Frontiers in Computational NeuroscienceNeurosciencePeer-reviewed journal article
Quantitative Analysis of the Optogenetic Excitability of CA1 Neurons
Ruben SchoetersiD, Thomas TarnaudiD, Laila WeyniD, Wout JosephiD, Robrecht RaedtiD, Emmeric TangheiD
Abstract
Optogenetics has emerged as a promising technique for modulating neuronal activity and holds potential for the treatment of neurological disorders such as temporal lobe epilepsy (TLE). However, clinical translation still faces many challenges. This in-silico study aims to enhance the understanding of optogenetic excitability in CA1 cells and to identify strategies for improving stimulation protocols. Employing state-of-the-art computational models, the optogenetic excitability of four CA1 cells, two pyramidal and two interneurons, expressing ChR2(H134R) is investigated. The results demonstrate that confining the opsin to specific neuronal membrane compartments significantly improves excitability. An improvement is also achieved by focusing the light beam on the most excitable cell region. Moreover, the perpendicular orientation of the optical fiber relative to the somato-dendritic axis yields superior results. Inter-cell variability is observed, highlighting the importance of considering neuron degeneracy when designing optogenetic tools. Opsin confinement to the basal dendrites of the pyramidal cells renders the neuron the most excitability. A global sensitivity analysis identified opsin location and expression level as having the greatest impact on simulation outcomes. The error reduction of simulation outcome due to coupling of neuron modeling with light propagation is shown. The results promote spatial confinement and increased opsin expression levels as important improvement strategies. On the other hand, uncertainties in these parameters limit precise determination of the irradiance thresholds. This study provides valuable insights on optogenetic excitability of CA1 cells useful for the development of improved optogenetic stimulation protocols for, for instance, TLE treatment.
- organism: mouse
- assay: electronic health records
- research focus: benchmarking
- approach: statistical model
- Citations
- 3
- FWCI
- 0.36
- Field percentile
- top 49%
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