Calcium imaging records large-scale neuronal activity with cellular resolution in vivo. Automated, fast, and reliable active neuron segmentation is a critical step in the analysis workflow of utilizing neuronal signals in real-time behavioral studies for discovery of neuronal coding properties. Here, to exploit the full spatiotemporal information in two-photon calcium imaging movies, we propose a 3D convolutional neural network to identify and segment active neurons. By utilizing a variety of two-photon microscopy datasets, we show that our method outperforms state-of-the-art techniques and is on a par with manual segmentation. Furthermore, we demonstrate that the network trained on data recorded at a specific cortical layer can be used to accurately segment active neurons from another layer with different neuron density. Finally, our work documents significant tabulation flaws in one of the most cited and active online scientific challenges in neuron segmentation. As our computationally fast method is an invaluable tool for a large spectrum of real-time optogenetic experiments, we have made our open-source software and carefully annotated dataset freely available online.

Fast and reliable quantification of cone photoreceptors is a bottleneck in the clinical utilization of adaptive optics scanning light ophthalmoscope (AOSLO) systems for the study, diagnosis, and prognosis of retinal diseases. To-date, manual grading has been the sole reliable source of AOSLO quantification, as no automatic method has been reliably utilized for cone detection in real-world low-quality images of diseased retina. We present a novel deep learning based approach that combines information from both the confocal and non-confocal split detector AOSLO modalities to detect cones in subjects with achromatopsia. Our dual-mode deep learning based approach outperforms the state-of-the-art automated techniques and is on a par with human grading.

Deep down in Israeli society's consciousness there is an enormous taboo which is, at the same time, a never-ending source of black humour -the Shoah (Holocaust). Why is it almost impossible to make jokes about the Shoah? How is it possible to get away with it? 'IfI say the words 'Hitler' and 'tomato', I want you to put them into a sentence to make a nice little joke' (Uzi Weirs 'Back Cover' column in the weekly Ha'Ir (The City). Hitler and a tomato? Evil personified and a simple fruit?Were it not for the 'sentence' the absurdity of the situation would be obvious. But an added feeling of guilt creeps in almost at once. A joke about the Shoah? No way! And yet; it's just so outrageous that it's almost impossible not to laugh. Oh, of course, you excuse yourselfstraight away and claim that it's the laughter of '. despair, the only possible excuse you can have for laughing at the following joke: 'Where was the heaviest concentration of Jews during the extermination?' Answer: 'In the atmosphere.'And then you get lost in all the pointless justifications. You shouldn't be ashamed. Laughter is liberating. Laughter is a legitimate defensive response. Laughter cures melancholy. Laughter helps give you a better grasp of the seriousness of the subject. Laughter does this; laughter does that. The only problem is that, when it's the Shoah you're talking about, not one of these arguments is automatically justified. Israel has been around for 56 years and yet the Shoah is still a sort of stowaway in our national sense of humour. And this despite a number of futile attempts to slaughter this sacred cow. After all, what can ever be funny about 6 million corpses? Nothing. Six million Jews turned into ashes cannot be a subject for humour.On the other hand, what can give rise to jokes of a particularly ferocious kind are subjects such as the 'Shoah industry' and the way that it has been used for political purposes. An edifying example is provided by the following dialogue taken from Sokhnei Mesillot