Associative learning shapes the neural code for stimulus magnitude in primary auditory cortex
Associative learning shapes the neural code for stimulus magnitude in primary auditory cortex
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DOI：
10.1073/pnas.0407586101
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发表时间：
2004-11-16
影响因子：
11.1
通讯作者：
Merzenich, MM
中科院分区：
文献类型：
--
作者：
Polley, DB;Heiser, MA;Merzenich, MM
自实验心理学诞生以来，研究人员一直在寻求了解感觉刺激的幅度与其知觉表征的幅度之间的基本关系。当代理论支持这样的观点，即大小是由初级传入通路中建立的放电频率的线性增加来编码的。在本研究中，我们研究了大鼠初级听觉皮质(AI)的声强编码，并通过配对刺激强化和器件性条件反射范式描述了其可塑性。在经过训练的动物中，随着刺激强度的增加，A1中的群体反应强度变得更加强烈的非线性。个体的Al反应对更有限的声强范围变得有选择性，作为一个群体，代表了更广泛的首选声级范围。这些实验证明，联想学习过程可以有力地重塑刺激幅度的表示，并表明人工智能中声音强度的代码可以从强度调整的神经元中推导出来，这些神经元根据声音强度的增加而改变而不是简单地增加其放电频率。
Since the dawn of experimental psychology, researchers have sought an understanding of the fundamental relationship between the amplitude of sensory stimuli and the magnitudes of their perceptual representations. Contemporary theories support the view that magnitude is encoded by a linear increase in firing rate established in the primary afferent pathways. In the present study, we have investigated sound intensity coding in the rat primary auditory cortex (AI) and describe its plasticity by following paired stimulus reinforcement and instrumental conditioning paradigms. In trained animals, population-response strengths in Al became more strongly nonlinear with increasing stimulus intensity. Individual Al responses became selective to more restricted ranges of sound intensities and, as a population, represented a broader range of preferred sound levels. These experiments demonstrate that the representation of stimulus magnitude can be powerfully reshaped by associative learning processes and suggest that the code for sound intensity within AI can be derived from intensity-tuned neurons that change, rather than simply increase, their firing rates in proportion to increases in sound intensity.