Pamplona Daniela, Hilgen Gerrit, Hennig Matthias H, Cessac Bruno, Sernagor Evelyne, Kornprobst Pierre
U2IS, École Nationale Supérieure de Techniques Avancées, Institut Polytechnique de Paris, Palaiseau, France.
Université Côte d'Azur, Inria, France.
J Neurophysiol. 2022 May 1;127(5):1334-1347. doi: 10.1152/jn.00076.2021. Epub 2022 Mar 2.
Computing the spike-triggered average (STA) is a simple method to estimate linear receptive fields (RFs) in sensory neurons. For random, uncorrelated stimuli, the STA provides an unbiased RF estimate, but in practice, white noise at high resolution is not an optimal stimulus choice as it usually evokes only weak responses. Therefore, for a visual stimulus, images of randomly modulated blocks of pixels are often used. This solution naturally limits the resolution at which an RF can be measured. Here, we present a simple super-resolution technique that can overcome these limitations. We define a novel stimulus type, the shifted white noise (SWN), by introducing random spatial shifts in the usual stimulus to increase the resolution of the measurements. In simulated data, we show that the average error using the SWN was 1.7 times smaller than when using the classical stimulus, with successful mapping of 2.3 times more neurons, covering a broader range of RF sizes. Moreover, successful RF mapping was achieved with brief recordings of light responses, lasting only about 1 min of activity, which is more than 10 times more efficient than the classical white noise stimulus. In recordings from mouse retinal ganglion cells with large scale multielectrode arrays, we successfully mapped 21 times more RFs than when using the traditional white noise stimuli. In summary, randomly shifting the usual white noise stimulus significantly improves RFs estimation, and requires only short recordings. We present a novel approach to measure receptive fields in large and heterogeneous populations of sensory neurons recorded with large-scale, high-density multielectrode arrays. Our approach leverages super-resolution principles to improve the yield of the spike-triggered average method. By simply designing a new stimulus, we provide experimentalists with a new and fast technique to simultaneously detect more receptive fields at higher resolution in population of hundreds to thousands of neurons.
计算脉冲触发平均值（STA）是估计感觉神经元线性感受野（RF）的一种简单方法。对于随机、不相关的刺激，STA可提供无偏的RF估计，但在实际中，高分辨率的白噪声并非最佳刺激选择，因为它通常只能引发微弱反应。因此，对于视觉刺激，常使用随机调制像素块的图像。这种解决方案自然限制了可测量RF的分辨率。在此，我们提出一种简单的超分辨率技术，可克服这些限制。我们通过在通常的刺激中引入随机空间偏移来定义一种新型刺激类型，即移位白噪声（SWN），以提高测量分辨率。在模拟数据中，我们表明使用SWN时的平均误差比使用传统刺激时小1.7倍，成功映射的神经元数量是传统刺激的2.3倍，覆盖更广泛的RF大小范围。此外，仅通过约1分钟的短暂光反应记录就实现了成功的RF映射，其效率比传统白噪声刺激高出10倍以上。在使用大规模多电极阵列对小鼠视网膜神经节细胞进行的记录中，我们成功映射的RF数量比使用传统白噪声刺激时多21倍。总之，随机移位通常的白噪声刺激可显著改善RF估计，且只需要短暂记录。我们提出了一种新方法来测量用大规模、高密度多电极阵列记录的大量异质性感觉神经元群体的感受野。我们的方法利用超分辨率原理提高脉冲触发平均法的成功率。通过简单设计一种新刺激，我们为实验人员提供了一种新的快速技术，可在数百到数千个神经元群体中以更高分辨率同时检测更多感受野。
