Butts Daniel A
Department of Neurobiology, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA.
Network. 2003 May;14(2):177-87.
Although the Shannon mutual information can be used to reveal general features of the neural code, it cannot directly address which symbols of the code are significant. Further insight can be gained by using information measures that are specific to particular stimuli or responses. The specific information is a previously proposed measure of the amount of information associated with a particular response; however, as I show, it does not properly characterize the amount of information associated with particular stimuli. Instead, I propose a new measure: the stimulus-specific information (SSI), defined to be the average specific information of responses given the presence of a particular stimulus. Like other information theoretic measures, the SSI does not rely on assumptions about the neural code, and is robust to non-linearities of the system. To demonstrate its applicability, the SSI is applied to data from simulated visual neurons, and identifies stimuli consistent with the neuron's linear kernel. While the SSI reveals the essential linearity of the visual neurons, it also successfully identifies the well-encoded stimuli in a modified example where linear analysis techniques fail. Thus, I demonstrate that the SSI is an appropriate measure of the information associated with particular stimuli, and provides a new unbiased method of analysing the significant stimuli of a neural code.
虽然香农互信息可用于揭示神经编码的一般特征，但它无法直接确定编码中的哪些符号是重要的。通过使用特定于特定刺激或反应的信息度量，可以获得进一步的见解。特定信息是先前提出的一种与特定反应相关的信息量度；然而，正如我所表明的，它不能恰当地表征与特定刺激相关的信息量。相反，我提出了一种新的量度：刺激特定信息（SSI），定义为在特定刺激存在的情况下反应的平均特定信息。与其他信息论量度一样，SSI不依赖于关于神经编码的假设，并且对系统的非线性具有鲁棒性。为了证明其适用性，将SSI应用于来自模拟视觉神经元的数据，并识别与神经元线性核一致的刺激。虽然SSI揭示了视觉神经元的基本线性，但它也成功地在一个修改后的示例中识别出编码良好的刺激，而在该示例中线性分析技术失效。因此，我证明了SSI是与特定刺激相关的信息的一种合适量度，并提供了一种新的无偏方法来分析神经编码中的重要刺激。
