Bayesian deconvolution for computational cognitive modeling of fMRI data

Bayesian deconvolution for computational cognitive modeling of fMRI data

A central goal of cognitive neuroscience is to make inferences about underlying cognitive processes from observable data. However, current fMRI analysis tools cannot directly estimate latent parameters in computational cognitive models from blood-oxygen-level-dependent (BOLD) signal. Here, we presen...

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Bibliographic Details
Main Authors: Jonathon R. Howlett, Katia M. Harlé, Alan N. Simmons, Charles T. Taylor
Format: Article
Language:English
Published: Elsevier 2025-05-01
Series:NeuroImage
Subjects:
Computational psychiatry
Reward processing
Bayesian inference
Monetary incentive delay
Striatum
Reinforcement learning
Online Access:http://www.sciencedirect.com/science/article/pii/S1053811925002162
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http://www.sciencedirect.com/science/article/pii/S1053811925002162

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