Computational Modeling of Channelrhodopsin-2 Photocurrent Characteristics in Relation to Neural Signaling
Roxana A. Stefanescu, R.G. Shivakeshavan, Pramod P. Khargonekar,, Sachin S. Talathi

TL;DR
This study evaluates whether a 4-state transition rate model better captures the photocurrent kinetics of new fast ChR2 variants, ChETA and ChRET/TC, in neural simulations compared to a 3-state model.
Contribution
It demonstrates that the 4-state model more accurately reproduces neural responses to optostimulation with new ChR2 variants than the traditional 3-state model.
Findings
4-state model better fits experimental neural responses
4-state model captures mono-exponential photocurrent decay
3-state model insufficient for new variants
Abstract
Channelrhodopsins-2 (ChR2) are a class of light sensitive proteins that offer the ability to use light stimulation to regulate neural activity with millisecond precision. In order to address the limitations in the efficacy of the wild-type ChR2 (ChRwt) to achieve this objective, new variants of ChR2 that exhibit fast mono-exponential photocurrent decay characteristics have been recently developed and validated. In this paper, we investigate whether the framework of transition rate model with 4 states, primarily developed to mimic the bi-exponential photocurrent decay kinetics of ChRwt, as opposed to the low complexity 3 state model, is warranted to mimic the mono-exponential photocurrent decay kinetics of the newly developed fast ChR2 variants: ChETA (Gunaydin et al., Nature Neurosci, 13:387-392, 2010) and ChRET/TC (Berndt et al., PNAS, 108:7595-7600, 2011). We begin by estimating the…
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Taxonomy
TopicsPhotoreceptor and optogenetics research · Neural dynamics and brain function · Neuroscience and Neural Engineering
