Melodic

ICA-Based Model-Free Analysis of 4D Data

Overview

MELODIC (Multivariate Exploratory Linear Optimized Decomposition into Independent Components) uses PICA (Probabilistic Independent Component Analysis) to decompose 4D data (for example FMRI data) into different interesting spatial and temporal components. It can pick out different activation and artefactual components without any model being specified. Thus the output is a new 4D data set (each volume being a separate spatial component) and a text file of separate time courses (temporal components).

Example MELODIC output
MELODIC slideshow (PDF file, including example descriptions of different artefactual components)

Papers

A paper on MELODIC Probabilistic ICA (PICA) has been published in IEEE TMI. For detail, see a technical report on MELODIC (PS/PDF/HTML).
A paper on Tensor ICA for multi-session and multi-subject analysis has been published in NeuroImage. For detail, see a technical report on TICA (PS/PDF/HTML).
A paper investigating resting-state connectivity using independent component analysis has been published in Philosophical Transactions of the Royal Society. For detail, see a technical report (PDF).

Software

MELODIC is available as part of the FMRIB Software Library.