Journal
BAYESIAN ANALYSIS
Volume 9, Issue 3, Pages 699-731Publisher
INT SOC BAYESIAN ANALYSIS
DOI: 10.1214/14-BA873
Keywords
Bayesian variable selection; fMRI; Ising distribution; Markov chain Monte Carlo
Funding
- National Science Foundation
- National Institutes for Health
- CRiSM
- NATIONAL INSTITUTE OF BIOMEDICAL IMAGING AND BIOENGINEERING [P41EB015909, R01EB012547] Funding Source: NIH RePORTER
- NATIONAL INSTITUTE OF NEUROLOGICAL DISORDERS AND STROKE [R01NS060910] Funding Source: NIH RePORTER
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A common objective of fMRI (functional magnetic resonance imaging) studies is to determine subject-specific areas of increased blood oxygenation level dependent (BOLD) signal contrast in response to a stimulus or task, and hence to infer regional neuronal activity. We posit and investigate a Bayesian approach that incorporates spatial and temporal dependence and allows for the task-related change in the BOLD signal to change dynamically over the scanning session. In this way, our model accounts for potential learning effects in addition to other mechanisms of temporal drift in task-related signals. We study the properties of the model through its performance on simulated and real data sets.
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