Does one simulate the other's value-based decision making by using the neural systems for his own?
Shinsuke
Suzuki1*,
Norihiro
Harasawa1,
Kenichi
Ueno2,
Sivaramakrishnan
Kaveri1, 3,
Justin
Gardner4,
Noritaka
Ichinohe5,
Masahiko
Haruno6,
Kang
Cheng2, 7 and
Hiroyuki
Nakahara1, 3
-
1
RIKEN BSI, Lab for Int Theor Neurosci, Japan
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2
RIKEN BSI, fMRI Support Unit, Japan
-
3
Tokyo Inst of Tech , Dpt Comp Intell & Sys Sci, Japan
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4
RIKEN BSI, Gardner Research Unit, Japan
-
5
Hirosaki Univ , Dept Neuroanatomy, Japan
-
6
Tamagawa Univ , Brain Science Institute, Japan
-
7
RIKEN BSI, Lab for Cognitive Brain Mapping, Japan
In social contexts, another person’s behavior often affects the outcome of one’s value-based decision making which involves valuation and learning, i.e., reinforcement learning. So predicting the other’s decision making is indispensable. In a broader context, it is often said in the field of social cognitive neuroscience that prediction about the other is made by ’simulating the other’; this simulation is often posited as using some systems like the so-called "mirror neuron system" that has been implicated in both one’s own actions/sensations/emotions and one’s perceptions of those by the other. For social value-based decision making, this could be translated to the question of whether one simulates the other’s value-based decision making by using the same systems for one’s own decision making or not. Thus, we asked (a) whether one actually simulates both valuation and learning of the other; and (b) whether this simulation uses the same neural mechanisms used for one’s own decision making. To address these issues, we conducted an fMRI experiment with model-based analysis, using two tasks: an instrumental learning task and a "predict-other" task in which subjects predict choices of another person who plays the first task. These tasks allow us to directly compare corresponding neural regions between the subject’s decision making in the first task and the subject’s simulation of the other’s decision making in the second task. In the instrumental task, subjects have to learn the reward probability for each option (learning) and compute an action-value (valuation) to make optimal choices. We confirmed that the subjects’ behavior was fitted well with a computational, reinforcement learning model. In the predict-other task, subjects should simulate the valuation and learning of the other to make correct predictions. To address if the subjects actually did so, we fitted the subject’s behavior with a computational model ("simulation model") that simulates the other’s learning and valuation. We compared the goodness of fit of the simulation model with two other models which involved only simulation of the other’s valuation or no simulation at all. We found that the simulation model accounted well for the subjects’ behavior and provided a better fit than the other two models. Using model-based fMRI, we investigated the relationship (e.g., overlap or separation) between neural correlates of the subject’s own decision making and those of the subject’s simulation of the other’s decision making. Our preliminary results indicate that several brain regions are correlated with the reward prediction error (PE) for both the subject and for the other, as might be expected for a PE-mirror neuron systems. We also found other regions correlated only with the other’s PE, but not the subject’s PE. These results suggest that one actually simulates both valuation and learning of the other and although preliminary, further that the same neural systems for one’s reward prediction (i.e. PE) are used for simulating the other, while additional systems are also involved.
Conference:
Computational and Systems Neuroscience 2010, Salt Lake City, UT, United States, 25 Feb - 2 Mar, 2010.
Presentation Type:
Poster Presentation
Topic:
Poster session I
Citation:
Suzuki
S,
Harasawa
N,
Ueno
K,
Kaveri
S,
Gardner
J,
Ichinohe
N,
Haruno
M,
Cheng
K and
Nakahara
H
(2010). Does one simulate the other's value-based decision making by using the neural systems for his own?.
Front. Neurosci.
Conference Abstract:
Computational and Systems Neuroscience 2010.
doi: 10.3389/conf.fnins.2010.03.00088
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Received:
20 Feb 2010;
Published Online:
20 Feb 2010.
*
Correspondence:
Shinsuke Suzuki, RIKEN BSI, Lab for Int Theor Neurosci, Wako, saitama, Japan, shinsuke@brain.riken.jp