FP6Individual fellowship2007–2009

DCMS · Dynamic connectivity in the Motor System during tasks in health and disease

FP6 — Marie Curie Actions (Human Resources and Mobility)

Duration
2007-04-01 → 2009-03-31
EU contribution
€170,500
Participants
1
Scheme
EIF

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Results in brief

Final Activity Report Summary - DCMS (Dynamic Connectivity in the Motor System during Tasks in Health and Disease)

The topic of our study was interactions between deep and superficial structures of the human brain at rest and during generation of voluntary movement. The deep brain structures involved in movement planning (the basal ganglia or BG) are difficult to study in humans because their electrical activity cannot be recorded non-invasively. We studied a very special group of patients who had electrodes implanted in their brain for treatment of advanced Parkinson's disease (PD). For a short period during the time these patients were hospitalized it was possible to record signals from these electrodes while the patients were fully awake and could be asked to perform a task. In addition to the signals from the electrodes, we recorded signals from superficial brain structures (the cerebral cortex) non-invasively. This was done using magnetoencephalography (MEG), a method involving highly sensitive scanner that can record brain activity by picking up very weak magnetic fields generated by large groups of brain cells. MEG was especially suitable for this project because it can simultaneously look at multiple brain areas without physical contact with the head, thus avoiding risk of infection in patients with fresh surgical wounds. Our project was the first study of this kind in the world and our most important scientific achievement to date is development of the methodology for analysis of the experimental data. This was not a trivial task as metal parts present in the deep brain electrodes created strong interference with the MEG signal hampering conventional analysis approaches. We showed that despite the interference the MEG signal contains physiologically important information that we were interested in. Furthermore, we developed generic methods for extracting this information. This paves the way for a variety of applications both in simultaneous MEG and deep brain recordings and for MEG studies of other groups of patients who have metal implants. We originally planned to record from 12 patients and this goal was fully realised. The data analysis performed until now revealed two novel findings. Firstly, we found that in most patients the structure where the electrodes were placed, the subthalamic nucleus (STN) has special interactions with one or more specific superficial brain areas. The activity in these superficial areas closely follows the STN activity even at rest when no task is performed. The interaction is limited to a specific frequency band (typically between 15 and 35 Hz). What differs between patients and even the two sides of the brain in the same patient is where these areas are located. We are now working on characterisation of these connectivity patterns in all patients and our goal is to find out what factors determine which areas will be driven by STN, whether this phenomenon also occurs in the healthy state or it is part of the disease pathology and whether the patient-specific interaction patterns are related to the specific symptoms each patient is suffering from. Secondly, we looked at the changes in deep and superficial brain activity while the patients performed voluntary movements (key-presses with their fingers). It has been known that the patterns of activity are similar in the part of the cerebral cortex involved in movement planning (the primary motor cortex or M1) and the STN. However, it was unclear whether it means that the same process takes place across both structures or their activities are similar but independent. Our analysis showed that neither possibility is completely true. The two structures seem to be independent to some degree, but also influence each other.

Data: CORDIS, © European Union

Project objective

The voluntary movement planning process involves highly complicated dynamic interactions between several key brain structures most notably the cerebral cortex, basal ganglia and cerebellum. Knowing how these interactions are affected by learning and by neurological diseases can both advance basic brain research and lead to development of new diagnostics and treatment strategies. In the recent years the group of Prof. Peter Brown has studied movement preparation by recording intracranially from patients during and following deep brain stimulation surgery. Relations were found between neural oscillations and the ability to generate or suppress voluntary movements.However, is not clear what the underlying neural mechanisms for these oscillations are and how these mechanisms are affected by learning. The group of Prof. Karl Friston has recently developed a new data analysis approach called Dynamic Causal Modelling (DCM). DCM makes it possible to naturally integrate data recorded with different neuroimaging methods and translate the results into biologically relevant terms. The proposed project is collaboration between the two groups with the purpose of extending the DCM approach to analysis of intracranially recorded data and combining these data with non-invasive magneto- or electro- encephalographic recordings.As a result, the group of Prof. Brown and a network of collaborating labs all over Europe will be provided with a novel and highly promising data analysis tool. On the other hand, the DCM approach will be tested on a system with non-trivial dynamic interactions, which has already been extensively studied on different levels, making it possible to validate the findings. The project will be carried out by a highly qualified postdoctoral fellow undertaking t ransnational mobility from Israel to the UK. This fellow will learn and develop both neurophysiological recording techniques in humans and highly advanced data analysis methods.

Original text from CORDIS.

Participants

  • INSTITUTE OF NEUROLOGY, UNIVERSITY COLLEGE LONDON · LONDONCoordinatorCity levelUnited Kingdom

Links

Data: CORDIS, © European Union