Visualizing synaptic plasticity in vivo by large-scale imaging of endogenous AMPA receptors

Elucidating how synaptic molecules such as AMPA receptors mediate neuronal communication and tracking their dynamic expression during behavior is crucial to understand cognition and disease, but current technological barriers preclude large-scale exploration of molecular dynamics in vivo. We have developed a suite of innovative methodologies that break through these barriers: a new knockin mouse line with fluorescently tagged endogenous AMPA receptors, two-photon imaging of hundreds of thousands of labeled synapses in behaving mice, and computer-vision-based automatic synapse detection. Using these tools, we can longitudinally track how the strength of populations of synapses changes during behavior. We used this approach to generate an unprecedentedly detailed spatiotemporal map of synapses undergoing changes in strength following sensory experience. More generally, these tools can be used as an optical probe capable of measuring functional synapse strength across entire brain areas during any behavioral paradigm, describing complex system-wide changes with molecular precision.

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Visualizing synaptic plasticity in vivo by large-scale imaging of endogenous AMPA receptors

10.1101/2020.03.01.972216 ◽

2020 ◽

Cited By ~ 2

Author(s):

Austin Graves ◽

Richard Roth ◽

Han Tan ◽

Qianwen Zhu ◽

Alexei Bygrave ◽

...

Keyword(s):

Synaptic Plasticity ◽

Ampa Receptors ◽

Large Scale ◽

Optical Probe ◽

Transgenic Mouse Line ◽

Neuronal Communication ◽

Two Photon ◽

Behavioral Paradigm ◽

Technological Barriers

SummaryElucidating how synaptic molecules such as AMPA receptors mediate neuronal communication is crucial to understanding cognition and disease, but current technological barriers preclude large-scale exploration of molecular dynamics in vivo. We have developed a suite of innovative methodologies that break through these barriers: a transgenic mouse line with fluorescently tagged endogenous AMPA receptors, two-photon imaging of hundreds of thousands of labeled synapses in behaving mice, and machine-learning-based automatic synapse detection. Using these tools, we can longitudinally track how the strength of individual synapses changes during behavior. We used this approach to generate an unprecedentedly detailed spatiotemporal map of synaptic plasticity underlying sensory experience. More generally, these tools can be used as an optical probe capable of measuring functional synapse strength across entire brain areas during any behavioral paradigm, describing complex system-wide changes with molecular precision.

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Fast and robust active neuron segmentation in two-photon calcium imaging using spatiotemporal deep learning

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1812995116 ◽

2019 ◽

Vol 116 (17) ◽

pp. 8554-8563 ◽

Cited By ~ 16

Author(s):

Somayyeh Soltanian-Zadeh ◽

Kaan Sahingur ◽

Sarah Blau ◽

Yiyang Gong ◽

Sina Farsiu

Keyword(s):

Real Time ◽

Calcium Imaging ◽

Large Scale ◽

Cortical Layer ◽

Fast Method ◽

Active Neuron ◽

Neuronal Coding ◽

Two Photon ◽

Neuron Density

Calcium imaging records large-scale neuronal activity with cellular resolution in vivo. Automated, fast, and reliable active neuron segmentation is a critical step in the analysis workflow of utilizing neuronal signals in real-time behavioral studies for discovery of neuronal coding properties. Here, to exploit the full spatiotemporal information in two-photon calcium imaging movies, we propose a 3D convolutional neural network to identify and segment active neurons. By utilizing a variety of two-photon microscopy datasets, we show that our method outperforms state-of-the-art techniques and is on a par with manual segmentation. Furthermore, we demonstrate that the network trained on data recorded at a specific cortical layer can be used to accurately segment active neurons from another layer with different neuron density. Finally, our work documents significant tabulation flaws in one of the most cited and active online scientific challenges in neuron segmentation. As our computationally fast method is an invaluable tool for a large spectrum of real-time optogenetic experiments, we have made our open-source software and carefully annotated dataset freely available online.

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An automated pipeline for bouton, spine, and synapse detection of in vivo two-photon images

BioData Mining ◽

10.1186/s13040-017-0161-5 ◽

2017 ◽

Vol 10 (1) ◽

Cited By ~ 4

Author(s):

Qiwei Xie ◽

Xi Chen ◽

Hao Deng ◽

Danqian Liu ◽

Yingyu Sun ◽

...

Keyword(s):

Two Photon ◽

Automated Pipeline ◽

Synapse Detection

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Segmentation-less, automated vascular vectorization robustly extracts neurovascular network statistics from in vivo two-photon images

10.1101/2020.06.15.151076 ◽

2020 ◽

Cited By ~ 1

Author(s):

Samuel A. Mihelic ◽

William A. Sikora ◽

Ahmed M. Hassan ◽

Michael R. Williamson ◽

Theresa A. Jones ◽

...

Keyword(s):

Image Segmentation ◽

Statistical Power ◽

Large Scale ◽

Performance Metrics ◽

Three Dimensional ◽

Vascular Anatomy ◽

Input Image ◽

Network Graph ◽

Two Photon

AbstractRecent advances in two-photon microscopy (2PM) have allowed large scale imaging and analysis of cortical blood vessel networks in living mice. However, extracting a network graph and vector representations for vessels remain bottlenecks in many applications. Vascular vectorization is algorithmically difficult because blood vessels have many shapes and sizes, the samples are often unevenly illuminated, and large image volumes are required to achieve good statistical power. State-of-the-art, three-dimensional, vascular vectorization approaches require a segmented/binary image, relying on manual or supervised-machine annotation. Therefore, voxel-by-voxel image segmentation is biased by the human annotator/trainer. Furthermore, segmented images oftentimes require remedial morphological filtering before skeletonization/vectorization. To address these limitations, we propose a vectorization method to extract vascular objects directly from unsegmented images. The Segmentation-Less, Automated, Vascular Vectorization (SLAVV) source code in MATLAB is openly available on GitHub. This novel method uses simple models of vascular anatomy, efficient linear filtering, and low-complexity vector extraction algorithms to remove the image segmentation requirement, replacing it with manual or automated vector classification. SLAVV is demonstrated on three in vivo 2PM image volumes of microvascular networks (capillaries, arterioles and venules) in the mouse cortex. Vectorization performance is proven robust to the choice of plasma- or endothelial-labeled contrast, and processing costs are shown to scale with input image volume. Fully-automated SLAVV performance is evaluated on various, simulated 2PM images based on the large, [1.4, 0.9, 0.6] mm input image, and performance metrics show greater robustness to image quality than an intensity-based thresholding approach.

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Optogenetic strategies for high-efficiency all-optical interrogation using blue light-sensitive opsins

eLife ◽

10.7554/elife.63359 ◽

2021 ◽

Vol 10 ◽

Author(s):

Angelo Forli ◽

Matteo Pisoni ◽

Yoav Printz ◽

Ofer Yizhar ◽

Tommaso Fellin

Keyword(s):

Blue Light ◽

Large Scale ◽

High Efficiency ◽

Average Power ◽

Optical Methods ◽

Neuronal Ensembles ◽

Two Photon ◽

All Optical ◽

Stimulation Of

All-optical methods for imaging and manipulating brain networks with high spatial resolution are fundamental to study how neuronal ensembles drive behavior. Stimulation of neuronal ensembles using holographic techniques requires high-sensitivity actuators to avoid photodamage and heating. Moreover, two-photon-excitable opsins should be insensitive to light at wavelengths used for imaging. To achieve this goal, we developed a novel soma-targeted variant of the large-conductance blue light-sensitive opsin CoChR (stCoChR). In the mouse cortex in vivo, we combined holographic two-photon stimulation of stCoChR with an amplified laser tuned at the opsin absorption peak and imaging of the red-shifted indicator jRCaMP1a. Compared to previously characterized blue light-sensitive soma-targeted opsins in vivo, stCoChR allowed neuronal stimulation with more than 10-fold lower average power and no spectral crosstalk. The combination of stCoChR, tuned amplified laser stimulation, and red-shifted functional indicators promises to be a powerful tool for large-scale interrogation of neural networks in the intact brain.

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Abstract P434: A Mouse Model To Control Vessel Diameter With Light

Circulation Research ◽

10.1161/res.129.suppl_1.p434 ◽

2021 ◽

Vol 129 (Suppl_1) ◽

Author(s):

Philip O'Herron ◽

David Hartmann ◽

Andy Y Shih

Keyword(s):

Smooth Muscle ◽

Cognitive Impairment ◽

Vascular Function ◽

Large Scale ◽

Imaging System ◽

Contractile Function ◽

Small Individual ◽

Two Photon ◽

Cranial Window

In diseases such as stroke, hypertension, vascular cognitive impairment, and Alzheimer’s disease, defects in the cerebrovascular system lead to reduced blood flow and vasoreactivity to stimuli. Recently, there has been increased appreciation for the role of small vessels in these vascular pathologies. For example, small vessel dysfunction can cause widespread microinfarcts and capillary stalling, which may underlie cognitive impairment in cases where large scale vascular abnormalities are not readily detected. However, vascular function is difficult to dissociate from concurrent neuronal deficits cause by damage to neuronal circuitry in brain pathology. Thus the ability to directly probe smooth muscle contraction of small, individual vessels in the intact brain would be a valuable tool for increasing our understanding of vascular contributions to cognitive impairment. We developed an experimental paradigm to optically probe the contractile function of arterioles in vivo with high spatiotemporal precision. This was done by expressing the excitatory opsin ReaChR in vascular smooth muscle cells and pericytes. Using a 594 nm light-emitting diode we were able to evoke widespread vasoconstriction across the cranial window. With a 1040 nm focused, pulsed laser for two-photon stimulation, we were able to evoke highly localized constrictions targeted to individual pial artery branches or penetrating arterioles. Our dual light-path imaging system allowed the optogenetic stimulation to be performed with simultaneous two-photon imaging to monitor vessel activity. Using a spatial light modulator, we were also able to constrict vessels both above and below the imaging plane. This is a powerful tool to assay vasoconstrictive function of single arterioles across 3-dimensional vascular networks in vivo. It also presents novel opportunities to study conductance of vascular signals and to modulate dynamics of functional hyperemia.

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Genetic voltage indicators

BMC Biology ◽

10.1186/s12915-019-0682-0 ◽

2019 ◽

Vol 17 (1) ◽

Cited By ~ 19

Author(s):

Yuki Bando ◽

Christiane Grimm ◽

Victor H Cornejo ◽

Rafael Yuste

Keyword(s):

Large Scale ◽

Plasma Membranes ◽

Synaptic Activity ◽

Neuronal Populations ◽

Two Photon ◽

Advantages And Disadvantages ◽

Research Initiatives ◽

Voltage Sensitive Dyes

Abstract As a “holy grail” of neuroscience, optical imaging of membrane potential could enable high resolution measurements of spiking and synaptic activity in neuronal populations. This has been partly achieved using organic voltage-sensitive dyes in vitro, or in invertebrate preparations yet unspecific staining has prevented single-cell resolution measurements from mammalian preparations in vivo. The development of genetically encoded voltage indicators (GEVIs) and chemogenetic sensors has enabled targeting voltage indicators to plasma membranes and selective neuronal populations. Here, we review recent advances in the design and use of genetic voltage indicators and discuss advantages and disadvantages of three classes of them. Although genetic voltage indicators could revolutionize neuroscience, there are still significant challenges, particularly two-photon performance. To overcome them may require cross-disciplinary collaborations, team effort, and sustained support by large-scale research initiatives.

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High-throughput synapse-resolving two-photon fluorescence microendoscopy for deep-brain volumetric imaging in vivo

eLife ◽

10.7554/elife.40805 ◽

2019 ◽

Vol 8 ◽

Cited By ~ 24

Author(s):

Guanghan Meng ◽

Yajie Liang ◽

Sarah Sarsfield ◽

Wan-chen Jiang ◽

Rongwen Lu ◽

...

Keyword(s):

High Throughput ◽

Brain Structures ◽

Optical Probe ◽

Volumetric Imaging ◽

Two Photon ◽

Anatomical Imaging ◽

Two Photon Fluorescence ◽

Photon Fluorescence ◽

Deep Brain

Optical imaging has become a powerful tool for studying brains in vivo. 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 in vivo.

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Net decrease in spine-surface GluA1-containing AMPA receptors after post-learning sleep in the adult mouse cortex

Nature Communications ◽

10.1038/s41467-021-23156-2 ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Daisuke Miyamoto ◽

William Marshall ◽

Giulio Tononi ◽

Chiara Cirelli

Keyword(s):

Ampa Receptors ◽

Motor Task ◽

Relative Advantage ◽

Two Photon ◽

Adult Mice ◽

Mature Brain ◽

Mouse Cortex ◽

Before And After ◽

Receptor Plasticity

AbstractThe mechanisms by which sleep benefits learning and memory remain unclear. Sleep may further strengthen the synapses potentiated by learning or promote broad synaptic weakening while protecting the newly potentiated synapses. We tested these ideas by combining a motor task whose consolidation is sleep-dependent, a marker of synaptic AMPA receptor plasticity, and repeated two-photon imaging to track hundreds of spines in vivo with single spine resolution. In mouse motor cortex, sleep leads to an overall net decrease in spine-surface GluA1-containing AMPA receptors, both before and after learning. Molecular changes in single spines during post-learning sleep are correlated with changes in performance after sleep. The spines in which learning leads to the largest increase in GluA1 expression have a relative advantage after post-learning sleep compared to sleep deprivation, because sleep weakens all remaining spines. These results are obtained in adult mice, showing that sleep-dependent synaptic down-selection also benefits the mature brain.

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