The neural correlates of subjective value during intertemporal choice

Kable, Joseph W.; Glimcher, Paul W.

doi:10.1038/nn2007

Cited by 1,739 publications

(1,860 citation statements)

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“…The thalamus serves as a critical relay structure between cortical and subcortical regions, facilitating information integration among the SN/VTA and striatum as well as prefrontal areas such as the vmPFC and dlPFC (Haber and Knutson, 2009). The vmPFC has been widely implicated in subjective value encoding Kable and Glimcher, 2007;Levy and Glimcher, 2012;Montague and Berns, 2002;Padoa-Schioppa and Assad, 2006;Plassmann et al, 2007) and has been shown to integrate value information during multi-attribute decision-making (Basten et al, 2010;Hare et al, 2011;Kahnt et al, 2011). Building on these findings, we here show that vmPFC encodes integrated cue values.…”

Section: Discussionsupporting

confidence: 65%

Probabilistic inference under time pressure leads to a cortical-to-subcortical shift in decision evidence integration

et al. 2017

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A B S T R A C TReal-life decision-making often involves combining multiple probabilistic sources of information under finite time and cognitive resources. To mitigate these pressures, people "satisfice", foregoing a full evaluation of all available evidence to focus on a subset of cues that allow for fast and "good-enough" decisions. Although this form of decision-making likely mediates many of our everyday choices, very little is known about the way in which the neural encoding of cue information changes when we satisfice under time pressure. Here, we combined human functional magnetic resonance imaging (fMRI) with a probabilistic classification task to characterize neural substrates of multi-cue decision-making under low (1500 ms) and high (500 ms) time pressure. Using variational Bayesian inference, we analyzed participants' choices to track and quantify cue usage under each experimental condition, which was then applied to model the fMRI data. Under low time pressure, participants performed nearoptimally, appropriately integrating all available cues to guide choices. Both cortical (prefrontal and parietal cortex) and subcortical (hippocampal and striatal) regions encoded individual cue weights, and activity linearly tracked trial-by-trial variations in the amount of evidence and decision uncertainty. Under increased time pressure, participants adaptively shifted to using a satisficing strategy by discounting the least informative cue in their decision process. This strategic change in decision-making was associated with an increased involvement of the dopaminergic midbrain, striatum, thalamus, and cerebellum in representing and integrating cue values. We conclude that satisficing the probabilistic inference process under time pressure leads to a cortical-to-subcortical shift in the neural drivers of decisions.

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Section: Discussionsupporting

confidence: 65%

Probabilistic inference under time pressure leads to a cortical-to-subcortical shift in decision evidence integration

et al. 2017

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“…(a) Aversive stimuli, whether decision options that involve increased risk or punishments themselves, have frequently been shown to activate insular cortex (INS) 33,52,53,58 and ventrolateral prefrontal cortex (vlPFC) 61 . (b) Unexpected rewards modulate activation of the striatum (STR) 43,46,53,59,76 , particularly its ventral aspect, as well as the medial prefrontal cortex (mPFC) 43,53,61,76 . (c) Executive control processes required for evaluation of uncertain choice options are supported by dorsolateral prefrontal cortex (dlPFC) 52,58 and posterior parietal cortex (PPC) 33,34 .…”

Section: Resultsmentioning

confidence: 99%

“…Based on anatomy, CGp is well situated to translate subjective valuation signals into choice because it makes connections with brain areas implicated in processing reward, attention and action 74 . Moreover, this area is activated during decision making when rewards are uncertain in either amount 75 or time 76 , and the magnitude of activation depends on the subjective appeal of proffered rewards 77 . Finally, neurophysiology shows that CGp neurons respond to salient visual stimuli 78 , after visual orienting movements 78,79 and after rewards 80 , and that all these responses scale with reward size and predictability 80 .…”

Section: Neuronal Correlates Of Outcome Uncertainty and Risky Decisiomentioning

confidence: 99%

Risky business: the neuroeconomics of decision making under uncertainty

2008

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Many decisions involve uncertainty, or imperfect knowledge about how choices lead to outcomes. Colloquial notions of uncertainty, particularly when describing a decision as 'risky', often carry connotations of potential danger as well. Gambling on a long shot, whether a horse at the racetrack or a foreign oil company in a hedge fund, can have negative consequences, but the impact of uncertainty on decision making extends beyond gambling. Indeed, uncertainty in some form pervades nearly all our choices in daily life. Stepping into traffic to hail a cab, braving an ice storm to be the first at work, or dating the boss's son or daughter also offer potentially great windfalls, at the expense of surety. We continually face trade-offs between options that promise safety and others that offer an uncertain potential for jackpot or bust. When mechanisms for dealing with uncertain outcomes fail, as in mental disorders such as problem gambling or addiction, the results can be disastrous. Thus, understanding decision making-indeed, understanding behavior itselfrequires knowing how the brain responds to and uses information about uncertainty.

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“…25 Animal and human studies have shown the relevance of this cortex in representing subjective value, particularly in relation to rewards, 26 and in error signalling after the omission of an expected reward. 27 The posterior cingulate typically responds to prediction error in conjunction with the ventromedial prefrontal cortex. 27 In previous studies, structural posterior cingulate cortex abnormalities were seen in children with callous unemotional traits 28 and some adults with psychopathy, 29 but these were not seen in the sample in this study.…”

Section: Discussionmentioning

confidence: 99%