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简单的增益控制模型解释 V1 群体反应的复杂动力学。

Complex dynamics of V1 population responses explained by a simple gain-control model.

机构信息

Department of Computer Sciences, The University of Texas at Austin, 1 University Station, A8000, Austin, TX 78712, USA.

出版信息

Neuron. 2009 Dec 24;64(6):943-56. doi: 10.1016/j.neuron.2009.08.041.

Abstract

To understand sensory encoding and decoding, it is essential to characterize the dynamics of population responses in sensory cortical areas. Using voltage-sensitive dye imaging in awake, fixating monkeys, we obtained complete quantitative measurements of the spatiotemporal dynamics of V1 responses over the entire region activated by small, briefly presented stimuli. The responses exhibit several complex properties: they begin to rise approximately simultaneously over the entire active region, but reach their peak more rapidly at the center. However, at stimulus offset the responses fall simultaneously and at the same rate at all locations. Although response onset depends on stimulus contrast, both the peak spatial profile and the offset dynamics are independent of contrast. We show that these results are consistent with a simple population gain-control model that generalizes earlier single-neuron contrast gain-control models. This model provides valuable insight and is likely to be applicable to other brain areas.

摘要

为了理解感觉编码和解码,刻画感觉皮质区域中群体反应的动力学至关重要。在清醒、注视的猴子中,我们使用电压敏感染料成像,对小而短暂呈现的刺激激活的整个 V1 区域的时空动力学,获得了完整的定量测量。这些反应表现出了几个复杂的特性:它们在整个活跃区域大致同时开始上升,但在中心更快达到峰值。然而,在刺激结束时,所有位置的反应以相同的速率同时下降。尽管反应起始取决于刺激对比度,但峰值空间分布和下降动力学都与对比度无关。我们表明,这些结果与一个简单的群体增益控制模型一致,该模型推广了早期的单个神经元对比度增益控制模型。这个模型提供了有价值的见解,并且可能适用于其他脑区。

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