Annu Int Conf IEEE Eng Med Biol Soc. 2021 Nov;2021:2997-3003. doi: 10.1109/EMBC46164.2021.9629611.
We developed Carignan, a real-time calcium imaging software that can automatically detect activity patterns of neurons. Carignan can activate an external device when synchronized neural activity is detected in calcium imaging obtained by a one-photon (1p) miniscope. Combined with optogenetics, our software enables closed-loop experiments for investigating functions of specific types of neurons in the brain. In addition to making existing pattern detection algorithms run in real-time seamlessly, we developed a new classification module that distinguishes neurons from false-positives using deep learning. We used a combination of convolutional and recurrent neural networks to incorporate both spatial and temporal features in activity patterns. Our method performed better than existing neuron detection methods for false-positive neuron detection in terms of the F1 score. Using Carignan, experimenters can activate or suppress a group of neurons when specific neural activity is observed. Because the system uses a 1p miniscope, it can be used on the brain of a freely-moving animal, making it applicable to a wide range of experimental paradigms.
我们开发了 Carignan，这是一款实时钙成像软件，可以自动检测神经元的活动模式。当在单光子（1p）显微镜获得的钙成像中检测到同步的神经活动时，Carignan 可以激活外部设备。结合光遗传学，我们的软件可以进行闭环实验，以研究大脑中特定类型神经元的功能。除了使现有的模式检测算法无缝实时运行之外，我们还开发了一个新的分类模块，该模块使用深度学习从假阳性中区分神经元。我们使用卷积和循环神经网络的组合来合并活动模式中的空间和时间特征。在假阳性神经元检测方面，我们的方法在 F1 评分方面优于现有的神经元检测方法。使用 Carignan，当观察到特定的神经活动时，实验人员可以激活或抑制一组神经元。由于该系统使用单光子显微镜，因此可以在自由移动的动物的大脑上使用，使其适用于广泛的实验范式。
