Neural substrates of reward magnitude, probability, and risk during a wheel of fortune decision-making task

Smith, Bruce W.; Mitchell, Derek; Hardin, Michael; Jazbec, Sandra; Fridberg, Daniel J.; Blair, R. J. R.; Ernst, Monique

doi:10.1016/j.neuroimage.2008.08.016

Cited by 158 publications

(165 citation statements)

References 66 publications

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“…Our results suggest that the IPL, an area previously implicated in the planning, execution, and observation of goal-directed actions (Fincham et al, 2002;Liljeholm et al, 2011Liljeholm et al, , 2012, as well as in the experience of agency (Chaminade and Decety, 2002;Farrer et al, 2008;Sperduti et al, 2011), implements a comparison of instrumental probability distributions. This finding has broad implications, potentially generalizing to other types of predictive relationships, and providing a means of linking action-outcome learning to more abstract features of goal-directed performance, such as agency and intent attribution.…”

Section: Discussionmentioning

confidence: 51%

Neural Correlates of the Divergence of Instrumental Probability Distributions

Liljeholm

Wang

Zhang

et al. 2013

Journal of Neuroscience

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Flexible action selection requires knowledge about how alternative actions impact the environment: a "cognitive map" of instrumental contingencies. Reinforcement learning theories formalize this map as a set of stochastic relationships between actions and states, such that for any given action considered in a current state, a probability distribution is specified over possible outcome states. Here, we show that activity in the human inferior parietal lobule correlates with the divergence of such outcome distributions-a measure that reflects whether discrimination between alternative actions increases the controllability of the future-and, further, that this effect is dissociable from those of other information theoretic and motivational variables, such as outcome entropy, action values, and outcome utilities. Our results suggest that, although ultimately combined with reward estimates to generate action values, outcome probability distributions associated with alternative actions may be contrasted independently of valence computations, to narrow the scope of the action selection problem.

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Section: Discussionmentioning

confidence: 51%

Neural Correlates of the Divergence of Instrumental Probability Distributions

Liljeholm

Wang

Zhang

et al. 2013

Journal of Neuroscience

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“…First, a number of neurophysiological and imaging studies have implicated distinct neural substrates in the processing of magnitude versus frequency information during behavioral choice. For instance, subcortical structures including nucleus accumbens have been linked to the former and cortical prefrontal structures have been linked to the latter (Knutson, Taylor, Kaufman, Peterson, & Glover, 2005; see also Smith et al, 2009;Yacubian et al, 2007). Perhaps the mechanisms mediating learning and/or expression of learning in visual search interface in distinct ways with the unique substrates representing magnitude and frequency information.…”

Section: Discussionmentioning

confidence: 99%

How do magnitude and frequency of monetary reward guide visual search?

Won

Leber

2016

Atten Percept Psychophys

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How does reward guide spatial attention during visual search? In the present study, we examine whether and how two types of reward information-magnitude and frequency-guide search behavior. Observers were asked to find a target among distractors in a search display to earn points. We manipulated multiple levels of value across the search display quadrants in two ways: For reward magnitude, targets appeared equally often in each quadrant, and the value of each quadrant was determined by the average points earned per target; for reward frequency, we varied how often the target appeared in each quadrant but held the average points earned per target constant across the quadrants. In Experiment 1, we found that observers were highly sensitive to the reward frequency information, and prioritized their search accordingly, whereas we did not find much prioritization based on magnitude information. In Experiment 2, we found that magnitude information for a nonspatial feature (color) could bias search performance, showing that the relative insensitivity to magnitude information during visual search is not generalized across all types of information. In Experiment 3, we replicated the negligible use of spatial magnitude information even when we used limited-exposure displays to incentivize the expression of learning. In Experiment 4, we found participants used the spatial magnitude information during a modified choice task-but again not during search. Taken together, these findings suggest that the visual search apparatus does not equally exploit all potential sources of spatial value information; instead, it favors spatial reward frequency information over spatial reward magnitude information.Keywords Visual search . Spatial attention . Spatial probability cueing . Statistical learning . Reward learning Interaction with our spatial environment is inherently goal driven, aimed at maximizing our behavioral outcomes. Consider a fisherman choosing between two equidistant locations to travel to and lower his lines. By a frequency maximization principle, he will pick the location that promises more fish caught in a given interval (all other things being equal). By a magnitude maximization principle, he will pick the location that promises individual fish that are more valuable to him (e.g., larger or tastier). Research has long examined the role of reward frequency and magnitude in learning (Crespi, 1942;Herrnstein, 1961). One classic demonstration of how these factors influence behavioral choice comes from Spear and Pavlik (1966), who used a T-maze procedure. Rats had to run through the Bstem^of the T toward a choice point, where they had to go left versus right to obtain a potential food reward at the end of the chosen arm. The frequency manipulation placed a reward more frequently in one arm than the other; the magnitude manipulation placed rewards equally often but altered the number of food pellets in each arm. Results showed that the rats took advantage of both frequency and magnitude information to maximize thei...

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“…Patients with damage to either region demonstrate impairments on laboratory models of 'real-world' decision making where levels of reward and cost are varied across options (Bechara et al, 1999;Brand et al, 2007;Manes et al, 2002;van Honk et al, 2013). Similarly, functional neuroimaging and intracranial electrophysiology suggest that the amygdala and ACC are involved in evaluating costs and rewards to guide subsequent behavior (Basten et al, 2010;Jenison et al, 2011;Smith et al, 2009;Williams et al, 2004), and internally generated changes in choice correlate with amygdala and ACC activity (Sokol-Hessner et al, 2013;Walton et al, 2004).…”

Section: Introductionmentioning

confidence: 99%

Dissociable Contributions of Anterior Cingulate Cortex and Basolateral Amygdala on a Rodent Cost/Benefit Decision-Making Task of Cognitive Effort

Hosking

Cocker

Winstanley

2014

Neuropsychopharmacol

119

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Personal success often requires the choice to expend greater effort for larger rewards, and deficits in such effortful decision making accompany a number of illnesses including depression, schizophrenia, and attention-deficit/hyperactivity disorder. Animal models have implicated brain regions such as the basolateral amygdala (BLA) and anterior cingulate cortex (ACC) in physical effort-based choice, but disentangling the unique contributions of these two regions has proven difficult, and effort demands in industrialized society are predominantly cognitive in nature. Here we utilize the rodent cognitive effort task (rCET), a modification of the five-choice serial reactiontime task, wherein animals can choose to expend greater visuospatial attention to obtain larger sucrose rewards. Temporary inactivation (via baclofen-muscimol) of BLA and ACC showed dissociable effects: BLA inactivation caused hard-working rats to 'slack off' and 'slacker' rats to work harder, whereas ACC inactivation caused all animals to reduce willingness to expend mental effort. Furthermore, BLA inactivation increased the time needed to make choices, whereas ACC inactivation increased motor impulsivity. These data illuminate unique contributions of BLA and ACC to effort-based decision making, and imply overlapping yet distinct circuitry for cognitive vs physical effort. Our understanding of effortful decision making may therefore require expanding our models beyond purely physical costs.

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Neural substrates of reward magnitude, probability, and risk during a wheel of fortune decision-making task

Cited by 158 publications

References 66 publications

Neural Correlates of the Divergence of Instrumental Probability Distributions

Neural Correlates of the Divergence of Instrumental Probability Distributions

How do magnitude and frequency of monetary reward guide visual search?

Dissociable Contributions of Anterior Cingulate Cortex and Basolateral Amygdala on a Rodent Cost/Benefit Decision-Making Task of Cognitive Effort

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