James Rowe and Hartwig Siebner have the honour of contributing with a review on movement disorders and the brain-mind interaction in general. James is a former DRCMR employee, now heading a research group at Cambridge University, England, whereas Hartwig is professor and head of research at the DRCMR.

The review is entitled The motor system and its disorders and has the following highlights:

• Establishing organisational principles of the motor system.
• Motor learning, inhibition, mirror neuron systems and action selection.
• Understanding human movement disorders, stroke and plasticity.
• Innovations in integrated multimodal imaging and new brain-behaviour models.

Currrently, an ambitious research project, ContAct, addressing the mind&body interaction is being conducted at the DRCMR and associated sites. The study became possible after a major Lundbeck grant was awarded to Hartwig Siebner.

The NeuroImage special issue edited by Arthur Toga, Richard Frackowiak and John Mazziotta contains a range of articles by high-profiled researchers on the state and future of neuroimaging.

Jan receives the prize together with Klaes Golman for their seminal work on the hyperpolarization technique, which in certain situations can improve the MR signal by a factor of 10000. The technique is uses at the DRCMR and elsewhere, e.g. for studies of cancer development and treatment response.

Further information:

• Homepage of Jan Henrik Ardenkjaer-Larsen who is employed by GE Healthcare, and is also heading the hyperpolarization lab in the Biomedical Engineering group at DTU
• Details about the event and the reasons for awarding Jan
• The DRCMR hyperpolarization group
• Introduction of the prize by Nobel laureate Richard Ernst
• Introduction to the hyperpolarization technique in Danish

Congratulations to Klaes and Jan!

The work was performed in collaboration between DTU Informatics (Lyngby, DK), the Danish Research Centre for Magnetic Resonance (Hvidovre, DK), and the Center for Functionally Integrative Neuroscience (Aarhus, DK).

Supervisor: Lars Kai Hansen, Technical University of Denmark

Co-supervisors:

• Kristoffer H. Madsen, Danish Research Centre for Magnetic Resonace,Copenhagen University Hospital Hvidovre.
• Torben E. Lund, Center of Functionally Integrative Neuroscience, Aarhus University Hospital

Abstract: This dissertation presents research results regarding mathematicalmodeling in the context of the analysis of functional neuroimages.Specifically, the research focuses on pattern-based analysis methodsthat recently have become popular within the neuroimaging community.Such methods attempt to predict or decode experimentally definedcognitive states based on brain scans. The topics covered in thedissertation are divided into two broad parts: The first partinvestigates the relative importance of model selection on the brainpatterns extracted form analysis models. Typical neuroimaging datasets are characterized by relatively few data observations in a highdimensional space. The process of building models in such data setsoften requires strong regularization. Often, the degree of modelregularization is chosen in order to maximize prediction accuracy. Wefocus on the relative influence of model regularization parameterchoices on the model generalization, the reliability of the spatialbrain patterns extracted from the analysis model, and the ability ofthe resulting model to identify relevant brain networks defining theunderlying neural encoding of the experiment. We show that known partsof brain networks can be overlooked in pursuing maximization ofprediction accuracy. This supports the view that the quality ofspatial patterns extracted from models cannot be assessed purely byfocusing on prediction accuracy. Our results instead suggest thatmodel regularization parameters must be carefully selected, so thatthe model and its visualization enhance our ability to interpret thebrain.The second part concerns interpretation of nonlinear models andprocedures for extraction of 'brain maps' from nonlinear kernelmodels. We assess the performance of the sensitivity map as means forextracting a global summary map from a trained model. Such summarymaps provides the investigator with an overview of brain locations ofimportance to the model's predictions. The sensitivity map proves as aversatile technique for model visualization. Furthermore, we perform apreliminary investigation of the use of pre-image estimation forlocalized interpretation of nonlinear models. In the context of imagedenoising the pre-image analysis proves to enhance the reliability ofbrain patterns extracted from multivariate models of the neuroimaging data. 

Axel then moved on to Brown University (Providence, RI) to join the lab of Luiz Pessoa (http://emotioncognition.org) in order to deepen his knowledge on fMRI, in particular on advanced analysis methods such as ROC and logistic regression analysis of fMRI data.

After that time, he joined the MPI for Biological Cybernetics (Tübingen, Germany), initially as PostDoc, and later as Project Group leader for multimodal TMS. After establishing a TMS lab (including the online combinations of TMS with fMRI and EEG, respectively), he conducted research on visual perception and, via collaborations, on sensorimotor integration.

Axel now joins the DRCMR as Senior Researcher and the Biomedical Engineering Section at DTU Elektro as an Associate Professor, allowing him to pursue both his methodological and neuroscientific interests. Continuing his research on sensorimotor integration, he will closely collaborate with Hartwig Siebner's ContAct group. He is looking forward to the possibility to further advance his methodological work on multimodal brain stimulation and electric field calculations at DTU Elektro.

Contact information:

Dr. Axel Thielscher

Danish Research Centre for Magnetic Resonance

Dept. 340, Hvidovre Hospital

DK-2650 Hvidovre

or

Biomedical Engineering Group

DTU Elektro, bldg 349

Ørsteds Plads

DK-2800 Kgs. Lyngby

The course is held by University of Copenhagen and runs between September 17th and 21st, 2012. For more information, see http://phdkursus.sund.ku.dk/frontPlanner/DetailKursus.aspx?id=95959