The superficial layers of the superior colliculus (sSC) receive retinal input and project to thalamic regions - the dorsal lateral geniculate (dLGN) and lateral posterior (LP; or pulvinar) nuclei -that convey visual information to cortex. A critical step towards understanding the functional impact of sSC neurons on these parallel thalamo-cortical pathways is determining whether different classes of sSC neurons, which are known to respond to different features of visual stimuli, innervate overlapping or distinct thalamic targets. Here, we identified a transgenic mouse line that labels sSC neurons that project to dLGN but not LP. We utilized selective expression of fluorophores and channelrhodopsin in this and previously characterized mouse lines to demonstrate that distinct cell types give rise to sSC projections to dLGN and LP. We further show that the glutamatergic sSC cell type that projects to dLGN also provides input to the sSC cell type that projects to LP. These results clarify the cellular origin of parallel sSC-thalamo-cortical pathways and reveal an interaction between these pathways via local connections within the sSC.

What can we learn from a connectome? We constructed a simplified model of the first two stages of the fly visual system, the lamina and medulla. The resulting hexagonal lattice convolutional network was trained using backpropagation through time to perform object tracking in natural scene videos. Networks initialized with weights from connectome reconstructions automatically discovered well-known orientation and direction selectivity properties in T4 neurons and their inputs, while networks initialized at random did not. Our work is the first demonstration, that knowledge of the connectome can enable in silico predictions of the functional properties of individual neurons in a circuit, leading to an understanding of circuit function from structure alone.

Each training step for a variational autoencoder (VAE) requires us to sample from the approximate posterior, so we usually choose simple (e.g. factorised) approximate posteriors in which sampling is an efficient computation that fully exploits GPU parallelism. However, such simple approximate posteriors are often insufficient, as they eliminate statistical dependencies in the posterior. While it is possible to use normalizing flow approximate posteriors for continuous latents, some problems have discrete latents and strong statistical dependencies. The most natural approach to model these dependencies is an autoregressive distribution, but sampling from such distributions is inherently sequential and thus slow. We develop a fast, parallel sampling procedure for autoregressive distributions based on fixed-point iterations which enables efficient and accurate variational inference in discrete state-space latent variable dynamical systems. To optimize the variational bound, we considered two ways to evaluate probabilities: inserting the relaxed samples directly into the pmf for the discrete distribution, or converting to continuous logistic latent variables and interpreting the K-step fixed-point iterations as a normalizing flow. We found that converting to continuous latent variables gave considerable additional scope for mismatch between the true and approximate posteriors, which resulted in biased inferences, we thus used the former approach. Using our fast sampling procedure, we were able to realize the benefits of correlated posteriors, including accurate uncertainty estimates for one cell, and accurate connectivity estimates for multiple cells, in an order of magnitude less time.

The mammalian hippocampus forms a cognitive map using neurons that fire according to an animal's position ("place cells") and many other behavioral and cognitive variables. The responses of these neurons are shaped by their presynaptic inputs and the nature of their postsynaptic integration. In CA1 pyramidal neurons, spatial responses in vivo exhibit a strikingly supralinear dependence on baseline membrane potential. The biophysical mechanisms underlying this nonlinear cellular computation are unknown. Here, through a combination of in vitro, in vivo, and in silico approaches, we show that persistent sodium current mediates the strong membrane potential dependence of place cell activity. This current operates at membrane potentials below the action potential threshold and over seconds-long timescales, mediating a powerful and rapidly reversible amplification of synaptic responses, which drives place cell firing. Thus, we identify a biophysical mechanism that shapes the coding properties of neurons composing the hippocampal cognitive map.

Many forms of human and animal behavior involve head movements. A new study reveals the neural code for three-dimensional head movements in the midbrain of freely moving mice.

Highlights:

• Biological specimens introduce wavefront aberrations and deteriorate the image quality of optical microscopy.
• Adaptive optics is used in optical microscopy to recover ideal imaging performance.
• Adaptive optical imaging improves structural imaging of neurons, allowing for synaptic-level resolution at depth.
• Adaptive optical imaging leads to a more accurate characterization of the functional properties of neurons.

With the ability to correct for the aberrations introduced by biological specimens, adaptive optics—a method originally developed for astronomical telescopes—has been applied to optical microscopy to recover diffraction-limited imaging performance deep within living tissue. In particular, this technology has been used to improve image quality and provide a more accurate characterization of both structure and function of neurons in a variety of living organisms. Among its many highlights, adaptive optical microscopy has made it possible to image large volumes with diffraction-limited resolution in zebrafish larval brains, to resolve dendritic spines over 600μm deep in the mouse brain, and to more accurately characterize the orientation tuning properties of thalamic boutons in the primary visual cortex of awake mice.

Recent advances in understanding intracellular amino acid transport and mechanistic target of rapamycin complex 1 (mTORC1) signaling shed light on solute carrier 38, family A member 9 (SLC38A9), a lysosomal transporter responsible for the binding and translocation of several essential amino acids. Here we present the first crystal structure of SLC38A9 from Danio rerio in complex with arginine. As captured in the cytosol-open state, the bound arginine was locked in a transitional state stabilized by transmembrane helix 1 (TM1) of drSLC38A9, which was anchored at the groove between TM5 and TM7. These anchoring interactions were mediated by the highly conserved WNTMM motif in TM1, and mutations in this motif abolished arginine transport by drSLC38A9. The underlying mechanism of substrate binding is critical for sensitizing the mTORC1 signaling pathway to amino acids and for maintenance of lysosomal amino acid homeostasis. This study offers a first glimpse into a prototypical model for SLC38 transporters.

This protocol describes how to apply appropriate pharmacological controls to induce mitochondrial fusion or fission in studies of mitochondria morphology for four different mammalian cell types, HepG2 human liver hepatocellular carcinoma cells, MCF7 human breast adenocarcinoma cells, HEK293 human embryonic kidney cells, and collagen sandwich culture of primary rat hepatocytes. The protocol provides methods of treating cells with these pharmacological controls, staining mitochondria with commercially available MitoTracker Green and TMRE dyes, and imaging the mitochondrial morphology in live cells using a confocal fluorescent microscope. It also describes the cell culture methods needed for this protocol. © 2018 by John Wiley & Sons, Inc.

Fluorescent proteins and vital dyes are invaluable tools for studying dynamic processes within living cells. However, the ability to distinguish more than a few different fluorescent reporters in a single sample is limited by the spectral overlap of available fluorophores. Here, we present a protocol for imaging live cells labeled with six fluorophores simultaneously. A confocal microscope with a spectral detector is used to acquire images, and linear unmixing algorithms are applied to identify the fluorophores present in each pixel of the image. We describe the application of this method to visualize the dynamics of six different organelles, and to quantify the contacts between organelles. However, this method can be used to image any molecule amenable to tagging with a fluorescent probe. Thus, multispectral live-cell imaging is a powerful tool for systems-level analysis of cellular organization and dynamics. © 2018 by John Wiley & Sons, Inc.