Neurodynamics of biased competition and cooperation for attention: A model with spiking neurons
Neurodynamics of biased competition and cooperation for attention: A model with spiking neurons
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DOI：
10.1152/jn.01095.2004
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发表时间：
2005-07-01
影响因子：
2.5
通讯作者：
Rolls, ET
中科院分区：
文献类型：
--
作者：
Deco, G;Rolls, ET
近期的神经生理学实验引出了一种关于注意力神经基础的有前景的“偏向竞争假说”。根据这一假说，注意力有时表现为一种非线性特性，它是由一种自上而下的偏向效应产生的，这种效应影响着皮质区域内以及皮质区域之间的竞争和协作相互作用。在本文中，我们对偏向竞争背后的突触和神经元放电机制进行了详细的动态分析。我们通过一种与潜在的突触和放电动力学相一致的平均场约化方法，探索参数空间中的稳定吸引子，从而对系统的动态能力进行了详细分析。通过一个具有现实动力学的整合 - 放电模型，研究了在神经元记录实验中测量到的非稳定动态行为。这阐明了协作和竞争在偏向竞争动力学中的作用，并说明了为什么在一个注意力网络中，皮质区域之间的反馈连接最优情况下需要比前馈连接弱约2.5倍。我们对自上而下的注意力和自下而上的刺激对比效应（在神经生理学上发现的）之间的相互作用进行了建模，并表明自上而下的注意力效应可以通过外部注意力输入使神经元偏向其非线性激活函数的不同部分来解释。此外，研究表明，尽管NMDA非线性效应在注意力中可能有用，但它们并非必需，因为非线性效应（可能表现为乘法效应）是以刚刚描述的方式产生的。
Recent neurophysiological experiments have led to a promising "biased competition hypothesis" of the neural basis of attention. According to this hypothesis, attention appears as a sometimes nonlinear property that results from a top-down biasing effect that influences the competitive and cooperative interactions that work both within cortical areas and between cortical areas. In this paper we describe a detailed dynamical analysis of the synaptic and neuronal spiking mechanisms underlying biased competition. We perform a detailed analysis of the dynamical capabilities of the system by exploring the stationary attractors in the parameter space by a mean-field reduction consistent with the underlying synaptic and spiking dynamics. The nonstationary dynamical behavior, as measured in neuronal recording experiments, is studied by an integrate-and-fire model with realistic dynamics. This elucidates the role of cooperation and competition in the dynamics of biased competition and shows why feedback connections between cortical areas need optimally to be weaker by a factor of about 2.5 than the feedforward connections in an attentional network. We modeled the interaction between top-down attention and bottom-up stimulus contrast effects found neurophysiologically and showed that top-down attentional effects can be explained by external attention inputs biasing neurons to move to different parts of their nonlinear activation functions. Further, it is shown that, although NMDA nonlinear effects may be useful in attention, they are not necessary, with nonlinear effects (which may appear multiplicative) being produced in the way just described.