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Animals have sophisticated mechanisms for coping with danger. Freezing is a unique state that, upon threat detection, allows evidence to be gathered, response possibilities to be previsioned and …

Despite decades of experimental and clinical practice, the neuropsychological mechanisms underlying neurofeedback (NF) training remain obscure. NF is a unique form of reinforcement learning (RL) task, during which …

Understanding the complexities of behavior is necessary to interpret neurophysiological data and establish animal models of neuropsychiatric disease. This understanding requires knowledge of the underlying information-processing structure …

Behavioral control is not unitary. It comprises parallel systems, model based and model free, that respectively generate flexible and habitual behaviors. Model-based decisions use predictions of the …

Animal behavior provides context for understanding disease models and physiology. However, that behavior is often characterized subjectively, creating opportunity for misinterpretation and misunderstanding. For example, spatial alternation tasks …

Contemporary reinforcement learning (RL) theory suggests that potential choices can be evaluated by strategies that may or may not be sensitive to the computational structure of tasks. A …

Bayesian decision theory provides a simple formal elucidation of some of the ways that representation and representational abstraction are involved with, and exploit, both prediction and its rather …

Naturalistic observations show that decisions to avoid or escape predators occur at different spatiotemporal scales and that they are supported by different computations and neural circuits. At their …

isual 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 …

Successful navigation can require realizing the current path choice was a mistake and the best strategy is to retreat along the recent path: 'back-track'. Despite the wealth …

Humans and other animals are able to discover underlying statistical structure in their environments and exploit it to achieve efficient and effective performance. However, such structure is often …

Humans build models of their environments and act according to what they have learnt. In simple experimental environments, such model-based behaviour is often well accounted for as …

In active avoidance tasks, subjects have to learn to execute particular actions in order to avoid an aversive stimulus, such as a shock. Such paradigms pose a number …

Serotonin has widespread, but computationally obscure, modulatory effects on learning and cognition. Here, we studied the impact of optogenetic stimulation of dorsal raphe serotonin neurons in mice performing …

Modern decision neuroscience offers a powerful and broad account of human behaviour using computational techniques that link psychological and neuroscientific approaches to the ways that individuals can generate …

Ideal decision-makers should constantly assess all sources of information about opportunities and threats, and be able to redetermine their choices promptly in the face of change. However …