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Minimally invasive neuromodulation using mechanically-sensitive ion channels and magnetically-actuated nanotransducers

Author(s)
Malkin, Elian
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Advisor
Anikeeva, Polina
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Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) Copyright retained by author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/
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Abstract
Traditional methods of neuronal activity modulation, like pharmacological interventions and noninvasive techniques such as transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS) have limitations in specificity and penetration depth. Deep brain stimulation (DBS), while effective, is invasive and carries surgical risks. This thesis advances the approach of utilizing magnetic nanoparticles as mechanical force transducers to achieve minimally invasive, wireless neuromodulation using magnetic fields as the stimulation modality. By leveraging magnetic fields and mechanically sensitive ion channels, this method aims to provide precise neuronal activation of deep neural circuits without surgery. We describe the molecular biology behind conferring mechanosensation to neurons, the design of a membrane targeting mechanism via SNAPtags expressed on neuronal membranes, and the observed neuromodulatory effects for a gamut of mechanoreceptors and stimulation conditions. Calcium imaging results demonstrate that this method of nanotransducer targeting can elicit neuronal responses at 40mT even via endogenous ion channels, and that greater amplitudes of response can be achieved through mechanosensitive ion channel expression and increased stimulation strength. We also develop data analysis code that is highly automated and employs advanced curve-fitting techniques to isolate the calcium imaging signal from background noise and fluorescence decay. The findings described in this thesis suggest that minimally-invasive mechanical neuromodulation can offer a safe and precise alternative to DBS for both clinical and research applications.
Date issued
2024-05
URI
https://hdl.handle.net/1721.1/157016
Department
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
Publisher
Massachusetts Institute of Technology

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