Department of Physiology and Biophysics, University of Washington, Seattle, United States.
Elife. 2024 Nov 5;13:RP93795. doi: 10.7554/eLife.93795.
Computation in neural circuits relies on the judicious use of nonlinear circuit components. In many cases, multiple nonlinear components work collectively to control circuit outputs. Separating the contributions of these different components is difficult, and this limits our understanding of the mechanistic basis of many important computations. Here, we introduce a tool that permits the design of light stimuli that predictably alter rod and cone phototransduction currents - including stimuli that compensate for nonlinear properties such as light adaptation. This tool, based on well-established models for the rod and cone phototransduction cascade, permits the separation of nonlinearities in phototransduction from those in downstream circuits. This will allow, for example, direct tests of how adaptation in rod and cone phototransduction affects downstream visual signals and perception.
神经回路中的计算依赖于明智地使用非线性电路元件。在许多情况下，多个非线性元件共同作用来控制电路输出。分离这些不同元件的贡献是困难的，这限制了我们对许多重要计算的机制基础的理解。在这里，我们引入了一种工具，该工具允许设计可预测地改变视杆和视锥光转导电流的光刺激 - 包括补偿非线性特性（如光适应）的刺激。该工具基于视杆和视锥光转导级联的成熟模型，允许将光转导中的非线性与下游电路中的非线性分离。例如，这将允许直接测试视杆和视锥光转导中的适应如何影响下游视觉信号和感知。
