The paper describes a non-commercial software system for analyzing functional magnetic image processing and statistical inference algorithms, and was developed by the Max Planck Institute of Cognitive Neuroscience in Leipzig, Germany. "Lipsia" has been in heavy use for the past 2-3 years. Thus, I think that the high number of citations results from the heavy usage of the system.

It does indeed describe a new methodology that is useful to others. The analysis of fMRI data is a complex and computationally expensive task. Usually, in the course of an fMRI experiment, about 16 volunteers are asked to participate in the study. For each test subject, a large data set is recorded comprising about 200 MBytes or more of data. Using "Lipsia" the processing chain of an fMRI data set from the raw data to the statistical parametric map takes less than 10 minutes on a standard Linux workstation. Thus, the data evaluation of the entire data generated within an fMRI experiment involving a group of 16 test subjects can be completed in less than three hours. For the sake of fairness, I should hasten to add that other very good software systems for the analysis of fMRI data exist as well. However, ours is probably one of the fastest. In addition to an efficient software implementation, "Lipsia" offers a number of algorithmic novelties in particular with respect to automatic image segmentation, geometric processing and data visualization.

The paper contributes to the field of "computational neuroscience". Methodological advances in this fast growing field are urgently needed by neuroscientists around the world as the imaging data that are recorded are difficult to process and even harder to interpret.

My co-authors and I are interested in developing new methods in computational neuroscience. The "Lipsia" system is a first step in that direction.

PD Dr. Gabriele Lohmann
Max Planck Institute of Cognitive Neuroscience
Leipzig, Germany