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行为灵长类动物的外侧膝状体神经元。II. 反应时间形状中视觉信息的编码。

Lateral geniculate neurons in behaving primates. II. Encoding of visual information in the temporal shape of the response.

作者信息

McClurkin J W, Gawne T J, Optican L M, Richmond B J

机构信息

Laboratory of Sensorimotor Research, National Eye Institute, National Institutes of Health, Bethesda, Maryland 20892.

出版信息

J Neurophysiol. 1991 Sep;66(3):794-808. doi: 10.1152/jn.1991.66.3.794.

Abstract
  1. We used the Karhunen-Loève (K-L) transform to quantify the temporal distribution of spikes in the responses of lateral geniculate (LGN) neurons. The basis functions of the K-L transform are a set of waveforms called principal components, which are extracted from the data set. The coefficients of the principal components are uncorrelated with each other and can be used to quantify individual responses. The shapes of each of the first three principal components were very similar across neurons. 2. The coefficient of the first principal component was highly correlated with the spike count, but the other coefficients were not. Thus the coefficient of the first principal component reflects the strength of the response, whereas the coefficients of the other principal components reflect aspects of the temporal distribution of spikes in the response that are uncorrelated with the strength of the response. Statistical analysis revealed that the coefficients of up to 10 principal components were driven by the stimuli. Therefore stimuli govern the temporal distribution as well as the number of spikes in the response. 3. Through the application of information theory, we were able to compare the amount of stimulus-related information carried by LGN neurons when two codes were assumed: first, a univariate code based on response strength alone; and second, a multivariate temporal code based on the coefficients of the first three principal components. We found that LGN neurons were able to transmit an average of 1.5 times as much information using the three-component temporal code as they could using the strength code. 4. The stimulus set we used allowed us to calculate the amount of information each neuron could transmit about stimulus luminance, pattern, and contrast. All neurons transmitted the greatest amount of information about stimulus luminance, but they also transmitted significant amounts of information about stimulus pattern. This pattern information was not a reflection of the luminance or contrast of the pixel centered on the receptive field. 5. In addition to measuring the average amount of information each neuron transmitted about all stimuli, we also measured the amount of information each neuron transmitted about the individual stimuli with both the univariate spike count code and the multivariate temporal code. We then compared the amount of information transmitted per stimulus with the magnitudes of the responses to the individual stimuli. We found that the magnitudes of both the univariate and the multivariate responses to individual stimuli were poorly correlated with the information transmitted about the individual stimuli.(ABSTRACT TRUNCATED AT 400 WORDS)
摘要
  1. 我们使用卡尔胡宁 - 洛伊夫(K - L)变换来量化外侧膝状体(LGN)神经元反应中尖峰的时间分布。K - L变换的基函数是一组称为主成分的波形,它们是从数据集中提取出来的。主成分的系数彼此不相关,可用于量化个体反应。前三个主成分中每个成分的形状在不同神经元之间非常相似。2. 第一主成分的系数与尖峰计数高度相关,但其他系数并非如此。因此,第一主成分的系数反映了反应的强度,而其他主成分的系数反映了反应中尖峰时间分布的一些方面,这些方面与反应强度无关。统计分析表明,多达10个主成分的系数受刺激驱动。因此,刺激不仅控制反应中尖峰的数量,还控制其时间分布。3. 通过应用信息论,我们能够比较在假设两种编码时,LGN神经元携带的与刺激相关的信息量:第一,仅基于反应强度的单变量编码;第二,基于前三个主成分系数的多变量时间编码。我们发现,使用三成分时间编码时,LGN神经元能够传输的信息量平均是使用强度编码时的1.5倍。4. 我们使用的刺激集使我们能够计算每个神经元可以传输的关于刺激亮度、图案和对比度的信息量。所有神经元传输的关于刺激亮度的信息量最大,但它们也传输了大量关于刺激图案的信息。这种图案信息并非以感受野中心像素的亮度或对比度为反映。5. 除了测量每个神经元传输的关于所有刺激的平均信息量外,我们还使用单变量尖峰计数编码和多变量时间编码测量了每个神经元传输的关于单个刺激的信息量。然后,我们将每个刺激传输的信息量与对单个刺激的反应幅度进行比较。我们发现,对单个刺激的单变量和多变量反应幅度与关于单个刺激传输的信息量之间相关性很差。(摘要截取自400字)

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