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Sparse codes of harmonic natural sounds and their modulatory interactions

机译:谐波自然声音的稀疏代码及其调制相互作用

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Sparse coding and its related theories have been successful to explain various response properties of early stages of sensory information processing such as primary visual cortex and peripheral auditory system, which suggests that the emergence of such properties results from adaptation of the nerve system to natural stimuli. The present study continues this line of research in a higher stage of auditory processing, focusing on harmonic structures that are often found in behaviourally important natural sound like animal vocalization. It has been physiologically shown that monkey primary auditory cortices (A1) have neurons with response properties capturing such harmonic structures: their response and modulation peaks are often found at frequencies that are harmonically related to each other. We hypothesize that such relations emerge from sparse coding of harmonic natural sounds. Our simulation shows that similar harmonic relations emerge from frequency-domain sparse codes of harmonic sounds, namely, piano performance and human speech. Moreover, the modulatory behaviours can be explained by competitive interactions of model neurons that capture partially common harmonic structures.
机译:稀疏编码及其相关理论已成功地解释了感觉信息处理早期阶段的各种响应特性,例如初级视觉皮层和周围听觉系统,这表明这些特性的出现是神经系统对自然刺激的适应导致的。本研究在听觉处理的更高阶段继续了这方面的研究,重点是通常在行为上很重要的自然声音(如动物发声)中发现的和声结构。生理上已经表明,猴子的初级听觉皮层(A1)的神经元具有捕获此类谐波结构的响应特性:它们的响应和调制峰经常出现在彼此谐波相关的频率上。我们假设这种关系是由谐波自然声音的稀疏编码产生的。我们的仿真表明,谐波声的频域稀疏码(即钢琴演奏和人类语音)也产生了相似的谐波关系。此外,可以通过捕获部分常见谐波结构的模型神经元的竞争性相互作用来解释调节行为。

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