Magn Reson Mater Phy (2010) 23:275–277 DOI 10.1007/s10334-010-0231-x EDITORIAL In vivo MR imaging of brain networks: illusion or revolution? Ewald Moser · Jean-Philippe Ranjeva Published online: 5 December 2010 © ESMRMB 2010 Substantial achievements have been made in brain research and the development of non-invasive brain mapping tools such as high-field functional MRI, positron-emission tomography (PET), and the expansion of classical electro- physiological methods like EEG and MEG, as well as the successful combination of such different methods as fMRI & EEG, and MRI & PET. These neuroimaging methods may help to provide a better understanding of the connectivity of large-scale brain networks, opening new insights into how the brain segregates and integrates information. Character- izing basal brain connectivity is a crucial issue, which may lead to a better understanding of brain functioning, and may also allow us to understand, anticipate, and monitor recov- ery of the clinical consequences of neurological diseases. Nevertheless, we should remind ourselves that we are still looking at the human brain from afar, in the same way an astronaut might view our planet. We observe only the hills or mountain peaks above the clouds (functional connectivity) or major motorways crisscrossing a country (fiber tracking, structural connectivity). Bridging the gap between this coarse global view and local neuronal activity remains challenging. In this special issue, we have compiled a number of stud- ies, mainly performed in Europe, selected to stimulate efforts in this field. Four reviews and nine research papers are col- E. Moser (B ) MR Center of Excellence, Division of MR-Physics, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, 1090 Vienna, Austria e-mail: ewald.moser@meduniwien.ac.at J.-P. Ranjeva (B ) Centre de Résonance Magnétique Biologique et Médicale UMR CNRS 6612, Université de la Méditerranée, Faculté de Médecine, 27 Boulevard Jean Moulin, 13385 Marseille cedex 05, France e-mail: jp.ranjeva@univmed.fr lated, covering various aspects of functional and structural connectivity assessed with MR-based methods. The first paper is a short historical overview of resting-state fMRI works presented by Mark Lowe, one of the pioneers in the field [1]. After the seminal paper of Bharat Biswal et al. in 1995 [2], the field of so-called ‘resting-state fMRI’ remained controversial until the early 2000’s, when Raichle’s group and others published several influential articles found- ing the concept of a ‘default mode’ of brain function [3–6]. Other brain networks were also reported, the current total being about 12 [7], a number which seems likely to increase steadily with increasing sensitivity and specificity of the mea- suring methods. The second paper is a provocative critical review of post-processing methods, which are used to extract relevant (and non-relevant) information from rs-fMRI data [8]. Margulies and colleagues focus on six prominent cate- gories of resting-state data analysis. The coexistence of so many different tools may reflect both limited data quality and a lack of deeper understanding of underlying models of brain function. The main criticism of rs-fMRI is the lack of control of the actual brain status during the so-called ‘rest- ing- state’. One possible solution to overcome this critical problem may rely on the use of simultaneous recordings of brain electrical activity during fMRI. A detailed review of the present applications and perspectives of this method are provided by Rosenkranz and Lemieux [9]. From a method- ological point of view, as we are basically looking at ‘brain noise’, increasing the field strength from 1.5 to 3 T and higher, combined with the use of multi-array coils, greatly improves sensitivity. Although this has led to the detection of consis- tent and reliable brain networks across healthy subjects (e.g. [7, 10]), there are still issues on how to separate physiologi- cal noise from relevant information without introducing other artefacts [11, 12]. There is also speculation that physiologi- cal fluctuations are a substantial contributor to resting-state 123