Walton, F. , McGlynn, E., Das, R. , Zhong, H., Heidari, H. and Degenaar, P. (2022) Magneto-optogenetic deep-brain multimodal neurostimulation. Advanced Intelligent Systems, 4(3), 2100082. (doi: 10.1002/aisy.202100082)
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Abstract
Electrical neurostimulation has been used successfully as a technique in both research and clinical contexts for over a century. Despite significant progress, inherent problems remain, hence there has been a drive for novel neurostimulation modalities including ultrasonic, magnetic, and optical, which have the potential to be less invasive, have enhanced biointegration, deeper stimulus penetration from the probe, and higher spatiotemporal resolution. Optogenetics—the optical stimulation of genetically photosensitized neurons, enables highly precise genetic targeting of the stimulus. Specifically, it allows for selective optical excitation and inhibition via different wavelengths. As such, optogenetics has become a prominent tool for neuroscience. Herein, the complementarity between different forms of neurostimulation is explored with a focus on cranial magnetic and optogenetic stimulation. Magnetic stimulation is complementary to optogenetics in that it does not require an electrochemical tissue interface like in the case of electrical stimulation. Furthermore, if incorporated onto the same probe as one with light emitters, its stimulation field can be orthogonal to the light emission field—allowing for complementary stimulus fields. Herein, dual optogenetic and magnetic modalities are proposed that can unite to yield a powerful and versatile tool for neural engineering.
| Item Type: | Articles |
|---|---|
| Status: | Published |
| Refereed: | Yes |
| Glasgow Author(s) Enlighten ID: | Walton, Mr Finlay and McGlynn, Eve and Heidari, Professor Hadi and Das, Dr Rupam and Zhong, Mr Hongze |
| Authors: | Walton, F., McGlynn, E., Das, R., Zhong, H., Heidari, H., and Degenaar, P. |
| College/School: | College of Science and Engineering > School of Engineering > Electronics and Nanoscale Engineering |
| Journal Name: | Advanced Intelligent Systems |
| Publisher: | Wiley |
| ISSN: | 2640-4567 |
| ISSN (Online): | 2640-4567 |
| Published Online: | 23 October 2021 |
| Copyright Holders: | Copyright © 2021 The Authors |
| First Published: | First published in Advanced Intelligent Systems 4(3): 2100082 |
| Publisher Policy: | Reproduced under a Creative Commons licence |
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