Quantitative phase imaging (QPI) has proven to be a valuable tool for advanced biological and pharmacological research, providing phase information for the study of cell features and physiology in label-free conditions. The next step for QPI to become a gold standard is the quantitative assessment of the phase gradients over the different microscopy setups. Given the large variety of QPI systems, a systematic comparison is a challenging task, and requires a calibration target representative of the living samples. In this paper, we introduce a tailor-made 3D-printed phantom derived from phase images of eukaryotic cells. It comprises typical morphologies and optical thicknesses found in biological cultures and is characterized with digital holographic microscopy (reference measurements). The performance of three different full field QPI optical systems, in terms of optical path difference and dry mass accuracy, were evaluated. This phantom opens up other possibilities for the validation of reconstruction algorithms and post-processing routines, and paves the way for calibration targets designed ad hoc for specific biological questions.

High-resolution tissue imaging is often compromised by sample-induced optical aberrations that degrade resolution and contrast. While wavefront sensor-based adaptive optics (AO) can measure these aberrations, such hardware solutions are typically complex, expensive to implement, and slow when serially mapping spatially varying aberrations across large fields of view. Here, we introduce AOViFT (Adaptive Optical Vision Fourier Transformer)---a machine learning-based aberration sensing framework built around a 3D multistage Vision Transformer that operates on Fourier domain embeddings. AOViFT infers aberrations and restores diffraction-limited performance in puncta-labeled specimens with substantially reduced computational cost, training time, and memory footprint compared to conventional architectures or real-space networks. We validated AOViFT on live gene-edited zebrafish embryos, demonstrating its ability to correct spatially varying aberrations using either a deformable mirror or post-acquisition deconvolution. By eliminating the need for the guide star and wavefront sensing hardware and simplifying the experimental workflow, AOViFT lowers technical barriers for high-resolution volumetric microscopy across diverse biological samples.

Hedonic eating is defined as food consumption driven by palatability without physiological need. However, neural control of palatable food intake is poorly understood. We discovered that hedonic eating is controlled by a neural pathway from the peri-locus ceruleus to the ventral tegmental area (VTA). Using photometry-calibrated optogenetics, we found that VTA dopamine (VTA) neurons encode palatability to bidirectionally regulate hedonic food consumption. VTA neuron responsiveness was suppressed during food consumption by semaglutide, a glucagon-like peptide receptor 1 (GLP-1R) agonist used as an antiobesity drug. Mice recovered palatable food appetite and VTA neuron activity during repeated semaglutide treatment, which was reversed by consumption-triggered VTA neuron inhibition. Thus, hedonic food intake activates VTA neurons, which sustain further consumption, a mechanism that opposes appetite reduction by semaglutide.

Vimentin intermediate filaments (VIFs) form complex, tightly packed networks; due to this density, traditional imaging approaches cannot discern single-filament behavior. To address this, we developed and validated a sparse vimentin-SunTag labeling strategy, enabling single-particle tracking of individual VIFs and providing a sensitive, unbiased, and quantitative method for measuring global VIF motility. Using this approach, we define the steady-state VIF motility rate, showing a constant ∼8% of VIFs undergo directed microtubule-based motion irrespective of subcellular location or local filament density. Significantly, our single-particle tracking approach revealed uncorrelated motion of individual VIFs within bundles, an observation seemingly at odds with conventional models of tightly cross-linked bundles. To address this, we acquired high-resolution focused ion beam scanning electron microscopy volumes of vitreously frozen cells and reconstructed three-dimensional VIF bundles, finding that they form only loosely organized, semi-coherent structures from which single VIFs frequently emerge to locally engage neighboring microtubules. Overall, this work demonstrates single VIF dynamics and organization in the cellular milieu for the first time.

bioRxiv Preprint: https://doi.org/10.1101/2024.06.10.598346

Synchronous neuronal ensembles play a pivotal role in the consolidation of long-term memory in the hippocampus. However, their organization during the acquisition of spatial memory remains less clear. In this study, we used neuronal population voltage imaging to investigate the synchronization patterns of CA1 pyramidal neuronal ensembles during the exploration of a new environment, a critical phase for spatial memory acquisition. We found synchronous ensembles comprising approximately 40% of CA1 pyramidal neurons, firing simultaneously in brief windows (∼25ms) during immobility and locomotion in novel exploration. Notably, these synchronous ensembles were not associated with ripple oscillations but were instead phase-locked to local field potential theta waves. Specifically, the subthreshold membrane potentials of neurons exhibited coherent theta oscillations with a depolarizing peak at the moment of synchrony. Among newly formed place cells, pairs with more robust synchronization during locomotion displayed more distinct place-specific activities. These findings underscore the role of synchronous ensembles in coordinating place cells of different place fields.

Synaptic plasticity alters neuronal connections in response to experience, which is thought to underlie learning and memory. However, the loci of learning-related synaptic plasticity, and the degree to which plasticity is localized or distributed, remain largely unknown. Here we describe a new method, DELTA, for mapping brain-wide changes in synaptic protein turnover with single-synapse resolution, based on Janelia Fluor dyes and HaloTag knock-in mice. During associative learning, the turnover of the ionotropic glutamate receptor subunit GluA2, an indicator of synaptic plasticity, was enhanced in several brain regions, most markedly hippocampal area CA1. More broadly distributed increases in the turnover of synaptic proteins were observed in response to environmental enrichment. In CA1, GluA2 stability was regulated in an input-specific manner, with more turnover in layers containing input from CA3 compared to entorhinal cortex. DELTA will facilitate exploration of the molecular and circuit basis of learning and memory and other forms of plasticity at scales ranging from single synapses to the entire brain.

A tool to map changes in synaptic strength during a defined time window could provide powerful insights into the mechanisms of learning and memory. Here we developed a technique, Extracellular Protein Surface Labeling in Neurons (EPSILON), to map α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR) exocytosis in vivo by sequential pulse-chase labeling of surface AMPARs with membrane-impermeable dyes. This approach yields synaptic-resolution maps of AMPAR exocytosis, a proxy for synaptic potentiation, in genetically targeted neurons during memory formation. In mice undergoing contextual fear conditioning, we investigated the relationship between synapse-level AMPAR exocytosis in CA1 pyramidal neurons and cell-level expression of the immediate early gene product cFos, a frequently used marker of engram neurons. We observed a strong correlation between AMPAR exocytosis and cFos expression, suggesting a synaptic mechanism for the association of cFos expression with memory engrams. The EPSILON technique is a useful tool for mapping synaptic plasticity and may be extended to investigate trafficking of other transmembrane proteins.

Internal signals from the body and external signals from the environment are processed by brain-wide circuits to guide behavior. However, the complete brain-wide circuit activity underlying interoception—the perception of bodily signals—and its interactions with sensorimotor circuits remain unclear due to technical barriers to accessing whole-brain activity at the cellular level during organ physiology perturbations. We developed an all-optical system for whole-brain neuronal imaging in behaving larval zebrafish during optical uncaging of gut-targeted nutrients and visuo-motor stimulation. Widespread neural activity throughout the brain encoded nutrient delivery, unfolding on multiple timescales across many specific peripheral and central regions. Evoked activity depended on delivery location and occurred with amino acids and D-glucose, but not L-glucose. Many gut-sensitive neurons also responded to swimming and visual stimuli, with brainstem areas primarily integrating gut and motor signals and midbrain regions integrating gut and visual signals. This platform links body-brain communication studies to brain-wide neural computation in awake, behaving vertebrates.

Monitoring GABAergic inhibition in the nervous system has been enabled by development of an intensiometric molecular sensor that directly detects GABA. However the first generation iGABASnFR exhibits low signal-to-noise and suboptimal kinetics, making in vivo experiments challenging. To improve sensor performance, we targeted several sites in the protein for near-saturation mutagenesis, and evaluated the resulting sensor variants in a high throughput screening system using evoked synaptic release in primary cultured neurons. This identified a sensor variant, iGABASnFR2, with 4.2-fold improved sensitivity and 20% faster kinetics, and binding affinity that remained in a range sensitive to changes in GABA concentration at synapses. We also identified sensors with an inverted response, decreasing fluorescence intensity upon GABA binding. We termed the best such negative-going sensor iGABASnFR2n, which can be used to corroborate observations with the positive-going sensor. These improvements yielded a qualitative enhancement of in vivo performance, enabling us to make the first measurements of direction selective GABA release in the retina and confirm a longstanding hypothesis for how sensitivity to motion arises in the visual system.

Vision provides animals with detailed information about their surroundings, conveying diverse features such as color, form, and movement across the visual scene. Computing these parallel spatial features requires a large and diverse network of neurons, such that in animals as distant as flies and humans, visual regions comprise half the brain’s volume. These visual brain regions often reveal remarkable structure-function relationships, with neurons organized along spatial maps with shapes that directly relate to their roles in visual processing. To unravel the stunning diversity of a complex visual system, a careful mapping of the neural architecture matched to tools for targeted exploration of that circuitry is essential. Here, we report a new connectome of the right optic lobe from a male Drosophila central nervous system FIB-SEM volume and a comprehensive inventory of the fly’s visual neurons. We developed a computational framework to quantify the anatomy of visual neurons, establishing a basis for interpreting how their shapes relate to spatial vision. By integrating this analysis with connectivity information, neurotransmitter identity, and expert curation, we classified the 53,000 neurons into 727 types, about half of which are systematically described and named for the first time. Finally, we share an extensive collection of split-GAL4 lines matched to our neuron type catalog. Together, this comprehensive set of tools and data unlock new possibilities for systematic investigations of vision in Drosophila, a foundation for a deeper understanding of sensory processing.