Financial gain and financial pain
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Studies of decision-making and financial gain implicate the striatum in encoding prediction errors. Functional magnetic resonance imaging experiments reveal how the brain responds to anticipation of financial loss.
Studies of decision-making and financial gain implicate the striatum in encoding prediction errors. But what about anticipation of financial loss, for example what distinguishes a reward that is greater than expected from a punishment or loss that is less than expected?
This week in the Journal of Neuroscience, Seymour et al. [1] used a pavlovian conditioning paradigm in which subjects were shown a series of visual stimuli followed by an indication of personal financial gain or loss. Subjects then made appetitive or aversive predictions, respectively, during functional magnetic resonance imaging.
Blood oxygenation level-dependent (BOLD) responses were elevated above baseline, as expected, in the striatum during appetitive predictions. Aversive predictions also elevated BOLD responses, a 'positive' (above baseline) response to financial loss. However, the signals were spatially distinct, with gain prediction provoking activation in more anterior and ventral areas and loss prediction associated with more posterior regions.
[1] Ben Seymour, Nathaniel Daw, Peter Dayan, Tania Singer, and Ray Dolan
This week in the Journal of Neuroscience, Seymour et al. [1] used a pavlovian conditioning paradigm in which subjects were shown a series of visual stimuli followed by an indication of personal financial gain or loss. Subjects then made appetitive or aversive predictions, respectively, during functional magnetic resonance imaging.
Blood oxygenation level-dependent (BOLD) responses were elevated above baseline, as expected, in the striatum during appetitive predictions. Aversive predictions also elevated BOLD responses, a 'positive' (above baseline) response to financial loss. However, the signals were spatially distinct, with gain prediction provoking activation in more anterior and ventral areas and loss prediction associated with more posterior regions.
[1] Ben Seymour, Nathaniel Daw, Peter Dayan, Tania Singer, and Ray Dolan
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