Kaspar Podgorski

Neurons transform thousands of synaptic inputs into spiking output, and understanding this transformation requires measuring many submicron synapses at millisecond timescales in vivo. Here we present SLAP2, a two-photon random access projection microscope with no per-target access time cost, yielding over 5-fold faster imaging than existing methods, and performant real-time hardware motion correction. Flexible scanning modes enable measurement of hundreds of synapses at ∼200 Hz, >800 synapses volumetrically at 50–100 Hz, and compartment-resolved dendritic voltage at 2–10 kHz in behaving mice. Simultaneous dendritic glutamate and somatic calcium imaging in visual cortex pyramidal neurons revealed nonlinear input-output amplification of stimulus onset and preferred stimulus orientation responses. Amplified features are associated with spatially organized inputs and stronger trial-to-trial coupling between synaptic activity and somatic output. These measurements establish SLAP2 as a powerful tool for recording intricate patterns of subcellular fluorescence dynamics in behaving animals.

Proper brain function requires the assembly and function of diverse populations of neurons and glia. Single cell gene expression studies have mostly focused on characterization of neuronal cell diversity; however, recent studies have also revealed substantial diversity of glial cells, particularly astrocytes. To better understand glial cell types and their roles in neurobiology, we built a new suite of adeno-associated viral (AAV)-based genetic tools to enable genetic access to astrocytes and oligodendrocytes. These oligodendrocyte and astrocyte enhancer-AAVs are highly specific (usually > 95% cell type specificity) with variable expression levels, and the astrocyte enhancer-AAVs show multiple distinct expression patterns reflecting the spatial distribution of astrocyte cell types. To provide the best glial-specific functional tools, several enhancer-AAVs were: optimized for higher expression levels, shown to be functional and specific in rat and macaque, shown to maintain specific activity across transgenes and in epilepsy where traditional promoters changed activity, and used to drive functional transgenes in astrocytes including Cre recombinase and acetylcholine-responsive sensor iAChSnFR. The astrocyte-specific iAChSnFR revealed a clear reward-dependent acetylcholine response in astrocytes of the nucleus accumbens during reinforcement learning. Together, this collection of glial enhancer-AAVs will enable characterization of astrocyte and oligodendrocyte populations and their functional roles.

Neurons exhibit tremendous structural plasticity during the growth of dendritic and axonal arbors in early brain circuit formation, followed by experience-driven structural plasticity throughout life. Advances in labeling and in vivo time-lapse imaging allow capture of dynamic structural changes within intact and awake animals, and fluorescent biosensors of neural activity offer opportunities to link structural and functional plasticity. However, the resulting large multi-dimensional data sets are challenging to quantify due to time-consuming tracking of minute structural changes throughout complex neuronal morphologies across time. Here, we present Dynamo: an open-source Python application that enables dynamic morphometrics, the quantitative analysis of morphological changes over time, by streamlining arbor reconstruction, registration of structures across time, and quantitative analyses of growth behavior. Dynamo yields rich characterization of neural structural changes necessary for determining how rapid growth events culminate into long-term patterning, linking structural and functional plasticity, and for identifying underlying molecular mechanisms.

Recent advances in fluorescent indicators and optical microscopy now enable in vivo synaptic imaging of glutamate, which transmits the majority of signals between neurons in the brain. Extracting fluorescence signals from these recordings is complicated by the minuscule scale and dense clustering of synapses on dendrites, as well as brain motion in behaving animals. Here we present the Glutamate Imaging Analysis Toolbox (GIAnT), a set of automated tools for glutamate imaging data that corrects sample motion, identifies active synapses with super-resolution precision, and extracts synaptic fluorescence signals. Compared to methods designed for cellular imaging, GIAnT reduces motion artifacts, more accurately identifies active synapses, and improves extracted signal quality by reducing contamination from overlapping synapses. By pairing in vivo glutamate imaging with post hoc expansion microscopy, we find that >70% of the putative synapses extracted using GIAnT matched one-to-one with glutamatergic synapses onto the postsynaptic cell. Our results establish GIAnT as an automated and validated pipeline for processing synaptic glutamate imaging data at scale.

Genetically encoded calcium indicators (GECIs) are vital tools for fluorescence-based visualization of neuronal activity with high spatial and temporal resolution. However, current highest-performance GECIs are predominantly green or red fluorescent, limiting multiplexing options and efficient excitation with fixed-wavelength femtosecond lasers operating at 1030 nm. In an effort to overcome these limitations, we developed OCaMP, an orange fluorescent GECI engineered from O-GECO1 through targeted substitutions to improve calcium affinity while retaining the favorable photophysical properties of mOrange2. OCaMP exhibits improved two-photon cross-section, responsiveness, photostability, and calcium affinity relative to O-GECO1. In cultured neurons, zebrafish, and mouse cortex, OCaMP outperforms the red GECIs jRCaMP1a and jRGECO1a in sensitivity, photostability, and signal-to-noise ratio. Here we show that OCaMP, an orange fluorescent GECI, is a robust tool for high-fidelity neural imaging optimized for wavelengths above 1000 nm and a practical option within the spectral gap between existing green and red GECIs.

For the brain to compute, electrical signals must propagate over the membranes of individual neurons, connecting synaptic inputs to synaptic outputs. Complex neuronal morphologies coupled with the spatial organization of synaptic inputs and outputs enable diverse voltage transformations that underlie cell-type specific computations. However, measuring these transformations in vivo has remained challenging, leaving a crucial gap in our mechanistic understanding of single neuron computation. Here, we develop ASAP7y, a genetically encoded voltage indicator with unprecedented subthreshold sensitivity and expanded excitation compatibility in both mice and flies. We leveraged ASAP7y combined with two-photon random-access microscopy to record sensory stimulus-evoked voltage dynamics with millisecond, subcellular, and subthreshold resolution along the neurites of individual neurons in Drosophila. We found remarkable heterogeneity in voltage propagation across cell-types, delineating a fundamental axis of electrical diversity. Leveraging a nanoscale EM reconstruction of the visual system, we modeled the electrotonic properties of single neurons spanning 717 cell types, revealing how morphology shapes voltage transformations. Finally, we demonstrate that confined voltage propagation creates substrates for local computation, producing subcellular domains with distinct feature selectivity across multiple cell types. These results provide mechanistic insight into how critical single neuron computations arise and reveal parallel processing in single neurons.

Understanding how neurons integrate signals from thousands of input synapses requires methods to monitor neurotransmission across many sites simultaneously. The fluorescent protein glutamate indicator iGluSnFR enables visualization of synaptic signaling, but the sensitivity, scale and speed of such measurements are limited by existing variants. Here we developed two highly sensitive fourth-generation iGluSnFR variants with fast activation and tailored deactivation rates: iGluSnFR4f for tracking rapid dynamics, and iGluSnFR4s for recording from large populations of synapses. These indicators detect glutamate with high spatial specificity and single-vesicle sensitivity in vivo. We used them to record natural patterns of synaptic transmission across multiple experimental contexts in mice, including two-photon imaging in cortical layers 1–4 and hippocampal CA1, and photometry in the midbrain. The iGluSnFR4 variants extend the speed, sensitivity and scalability of glutamate imaging, enabling direct observation of information flow through neural networks in the intact brain.

Proper brain function requires the assembly and function of diverse populations of neurons and glia. Single cell gene expression studies have mostly focused on characterization of neuronal cell diversity; however, recent studies have also revealed substantial diversity of glial cells, particularly astrocytes. To better understand glial cell types and their roles in neurobiology, we built a new suite of adeno-associated viral (AAV)-based genetic tools to enable genetic access to astrocytes and oligodendrocytes. These oligodendrocyte and astrocyte enhancer-AAVs are highly specific (usually > 95% cell type specificity) with variable expression levels, and the astrocyte enhancer-AAVs show multiple distinct expression patterns reflecting the spatial distribution of astrocyte cell types. To provide the best glial-specific functional tools, several enhancer-AAVs were: optimized for higher expression levels, shown to be functional and specific in rat and macaque, shown to maintain specific activity across transgenes and in epilepsy where traditional promoters changed activity, and used to drive functional transgenes in astrocytes including Cre recombinase and acetylcholine-responsive sensor iAChSnFR. The astrocyte-specific iAChSnFR revealed a clear reward-dependent acetylcholine response in astrocytes of the nucleus accumbens during reinforcement learning. Together, this collection of glial enhancer-AAVs will enable characterization of astrocyte and oligodendrocyte populations and their roles across species, disease states, and behavioral epochs.

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.