some reason, the talk by Michael Gazzaniga is missing – as well as all the talks from this year’s educational courses as podcasts. You can find them here.

The keynotes include talks by Mel Goodale, Mark D’Esposito (on the top-down modulation of FFA and PPA activation in visula perception), David van Essen (brain maps!, brain maps!), and Aina Puce (on social neuroscience). The educational workshops include talks on “Advanced fMRI”, “Basic fMRI/EEG”, “Diffusion Imaging and Tractography”, and “From Dynamic Modeling to Cognitive Neuroscience”. So, if you want to brush up your knowledge about neuroimaging methodology these podcasts offer a good opportunity.

By the way, I still plan to write a couple of posts about my impressions of the meeting. Stay tuned for that!


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Poster from the 14th Human Brain Mapping conference in Melbourne. Sorry about the bad photograph. The title of the poster reads: “EEG Default Mode Network: Olympic Hymn”.


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