A three-dimensional single-cell-resolution mammalian brain atlas will accelerate systems-level identification and analysis of cellular circuits underlying various brain functions. However, its construction requires efficient subcellular-resolution imaging throughout the entire brain. To address this challenge, we developed a fluorescent-protein-compatible, whole-organ clearing and homogeneous expansion protocol based on an aqueous chemical solution (CUBIC-X). The expanded, well-cleared brain enabled us to construct a point-based mouse brain atlas with single-cell annotation (CUBIC-Atlas). CUBIC-Atlas reflects inhomogeneous whole-brain development, revealing a significant decrease in the cerebral visual and somatosensory cortical areas during postnatal development. Probabilistic activity mapping of pharmacologically stimulated Arc-dVenus reporter mouse brains onto CUBIC-Atlas revealed the existence of distinct functional structures in the hippocampal dentate gyrus. CUBIC-Atlas is shareable by an open-source web-based viewer, providing a new platform for whole-brain cell profiling.

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The authors wish to note the following: "We wish to acknowledge that during the writing of our manuscript we had access to an unpublished preprint from the Princeton group of H. Yang and coauthors, which similarly dealt with the theory of feedback control of Janus particles based on optically heated self-thermophoretic motion of Janus particles (photon nudging).* Through the state-of-the-art realization of 3D control, they analyzed the statistics and traveling time for a hot microswimmer in light of the optimal strategy for run-and-tumble motion of Escherichia coli. They developed a rigorous theory for evaluating on-time (self-propulsion period) and off-time (rotational diffusion period) distributions by making use of the first-passage time distribution (FPTD), which agreed with exponential tails known in biology. The optimum acceptance angle for self-propulsion was determined as 90 degrees for photon nudging, similar to the prediction for the optimal chemotactic strategy for E. coli (27). The same paper (27) hinted to us to use the probability distribution function with absorbing boundary conditions in solving the heat (diffusion) equation. The solution can be found in Selmke's paper* and our paper, as well as Zauderer's book (25). However, the normalization factor, which is necessary to compare the theory and the simulation, cannot be found to the best of our knowledge except for in our paper. FPTD is used to formulate the exact solution of the average displacement during active Brownian motion (ABM) in our paper, while in Selmke's paper,* it is used either to obtain exponential tails in on-time/offtime distribution or to obtain an asymptotic form to conclude the optimal acceptance angle to be 90 degrees. Our results revealed that the optimal angle varies from 0 to 90 degrees depending on signal to noise ratio for the deterministic feedback. Therefore, the usages and conclusions are very different."Accordingly, we wish to add the following text on page 1 in the right column: 'Researchers have been inspired by chemotactic behaviors of microorganisms and implemented such functions to self-propelled particles (11, 12, 34) for targeting their motion. Run-and-tumble is a well-known strategy for tactic behavior of E. coli, and it has been thoroughly compared with ABM of self-propelled particles from the view point of statistical mechanics (35)(36)(37)(38). The concept of run-and-tumble has been applied to Janus particles (13). The optimization of the run-andtumble algorithm for controlling microswimmers has been carried out rigorously using a first-passage time approach (Selmke et al., unpublished*).' "We apologize for the oversight in removing the reference to Selmke et al., which had been included in an earlier version of the paper. The reference was deleted because PNAS does not allow citations to unpublished work." Published under the PNAS license.www.pnas.org/cgi

In this photo essay, we present a sampling of technologies from laboratories at the forefront of whole-brain clearing and imaging for high-resolution analysis of cell populations and neuronal circuits. The data presented here were provided for the eponymous Mini-Symposium presented at the Society for Neuroscience's 2018 annual meeting.

Tissue clearing is one of the most powerful strategies for a comprehensive analysis of disease progression. Here, we established an integrated pipeline that combines tissue clearing, 3D imaging, and machine learning and applied to a mouse tumour model of experimental lung metastasis using human lung adenocarcinoma A549 cells. This pipeline provided the spatial information of the tumour microenvironment. We further explored the role of transforming growth factor-β (TGF-β) in cancer metastasis. TGF-β-stimulated cancer cells enhanced metastatic colonization of unstimulated-cancer cells in vivo when both cells were mixed. RNA-sequencing analysis showed that expression of the genes related to coagulation and inflammation were up-regulated in TGF-β-stimulated cancer cells. Further, whole-organ analysis revealed accumulation of platelets or macrophages with TGF-β-stimulated cancer cells, suggesting that TGF-β might promote remodelling of the tumour microenvironment, enhancing the colonization of cancer cells. Hence, our integrated pipeline for 3D profiling will help the understanding of the tumour microenvironment.

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Recent advancements in tissue clearing technologies have offered unparalleled opportunities for researchers to explore the whole mouse brain at cellular resolution. With the expansion of this experimental technique, however, a scalable and easy-to-use computational tool is in demand to effectively analyze and integrate whole-brain mapping datasets. To that end, here we present CUBIC-Cloud, a cloud-based framework to quantify, visualize and integrate whole mouse brain data. CUBIC-Cloud is a fully automated system where users can upload their whole-brain data, run analysis and publish the results. We demonstrate the generality of CUBIC-Cloud by a variety of applications. First, we investigated brain-wide distribution of PV, Sst, ChAT, Th and Iba1 expressing cells. Second, Aβ plaque deposition in AD model mouse brains were quantified. Third, we reconstructed neuronal activity profile under LPS-induced inflammation by c-Fos immunostaining. Last, we show brain-wide connectivity mapping by pseudo-typed Rabies virus. Together, CUBIC-Cloud provides an integrative platform to advance scalable and collaborative whole-brain mapping.

The homeostatic regulation of sleep is characterized by rebound sleep after prolonged wakefulness, but the molecular and cellular mechanisms underlying this regulation are still unknown. We show here that Ca2+/calmodulin-dependent protein kinase II (CaMKII)-dependent activity control of parvalbumin (PV)-expressing cortical neurons is involved in sleep homeostasis regulation. Prolonged wakefulness enhances cortical PV-neuron activity. Chemogenetic suppression or activation of cortical PV neurons inhibits or induces rebound sleep, implying that rebound sleep is dependent on increased activity of cortical PV neurons. Furthermore, we discovered that CaMKII kinase activity boosts the activity of cortical PV neurons, and that kinase activity is important for homeostatic sleep rebound. We propose that CaMKII-dependent PV-neuron activity represents negative feedback inhibition of cortical neural excitability, which serves as the distributive cortical circuits for sleep homeostatic regulation.