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Computational analysis of optogenetic inhibition of CA1 neurons using a data-efficient and interpretable potassium and chloride conducting opsin model

 
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cris.virtual.orcid0000-0002-8246-6888
cris.virtual.orcid0000-0003-4943-4435
cris.virtual.orcid0000-0002-2414-3044
cris.virtual.orcid0000-0003-0020-6466
cris.virtual.orcid0000-0002-8807-0673
cris.virtualsource.department5e44ddde-1363-426a-bd9f-b67fc5a7d75c
cris.virtualsource.departmentc7247f84-b9af-4ea2-b947-c06000e9e31d
cris.virtualsource.department04550795-be39-45e5-b23e-6bafee55650f
cris.virtualsource.department781f9930-4af8-4123-8064-208f6863dd1c
cris.virtualsource.department79248d32-9470-424f-82b9-55f4ffa70920
cris.virtualsource.departmentea2b6cf8-5ffb-468d-8cf4-393b5a87a5e1
cris.virtualsource.orcid5e44ddde-1363-426a-bd9f-b67fc5a7d75c
cris.virtualsource.orcidc7247f84-b9af-4ea2-b947-c06000e9e31d
cris.virtualsource.orcid04550795-be39-45e5-b23e-6bafee55650f
cris.virtualsource.orcid781f9930-4af8-4123-8064-208f6863dd1c
cris.virtualsource.orcid79248d32-9470-424f-82b9-55f4ffa70920
cris.virtualsource.orcidea2b6cf8-5ffb-468d-8cf4-393b5a87a5e1
dc.contributor.authorWeyn, Laila
dc.contributor.authorTarnaud, Thomas
dc.contributor.authorSchoeters, Ruben
dc.contributor.authorDe Becker, Xavier
dc.contributor.authorJoseph, Wout
dc.contributor.authorRaedt, Robrecht
dc.contributor.authorTanghe, Emmeric
dc.contributor.imecauthorWeyn, Laila
dc.contributor.imecauthorTarnaud, Thomas
dc.contributor.imecauthorSchoeters, Ruben
dc.contributor.imecauthorDe Becker, Xavier
dc.contributor.imecauthorJoseph, Wout
dc.contributor.imecauthorTanghe, Emmeric
dc.contributor.orcidimecWeyn, Laila::0000-0003-4943-4435
dc.contributor.orcidimecSchoeters, Ruben::0000-0002-8246-6888
dc.contributor.orcidimecDe Becker, Xavier::0000-0002-2414-3044
dc.contributor.orcidimecJoseph, Wout::0000-0002-8807-0673
dc.contributor.orcidimecTanghe, Emmeric::0000-0003-0020-6466
dc.date.accessioned2025-09-02T03:58:00Z
dc.date.available2025-09-02T03:58:00Z
dc.date.issued2025
dc.description.abstractObjective. Optogenetic inhibition of excitatory neuronal populations has emerged as a potential strategy for the treatment of refractory epilepsy. However, achieving effective seizure suppression in animal models using optogenetic techniques has proven challenging. This difficulty can be attributed to a suboptimal stimulation method that involves numerous complex variables. This study aims to examine how various stimulation parameters and opsin characteristics influence the efficacy of optogenetic inhibition protocols. Additionally, a new opsin model is introduced that permits easy implementation of the experimentally derived parameters describing the opsin’s opening and closing dynamics. Approach. The mathematical description of a chloride and potassium conducting opsin was combined with a conductance-based model of a pyramidal CA1 neuron. Simulations with varying parameters were conducted to explore the effects of the stimulation paradigm and the neuronal environment on inhibition. A simplified, adaptable opsin model was used to test the robustness of these results and explore the impact of variations in opsin characteristics. Main results. Stronger inhibition was achieved with higher illumination intensities, pulse repetition frequencies, and duty cycles. Potassium conducting opsins were found to be more stable than chloride conducting ones. These findings were independent of the opsin’s parameters. Additionally, changes in the opsin’s dynamics had negligible impact when the opening and closing time constants were varied by factors between 0.5 and 2. Significance. This study provides key insights into the stimulation and physiological parameters that affect optogenetic inhibition. The findings highlight the importance of choosing the right stimulation protocol and opsin for optimizing optogenetic strategies. The newly developed opsin model also offers a new, valuable tool that will facilitate future research into the development of an improved optogenetic modulation protocol for seizure suppression.
dc.description.wosFundingTextWe would like to thank Dr Jonas Wietek and Dr Franziska Schneider-Warme for sharing their experimental data on GtACR1/2. R Schoeters was a PhD Fellow of the FWO. X De Becker is a PhD Fellow of the FWO. T Tarnaud is a postdoctoral fellow of the FWO. This work is supported by BOF project SOFTRESET.
dc.identifier.doi10.1088/1741-2552/adf94a
dc.identifier.issn1741-2560
dc.identifier.pmidMEDLINE:40774311
dc.identifier.urihttps://imec-publications.be/handle/20.500.12860/46143
dc.publisherIOP Publishing Ltd
dc.source.issue4
dc.source.journalJOURNAL OF NEURAL ENGINEERING
dc.source.numberofpages17
dc.source.volume22
dc.subject.keywordsUNDERLYING OPTICAL STIMULATION
dc.subject.keywordsLIGHT
dc.subject.keywordsCHANNELRHODOPSIN-2
dc.subject.keywordsDYNAMICS
dc.subject.keywordsDRIVEN
dc.subject.keywordsFUTURE
dc.title

Computational analysis of optogenetic inhibition of CA1 neurons using a data-efficient and interpretable potassium and chloride conducting opsin model

dc.typeJournal article
dspace.entity.typePublication
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