Neural correlates of effort-based valuation with prospective choices.

How is effort integrated in value-based decision-making? Animal models and human neuroimaging studies primarily linked the anterior cingulate cortex (ACC) and ventral striatum (VS) to the integration of effort in valuation. Other studies demonstrated the role of these regions in invigoration to effort demands, thus it is hard to separate the neural activity linked to anticipation and subjective valuation from actual performance. Here, we studied the neural basis of effort valuation separated from performance. We scanned forty participants with fMRI, while they were asked to accept or reject monetary gambles that could be resolved with future performance of a familiar grip force effort challenge or a fixed risk prospect. Participants' willingness to accept prospective gambles reflected discounting of values by physical effort and risk. Choice-locked neural activation in contralateral primary sensory cortex and ventromedial prefrontal cortex (vmPFC) tracked the magnitude of prospective effort the participants faced, independent of choice time and monetary stakes. Estimates of subjective value discounted by effort were found to be tracked by the activation of a network of regions common to valuation under risk and delay, including vmPFC, VS and sensorimotor cortex. Together, our findings show separate neural mechanisms underlying prospective effort and actual effort performance.

Reply to Vinken and Vogels.

In their comment, Vinken and Vogels [1] take issue with our claim [2] that "IT neurons encode long-term, latent probabilistic information about stimulus occurrence". They offer a biologically plausible model of our findings, which they argue is based on neuronal fatigue. However, like our account, their model includes latent variables that are modulated slowly with stimulus probability; models without such latent processes, such as those based on temporally local fatigue effects, cannot explain our findings. Although we share their desire for more clarity about the mechanisms underlying visual expectation, and appreciate their thoughtful critique, we argue here that their comment mostly restates our findings with a more complex model and alternative terminology.

Encoding of Stimulus Probability in Macaque Inferior Temporal Cortex.

Optimal perceptual decisions require sensory signals to be combined with prior information about stimulus probability. Although several theories propose that probabilistic information about stimulus occurrence is encoded in sensory cortex, evidence from neuronal recordings has not yet fully supported this view. We recorded activity from single neurons in inferior temporal cortex (IT) while monkeys performed a task that involved discriminating degraded images of faces and fruit. The relative probability of the cue being a face versus a fruit was manipulated by a latent variable that was not revealed to the monkeys and that changed unpredictably over the course of each recording session. In addition to responding to stimulus identity (face or fruit), population responses in IT encoded the long-term stimulus probability of whether a face or a fruit stimulus was more likely to occur. Face-responsive neurons showed reduced firing rates to expected faces, an effect consistent with "expectation suppression," but expected stimuli were decoded from multivariate population signals with greater accuracy. These findings support "predictive coding" theories, whereby neural signals in the mammalian visual system actively encode and update predictions about the local sensory environment.

Beyond dopamine: the noradrenergic system and mental effort.

An opportunity cost model of effort requires flexible integration of valuation and self-control systems. Reciprocal connections between these networks and brainstem neuromodulatory systems are likely to provide the signals that affect subsequent persistence or failure when faced with effort challenges. The interaction of these systems should be taken into account to strengthen a normative neural model of effort.

Relationship between functional magnetic resonance imaging-identified regions and neuronal category selectivity.

Functional magnetic resonance imaging (fMRI) has been used extensively to identify regions in the inferior temporal (IT) cortex that are selective for categories of visual stimuli. However, comparatively little is known about the neuronal responses relative to these fMRI-defined regions. Here, we compared in nonhuman primates the distribution and response properties of IT neurons recorded within versus outside fMRI regions selective for four different visual categories: faces, body parts, objects, and places. Although individual neurons that preferred each of the four categories were found throughout the sampled regions, they were most concentrated within the corresponding fMRI region, decreasing significantly within 1-4 mm from the edge of these regions. Furthermore, the correspondence between fMRI and neuronal distributions was specific to neurons that increased their firing rates in response to the visual stimuli but not to neurons suppressed by visual stimuli, suggesting that the processes associated with inhibiting neuronal activity did not contribute strongly to the fMRI signal in this experiment.