The most influential account of phasic dopamine holds that it reports reward prediction
errors (RPEs). The RPE-based interpretation of dopamine signaling is, in its original form …

Synaptic plasticity, the activity-dependent change in neuronal connection strength, has long
been considered an important component of learning and memory. Computational and …

Deep reinforcement learning (RL) methods have driven impressive advances in artificial
intelligence in recent years, exceeding human performance in domains ranging from Atari to …

Motivational processes underlie behaviors that enrich the human experience, and
impairments in motivation are commonly observed in psychiatric illness. While motivated …

Dopamine is a critical modulator of both learning and motivation. This presents a problem:
how can target cells know whether increased dopamine is a signal to learn or to move? It is …

The striatum is essential for learning which actions lead to reward and for implementing
those actions. Decades of experimental and theoretical work have led to several influential …

Dopamine (DA) is a key neurotransmitter involved in multiple physiological functions
including motor control, modulation of affective and emotional states, reward mechanisms …

Cognitive control, the ability to orchestrate behavior in accord with our goals, depends on
the prefrontal cortex. These cognitive functions are heavily influenced by the …

Over the past 20 years, neuroscience research on reward-based learning has converged on
a canonical model, under which the neurotransmitter dopamine 'stamps in'associations …

Deep learning networks have been trained to recognize speech, caption photographs, and
translate text between languages at high levels of performance. Although applications of …