Two-photon probe excitation data are commonly presented as absorption cross section or molecular brightness (the detected fluorescence rate per molecule). We report two-photon molecular brightness spectra for a diverse set of organic and genetically encoded probes with an automated spectroscopic system based on fluorescence correlation spectroscopy. The two-photon action cross section can be extracted from molecular brightness measurements at low excitation intensities, while peak molecular brightness (the maximum molecular brightness with increasing excitation intensity) is measured at higher intensities at which probe photophysical effects become significant. The spectral shape of these two parameters was similar across all dye families tested. Peak molecular brightness spectra, which can be obtained rapidly and with reduced experimental complexity, can thus serve as a first-order approximation to cross-section spectra in determining optimal wavelengths for two-photon excitation, while providing additional information pertaining to probe photostability. The data shown should assist in probe choice and experimental design for multiphoton microscopy studies. Further, we show that, by the addition of a passive pulse splitter, nonlinear bleaching can be reduced-resulting in an enhancement of the fluorescence signal in fluorescence correlation spectroscopy by a factor of two. This increase in fluorescence signal, together with the observed resemblance of action cross section and peak brightness spectra, suggests higher-order photobleaching pathways for two-photon excitation.

The hippocampus is critical for producing stable representations of familiar spaces. How these representations arise is poorly understood, largely because changes to hippocampal inputs have not been measured during spatial learning. Here, using intracellular recording, we monitored inputs and plasticity-inducing complex spikes (CSs) in CA1 neurons while mice explored novel and familiar virtual environments. Inputs driving place field spiking increased in amplitude - often suddenly - during novel environment exploration. However, these increases were not sustained in familiar environments. Rather, the spatial tuning of inputs became increasingly similar across repeated traversals of the environment with experience - both within fields and throughout the whole environment. In novel environments, CSs were not necessary for place field formation. Our findings support a model in which initial inhomogeneities in inputs are amplified to produce robust place field activity, then plasticity refines this representation into one with less strongly modulated, but more stable, inputs for long-term storage.

From 1980 to 1992, a series of influential papers reported on the discovery, genetics, and evolution of a periodic cycling of the interval between Drosophila male courtship song pulses. The molecular mechanisms underlying this periodicity were never described. To reinitiate investigation of this phenomenon, we previously performed automated segmentation of songs but failed to detect the proposed rhythm [Arthur BJ, et al. (2013) BMC Biol 11:11; Stern DL (2014) BMC Biol 12:38]. Kyriacou et al. [Kyriacou CP, et al. (2017) Proc Natl Acad Sci USA 114:1970-1975] report that we failed to detect song rhythms because (i) our flies did not sing enough and (ii) our segmenter did not identify many of the song pulses. Kyriacou et al. manually annotated a subset of our recordings and reported that two strains displayed rhythms with genotype-specific periodicity, in agreement with their original reports. We cannot replicate this finding and show that the manually annotated data, the original automatically segmented data, and a new dataset provide no evidence for either the existence of song rhythms or song periodicity differences between genotypes. Furthermore, we have reexamined our methods and analysis and find that our automated segmentation method was not biased to prevent detection of putative song periodicity. We conclude that there is no evidence for the existence of Drosophila courtship song rhythms.

During courtship males attract females with elaborate behaviors. In mice, these displays include ultrasonic vocalizations. Ultrasonic courtship vocalizations were previously attributed to the courting male, despite evidence that both sexes produce virtually indistinguishable vocalizations. Because of this similarity, and the difficulty of assigning vocalizations to individuals, the vocal contribution of each individual during courtship is unknown. To address this question, we developed a microphone array system to localize vocalizations from socially interacting, individual adult mice. With this system, we show that female mice vocally interact with males during courtship. Males and females jointly increased their vocalization rates during chases. Furthermore, a female's participation in these vocal interactions may function as a signal that indicates a state of increased receptivity. Our results reveal a novel form of vocal communication during mouse courtship, and lay the groundwork for a mechanistic dissection of communication during social behavior.

SUMMARY: Here, we propose Fourier ring correlation-based quality estimation (FRC-QE) as a new metric for automated image quality estimation in 3D fluorescence microscopy acquisitions of cleared organoids that yields comparable measurements across experimental replicates, clearing protocols and works for different microscopy modalities.

AVAILABILITY AND IMPLEMENTATION: FRC-QE is written in ImgLib2/Java and provided as an easy-to-use and macro-scriptable plugin for Fiji. Code, documentation, sample images and further information can be found under https://github.com/PreibischLab/FRC-QE.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Identifying the input-output operations of neurons requires measurements of synaptic transmission simultaneously at many of a neuron’s thousands of inputs in the intact brain. To facilitate this goal, we engineered and screened 3365 variants of the fluorescent protein glutamate indicator iGluSnFR3 in neuron culture, and selected variants in the mouse visual cortex. Two variants have high sensitivity, fast activation (< 2 ms) and deactivation times tailored for recording large populations of synapses (iGluSnFR4s, 153 ms) or rapid dynamics (iGluSnFR4f, 26 ms). By imaging action-potential evoked signals on axons and visually-evoked signals on dendritic spines, we show that iGluSnFR4s/4f primarily detect local synaptic glutamate with single-vesicle sensitivity. The indicators detect a wide range of naturalistic synaptic transmission, including in the vibrissal cortex layer 4 and in hippocampal CA1 dendrites. iGluSnFR4 increases the sensitivity and scale (4s) or speed (4f) of tracking information flow in neural networks in vivo.

Identifying the input-output operations of neurons requires measurements of synaptic transmission simultaneously at many of a neuron’s thousands of inputs in the intact brain. To facilitate this goal, we engineered and screened 3365 variants of the fluorescent protein glutamate indicator iGluSnFR3 in neuron culture, and selected variants in the mouse visual cortex. Two variants have high sensitivity, fast activation (< 2 ms) and deactivation times tailored for recording large populations of synapses (iGluSnFR4s, 153 ms) or rapid dynamics (iGluSnFR4f, 26 ms). By imaging action-potential evoked signals on axons and visually-evoked signals on dendritic spines, we show that iGluSnFR4s/4f primarily detect local synaptic glutamate with single-vesicle sensitivity. The indicators detect a wide range of naturalistic synaptic transmission, including in the vibrissal cortex layer 4 and in hippocampal CA1 dendrites. iGluSnFR4 increases the sensitivity and scale (4s) or speed (4f) of tracking information flow in neural networks in vivo.

The HMMER website, available at http://www.ebi.ac.uk/Tools/hmmer/, provides access to the protein homology search algorithms found in the HMMER software suite. Since the first release of the website in 2011, the search repertoire has been expanded to include the iterative search algorithm, jackhmmer. The continued growth of the target sequence databases means that traditional tabular representations of significant sequence hits can be overwhelming to the user. Consequently, additional ways of presenting homology search results have been developed, allowing them to be summarised according to taxonomic distribution or domain architecture. The taxonomy and domain architecture representations can be used in combination to filter the results according to the needs of a user. Searches can also be restricted prior to submission using a new taxonomic filter, which not only ensures that the results are specific to the requested taxonomic group, but also improves search performance. The repertoire of profile hidden Markov model libraries, which are used for annotation of query sequences with protein families and domains, has been expanded to include the libraries from CATH-Gene3D, PIRSF, Superfamily and TIGRFAMs. Finally, we discuss the relocation of the HMMER webserver to the European Bioinformatics Institute and the potential impact that this will have.

HortaCloud is a cloud-based, open-source platform designed to facilitate the collaborative reconstruction of long-range projection neurons from whole-brain light microscopy data. By providing virtual environments directly within the cloud, it eliminates the need for costly and time-consuming data downloads, allowing researchers to work efficiently with terabyte- scale volumetric datasets. Standardization of computational resources in the cloud make deployment easier and more predictable. The pay-as-you-go cloud model reduces adoption barriers by eliminating upfront investments in expensive hardware. Finally, HortaCloud’s decentralized architecture enables global collaboration between researchers and between institutions.

Machine learning models are only as good as the data to which they are fit. As such, it is always preferable to use as much data as possible in training models. What data can be used for fitting a model depends a lot on the formulation of the task. We introduce Hot-Distance, a novel segmentation target that incorporates the strength of signed boundary distance prediction with the flexibility of one-hot encoding, to increase the amount of usable training data for segmentation of subcellular structures in focused ion beam scanning electron microscopy (FIB-SEM).