Chawla, ManishaManishaChawlaMiyapuram, Krishna P.Krishna P.Miyapuram2025-08-302025-08-302015-09-28[9781479919604]10.1109/IJCNN.2015.72804342-s2.0-84951117689https://d8.irins.org/handle/IITG2025/22022Neural 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.falseActivation likelihood Estimate | decision making | functional MRI | GingerALE | Meta-Analysis | Multi-level kernel Density Analysis (MKDA) | NeuroSynth | re-wardConference Paper28 September 201537280434cpConference Proceeding1