S ections 3 through 5 present a fascinating set of chapters on the many different psychological processes that may contribute to pathological drug-seeking behavior in addiction, with an emphasis on implicit automatic processes. We briefly address some highlights. The idea that addiction may result from dys-function that alters the balance among multiple different psychological processes, which ...

We present CCMC (Conditional CSL Model Checker), a model checker for continuous-time Markov chains (CTMCs) with respect to formulas specified in continuoustime stochastic logic (CSL). Existing CTMC model checkers such as PRISM or MRMC handle only binary CSL until path formulas. CCMC is the first tool that supports algorithms for analyzing multiple until path formulas. Moreover, CCMC supports a ...

Human behaviour is generally guided by the anticipation of potential outcomes that are considered to be rewarding. Reward processing can thus be dissected into a phase of reward anticipation and a phase of reward consumption. A number of brain structures have been suggested to be involved in reward processing. However, it is unclear whether anticipation and consumption are mediated by the same ...

Associating stimuli with the prospect of reward typically facilitates responses to those stimuli due to an enhancement of attentional and cognitive-control processes. Such reward-induced facilitation might be especially helpful when cognitive-control mechanisms are challenged, as when one must overcome interference from irrelevant inputs. Here, we investigated the neural dynamics of reward effe...

Anhedonia - diminished pleasure and/or decreased reactivity to pleasurable stimuli - is a core feature of depression that frequently persists after treatment. As a result, extensive effort has been directed towards characterizing the psychological and biological processes that mediate dysfunctional reward processing in depression. Reward processing can be parsed into sub-components that include...

Reinforcement learning has achieved broad and successful application in cognitive science in part because of its general formulation of the adaptive control problem as the maximization of a scalar reward function. The computational reinforcement learning framework is motivated by correspondences to animal reward processes, but it leaves the source and nature of the rewards unspecified. This pap...

The brain's reward circuitry consists of an "in series" circuit of dopaminergic (DA) neurons in the ventral tegmental area (VTA), nucleus accumbens (Acb), and that portion of the medial forebrain bundle (MFB) which links the VTA and Acb. Drugs which enhance brain reward (and have derivative addictive potential) have common actions on this core DA reward system and on animal behaviors relating t...

It is well known that eye movement patterns are influenced by both goal- and salience-driven factors. Recent studies, however, have demonstrated that objects that are nonsalient and task irrelevant can still capture our eyes if moving our eyes to those objects has previously produced reward. Here we demonstrate that training such an association between eye movements to an object and delivery of...

The brain contains multiple yet distinct systems involved in reward prediction. To understand the nature of these processes, we recorded single-unit activity from the lateral prefrontal cortex (LPFC) and the striatum in monkeys performing a reward inference task using an asymmetric reward schedule. We found that neurons both in the LPFC and in the striatum predicted reward values for stimuli th...

Brain processing of reward information is essential for complex functions such as learning and motivation. Recent primate electrophysiological studies using concepts from information, economic and learning theories indicate that the midbrain may code two statistical parameters of reward information: a transient reward error prediction signal that varies linearly with reward probability and a su...