Abstract
Transcranial brain stimulation (TBS) uses electrodes or magnetic coils to create an electric field in the brain that alters its activity, without the need of surgery and with minimal side effects. These methods are widely used in neuroscience research and are steadily gaining importance in the treatment of neurological and psychiatric disorders. However, the electric fields created by TBS methods in the brain are affected by the individual head anatomy in complex ways. This causes an interindividual variability of the applied stimulation dose that is likely a major factor of the variable TBS effects observed in practice in research and clinical applications.
As directly measuring these electric fields is a very difficult endeavor that is only feasible in animal models and selected patients, involving the surgical implantation of electrodes, researchers have turned to computational methods for better understanding how individual anatomy shapes the electric fields caused by TBS. These simulations typically use individualized head models, created by segmenting magnetic resonance images into major tissues such as brain gray and white matter, cerebrospinal fluid, skull, and skin. The first part of the thesis compares electric fields obtained in simulations with measurements. It will be demonstrated that these models provide useful electric field estimates, but that there are severe limitations in using data from intracranial measurement for validating models.
Because of the complex electric field patterns created by TBS in the brain, it is often challenging to know how to best apply TBS interventions. The second part of the thesis introduces computational algorithms to find optimal ways to create electric fields that are focused on specific brain regions. These algorithms are then used to map which brain regions are suited for focal transcranial electric stimulation.
The final part of the thesis described our efforts to develop free and open source software to make computational modelling and optimization of TBS available for researchers across the world. The software will enable researchers to uncover new aspects of human brain function and possibly lead to novel treatments for neurological and psychiatric disorders.
As directly measuring these electric fields is a very difficult endeavor that is only feasible in animal models and selected patients, involving the surgical implantation of electrodes, researchers have turned to computational methods for better understanding how individual anatomy shapes the electric fields caused by TBS. These simulations typically use individualized head models, created by segmenting magnetic resonance images into major tissues such as brain gray and white matter, cerebrospinal fluid, skull, and skin. The first part of the thesis compares electric fields obtained in simulations with measurements. It will be demonstrated that these models provide useful electric field estimates, but that there are severe limitations in using data from intracranial measurement for validating models.
Because of the complex electric field patterns created by TBS in the brain, it is often challenging to know how to best apply TBS interventions. The second part of the thesis introduces computational algorithms to find optimal ways to create electric fields that are focused on specific brain regions. These algorithms are then used to map which brain regions are suited for focal transcranial electric stimulation.
The final part of the thesis described our efforts to develop free and open source software to make computational modelling and optimization of TBS available for researchers across the world. The software will enable researchers to uncover new aspects of human brain function and possibly lead to novel treatments for neurological and psychiatric disorders.
| Originalsprog | Engelsk |
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| Forlag | Department of Health Technology, Technical University of Denmark |
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| Status | Udgivet - 2020 |