Decoding unstable decision preferences from brain activity
Grant number: DE140100350 | Funding period: 2014 - 2017
We often have to make decisions despite lacking clear preferences. This leaves us susceptible to biases from stimuli and information in our environment. This project investigates how simple, perceptual decisions and financial decisions are influenced by contextual information. The project will combine state-of-the-art neuroimaging technology with machine learning methods to develop a novel decision-decoding toolbox that directly predicts decision outcomes from brain activity. This will allow investigation of how decision encoding in the brain changes under the influence of contextual information, and will provide the basis for developing an advanced model for human decision-making in real-li..View full description
Related publications (22)
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Daniel Bennett, Karen Sasmita, Ryan T Maloney, Carsten Murawski, Stefan Bode
Belief updating entails the incorporation of new information about the environment into internal models of the world. Bayesian inf..
The neural encoding of information prediction errors during non-instrumental information seeking
Maja Brydevall, Daniel Bennett, Carsten Murawski, Stefan Bode
In a dynamic world, accurate beliefs about the environment are vital for survival, and individuals should therefore regularly seek..
Uncovering contextual biases in human decision-making. A multivariate analysis approach for patterns of functional magnetic resonance imaging data and event-related potentials
Decision-making is a fundamental aspect of human cognition and behaviour. Every day, we make a multitude of decisions, ranging fro..