Approaches to Information-Theoretic Analysis of Neural Activity.
Approaches to Information-Theoretic Analysis of Neural Activity.
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DOI：
10.1162/biot.2006.1.3.302
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发表时间：
2006-01-01
期刊：
影响因子：
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通讯作者：
Victor, Jonathan D
中科院分区：
文献类型：
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作者：
Victor, Jonathan D
了解神经元如何表征、处理和操纵信息是神经科学的主要目标之一。这些问题从根本上是抽象的，信息理论在形式化和解决这些问题方面起着关键作用。然而，将信息论应用于实验数据充满了许多挑战。为了应对这些挑战，出现了各种创新的分析技术，这些技术具有互补的适用性，假设和目标。
Understanding how neurons represent, process, and manipulate information is one of the main goals of neuroscience. These issues are fundamentally abstract, and information theory plays a key role in formalizing and addressing them. However, application of information theory to experimental data is fraught with many challenges. Meeting these challenges has led to a variety of innovative analytical techniques, with complementary domains of applicability, assumptions, and goals.