877.12
Probability transitions in a decision making under risk paradigm
Elise M. Dagenbach1 & Scott A. Huettel2,3
1Neuroscience
Duke
University
INTRODUCTION
Many economic decisions are made using information about possible
rewards and the probability that they will be received. A central finding
from behavioral economics is that probabilities are not weighted linearly
in decision making. In particular, people tend to overweight very small
probabilities and underweight very large probabilities (e.g., Tversky &
Fox, 1995), as reflected by the solid line in the graph below.
This behavior may reflect a special
status for certainty, such that people
overvalue events that are
guaranteed to occur – perhaps
because such decisions do not lead
to regret. Thus, changes in
probability have different effects
depending upon the starting point: a
10% increase in probability has a
greater effect if from 90% to 100%
than from 40% to 50%.
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5
METHODS
Experimental Task
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Subjects chose between a gamble with known probability (e.g., 10%) and a gamble with unknown probability (e.g., 0% or 20%).
Gambles had low (0%, 10%, 20%) or high (80%, 90%, or 100%) probabilities of winning a monetary reward.
On free choice trials, subjects chose between the known and unknown gambles. On forced choice trials, subjects were
presented with both gambles but only one was available for selection. Subjects played 240 trials/session (all factors randomized).
After the decision response was made, the true value of the chosen gamble was revealed and then played.
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p = .0025
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Response Phase
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100
Data Acquisition using fMRI at 4T
We conducted multiple regression analyses using SPM2.
Regressors were created for the presentation, reveal, spinning, and reward phases (along with head motion parameters).
Regressors were analyzed by trial type, response, probability increase or decrease, resolution of uncertainty, and reward outcome.
Significance was assessed using second-order random effects analyses.
0.5
BOLD Signal Change (%)
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Adapted from: Tversky & Fox (1995)
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P(High)
EXPERIMENTAL PARADIGM
P(Low)
While the neural substrates of reward have been heavily studied, less
research has been conducted into how the brain codes for and uses
information about probabilities. The firing rates of dopaminergic
neurons have been shown to depend both on reward probability
(maximal at P = 1) and reward uncertainty (maximal at P = 0.5), as
demonstrated by Fiorillo and colleagues (2003). Functional
neuroimaging studies have shown that a brain system including the
medial and lateral prefrontal cortices and the parietal cortex is
modulated by stimulus probability during decision making (Volz et al.,
2003, Huettel et al., 2005). However, in all such studies subjects
made decisions based on the estimated or expected probability
engendered by stimulus events, without transitions from one
probability to another. Thus, it remains unknown whether changes in
probability activate decision making systems and whether any such
effects are directional.
Fiorillo, C. D., Tobler, P. N., & Schultz, W. (2003). Discrete coding of reward probability
and uncertainty by dopamine neurons. Science, 299(5614), 1898-1902.
This research was supported by NIMH R01-070685.
100
6
20
Free Double
0
0
Forced Single
80
80
80
y= 14
p = .0025
100
You Won
Presentation
4
15 s
Forced Double
Reveal Phase
Activation in the posterior lateral
prefrontal cortex (pIFS, left) is
greater when probability decreased
(90% to 80%) than when probability
increased (90% to 100%).
Reward
Reveal
STRATEGIES
Singles
No Strategy
Doubles
Low Single,
High Double
When subjects were allowed to make free decisions between gambles with
different probabilities (compared to forced selection), increased activation was
observed in the ACC and IPS. These regions are associated with behavioral
control, particularly in scenarios involving risky choices.
x= 0
0.6
0.5
Response
Different subjects used different decision
strategies; thus, future evaluation of the
effects of strategy will be critical.
1.
Forced Single
Time (s)
L
6s - 11s
90
100
0.4
PROBABILITY TRANSITIONS
Free
1s - 3s
80
90
x= 4
10
10
10
Free Single
100
20
20
15 s
90
80
0
Time (s)
p = .00001
Volz, K. G., Schubotz, R. I., & von Cramon, D. Y. (2003). Predicting events of varying
probability: Uncertainty investigated by fMRI. NeuroImage, 19(2 Pt 1), 271-280.
ACKNOWLEDGMENTS
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90
RT
Huettel, S. A., Song, A. W., & McCarthy, G. (2005). Decisions under uncertainty:
Probabilistic context influences activity of prefrontal and parietal cortices. Journal of
Neuroscience, 25(13), 3304-3311.
CONCLUSIONS
90
Forced Double
Here, we investigated how transitions in probability influenced brain
activation in a task involving decision making under uncertainty. Our
subjects chose between two types of gambles: singles that had a
known probability (e.g., 90%) of winning a monetary reward, and
doubles that could take either of two possible probabilities (e.g., 80%
or 100%) with equal odds of each. If a double was chosen, then the
probability to be played was revealed following the subject’s choice
(e.g., the subject actually played a 80% gamble). During the
experiment, we measured changes in the amount of deoxygenated
hemoglobin, an index of local neuronal activity, using functional
Magnetic Resonance Imaging (fMRI). We hypothesized that we
would observe activation associated with transitions in reward
probability, even when those transitions were not contingent
upon decisions made by subjects or the delivery of a reward.
Tversky, A., & Fox, C. R. (1995). Weighing risk and uncertainty. Psychological Review,
102(2), 269-283.
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80
80
The Present Study
REFERENCES
Activation in the intraparietal
sulcus (IPS, left) and
anterior cingulate cortex
(ACC, right) is greater for free
choice trials than forced
choice trials.
y= -72
Data Analysis
BOLD Signal Change (%)
BOLD T2*-weighted images were collected using a gradient-echo inverse-spiral sequence (TR: 1500ms; TE: 35ms).
There were 34 axial slices (3.75*3.75*3.8mm voxels).
Preprocessing included motion correction, slice timing correction, normalization, and smoothing (8mm).
Time (s)
Preliminary results suggest a
similar effect in the posterior
cingulate cortex (PCC, right).
12 s
100% Revealed
80% Revealed
20% Revealed
BOLD Signal Change (%)
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The Neuroscience of Probability Judgments
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p = .00001
L
Participants were 9 young adults (mean: 22y).
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Duke Center for
Neuroeconomic Studies
FREE vs. FORCED DECISIONS
Subjects
BOLD Signal Change (%)
1
Probability Transitions Influence Behavior
Program, University of Michigan; 2Brain Imaging and Analysis Center, 3Department of Psychiatry, Duke University Medical Center
[email protected] [email protected] www.biac.duke.edu
Time (s)
12 s
0% Revealed
2. Changes in probability – independent of any subject decision or delivered outcome – evoked
greater activation in the lateral prefrontal cortex. This region may play a particular role in
behavioral control: choosing the appropriate context in which to evaluate a situation.
3. Thus, the neural effects of probability transitions may depend upon their context,
consistent with prior behavioral results.