Guido Biele

Perceptual decision making in monkeys relies on decision neurons, which accumulate evidence and maintain choices until a response is given. In humans, several brain regions have been proposed to accumulate evidence, but it is unknown if these regions also maintain choices. To test if accumulator regions in humans also maintain decisions we compared delayed and self-paced responses during a face/house discrimination decision making task. Computational modeling and fMRI results revealed dissociated processes of evidence accumulation and decision maintenance, with potential accumulator activations found in the dorsomedial prefrontal cortex, right inferior frontal gyrus and bilateral insula. Potential maintenance activation spanned the frontal pole, temporal gyri, precuneus and the lateral occipital and frontal orbital cortices. Results of a quantitative reverse inference meta-analysis performed to differentiate the functions associated with the identified regions did not narrow down potential accumulation regions, but suggested that response-maintenance might rely on a verbalization of the response.

Deficient reward processing has gained attention as an important aspect of ADHD, but little is known about reward-based decision-making (DM) in adults with ADHD. This article summarizes research on DM in adult ADHD and contextualizes DM deficits by comparing them to attention deficits. Meta-analytic methods were used to calculate average effect sizes for different DM domains and continuous performance task (CPT) measures. None of the 59 included studies (DM: 12 studies; CPT: 43; both: 4) had indications of publication bias. DM and CPT measures showed robust, small to medium effects. Large effect sizes were found for a drift diffusion model analysis of the CPT. The results support the existence of DM deficits in adults with ADHD, which are of similar magnitude as attention deficits. These findings warrant further examination of DM in adults with ADHD to improve the understanding of underlying neurocognitive mechanisms.

The mesocorticolimbic dopamine (DA) system linking the dopaminergic midbrain to the prefrontal cortex and subcortical striatum has been shown to be sensitive to reinforcement in animals and humans. Within this system, coexistent segregated striato-frontal circuits have been linked to different functions. In the present study, we tested patients with Parkinson's disease (PD), a neurodegenerative disorder characterized by dopaminergic cell loss, on two reward-based learning tasks assumed to differentially involve dorsal and ventral striato-frontal circuits. 15 non-depressed and non-demented PD patients on levodopa monotherapy were tested both on and off medication. Levodopa had beneficial effects on the performance on an instrumental learning task with constant stimulus-reward associations, hypothesized to rely on dorsal striato-frontal circuits. In contrast, performance on a reversal learning task with changing reward contingencies, relying on ventral striato-frontal structures, was better in the unmedicated state. These results are in line with the “overdose hypothesis” which assumes detrimental effects of dopaminergic medication on functions relying upon less affected regions in PD. This study demonstrates, in a within-subject design, a double dissociation of dopaminergic medication and performance on two reward-based learning tasks differing in regard to whether reward contingencies are constant or dynamic. There was no evidence for a dose effect of levodopa on reward-based behavior with the patients’ actual levodopa dose being uncorrelated to their performance on the reward-based learning tasks.

The ability to rapidly and flexibly adapt decisions to available rewards is crucial for survival in dynamic environments. Reward-based decisions are guided by reward expectations that are updated based on prediction errors, and processing of these errors involves dopaminergic neuromodulation in the striatum. To test the hypothesis that the COMT gene Val(158)Met polymorphism leads to interindividual differences in reward-based learning, we used the neuromodulatory role of dopamine in signaling prediction errors. We show a behavioral advantage for the phylogenetically ancestral Val/Val genotype in an instrumental reversal learning task that requires rapid and flexible adaptation of decisions to changing reward contingencies in a dynamic environment. Implementing a reinforcement learning model with a dynamic learning rate to estimate prediction error and learning rate for each trial, we discovered that a higher and more flexible learning rate underlies the advantage of the Val/Val genotype. Model-based fMRI analysis revealed that greater and more differentiated striatal fMRI responses to prediction errors reflect this advantage on the neurobiological level. Learning rate-dependent changes in effective connectivity between the striatum and prefrontal cortex were greater in the Val/Val than Met/Met genotype, suggesting that the advantage results from a downstream effect of the prefrontal cortex that is presumably mediated by differences in dopamine metabolism. These results show a critical role of dopamine in processing the weight a particular prediction error has on the expectation updating for the next decision, thereby providing important insights into neurobiological mechanisms underlying the ability to rapidly and flexibly adapt decisions to changing reward contingencies.

To make decisions based on the value of different options, we often have to combine different sources of probabilistic evidence. For example, when shopping for strawberries on a fruit stand, one uses their color and size to infer-with some uncertainty-which strawberries taste best. Despite much progress in understanding the neural underpinnings of value-based decision making in humans, it remains unclear how the brain represents different sources of probabilistic evidence and how they are used to compute value signals needed to drive the decision. Here, we use a visual probabilistic categorization task to show that regions in ventral temporal cortex encode probabilistic evidence for different decision alternatives, while ventromedial prefrontal cortex integrates information from these regions into a value signal using a difference-based comparator operation.