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Spatially specific, closed-loop infrared thalamocortical deep brain stimulation
Deep brain stimulation (DBS) is a powerful tool for the treatment of circuitopathy-related neurological and psychiatric diseases and disorders such as Parkinson’s disease and obsessive-compulsive disorder, as well as a critical research tool for perturbing neural circuits and exploring neuroprosthes...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10614743/ https://www.ncbi.nlm.nih.gov/pubmed/37904955 http://dx.doi.org/10.1101/2023.10.04.560859 |
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author | Coventry, Brandon S Lawlor, Georgia L Bagnati, Christina B Krogmeier, Claudia Bartlett, Edward L |
author_facet | Coventry, Brandon S Lawlor, Georgia L Bagnati, Christina B Krogmeier, Claudia Bartlett, Edward L |
author_sort | Coventry, Brandon S |
collection | PubMed |
description | Deep brain stimulation (DBS) is a powerful tool for the treatment of circuitopathy-related neurological and psychiatric diseases and disorders such as Parkinson’s disease and obsessive-compulsive disorder, as well as a critical research tool for perturbing neural circuits and exploring neuroprostheses. Electrically-mediated DBS, however, is limited by the spread of stimulus currents into tissue unrelated to disease course and treatment, potentially causing undesirable patient side effects. In this work, we utilize infrared neural stimulation (INS), an optical neuromodulation technique that uses near to mid-infrared light to drive graded excitatory and inhibitory responses in nerves and neurons, to facilitate an optical and spatially constrained DBS paradigm. INS has been shown to provide spatially constrained responses in cortical neurons and, unlike other optical techniques, does not require genetic modification of the neural target. We show that INS produces graded, biophysically relevant single-unit responses with robust information transfer in thalamocortical circuits. Importantly, we show that cortical spread of activation from thalamic INS produces more spatially constrained response profiles than conventional electrical stimulation. Owing to observed spatial precision of INS, we used deep reinforcement learning for closed-loop control of thalamocortical circuits, creating real-time representations of stimulus-response dynamics while driving cortical neurons to precise firing patterns. Our data suggest that INS can serve as a targeted and dynamic stimulation paradigm for both open and closed-loop DBS. |
format | Online Article Text |
id | pubmed-10614743 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Cold Spring Harbor Laboratory |
record_format | MEDLINE/PubMed |
spelling | pubmed-106147432023-10-31 Spatially specific, closed-loop infrared thalamocortical deep brain stimulation Coventry, Brandon S Lawlor, Georgia L Bagnati, Christina B Krogmeier, Claudia Bartlett, Edward L bioRxiv Article Deep brain stimulation (DBS) is a powerful tool for the treatment of circuitopathy-related neurological and psychiatric diseases and disorders such as Parkinson’s disease and obsessive-compulsive disorder, as well as a critical research tool for perturbing neural circuits and exploring neuroprostheses. Electrically-mediated DBS, however, is limited by the spread of stimulus currents into tissue unrelated to disease course and treatment, potentially causing undesirable patient side effects. In this work, we utilize infrared neural stimulation (INS), an optical neuromodulation technique that uses near to mid-infrared light to drive graded excitatory and inhibitory responses in nerves and neurons, to facilitate an optical and spatially constrained DBS paradigm. INS has been shown to provide spatially constrained responses in cortical neurons and, unlike other optical techniques, does not require genetic modification of the neural target. We show that INS produces graded, biophysically relevant single-unit responses with robust information transfer in thalamocortical circuits. Importantly, we show that cortical spread of activation from thalamic INS produces more spatially constrained response profiles than conventional electrical stimulation. Owing to observed spatial precision of INS, we used deep reinforcement learning for closed-loop control of thalamocortical circuits, creating real-time representations of stimulus-response dynamics while driving cortical neurons to precise firing patterns. Our data suggest that INS can serve as a targeted and dynamic stimulation paradigm for both open and closed-loop DBS. Cold Spring Harbor Laboratory 2023-10-19 /pmc/articles/PMC10614743/ /pubmed/37904955 http://dx.doi.org/10.1101/2023.10.04.560859 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator. |
spellingShingle | Article Coventry, Brandon S Lawlor, Georgia L Bagnati, Christina B Krogmeier, Claudia Bartlett, Edward L Spatially specific, closed-loop infrared thalamocortical deep brain stimulation |
title | Spatially specific, closed-loop infrared thalamocortical deep brain stimulation |
title_full | Spatially specific, closed-loop infrared thalamocortical deep brain stimulation |
title_fullStr | Spatially specific, closed-loop infrared thalamocortical deep brain stimulation |
title_full_unstemmed | Spatially specific, closed-loop infrared thalamocortical deep brain stimulation |
title_short | Spatially specific, closed-loop infrared thalamocortical deep brain stimulation |
title_sort | spatially specific, closed-loop infrared thalamocortical deep brain stimulation |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10614743/ https://www.ncbi.nlm.nih.gov/pubmed/37904955 http://dx.doi.org/10.1101/2023.10.04.560859 |
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