DecisionMaking

Temporal characteristics of the influence of punishment on perceptual decision making in the human brain

Perceptual decision making is the process by which information from sensory systems is combined and used to influence our behavior. In addition to the sensory input, this process can be affected by other factors, such as reward and punishment for …

How expert advice influences decision making

People often use expert advice when making decisions in our society, but how we are influenced by this advice has yet to be understood. To address this, using functional magnetic resonance imaging, we provided expert and novice advice to participants …

Changes in neural connectivity underlie decision threshold modulation for reward maximization

Using neuroimaging in combination with computational modeling, this study shows that decision threshold modulation for reward maximization is accompanied by a change in effective connectivity within corticostriatal and cerebellar-striatal brain …

The neural basis of following advice

Learning by following explicit advice is fundamental for human cultural evolution, yet the neurobiology of adaptive social learning is largely unknown. Here, we used simulations to analyze the adaptive value of social learning mechanisms, …

How the brain integrates costs and benefits during decision making

When we make decisions, the benefits of an option often need to be weighed against accompanying costs. Little is known, however, about the neural systems underlying such cost-benefit computations. Using functional magnetic resonance imaging and …

Differential influence of levodopa on reward-based learning in Parkinson's disease

The mesocorticolimbic dopamine (DA) system linking the dopaminergic midbrain to the prefrontal cortex and subcortical striatum has been shown to be sensitive to reinforcement in animals and humans. Within this system, coexistent segregated …

Temporal dynamics of prediction error processing during reward-based decision making

Adaptive decision making depends on the accurate representation of rewards associated with potential choices. These representations can be acquired with reinforcement learning (RL) mechanisms, which use the prediction error (PE, the difference …

A mechanistic account of value computation in the human brain

To make decisions based on the value of different options, we often have to combine different sources of probabilistic evidence. For example, when shopping for strawberries on a fruit stand, one uses their color and size to infer-with some …

Neural processing of risk

In our everyday life, we often have to make decisions with risky consequences, such as choosing a restaurant for dinner or choosing a form of retirement saving. To date, however, little is known about how the brain processes risk. Recent …

Neural foundations of risk-return trade-off in investment decisions

Many decisions people make can be described as decisions under risk. Understanding the mechanisms that drive these decisions is an important goal in decision neuroscience. Two competing classes of risky decision making models have been proposed to …