Potential confounds in estimating trial-to-trial correlations between neuronal response and behavior using choice probabilities
Potential confounds in estimating trial-to-trial correlations between neuronal response and behavior using choice probabilities
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DOI：
10.1152/jn.00471.2012
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发表时间：
2012-12-01
影响因子：
2.5
通讯作者：
Maunsell, John H. R.
中科院分区：
文献类型：
--
作者：
Kang, Incheol;Maunsell, John H. R.
Kang I，Maunsell JH.使用选择概率估计神经元反应和行为之间试验间相关性的潜在混淆。J Neurophysiol 108：3403-3415，2012.首次发表于2012年9月19日; doi：10.1152/jn.00471.2012.-单个感觉神经元反应的试验间波动与感知报告之间的相关性（通常用选择概率（CP）量化）已被广泛用作评估神经元对行为贡献的重要工具。这些相关性通常很弱，通常需要大量的试验才能得到可靠的估计。因此，使用CP等措施需要在数据分析中谨慎行事，并在数据收集过程中进行严格控制。在这里，我们确定潜在的混淆，可能会出现在数据分析中，并导致有偏见的估计CP，并建议方法，以避免偏见。特别是，我们表明，在不同的刺激条件下与z分数归一化相结合的神经元反应的常见做法可能会导致低估CP时，两个行为反应类别的试验次数的比率在不同的刺激条件。我们还讨论了使用可变的时间间隔量化神经元反应CP测量的影响。最后，我们证明，严重的文物可能会出现在反应时间任务，使用不同的测量间隔，如果平均神经元反应和平均行为表现随时间变化的试验。为了强调在神经生理学数据中解决这些问题的重要性，我们提出了一组从猕猴V1细胞收集的数据，而动物执行检测任务。
Kang I, Maunsell JH. Potential confounds in estimating trial-to-trial correlations between neuronal response and behavior using choice probabilities. J Neurophysiol 108: 3403-3415, 2012. First published September 19, 2012; doi:10.1152/jn.00471.2012.-Correlations between trial-to-trial fluctuations in the responses of individual sensory neurons and perceptual reports, commonly quantified with choice probability (CP), have been widely used as an important tool for assessing the contributions of neurons to behavior. These correlations are usually weak and often require a large number of trials for a reliable estimate. Therefore, working with measures such as CP warrants care in data analysis as well as rigorous controls during data collection. Here we identify potential confounds that can arise in data analysis and lead to biased estimates of CP, and suggest methods to avoid the bias. In particular, we show that the common practice of combining neuronal responses across different stimulus conditions with z-score normalization can result in an underestimation of CP when the ratio of the numbers of trials for the two behavioral response categories differs across the stimulus conditions. We also discuss the effects of using variable time intervals for quantifying neuronal response on CP measurements. Finally, we demonstrate that serious artifacts can arise in reaction time tasks that use varying measurement intervals if the mean neuronal response and mean behavioral performance vary over time within trials. To emphasize the importance of addressing these concerns in neurophysiological data, we present a set of data collected from V1 cells in macaque monkeys while the animals performed a detection task.