We report an intensiometric, near-infrared fluorescent, genetically encoded calcium ion (Ca) indicator (GECI) with excitation and emission maxima at 678 and 704 nm, respectively. This GECI, designated NIR-GECO1, enables imaging of Ca transients in cultured mammalian cells and brain tissue with sensitivity comparable to that of currently available visible-wavelength GECIs. We demonstrate that NIR-GECO1 opens up new vistas for multicolor Ca imaging in combination with other optogenetic indicators and actuators.

Animals are not simple input-output machines. Their responses to even very similar stimuli are variable. A key, long-standing question in neuroscience is to understand the neural correlates of such behavioral variability. To reveal these correlates, behavior and neural population activity must be related to one another on single trials. Such analysis is challenging due to the dynamical nature of brain function (e.g., in decision making), heterogeneity across neurons and limited sampling of the relevant neural population. By analyzing population recordings from mouse frontal cortex in perceptual decision-making tasks, we show that an analysis approach tailored to the coarse grain features of the dynamics is able to reveal previously unrecognized structure in the organization of population activity. This structure is similar on error and correct trials, suggesting dynamics that may be constrained by the underlying circuitry, is able to predict multiple aspects of behavioral variability and reveals long time-scale modulation of population activity.

Advances in fluorescence microscopy enable monitoring larger brain areas in-vivo with finer time resolution. The resulting data rates require reproducible analysis pipelines that are reliable, fully automated, and scalable to datasets generated over the course of months. We present CaImAn, an open-source library for calcium imaging data analysis. CaImAn provides automatic and scalable methods to address problems common to pre-processing, including motion correction, neural activity identification, and registration across different sessions of data collection. It does this while requiring minimal user intervention, with good scalability on computers ranging from laptops to high-performance computing clusters. CaImAn is suitable for two-photon and one-photon imaging, and also enables real-time analysis on streaming data. To benchmark the performance of CaImAn we collected and combined a corpus of manual annotations from multiple labelers on nine mouse two-photon datasets. We demonstrate that CaImAn achieves near-human performance in detecting locations of active neurons

BACKGROUND: Unbiased screening studies have repeatedly identified actin-related proteins as one of the families of proteins most influenced by neurotrauma. Nevertheless, the status quo model of cytoskeletal reorganization after neurotrauma excludes actin and incorporates only changes in microtubules and intermediate filaments. Actin is excluded in part because it is difficult to image with conventional techniques. However, recent innovations in fluorescent microscopy provide an opportunity to image the actin cytoskeleton at super-resolution resolution in living cells. This study applied these innovations to an in vitro model of neurotrauma.

NEW METHOD: New methods are introduced for traumatizing neurons before imaging them with high speed structured illumination microscopy or lattice light sheet microscopy. Also, methods for analyzing structured illumination microscopy images to quantify post-traumatic neurite dystrophy are presented.

RESULTS: Human induced pluripotent stem cell-derived neurons exhibited actin organization typical of immature neurons. Neurite dystrophy increased after trauma but was not influenced by jasplakinolide treatment. The F-actin content of dystrophies varied greatly from one dystrophy to another.

COMPARISON WITH EXISTING METHODS: In contrast to fixation dependent methods, these methods capture the evolution of the actin cytoskeleton over time in a living cell. In contrast to prior methods based on counting dystrophies, this quantification scheme parameterizes the severity of a given dystrophy as it evolves from a local swelling to an almost-perfect spheroid that threatens to transect the neurite.

CONCLUSIONS: These methods can be used to investigate genetic factors and therapeutic interventions that modulate the course of neurite dystrophy after trauma.

Understanding the circuit mechanisms behind motion detection is a long-standing question in visual neuroscience. In , recent synapse-level connectomes in the optic lobe, particularly in ON-pathway (T4) receptive-field circuits, in concert with physiological studies, suggest an increasingly intricate motion model compared with the ubiquitous Hassenstein-Reichardt model, while our knowledge of OFF-pathway (T5) has been incomplete. Here we present a conclusive and comprehensive connectome that for the first time integrates detailed connectivity information for inputs to both T4 and T5 pathways in a single EM dataset covering the entire optic lobe. With novel reconstruction methods using automated synapse prediction suited to such a large connectome, we successfully corroborate previous findings in the T4 pathway and comprehensively identify inputs and receptive fields for T5. While the two pathways are likely evolutionarily linked and indeed exhibit many similarities, we uncover interesting differences and interactions that may underlie their distinct functional properties.

Optical and electron microscopy have made tremendous inroads toward understanding the complexity of the brain. However, optical microscopy offers insufficient resolution to reveal subcellular details, and electron microscopy lacks the throughput and molecular contrast to visualize specific molecular constituents over millimeter-scale or larger dimensions. We combined expansion microscopy and lattice light-sheet microscopy to image the nanoscale spatial relationships between proteins across the thickness of the mouse cortex or the entire Drosophila brain. These included synaptic proteins at dendritic spines, myelination along axons, and presynaptic densities at dopaminergic neurons in every fly brain region. The technology should enable statistically rich, large-scale studies of neural development, sexual dimorphism, degree of stereotypy, and structural correlations to behavior or neural activity, all with molecular contrast.

Mutations in the retinal protein retinoschisin (RS1) cause progressive loss of vision in young males, a form of macular degeneration called X-linked retinoschisis (XLRS). We previously solved the structure of RS1, a 16-mer composed of paired back-to-back octameric rings. Here, we show by cryo-electron microscopy that RS1 16-mers can assemble into extensive branched networks. We classified the different configurations, finding four types of interaction between the RS1 molecules. The predominant configuration is a linear strand with a wavy appearance. Three less frequent types constitute the branch points of the network. In all cases, the "spikes" around the periphery of the double rings are involved in these interactions. In the linear strand, a loop (usually referred to as spike 1) occurs on both sides of the interface between neighboring molecules. Mutations in this loop suppress secretion, indicating the possibility of intracellular higher-order assembly. These observations suggest that branched networks of RS1 may play a stabilizing role in maintaining the integrity of the retina.

Serial electron microscopic analysis shows that the Drosophila brain at hatching possesses a large fraction of developmentally arrested neurons with a small soma, heterochromatin-rich nucleus, and unbranched axon lacking synapses. We digitally reconstructed all 802 "small undifferentiated" (SU) neurons and assigned them to the known brain lineages. By establishing the coordinates and reconstructing trajectories of the SU neuron tracts, we provide a framework of landmarks for the ongoing analyses of the L1 brain circuitry. To address the later fate of SU neurons, we focused on the 54 SU neurons belonging to the DM1-DM4 lineages, which generate all columnar neurons of the central complex. Regarding their topologically ordered projection pattern, these neurons form an embryonic nucleus of the fan-shaped body ("FB pioneers"). Fan-shaped body pioneers survive into the adult stage, where they develop into a specific class of bi-columnar elements, the pontine neurons. Later born, unicolumnar DM1-DM4 neurons fasciculate with the fan-shaped body pioneers. Selective ablation of the fan-shaped body pioneers altered the architecture of the larval fan-shaped body primordium but did not result in gross abnormalities of the trajectories of unicolumnar neurons, indicating that axonal pathfinding of the two systems may be controlled independently. Our comprehensive spatial and developmental analysis of the SU neurons adds to our understanding of the establishment of neuronal circuitry.

Optical imaging has become a powerful tool for studying brains . The opacity of adult brains makes microendoscopy, with an optical probe such as a gradient index (GRIN) lens embedded into brain tissue to provide optical relay, the method of choice for imaging neurons and neural activity in deeply buried brain structures. Incorporating a Bessel focus scanning module into two-photon fluorescence microendoscopy, we extended the excitation focus axially and improved its lateral resolution. Scanning the Bessel focus in 2D, we imaged volumes of neurons at high-throughput while resolving fine structures such as synaptic terminals. We applied this approach to the volumetric anatomical imaging of dendritic spines and axonal boutons in the mouse hippocampus, and functional imaging of GABAergic neurons in the mouse lateral hypothalamus .

This tutorial paper deals with the Internal Model Principle (IMP) from different perspectives. The goal is to start from the principle as introduced and commonly used in the control theory and then enlarge the vision to other fields where “internal models” play a role. The biology and neuroscience fields are specifically targeted in the paper. The paper ends by presenting an “abstract” theory of IMP applicable to a large class of systems.