Translational pipelines for closed-loop neuromodulation
<p>Closed-loop neuromodulation systems have shown significant potential for addressing unmet needs in the treatment of disorders of the central nervous system, yet progress towards clinical adoption has been slow. Advanced technological developments often stall in the preclinical stage by fail...
| Հիմնական հեղինակ: | |
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| Այլ հեղինակներ: | |
| Ձևաչափ: | Թեզիս |
| Լեզու: | English |
| Հրապարակվել է: |
2024
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| Խորագրեր: |
| _version_ | 1826313322478174208 |
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| author | Toth, R |
| author2 | Sharott, A |
| author_facet | Sharott, A Toth, R |
| author_sort | Toth, R |
| collection | OXFORD |
| description | <p>Closed-loop neuromodulation systems have shown significant potential for addressing unmet needs in the treatment of disorders of the central nervous system, yet progress towards clinical adoption has been slow. Advanced technological developments often stall in the preclinical stage by failing to account for the constraints of implantable medical devices, and due to the lack of research platforms with a translational focus. This thesis presents the development of three clinically relevant research systems focusing on refinements of deep brain stimulation therapies.</p>
<p>First, we introduce a system for synchronising implanted and external stimulation devices, allowing for research into multi-site stimulation paradigms, cross-region neural plasticity, and questions of phase coupling. The proposed design aims to sidestep the limited communication capabilities of existing commercial implant systems in providing a stimulation state readout without reliance on telemetry, creating a cross-platform research tool.</p>
<p>Next, we present work on the Picostim-DyNeuMo adaptive neuromodulation platform, focusing on expanding device capabilities from activity and circadian adaptation to bioelectric marker--based responsive stimulation. Here, we introduce a computationally optimised implementation of a popular band power--estimation algorithm suitable for deployment in the DyNeuMo system. The new algorithmic capability was externally validated to establish neural state classification performance in two widely-researched use cases: Parkinsonian beta bursts and seizures. For in vivo validation, a pilot experiment is presented demonstrating responsive neurostimulation to cortical alpha-band activity in a non-human primate model for the modulation of attention state.</p>
<p>Finally, we turn our focus to the validation of a recently developed method to provide computationally efficient real-time phase estimation. Following theoretical analysis, the method is integrated into the commonly used Intan electrophysiological recording platform, creating a novel closed-loop optogenetics research platform. The performance of the research system is characterised through a pilot experiment, targeting the modulation of cortical theta-band activity in a transgenic mouse model.</p> |
| first_indexed | 2024-09-25T04:12:49Z |
| format | Thesis |
| id | oxford-uuid:d54cde9a-8272-4fb4-970d-2ea40bfbbeea |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-09-25T04:12:49Z |
| publishDate | 2024 |
| record_format | dspace |
| spelling | oxford-uuid:d54cde9a-8272-4fb4-970d-2ea40bfbbeea2024-06-25T09:47:58ZTranslational pipelines for closed-loop neuromodulationThesishttp://purl.org/coar/resource_type/c_db06uuid:d54cde9a-8272-4fb4-970d-2ea40bfbbeeaNeural engineeringBrain stimulationBrain-computer interfacesEnglishHyrax Deposit2024Toth, RSharott, ADenison, T<p>Closed-loop neuromodulation systems have shown significant potential for addressing unmet needs in the treatment of disorders of the central nervous system, yet progress towards clinical adoption has been slow. Advanced technological developments often stall in the preclinical stage by failing to account for the constraints of implantable medical devices, and due to the lack of research platforms with a translational focus. This thesis presents the development of three clinically relevant research systems focusing on refinements of deep brain stimulation therapies.</p> <p>First, we introduce a system for synchronising implanted and external stimulation devices, allowing for research into multi-site stimulation paradigms, cross-region neural plasticity, and questions of phase coupling. The proposed design aims to sidestep the limited communication capabilities of existing commercial implant systems in providing a stimulation state readout without reliance on telemetry, creating a cross-platform research tool.</p> <p>Next, we present work on the Picostim-DyNeuMo adaptive neuromodulation platform, focusing on expanding device capabilities from activity and circadian adaptation to bioelectric marker--based responsive stimulation. Here, we introduce a computationally optimised implementation of a popular band power--estimation algorithm suitable for deployment in the DyNeuMo system. The new algorithmic capability was externally validated to establish neural state classification performance in two widely-researched use cases: Parkinsonian beta bursts and seizures. For in vivo validation, a pilot experiment is presented demonstrating responsive neurostimulation to cortical alpha-band activity in a non-human primate model for the modulation of attention state.</p> <p>Finally, we turn our focus to the validation of a recently developed method to provide computationally efficient real-time phase estimation. Following theoretical analysis, the method is integrated into the commonly used Intan electrophysiological recording platform, creating a novel closed-loop optogenetics research platform. The performance of the research system is characterised through a pilot experiment, targeting the modulation of cortical theta-band activity in a transgenic mouse model.</p> |
| spellingShingle | Neural engineering Brain stimulation Brain-computer interfaces Toth, R Translational pipelines for closed-loop neuromodulation |
| title | Translational pipelines for closed-loop neuromodulation |
| title_full | Translational pipelines for closed-loop neuromodulation |
| title_fullStr | Translational pipelines for closed-loop neuromodulation |
| title_full_unstemmed | Translational pipelines for closed-loop neuromodulation |
| title_short | Translational pipelines for closed-loop neuromodulation |
| title_sort | translational pipelines for closed loop neuromodulation |
| topic | Neural engineering Brain stimulation Brain-computer interfaces |
| work_keys_str_mv | AT tothr translationalpipelinesforclosedloopneuromodulation |