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Image analysis and statistics in neuroeconomics

Neuroeconomics explores the relationship between decision making and brain activity, with the aim of discovering which neural processes that governs "economic decision-making". Methodologically brain imaging is combined with economic experiments. Most studies use functional magnetic resonance imaging (fMRI) to study brain activation. Economic-decision making defined in a broad sense include behaviours related to empathy, risk taking, fairness, reciprocity and trust. The project comprises a series of studies in this area related to for instance decisions on buying, priority setting in health care, and the functioning of the reward system in the brain.

The first study focuses on comparing the neural processes related to hypothetical and real purchase decisions. The fMRI-paradigm builds on a study by B. Knutson et al (Neuron 2007) investigating the neural correlates of purchase decisions. There is a substantial literature in economics on hypothetical willingness to pay, where the willingness to pay often is overestimated. However, the neural mechanisms behind these overestimations are unclear.

Within this project we will also study the methods used to analyse fMRI data, specifically the statistical analysis. The fMRI data contains much noise, such that sophisticated image processing and statistical tools is required for robust detection of activated regions in the brain. Hence, we will review the performance of commonly used software for fMRI data analysis and we aim to improve and develop the methods of analysis.

 
Example showing activated regions of the brain, Eklund et al. "A
GPU Accelerated Interactive Interface for Exploratory Functional
Connectivity Analysis of fMRI Data",Proceedings from IEEE
International Conference on Image Processing (ICIP); Brussels,
Belgium.


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