Single-Neuron Level One-Photon Voltage Imaging With Sparsely Targeted Genetically Encoded Voltage Indicators

Voltage imaging of many neurons simultaneously at single-cell resolution is hampered by the difficulty of detecting small voltage signals from overlapping neuronal processes in neural tissue. Recent advances in genetically encoded voltage indicator (GEVI) imaging have shown single-cell resolution optical voltage recordings in intact tissue through imaging naturally sparse cell classes, sparse viral expression, soma restricted expression, advanced optical systems, or a combination of these. Widespread sparse and strong transgenic GEVI expression would enable straightforward optical access to a densely occurring cell type, such as cortical pyramidal cells. Here we demonstrate that a recently described sparse transgenic expression strategy can enable single-cell resolution voltage imaging of cortical pyramidal cells in intact brain tissue without restricting expression to the soma. We also quantify the functional crosstalk in brain tissue and discuss optimal imaging rates to inform future GEVI experimental design

Adamantane-Resistant Influenza Infection During the 2004–05 Season

Adamantane-resistant influenza A is an emerging problem, but infections caused by resistant and susceptible viruses have not been compared. We identified adamantane resistance in 47% of 152 influenza A virus (H3N2) isolates collected during 2005. Resistant and susceptible viruses caused similar symptoms and illness duration. The prevalence of resistance was highest in children

Self-oligomerization regulates stability of survival motor neuron protein isoforms by sequestering an SCF^Slmb degron

Spinal muscular atrophy (SMA) is caused by homozygous mutations in human SMN1. Expression of a duplicate gene (SMN2) primarily results in skipping of exon 7 and production of an unstable protein isoform, SMNΔ7. Although SMN2 exon skipping is the principal contributor to SMA severity, mechanisms governing stability of survival motor neuron (SMN) isoforms are poorly understood. We used a Drosophila model system and label-free proteomics to identify the SCFSlmb ubiquitin E3 ligase complex as a novel SMN binding partner. SCFSlmb interacts with a phosphor degron embedded within the human and fruitfly SMN YG-box oligomerization domains. Substitution of a conserved serine (S270A) interferes with SCFSlmb binding and stabilizes SMNΔ7. SMA-causing missense mutations that block multimerization of full-length SMN are also stabilized in the degron mutant background. Overexpression of SMNΔ7S270A, but not wild-type (WT) SMNΔ7, provides a protective effect in SMA model mice and human motor neuron cell culture systems. Our findings support a model wherein the degron is exposed when SMN is monomeric and sequestered when SMN forms higher-order multimers

Teasing apart optical correlates of neuronal excitation

Dynamic optical properties in neural tissue have the potential to revolutionize the way doctors and scientists measure and image brain function. The current state of functiona! imaging technology falls short of the spatial and temporal resolution needed to tease apart the neural circuitry underlying our every thought. Optically tracking the activity of individual brain cells over large populations carries many potential benefits, including development of treatment for mental illness and neurodegenerative diseases

Computer-generated holography enhances voltage dye fluorescence discrimination in adjacent neuronal structures

Voltage-sensitive fluorescence indicators enable tracking neuronal electrical signals simultaneously in multiple neurons or neuronal subcompartments difficult to access with patch electrodes. However, efficient widefield epifluorescence detection of rapid voltage fluorescence transients necessitates that imaged cells and structures lie sufficiently far from other labeled structures to avoid contamination from out of focal plane and scattered light. We overcame this limitation by exciting dye fluorescence with one-photon computer-generated holography shapes contoured to axons or dendrites of interest, enabling widefield detection of voltage fluorescence with high spatial specificity. By shaping light onto neighboring axons and dendrites, we observed that dendritic back-propagating action potentials were broader and slowly rising compared with axonal action potentials, differences not measured in the same structures illuminated with a large “pseudowidefield” (pWF) spot of the same excitation density. Shaped illumination trials showed reduced baseline fluorescence, higher baseline noise, and fractional fluorescence transient amplitudes two times greater than trials acquired with pWF illumination of the same regions

Advances in two photon scanning and scanless microscopy technologies for functional neural circuit imaging

Recent years have seen substantial developments in technology for imaging neural circuits, raising the prospect of large scale imaging studies of neural populations involved in information processing, with the potential to lead to step changes in our understanding of brain function and dysfunction. In this article we will review some key recent advances: improved fluorophores for single cell resolution functional neuroimaging using a two photon microscope; improved approaches to the problem of scanning active circuits; and the prospect of scanless microscopes which overcome some of the bandwidth limitations of current imaging techniques. These advances in technology for experimental neuroscience have in themselves led to technical challenges, such as the need for the development of novel signal processing and data analysis tools in order to make the most of the new experimental tools. We review recent work in some active topics, such as region of interest segmentation algorithms capable of demixing overlapping signals, and new highly accurate algorithms for calcium transient detection. These advances motivate the development of new data analysis tools capable of dealing with spatial or spatiotemporal patterns of neural activity, that scale well with pattern size.</p

Light-Field Microscopy for Optical Imaging of Neuronal Activity: When Model-Based Methods Meet Data-Driven Approaches.

Understanding how networks of neurons process information is one of the key challenges in modern neuroscience. A necessary step to achieve this goal is to be able to observe the dynamics of large populations of neurons over a large area of the brain. Light-field microscopy (LFM), a type of scanless microscope, is a particularly attractive candidate for high-speed three-dimensional (3D) imaging. It captures volumetric information in a single snapshot, allowing volumetric imaging at video frame-rates. Specific features of imaging neuronal activity using LFM call for the development of novel machine learning approaches that fully exploit priors embedded in physics and optics models. Signal processing theory and wave-optics theory could play a key role in filling this gap, and contribute to novel computational methods with enhanced interpretability and generalization by integrating model-driven and data-driven approaches. This paper is devoted to a comprehensive survey to state-of-the-art of computational methods for LFM, with a focus on model-based and data-driven approaches