Browsing by Author "Nieminen, Jaakko, Dr., Aalto University, Finland"

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Improving the reliability of transcranial magnetic stimulation targeting
(2022) Nieminen, Aino
School of Science | Doctoral dissertation (article-based)
Neurons in the human brain can be locally activated with transcranial magnetic stimulation (TMS). TMS is applied to study brain dynamics, to map cortical functions, and to treat neurological and psychiatric disorders. In TMS, an electric field is induced in the brain. The location of the electric field maximum is targeted with a neuronavigation system that shows the coil placement and the peak electric field on a brain image. To find a suitable stimulation location and orientation, the TMS operator gives pulses with varying stimulus parameters and observes the responses, such as muscle twitches upon stimulating the motor cortex. This mapping procedure is, however, operator-dependent and slow. In addition, TMS navigation systems are not error-free. Inaccuracies and variation in TMS methods can cause varying results that may be difficult to interpret and compare. This Thesis aimed at increasing the reliability of TMS targeting by developing automated targeting methods. Publication 1 presents an algorithm to automatically identify the best stimulation location and orientation in the motor cortex, i.e., the stimulus parameters that maximize the motor responses measured with electromyography. In Publication 2, a similar closed-loop approach was applied to search for the optimal stimulus orientation but now with electroencephalography as a feedback signal. Automated procedures require a way for non-manual adjustment of TMS parameters. In Publications 1 and 2, the stimulus location or orientation was electronically controlled with a 2-coil multi-locus TMS, which concurrently drives two overlapping coils. By adding more coils into the system, one can extend the electronically adjustable parameter space. This was realized in Publication 3 with a 5-coil device, which enabled a demonstration of an automated mapping of the hand motor area with predefined stimulus locations and orientations. Publication 4 aimed at analyzing errors related to TMS navigation systems. The simulations showed that the magnitudes of the errors in navigation depend on the methods employed. The operator can ensure reliable TMS navigation by performing related preparations carefully and by selecting the most accurate methods for navigation. The automated procedures developed in this Thesis allow operating TMS in a fast and user-independent way, increasing the reliability of TMS. Moreover, the closed-loop algorithms pave the way for adaptive TMS treatments, i.e., the real-time adjustment of the TMS delivery with observed effects so that the clinical outcome is maximized. This, together with accurate navigation, is expected to increase the efficacy of TMS therapy, bringing help to patients suffering from brain dysfunctions.