Large-scale fluorescence calcium imaging methods have become widely adopted for studies of long-term hippocampal and cortical neuronal dynamics. Pyramidal neurons of the rodent hippocampus show spatial tuning in freely foraging or head-fixed navigation tasks. Development of efficient neural decoding methods for reconstructing the animal's position in real or virtual environments can provide a fast readout of spatial representations in closed-loop neuroscience experiments. Here, we develop an efficient strategy to extract features from fluorescence calcium imaging traces and further decode the animal's position. We validate our spike inference-free decoding methods in multiple in vivo calcium imaging recordings of the mouse hippocampus based on both supervised and unsupervised decoding analyses. We systematically investigate the decoding performance of our proposed methods with respect to the number of neurons, imaging frame rate, and signal-to-noise ratio. Our proposed supervised decoding analysis is ultrafast and robust, and thereby appealing for real-time position decoding applications based on calcium imaging.

中文翻译：

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基于小鼠海马荧光钙成像的高效位置解码方法


大规模荧光钙成像方法已广泛应用于长期海马和皮质神经元动力学的研究。啮齿动物海马体的锥体神经元在自由觅食或头部固定导航任务中表现出空间调谐。开发用于重建动物在真实或虚拟环境中的位置的有效神经解码方法可以在闭环神经科学实验中提供空间表示的快速读出。在这里，我们开发了一种有效的策略来从荧光钙成像痕迹中提取特征并进一步解码动物的位置。我们基于监督和无监督解码分析，在小鼠海马体的多个体内钙成像记录中验证了我们的无尖峰推断解码方法。我们系统地研究了我们提出的方法在神经元数量、成像帧速率和信噪比方面的解码性能。我们提出的监督解码分析超快且稳健，因此对基于钙成像的实时位置解码应用很有吸引力。