Fusion of structural and mathematical modelling of the electrode/brain interface during deep brain stimulation in humans
Lead Research Organisation:
Imperial College London
Department Name: Div of Neuroscience & Mental Health
Abstract
Brain cells communicate with one another via electrical signals. When a person has a neurological disorder, an increasingly used treatment called Deep Brain Stimulation involves applying an electrical current, via surgically implanted electrodes, to the patient’s brain. In particular, this technique has been used to treat the symptoms of different movement disorders, for example the tremor associated with Parkinson‘s disease. Although this therapy is widely used, the way in which the injected current affects the electrical activity of the brain is not fully understood. By gaining a better understanding of these mechanisms, we can better target the abnormal neural activity and treat the ailment. We propose the development of a 3-dimensional computational model of the implanted electrode and the surrounding area of the human brain, which will show how the injected current interacts with the surrounding neural tissue. This model will be combined with a mathematical study looking at how different patterns of current change the electrical activity of the brain. Therefore we will better understand how the current is influencing the brain‘s activity, and predict how to use this treatment in patients more accurately.
Technical Summary
Deep brain stimulation (DBS) is an increasingly widely used clinical technique for treating various neurological conditions, in particular movement disorders such as the tremor associated with Parkinson‘s disease. However, the mechanism by which this high frequency stimulation acts on neuronal activity to achieve the desired clinical outcome is unknown, and also disputed within the literature. Increasing our understanding of the precise effects of the injected current on the surrounding neural tissue will allow us to predict stimulation parameters based on theory.
In order to address these questions, we propose a 3-dimensional dynamic model of the stimulating electrode and the tissue in its immediate surroundings. This model will be implemented using the finite element method, and therefore the structural details of the electrode-brain system are persevered. The results from the model will yield an understanding of the current flow in the tissue surrounding the electrode.
A limited attempt has been made in the past to model the static conditions of current flow in 2-dimensional models of injected electrodes. However these models do not include the dynamic features of the stimulation current nor of the electrode-brain interface. This interface is dynamic in time, and will therefore change the nature of the interaction between the stimulating current and the neural activity over time.
We also propose a simultaneous mathematical study of the oscillatory patterns of the injected current. This will allow us to consider the relative effects of these patterns on the de-synchronisation of neuronal activity, in order to understand which current patterns are optimal.
Experimental investigation of the mechanism of DBS would either involve the use of animal models, or require complex clinical trials in human patients. The proposed supplementary technique is to produce computational models of the current flow produced by DBS, and investigate theoretically. We can then validate the results with clinical data, and use the model to gain a fuller understanding of the impact of the injected current on the neuronal activity, finally predicting which stimulation parameters will best achieve the desired therapeutic effect.
The combination of mathematical and structural modelling will allow us to look at the different yet inseparable aspects of the effects of DBS, and therefore better understand the mechanism at work. Given the increase in the use of this technique, our results will shed light on how best to maximize the clinical effect in the future.
In order to address these questions, we propose a 3-dimensional dynamic model of the stimulating electrode and the tissue in its immediate surroundings. This model will be implemented using the finite element method, and therefore the structural details of the electrode-brain system are persevered. The results from the model will yield an understanding of the current flow in the tissue surrounding the electrode.
A limited attempt has been made in the past to model the static conditions of current flow in 2-dimensional models of injected electrodes. However these models do not include the dynamic features of the stimulation current nor of the electrode-brain interface. This interface is dynamic in time, and will therefore change the nature of the interaction between the stimulating current and the neural activity over time.
We also propose a simultaneous mathematical study of the oscillatory patterns of the injected current. This will allow us to consider the relative effects of these patterns on the de-synchronisation of neuronal activity, in order to understand which current patterns are optimal.
Experimental investigation of the mechanism of DBS would either involve the use of animal models, or require complex clinical trials in human patients. The proposed supplementary technique is to produce computational models of the current flow produced by DBS, and investigate theoretically. We can then validate the results with clinical data, and use the model to gain a fuller understanding of the impact of the injected current on the neuronal activity, finally predicting which stimulation parameters will best achieve the desired therapeutic effect.
The combination of mathematical and structural modelling will allow us to look at the different yet inseparable aspects of the effects of DBS, and therefore better understand the mechanism at work. Given the increase in the use of this technique, our results will shed light on how best to maximize the clinical effect in the future.