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Abstract：
We present a novel approach to representing perceptual and cognitive knowledge, spectral knowledge representation, that is focused on the oscillatory behaviour of the brain. The model is presented in the context of a larger hypothetical cognitive architecture. The model uses literal representations of waves to describe the dynamics of neural assemblies as they process perceived input. We show how the model can be applied to representations of sound, and usefully model music perception, specifically harmonic distance. We demonstrate that the model naturally captures both pitch and chord/key distance as empirically measured by Krumhansl and Kessler, thereby providing an underlying mechanism from which their toroidal model might arise. We evaluate our model with respect to those of Milne and others.
摘要：
我们提出了一种新的方法来表示感知和认知知识，光谱知识表示，集中在大脑的振荡行为上。该模型是在更大的假设认知架构的背景下提出的。该模型使用波的文字表示来描述神经组件在处理感知输入时的动力学。我们展示了该模型如何应用于声音的表示，并有效地模拟音乐感知，特别是谐波距离。我们证明了该模型自然地捕获了由Krumhansl和Kessler根据经验测量的音高和和弦/键距离，从而提供了一种潜在的机制，它们的环形模型可能会出现。我们根据米尔恩和其他人的模型来评估我们的模型。
