Comparison of meta-analysis approaches for neuroimaging studies of reward processing: A case study
Source
Proceedings of the International Joint Conference on Neural Networks
Date Issued
2015-09-28
Author(s)
Chawla, Manisha
Abstract
Neural correlates corresponding to a specific cognitive tasks has been made possible with techniques like functional magnetic resonance imaging. The increasing number of neuroimaging studies has made meta-analysis methods popular for useful inferencing across multiple studies. The easy availability of neuroinformatic tools has also resulted in increasing the number of meta-analysis studies. We compare different meta-analysis approaches using hand-curated database (Brainmap) and automated database (neurosynth) using the case study of reward-related studies. We combine meta-analysis with atlas-based approaches to quantitatively compare different meta-analysis approaches. Based on our results, we propose further integration of different meta-analytic approaches with automated data mining methods for neuroimaging.
Subjects
Activation likelihood Estimate | decision making | functional MRI | GingerALE | Meta-Analysis | Multi-level kernel Density Analysis (MKDA) | NeuroSynth | re-ward
