This article presents a comprehensive survey of research concerning interactions between
associative learning and attention in humans. Four main findings are described. First …

Phasic activity of midbrain dopamine neurons is currently thought to encapsulate the
prediction-error signal described in model-free reinforcement learning algorithm. This phasic …

For centuries, human self-control has fascinated scientists and nonscientists alike. Current
theories often attribute it to an executive control system. But even though executive control …

Dopamine neurons are proposed to signal the reward prediction error in model-free
reinforcement learning algorithms. This term represents the unpredicted or 'excess' value of …

Besides visual salience and observers' current intention, prior learning experience may
influence deployment of visual attention. Associative learning models postulate that …

Prior research has suggested that attention is determined by exploiting what is known about
the most valid predictors of outcomes and exploring those stimuli that are associated with …

Highlights•Attention is powerfully affected by our prior experiences.•Reward-related stimuli
continue to capture attention when no longer task-relevant.•Stimuli that previously signaled …

Attentional theories of associative learning and categorization propose that learning about
the predictiveness of a stimulus influences the amount of attention that is paid to that …

Visual selective attention acts as a filter on perceptual information, facilitating learning and
inference about important events in an agent's environment. A role for visual attention in …

It has been suggested that the basal forebrain (BF) exerts strong influences on the formation
of memory and behavior. However, what information is used for the memory-behavior …