Dysfunction in differential reward-punishment responsiveness in conduct disorder relates to severity of callous-unemotional traits but not irritability

Background Conduct disorder (CD) has been associated with dysfunction in reinforcement-based decision-making. Two forms of affective traits that reflect the components of CD severity are callous-unemotional (CU; reduced guilt/empathy) traits and irritability. The form of the reinforcement-based decision-making dysfunction with respect to CD and CU traits remains debated and has not been examined with respect to irritability in cases with CD. The goals of the current study were to determine the extent of dysfunction in differential (reward v. punishment) responsiveness in CD, and CU traits and irritability in participants with CD. Methods The study involved 178 adolescents [typically developing (TD; N = 77) and cases with CD (N = 101)]. Participants were scanned with fMRI during a passive avoidance task that required participants to learn to respond to (i.e. approach) stimuli that engender reward and refrain from responding to (i.e. passively avoid) stimuli that engender punishment. Results Adolescents with CD showed reduced differential reward-punishment responsiveness within the striatum relative to TD adolescents. CU traits, but not irritability, were associated with reduced differential reward-punishment responsiveness within the striatum, rostromedial, and lateral frontal cortices. Conclusions The results suggest CD is associated with reduced differential reward-punishment responsiveness and the extent of this dysfunction in participants with CD is associated with the severity of CU traits but not irritability.

Orbitofrontal cortex neurons code utility changes during natural reward consumption as correlates of relative reward-specific satiety

Natural, on-going reward consumption can differentially reduce the subjective value (‘utility’) of specific rewards, which indicates relative, reward-specific satiety. Two-dimensional choice indifference curves (IC) represent the utility of choice options with two distinct reward components (‘bundles’) according to Revealed Preference Theory. We estimated two-dimensional ICs from stochastic choices and found that natural on-going consumption of two bundle rewards induced specific IC distortions that indicated differential reduction of reward utility indicative of relative reward-specific satiety. Licking changes confirmed satiety in a mechanism-independent manner. Neuronal signals in orbitofrontal cortex (OFC) that coded the value of the chosen option followed closely the consumption-induced IC distortions within recording periods of individual neurons. A neuronal classifier predicted well the changed utility inferred from the altered behavioral choices. Neuronal signals for more conventional single-reward choice options showed similar relationships to utility alterations from on-going consumption. These results demonstrate a neuronal substrate for the differential, reward-specific alteration of utility by on-going reward consumption reflecting reward-specific satiety.SignificanceRepeated delivery reduces the subjective value (‘utility’) of rewards to different degrees depending on their individual properties, a phenomenon commonly referred to as sensory-specific satiety. We tested monkeys during economic choice of two-component options. On-going consumption differentially reduced reward utility in a way that suggested relative reward-specific satiety between the two components. Neurons in the orbitofrontal cortex (OFC) changed their responses in close correspondence to the differential utility reduction, thus representing a neuronal correlate of relative reward-specific satiety. Control experiments with conventional single-component choice showed similar satiety-induced differential response reductions. These results are compatible with the notion of OFC neurons coding crucial decision variables robustly across different satiety levels.

Reward-Related Suppression of Neural Activity in Macaque Visual Area V4

In order for organisms to survive, they need to detect rewarding stimuli, for example, food or a mate, in a complex environment with many competing stimuli. These rewarding stimuli should be detected even if they are nonsalient or irrelevant to the current goal. The value-driven theory of attentional selection proposes that this detection takes place through reward-associated stimuli automatically engaging attentional mechanisms. But how this is achieved in the brain is not very well understood. Here, we investigate the effect of differential reward on the multiunit activity in visual area V4 of monkeys performing a perceptual judgment task. Surprisingly, instead of finding reward-related increases in neural responses to the perceptual target, we observed a large suppression at the onset of the reward indicating cues. Therefore, while previous research showed that reward increases neural activity, here we report a decrease. More suppression was caused by cues associated with higher reward than with lower reward, although neither cue was informative about the perceptually correct choice. This finding of reward-associated neural suppression further highlights normalization as a general cortical mechanism and is consistent with predictions of the value-driven attention theory.

Affective-Associative Two-Process theory: A neural network investigation of adaptive behaviour in differential outcomes training

In this article we present a novel neural network implementation of Associative Two-Process (ATP) theory based on an Actor–Critic-like architecture. Our implementation emphasizes the affective components of differential reward magnitude and reward omission expectation and thus we model Affective-Associative Two-Process theory (Aff-ATP). ATP has been used to explain the findings of differential outcomes training (DOT) procedures, which emphasize learning differentially valuated outcomes for cueing actions previously associated with those outcomes. ATP hypothesizes the existence of a ‘prospective’ memory route through which outcome expectations can bring to bear on decision making and can even substitute for decision making based on the ‘retrospective’ inputs of standard working memory. While DOT procedures are well recognized in the animal learning literature they have not previously been computationally modelled. The model presented in this article helps clarify the role of ATP computationally through the capturing of empirical data based on DOT. Our Aff-ATP model illuminates the different roles that prospective and retrospective memory can have in decision making (combining inputs to action selection functions). In specific cases, the model’s prospective route allows for adaptive switching (correct action selection prior to learning) following changes in the stimulus–response–outcome contingencies.