Archive for the ‘decision making’ 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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Thomas + BecharaAntoine Bechara, the inventer of the Iowa Gambling Task, and together with Antonio Damasio the architect of the “somatic marker hypothesis” is visiting the Decision Neuroscience Research Group at the Copenhagen Business School at the moment. Here he is explaining to Thomas the role of gut feelings in making a decision to drink the bad CBS coffee or not.


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During the spring of 2009 I organized a course course entitled “Neuroeconomics”, together with Prof.s Elke Weber and Eric Johnson. In this course, we made a compendium of articles on neuroeconomics. Fortunately, almost all of those papers were to be found on the web.

On a new page on the BrainEthics site, we bring you the list of articles we used for the course. Consider this as a suggestion for required readings for those interested in neuroeconomics. We hope to update the list along the way, but still with the aim of retaining a recommended reading rather than comprehensive listing of articles.

– Thomas

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The role of the insula in many human behaviors

The role of the insula in many human behaviors

Following up on my lead on Antoine Bechara’s upcoming visit, it is worthnotinv one of the new trends in decision making research. In particular, working from an extension of the somatic market theory and the role of ventromedial prefrontal cortex (vmPfC), Bechara and colleagues have recently demonstrated how the role of the insula seems to play an important role in decision making involving risk and aversion.

In the article entitled Differential effects of insular and ventromedial prefrontal cortex lesions on risky decision-making, the researchers compared patients with lesions to vmPfC and the insula to healthy controls and lesion controls on the Cambridge Gamling Task (nice demo here). The authors note that:

The vmPFC and insular cortex patients showed selective and distinctive disruptions of betting behaviour. VmPFC damage was associated with increased betting regardless of the odds of winning, consistent with a role of vmPFC in biasing healthy individuals towards conservative options under risk. In contrast, patients with insular cortex lesions failed to adjust their bets by the odds of winning, consistent with a role of the insular cortex in signalling the probability of aversive outcomes. The insular group attained a lower point score on the task and experienced more ‘bankruptcies’.

The results thus confirmed previous findings of a role of the vmPfC in gambling tasks, while the surprising finding was that insular lesions would also have detrimental effects on decision making. in particular, while vmPfC patients responded to reduced likelihood ratios of the gambles, betting behaviour in insular patients did not show much response to decreasing probabilities. This is demonstrated nicely in the following figure:


The effect of ratio on betting behaviour in the four groups of participants: healthy controls, vmPFC lesions, insular cortex lesions and the lesion control group.

Furthermore, over the course of the entire gambling task, insular patients suffered significantly more bankrupcies than both the vmPfC group and control groups. This does suggest that one role of the insula is guiding behaviour through aversive coding. In other words, it may be that the insula is responsible for loss aversion (as well as risk aversion, judging from the task).

The researchers further suggest that the findings were expected from the somatic marker theory:

The detrimental effect of insular cortex damage on emotional decision-making is also predicted by the Somatic Marker hypothesis (Damasio, 1994; Bechara and Damasio, 2005), which posits a crucial role for the insular cortex in holding the representations of bodily states associated with different choice options.

The results are also relevant to other studies, including Lawrence et al. (2009), who report that using the Iowa Gambling Task, choices from disadvantageous versus advantageous card decks produced activation in the medial frontal gyrus, lateral orbitofrontal cortex, and insula. So does the insula play a role in other forms of decision making, and is it a cause in pathological gambling? To date, no conclusive studies have emerged, which is why our own research has now turned to aversion-related activations in gambling, and the study of the dynamics (and overlap) between aversion related and reward related neural functions. The recent study by Clark et al demonstrates that the insula is a structure – long ignored – to take into considerations in decision making studies.


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Antoine Bechara (left) and Antonio Damasio

Antoine Bechara (left) and Antonio Damasio

As I mentioned in my previous post, I am currently giving lectures on an April course on neuroeconomics together with Prf.s Elke Weber and Eric Johnson. Needless to say, these lectures are probably as entertaining and useful for me, and my attending colleagues, as they are to the students.

However, change is coming to Copenhagen. Through our newly born Decision Neuroscience Research Group (homepage soon to come), we have additional high-profile researchers coming to Copenhagen to provide lectures and hopefully to be attracted to collaborations with us. In May, Antoine Bechara will be in our group for a couple of weeks. Bechara is well-known for his excellent work on decision making, and the role of emotions in decision making processes. Besides his decades of work on the Iowa Gambling Task, his recent publications are much about the role of the insula in emotions and decision making, in particular addiction. Therefore, our current project on loss/risk aversion in decision making (and in pathological gamblers) will definintely profit from his stay.

In the same vein, Copenhagen will see another great name in June: Antonio Damasio, who will become an honorary doctorate at the Copenhagen Business School. Damasio is well-known for his theory of (and work with Bechara on) somatic markers, and the role of emotions and the body in decision making. Recently, we have been attentive to his criticism to the discussion about mirror neurons, where he points back to his older papers on convergence-divergence zones in the brain, and how they may provide an alternative explanation (and a dethronement of) theories of mirror neurons.

This spring and summer, we therefore hope that anybody with interest in these researchers may consider coming to Copenhagen, even if it’s just for a brief visit.

The Decision Neuroscience Research Group is shaping up, and there is plenty of more to come.


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Current Opinion in Neurobiology now hosts a wonderful special issue on “Cognitive Neuroscience”. Well, it’s actually more narrow and to the point than this. Many of the articles are about the neurobiology of preference formation and decision making. The following articles are included:

Dissociating explicit timing from temporal expectation with fMRI
by JT Coull, AC Nobre

The neurobiology of social decision-making
by James K Rilling, Brooks King-Casas, Alan G Sanfey

Anchors, scales and the relative coding of value in the brain
by Ben Seymour, Samuel M McClure

Reinforcement learning: The Good, The Bad and The Ugly
by Peter Dayan, Yael Niv

Axiomatic methods, dopamine and reward prediction error
by Andrew Caplin, Mark Dean

New insights on the subcortical representation of reward
Okihide Hikosaka, Ethan Bromberg-Martin, Simon Hong, Masayuki Matsumoto

From biophysics to cognition: reward-dependent adaptive choice behavior
by Alireza Soltani, Xiao-Jing Wang

Spiking networks for Bayesian inference and choice
by Wei Ji Ma, Jeffrey M Beck, Alexandre Pouget

No doubt: if you read these articles, you will be very much up to date with the latest developments in decision neuroscience, neuromarketing, or whatever you wish to call it. Although these articles are not explicitly part of a special issue dedicated to this theme, they nevertheless could be read as such. A wonderful update from a journal that rarely makes the headlines but deserves all the attention it can get.


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Does economics need brain science? This is the aim of a recent article in the Economist. Throughout the history of economics, major advances have sometimes come from areas outside of the core discipline. Just as similar developments in other scientific disciplines. This includes the influence from psychology, which has demonstrated that decisions are not made through the rational, overt weighing of alternatives before consciously choosing the right option. Rather, choices are influenced by context, internal states, unconscious processes, emotions, and a whole host of less (or different form of) rational processes.

Today, few seriously think that homo economicus, or the rational man view, is the best model of human decision making. Nevertheless, such assumptions haunt several economic models, most often in implicit ways. One may, of course, say that the unconscious and emotional processes that influence preferences and decisions are built on some kind of rationality. Indeed, they are the remains of adaptive strategies throughout human and mammalian phylogeny.

But this begs the question of the rational man idea. Human preferences and decisions are the result of both overt and covert processes in the mind and brain. What drives our decisions and indeed our behaviours in general are the result of a convergence of several parallel processes of perceptual, emotional, cognitive and social processes. Conscious as well as unconscious kinds. Models of decision making are currently lacking the full implementation of such multidimensional factors, and in particular the temporal aspect of this.

Cognitive neuroscience has thus been suggested as a means to improve this, by applying both the insights from its own research, as well as in direct testing of ideas from economics. This branch, often referred to as neuroeconomics, but also decision neuroscience, has received a lion’s share of attention both within academia and in the media. And, not surprisingly, many economists are sceptic.

And they should be! In present-day pop-science culture, showing a brain image — or better, a brain activation image — is an exceptional way of getting attention, and give the impression of scientific rigour. But going beyond the brain blobs, it becomes harder to know exactly how much news there is  in the image. So let’s say that you find that regions x, y and z show increased activation when performing behaviour B. Interesting, right? This is what makes many people fascinated (simplified). “Yeah, they found that this region called orbitofrontal cortex was activated when people expected a reward”. But if you ask yourself or that person: “so what?” what is your answer? What is really the most valuable information in this?

Looking at blobs are, of course not sufficient. But it may be one of the underlying causes of the scepticism and criticism that neuroeconomics has received. There are too many just so stories (or so what stories). Blobs don’t tell stories or hint at causal relations, not even why the brain is important. This is covered briefly in The Economist article:

The fiercest attack on neuroeconomics, and indeed behavioural economics, has come from two economists at Princeton University, Faruk Gul and Wolfgang Pesendorfer. In an article in 2005, “The Case for Mindless Economics” (PDF), they argued that neuroscience could not transform economics because what goes on inside the brain is irrelevant to the discipline. What matters are the decisions people take—in the jargon, their “revealed preferences”—not the process by which they reach them. For the purposes of understanding how society copes with the consequences of those decisions, the assumption of rational utility-maximisation works just fine.

It’s funny to note that this article by Gul and Pesendorfer was published online long before it seems to have hit the presses. And what a smear! Don’t we always want the best possible model with the most available details? But the main claim — that what goes on in the brain is irrelevant to economics — is actually a widespread idea. And to some extent, rightfully so!

Neuroimaging results are not self-evident. It needs to be explained. And it needs to be related to existing knowledge about the brain. Consequently, we need to move beyond the blobology fascination and look into causal relationships, and ultimately how this affects behaviour. Neuroscience has the tools to provide this. For example, if we look at the brain during a decision making task, we learn that one may be able to define specific sub-processes that occur before and during the decision behaviour. According to the oft-cited 2007 Neuron study by Knutson et al. (PDF) we may distinguish between preference formation, valuation, and decision making. Already during the viewing of a product, activation in the nucleus accumbens was positively related to purchase behaviour (occuring several seconds later). Product price that exceeded that of an expected price lead to increased activation in the insula, and was negatively related to purchase behaviour. Among many other factors in this study, it neatly illustrates that decision making (the end product) can be disentangled into relevant sub-processes. And this information is unavailable unless you use neuroimaging.

Furthermore, knowing brain substrates and time-frames allows us to alter behaviour. If an identified region — say the amygdala — is implemented in pathological gambling, we may assume that altering the function of this region may also influence the (undesired) behaviour. Since the amygdala is largely serotonergic, applying medication that increase or decrease the levels of serotonin may affect gambling behaviour. And indeed, this is what research indicates.

This, neuroeconomics should be expected to allow us to probe into the detailed processes that lead to decision behaviour. Knowing the where and when (and why) of the brain during decision making is also going to allow us to affect the causal mechanisms. In effect, neuroeconomics is already today proving its’ effect. And researchers such as Gul and Pesendorfer should pay heed to the discipline. But we — and they — need to go way beyond the blobology so often offered in this arena. Cognitive neuroscience has the tremendous power to influence a whole range of theories of the mind — from psychology and paedagogics to economics and politology. But in order for it to succeed, the science needs to be closely accompanied by valid explanations and less sensationalism.


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Just noticed this very attractive title by the Brafman brothers- The book, Sway — the irresistable pull of irrational behavior, “will challenge your every thought”, according to a NY Times review. And it gets similarly good reviews from other prominent people, like Michael Shermer, the author of the recent book The mind of the market, which I blogged about recently.

I found a couple of good videos on this book that’s good to share:

A longer version with more nuances can be seen here:

So after this, you get the idea: unconscious, automatic thought patterns act out and cause irrational behaviours, sometimes at the worst possible time and place.The questions raised are, of course, interesting and important. Why do we sometimes make horrific decisions, despite having all the information available to make better ones? Why do prominent people, like George W. Bush, suffer from loss aversion, leading to billions of dollars spent and thousands of lives lost? Because it’s “too late” to pull out? Because the pain of acknowledging defeat, error or insufficiency is bigger than the benefit of sparing yet more money and lives?

Other examples can be found at the Wall Street, military, aircraft captains, and even yourself. Maybe even on a daily basis. Taken together, the examples presented in these videos and the book demonstrate that we are all susceptible to make these kinds of errors. The next and better step is, of course, to identify these errors in ourselves (and others) and act upon them in time. Coaching, anyone?

I guess I should read the book, if the publishers will send me the book 8)


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In a recent review article in Nature Reviews Neuroscience, Antonio Rangel, Colin Camerer and Read Montague suggest a framework for neuroeconomic research. Indeed, the very core of its idea is simple, but not simplistic. After reading the article, I think it will provide a useful reference for future research into neuroeconomics, aka value-based decision making. I’ve made a copy of the model here for you to see:

The caption reads:

Basic computations involved in making a choice. Value-based decision making can be broken down into five basic processes: first, the construction of a representation of the decision problem, which entails identifying internal and external states as well as potential courses of action; second, the valuation of the different actions under consideration; third, the selection of one of the actions on the basis of their valuations; fourth, after implementing the decision the brain needs to measure the desirability of the outcomes that follow; and finally, the outcome evaluation is used to update the other processes to improve the quality of future decisions.

In my own emerging work on this arena, I am trying to combine this with recent advances cognitive neuroscience. First, the advances in imaging genetics, i.e., the knowledge and study of how genetic variance leads to specific changes in neurotransmission, which in turn may affect cognition, emotion and behaviour. Second, the advances in the cognitive neuroscience of ageing, i.e, the relationship between age-related changes in brain structures and functions, and mental alterations.

Briefly put, in a just submitted manuscript, I suggest that the Rangel-Camerer-Montague framework can serve as a model for looking at genotype and age effects. This leads us to three advances: first, it provides a better way to illustrate and understand the minute details of the preference and decision making systems. Second, it serves as a demonstration that individual (and intra-individual) differences must be taken into account. The “economic agent” is not a homogenous subject, but an agent that differs from person to person and with persons over time. Finally, it may also serve as a framework for identifying potential ways to induce alterations in the systems, e.g., through medical intervention. More on this story later, given that the manuscript is accepted 😉 For now, here’s an illustration of how genotype (exemplified through COMT, MAO-A and 5-HT) and age effects may expand the model. Of course, this is only scratching the surface, but I hope you’ll see what I mean.

This is an extended version of the Rangel-Camerer-Montague model. Within each processing node, two dimensions are added, here exemplified with the three primary nodes. The genotype dimension is a categorical variable that divides subjects into two or three classes, while the age dimension is continuous (inset, top left).


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