How the brain integrates costs and benefits during decision making

Abstract

When we make decisions, the benefits of an option often need to be weighed against accompanying costs. Little is known, however, about the neural systems underlying such cost-benefit computations. Using functional magnetic resonance imaging and choice modeling, we show that decision making based on cost-benefit comparison can be explained as a stochastic accumulation of costbenefit difference. Model-driven functional MRI shows that ventromedial and left dorsolateral prefrontal cortex compare costs and benefits by computing the difference between neural signatures of anticipated benefits and costs from the ventral striatum and amygdala, respectively. Moreover, changes in blood oxygen level dependent (BOLD) signal in the bilateral middle intraparietal sulcus reflect the accumulation of the difference signal from ventromedial prefrontal cortex. In sum, we show that a neurophysiological mechanism previously established for perceptual decision making, that is, the difference-based accumulation of evidence, is fundamental also in value-based decisions. The brain, thus, weighs costs against benefits by combining neural benefit and cost signals into a single, differencebased neural representation of net value, which is accumulated over time until the individual decides to accept or reject an option.hen we make decisions, the benefits of a decision option often need to be weighed against accompanying costs. Cost-benefit integration, thus, is an important aspect of decision making. However, value-based decision making is typically investigated in the context of decision uncertainty (1-3), so little is known about the neural mechanisms underlying the integration of costs and benefits as such.Cost-benefit-based decision making involves the binary decision to either accept or reject a choice option based on two competing attributes-the option's expected rewards and losses. Such binary accept-versus-reject decisions bear a strong resemblance to twoalternative choices in perceptual decision making (4, 5). For example, when monkeys performed a direction-of-motion discrimination task in which they had to decide whether a noisy field of dots was moving in one direction or its opposite direction (e.g., leftward or rightward) and indicated their choice with a quick eye movement to the target on the respective side, motion-sensitive neurons in middle temporal visual area MT either respond to leftward motion or to rightward motion. Prefrontal and parietal neurons, in contrast, form a decision by accumulating the difference in the activities of populations of neurons in area MT that code for opposite directions of motion. The monkey's saccade response is faster when more dots are moving in one direction, and this effect is predicted by the strength of the accumulated neuronal difference signal (6). A difference-based decision mechanism has also been identified in the human dorsolateral prefrontal cortex (DLPFC) during perceptual face-house decisions (4, 7). Thus, we hypothesized that cost-benefit decisions involve an analogous decisio...

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

“…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.…”

Quantifying the time for accurate EEG decoding of single value-based decisions

“…The experimental protocol was adapted from a previous functional magnetic resonance imaging (fMRI) study (Basten et al, 2010). It consisted of two phases: the training phase and the main experiment.…”

“…Recent studies suggest that similar mechanisms of evidence accumulation might also be involved in value-based decision making, where values corresponding to an offer are encoded, compared and accumulated over time according to DDM (Basten et al, 2010). A widespread network of brain regions is involved in this process, with the ventromedial prefrontal cortex being a value integration region (Basten et al, 2010;Philiastides et al, 2010), and parietal regions accumulating results of this integration (Basten et al, 2010;Gluth et al, 2012;Hunt et al, 2012).…”

“…A widespread network of brain regions is involved in this process, with the ventromedial prefrontal cortex being a value integration region (Basten et al, 2010;Philiastides et al, 2010), and parietal regions accumulating results of this integration (Basten et al, 2010;Gluth et al, 2012;Hunt et al, 2012). Because an accumulation mechanism implies a dynamic process which evolves over time, assessing the temporal dynamics of decision-making can be highly informative of the underlying neural process.…”

“…A previous study has shown that this task follows behaviorally a DDM (Basten et al, 2010). Here, we assumed the same behavioral model and aimed at extracting neural activity preceding single decisions.…”