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海马体中神经编码的形成:痕迹条件反射作为研究随机重新编码假说的典型范式。

The formation of neural codes in the hippocampus: trace conditioning as a prototypical paradigm for studying the random recoding hypothesis.

作者信息

Levy W B, Sanyal A, Rodriguez P, Sullivan D W, Wu X B

机构信息

Department of Neurosurgery, University of Virginia, P.O. Box 800420, Charlottesville, VA 22908, USA.

出版信息

Biol Cybern. 2005 Jun;92(6):409-26. doi: 10.1007/s00422-005-0568-9. Epub 2005 Jun 16.

DOI:10.1007/s00422-005-0568-9
PMID:15965710
Abstract

The trace version of classical conditioning is used as a prototypical hippocampal-dependent task to study the recoding sequence prediction theory of hippocampal function. This theory conjectures that the hippocampus is a random recoder of sequences and that, once formed, the neuronal codes are suitable for prediction. As such, a trace conditioning paradigm, which requires a timely prediction, seems by far the simplest of the behaviorally-relevant paradigms for studying hippocampal recoding. Parameters that affect the formation of these random codes include the temporal aspects of the behavioral/cognitive paradigm and certain basic characteristics of hippocampal region CA3 anatomy and physiology such as connectivity and activity. Here we describe some of the dynamics of code formation and describe how biological and paradigmatic parameters affect the neural codes that are formed. In addition to a backward cascade of coding neurons, we point out, for the first time, a higher-order dynamic growing out of the backward cascade-a particular forward and backward stabilization of codes as training progresses. We also observe that there is a performance compromise involved in the setting of activity levels due to the existence of three behavioral failure modes. Each of these behavioral failure modes exists in the computational model and, presumably, natural selection produced the compromise performance observed by psychologists. Thus, examining the parametric sensitivities of the codes and their dynamic formation gives insight into the constraints on natural computation and into the computational compromises ensuing from these constraints.

摘要

经典条件反射的痕迹版本被用作一种典型的海马体依赖任务,以研究海马体功能的重新编码序列预测理论。该理论推测,海马体是序列的随机重新编码者,并且一旦形成,神经元编码就适合进行预测。因此,一种需要及时预测的痕迹条件反射范式,似乎是研究海马体重新编码的行为相关范式中最简单的一种。影响这些随机编码形成的参数包括行为/认知范式的时间方面以及海马体CA3区解剖学和生理学的某些基本特征,如连通性和活性。在这里,我们描述了编码形成的一些动态过程,并描述了生物学和范式参数如何影响所形成的神经编码。除了编码神经元的反向级联,我们首次指出,在反向级联之外还存在一种高阶动态——随着训练的进行,编码会出现特定的向前和向后稳定。我们还观察到,由于存在三种行为失败模式,在设定活动水平时存在性能折衷。这些行为失败模式中的每一种都存在于计算模型中,并且推测自然选择产生了心理学家所观察到的折衷性能。因此,研究编码的参数敏感性及其动态形成,可以深入了解自然计算的约束以及由这些约束导致的计算折衷。

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