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Anticipatory affect and financial risk taking - Brian Knutson
1. Anticipatory affect and
financial risk taking
Brian Knutson
Stanford University
03.29.12: World Economic Forum Symposium, San Francisco CA
2.
3.
4.
5. Questions
• Which brain mechanisms anticipate good
and bad events? (affective neuroscience)
• Does their activity influence choice?
(neuroeconomics)
input output
9. “Reward” circuitry
Haber SN, Knutson B (2010) Neuropsychopharm, 35, 4-26.
10. MEG & ERP Functional MRI
PET Naturally
Occurring
Lesions
TMS
Multi-Unit
Recording
Single-Cell Recording
deep
seconds
millimeters
11. Anticipatory Affect Model
• Neural targets
– Gain anticipation: Nucleus accumbens (NAcc)
– Loss anticipation: Anterior insula
– Value integration: Medial prefrontal cortex (MPFC)
Knutson B, Greer SM (2008). Phil Trans Royal Soc B, 363, 3771-3786.
12. Risk Taking Predictions
• Risks involve uncertain but large gains and losses
• NAcc activation promotes risk seeking
• Anterior insula activation promotes risk avoidance
13. Behavioral Investment Allocation Strategy
(BIAS) Task
• 20 blocks of 10 trials
• At block outset, one stock is randomly assigned as “good,”
the other is “bad”
• Subjects know one stock is better, but don’t know which:
Good stock: Bad stock:
+$10 w/ prob. 50% +$10 w/ prob. 25%
-$10 w/ prob. 25% -$10 w/ prob. 50%
$0 w/ prob. 25% $0 w/ prob. 25%
Bond:
+$1 w/ prob. 100%
Kuhnen CM, Knutson B (2005) Neuron, 47, 763-770.
25. Incidental Affect
• Incidental affective cues can influence
financial risk taking
Knutson B, Wimmer GE, Kuhnen CM, Winkielman P (2008) NeuroReport, 19, 509-513.
26. Incidental Affect
• Partial mediation by brain activation.
Knutson B, Wimmer GE, Kuhnen CM, Winkielman P (2008) NeuroReport, 19, 509-513.
27. Summary
• Neural activity related to anticipatory
affect can be localized with FMRI
• Anticipatory activity in these circuits
predicts financial risk taking
• Predictions extend beyond those made
by standard theories (e.g., mean-variance)
28. Questions
• Can other circuits (e.g., habitual, symbolic,
reflective) modulate or overshadow the
influence of these affective circuits (and if
so, when)?
• Do individual influences scale to the
group level (and if so, when)?
We know that market financial events can affect emotions, Not just in laypeople, but Even in “sophisticated” market players…
In both positive
And negative ways. We also suspect the opposite: that emotions can influence financial choice. But what is the scientific evidence for this?
In fact, my laboratory addresses two questions about how brain mechanisms anticipate good and bad events (you will see that money is a particularly useful tool in this endeavor) and also whether anticipation of good and bad events as reflected by brain activity influences choice. My laboratory addresses two questions that are also central to two new hybrid fields. The first question – do different mechanisms in the brain anticipate good and bad events – is relevant to affective neuroscience, And the second – does their activity influence choice – is relevant to neuroeconomics. Pleas NOTE that even if we can answer these questions, their answers may or may not overlap.
We believe that the overlapping circuits responsible lie deep in the brain, are evolutionarily served, and promote survival and procreation, In other words, they are affective.
We have yet to identify the “smoking gun.” Today, I will argue that technology can help.
If you want to look for emotional traits, you might want to aim at the subcortex. Why? That’s where many sites lie that animals will work very hard to stimulate or avoid getting stimulated.
The regions that facilitate self-stimulation tend to lie along the ascending trajectory of midbrain neurons, particularly the ventral projections from the ventral tegmental area (or VTA) The same circuits support the same types of behavior in humans and monkeys. Problem for measurement: these circuits are partially subcortical, small, and fast. How can we measure their activity in humans?
About 15 years ago, a new type of neuroimaging, functional magnetic resonance imaging, was introduced, which gave us adequate spatial and temporal resolution to look deep into the brain and ask what was happening before people made choices.
FMRI, combined wi th monetary tasks, helped us identify brain regions which responded to antcipation of gain, loss, and integration of this information. The first two regions lie in areas of the brain that are deep and implicated in emotion. The model is related to risk as feelings and somatic marker models (but the signals need only come from the brain). But it adds value, as well as neural targets, which should allow us to predict which behavior comes next: Approach or avoidance.
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Importantly, information is not enough. It must be integrated and it must be evaluable.
Importantly, information is not enough. It must be integrated and it must be evaluable.