The Explanatory Force of Dynamical and Mathematical Models in Neuroscience: A Mechanistic Perspective
The Explanatory Force of Dynamical and Mathematical Models in Neuroscience: A Mechanistic Perspective
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DOI：
10.1086/661755
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发表时间：
2011-10-01
影响因子：
1.7
通讯作者：
Craver, Carl F.
中科院分区：
文献类型：
--
作者：
Kaplan, David Michael;Craver, Carl F.
我们认为，只有当模型中的元素与现象机制中的元素之间存在可信的映射时，系统和认知神经科学中的动力学和数学模型才能解释(而不是重新描述)现象。我们演示了这种模型到机制的映射约束在满足时，如何赋予模型对要解释的现象的解释力。探讨了双手协调的Haken-Kelso-Bunz模型和视觉感受野的高斯差模型等几种典型模型。
We argue that dynamical and mathematical models in systems and cognitive neuroscience explain (rather than redescribe) a phenomenon only if there is a plausible mapping between elements in the model and elements in the mechanism for the phenomenon. We demonstrate how this model-to-mechanism-mapping constraint, when satisfied, endows a model with explanatory force with respect to the phenomenon to be explained. Several paradigmatic models including the Haken-Kelso-Bunz model of bimanual coordination and the difference-of-Gaussians model of visual receptive fields are explored.