Spatiotemporal Response Properties of Optic-Flow Processing Neurons
Spatiotemporal Response Properties of Optic-Flow Processing Neurons
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DOI：
10.1016/j.neuron.2010.07.017
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发表时间：
2010-08
期刊：
影响因子：
16.2
通讯作者：
Franz Weber;C. Machens;A. Borst
中科院分区：
文献类型：
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作者：
Franz Weber;C. Machens;A. Borst
感觉神经科学的一个中心目标是充分表征神经元的输入-输出关系。然而，感觉神经元反应的强非线性使得难以开发推广到任意刺激的模型。通常，当神经元表现出其增益或选择性的刺激依赖性调制时，标准的线性-非线性模型就会崩溃。我们在苍蝇的光流处理神经元中研究了这些问题。我们发现，神经元的感受野是完全描述的时变向量场是时空可分离的。然而，增加刺激强度会大大降低神经元的增益和选择性。为了捕捉这些变化的响应行为，我们扩展了线性-非线性模型的生物药理学动机的增益和选择性机制。我们将所有模型参数直接拟合到数据中，并表明该模型现在可以在整个运动刺激范围内很好地表征神经元的输入-输出关系。
A central goal in sensory neuroscience is to fully characterize a neuron's input-output relation. However, strong nonlinearities in the responses of sensory neurons have made it difficult to develop models that generalize to arbitrary stimuli. Typically, the standard linear-nonlinear models break down when neurons exhibit stimulus-dependent modulations of their gain or selectivity. We studied these issues in optic-flow processing neurons in the fly. We found that the neurons' receptive fields are fully described by a time-varying vector field that is space-time separable. Increasing the stimulus strength, however, strongly reduces the neurons' gain and selectivity. To capture these changes in response behavior, we extended the linear-nonlinear model by a biophysically motivated gain and selectivity mechanism. We fit all model parameters directly to the data and show that the model now characterizes the neurons' input-output relation well over the full range of motion stimuli.