Designing optimal stimuli to control neuronal spike timing
Designing optimal stimuli to control neuronal spike timing
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DOI：
10.1152/jn.00427.2010
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发表时间：
2011-08-01
影响因子：
2.5
通讯作者：
Paninski, Liam
中科院分区：
文献类型：
--
作者：
Ahmadian, Yashar;Packer, Adam M.;Paninski, Liam
Ahmadian Y，Packer AM，Yuste R，Paninski L.设计最佳刺激以控制神经元发放时间。J Neurophysiol 106：1038-1053，2011.首次发表于2011年4月20日; doi：10.1152/jn.00427.2010.-实验刺激方法的最新进展提出了以下重要的计算问题：我们如何选择一个刺激，将驱动神经元输出一个目标尖峰列车具有最佳精度，给定的生理约束？在这里，我们采用了一种基于模型的方法，该模型描述了刺激剂（例如注入的电流或激光与笼状神经递质或光敏离子通道相互作用）如何影响神经元的尖峰活动。基于这些模型，我们解决了相反的问题，找到最佳的时间依赖性调制的输入，受硬件限制以及生理启发的安全措施，导致神经元发出的尖峰序列，具有最高的概率将接近目标尖峰序列。我们采用快速凸约束优化方法来解决这个问题。我们的方法可以在真实的时间内实现，也可以推广到许多细胞的情况下，适合神经假体的应用。通过使用生物敏感的参数和约束，我们的方法发现在模拟实验中产生非常精确的尖峰序列的刺激模式。我们还测试了在小鼠皮层切片锥体细胞的细胞内电流注入方法，量化的依赖尖峰的可靠性和定时精度施加的电流上的约束。
Ahmadian Y, Packer AM, Yuste R, Paninski L. Designing optimal stimuli to control neuronal spike timing. J Neurophysiol 106: 1038-1053, 2011. First published April 20, 2011; doi:10.1152/jn.00427.2010.-Recent advances in experimental stimulation methods have raised the following important computational question: how can we choose a stimulus that will drive a neuron to output a target spike train with optimal precision, given physiological constraints? Here we adopt an approach based on models that describe how a stimulating agent (such as an injected electrical current or a laser light interacting with caged neurotransmitters or photosensitive ion channels) affects the spiking activity of neurons. Based on these models, we solve the reverse problem of finding the best time-dependent modulation of the input, subject to hardware limitations as well as physiologically inspired safety measures, that causes the neuron to emit a spike train that with highest probability will be close to a target spike train. We adopt fast convex constrained optimization methods to solve this problem. Our methods can potentially be implemented in real time and may also be generalized to the case of many cells, suitable for neural prosthesis applications. With the use of biologically sensible parameters and constraints, our method finds stimulation patterns that generate very precise spike trains in simulated experiments. We also tested the intracellular current injection method on pyramidal cells in mouse cortical slices, quantifying the dependence of spiking reliability and timing precision on constraints imposed on the applied currents.