Localized APP expression results in progressive network dysfunction by disorganizing spike timing.

Progressive cognitive decline in Alzheimer's disease could either be caused by a spreading molecular pathology or by an initially focal pathology that causes aberrant neuronal activity in a larger network. To distinguish between these possibilities, we generated a mouse model with expression of mutant human amyloid precursor protein (APP) in only hippocampal CA3 cells. We found that performance in a hippocampus-dependent memory task was impaired in young adult and aged mutant mice. In both age groups, we then recorded from the CA1 region, which receives inputs from APP-expressing CA3 cells. We observed that theta oscillation frequency in CA1 was reduced along with disrupted relative timing of principal cells. Highly localized pathology limited to the presynaptic CA3 cells is thus sufficient to cause aberrant firing patterns in postsynaptic neuronal networks, which indicates that disease progression is not only from spreading pathology but also mediated by progressively advancing physiological dysfunction.

Genetic Probe for Visualizing Glutamatergic Synapses and Vesicles by 3D Electron Microscopy.

Communication between neurons relies on the release of diverse neurotransmitters, which represent a key-defining feature of a neuron's chemical and functional identity. Neurotransmitters are packaged into vesicles by specific vesicular transporters. However, tools for labeling and imaging synapses and synaptic vesicles based on their neurochemical identity remain limited. We developed a genetically encoded probe to identify glutamatergic synaptic vesicles at the levels of both light and electron microscopy (EM) by fusing the mini singlet oxygen generator (miniSOG) probe to an intralumenal loop of the vesicular glutamate transporter-2. We then used a 3D imaging method, serial block-face scanning EM, combined with a deep learning approach for automatic segmentation of labeled synaptic vesicles to assess the subcellular distribution of transporter-defined vesicles at nanometer scale. These tools represent a new resource for accessing the subcellular structure and molecular machinery of neurotransmission and for transmitter-defined tracing of neuronal connectivity.

Microglial Gi-dependent dynamics regulate brain network hyperexcitability.

Microglial surveillance is a key feature of brain physiology and disease. Here, we found that Gi-dependent microglial dynamics prevent neuronal network hyperexcitability. By generating MgPTX mice to genetically inhibit Gi in microglia, we show that sustained reduction of microglia brain surveillance and directed process motility induced spontaneous seizures and increased hypersynchrony after physiologically evoked neuronal activity in awake adult mice. Thus, Gi-dependent microglia dynamics may prevent hyperexcitability in neurological diseases.

CDeep3M-Plug-and-Play cloud-based deep learning for image segmentation.

As biomedical imaging datasets expand, deep neural networks are considered vital for image processing, yet community access is still limited by setting up complex computational environments and availability of high-performance computing resources. We address these bottlenecks with CDeep3M, a ready-to-use image segmentation solution employing a cloud-based deep convolutional neural network. We benchmark CDeep3M on large and complex two-dimensional and three-dimensional imaging datasets from light, X-ray, and electron microscopy.

Iron-specific Signal Separation from within Heavy Metal Stained Biological Samples Using X-Ray Microtomography with Polychromatic Source and Energy-Integrating Detectors.

Biological samples are frequently stained with heavy metals in preparation for examining the macro, micro and ultra-structure using X-ray microtomography and electron microscopy. A single X-ray microtomography scan reveals detailed 3D structure based on staining density, yet it lacks both material composition and functional information. Using a commercially available polychromatic X-ray source, energy integrating detectors and a two-scan configuration labelled by their energy- "High" and "Low", we demonstrate how a specific element, here shown with iron, can be detected from a mixture with other heavy metals. With proper selection of scan configuration, achieving strong overlap of source characteristic emission lines and iron K-edge absorption, iron absorption was enhanced enabling K-edge imaging. Specifically, iron images were obtained by scatter plot material analysis, after selecting specific regions within scatter plots generated from the "High" and "Low" scans. Using this method, we identified iron rich regions associated with an iron staining reaction that marks the nodes of Ranvier along nerve axons within mouse spinal roots, also stained with osmium metal commonly used for electron microscopy.

Dual Anterograde and Retrograde Viral Tracing of Reciprocal Connectivity.

Current large-scale approaches in neuroscience aim to unravel the complete connectivity map of specific neuronal circuits, or even the entire brain. This emerging research discipline has been termed connectomics. Recombinant glycoprotein-deleted rabies virus (RABV ∆G) has become an important tool for the investigation of neuronal connectivity in the brains of a variety of species. Neuronal infection with even a single RABV ∆G particle results in high-level transgene expression, revealing the fine-detailed morphology of all neuronal features-including dendritic spines, axonal processes, and boutons-on a brain-wide scale. This labeling is eminently suitable for subsequent post-hoc morphological analysis, such as semiautomated reconstruction in 3D. Here we describe the use of a recently developed anterograde RABV ∆G variant together with a retrograde RABV ∆G for the investigation of projections both to, and from, a particular brain region. In addition to the automated reconstruction of a dendritic tree, we also give as an example the volume measurements of axonal boutons following RABV ∆G-mediated fluorescent marker expression. In conclusion RABV ∆G variants expressing a combination of markers and/or tools for stimulating/monitoring neuronal activity, used together with genetic or behavioral animal models, promise important insights in the structure-function relationship of neural circuits.

Structural-functional connectivity deficits of neocortical circuits in the Fmr1 (-/y) mouse model of autism.

Fragile X syndrome (FXS), the most common inherited form of intellectual disability disorder and a frequent cause of autism spectrum disorder (ASD), is characterized by a high prevalence of sensory symptoms. Perturbations in the anatomical connectivity of neocortical circuits resulting in their functional defects have been hypothesized to contribute to the underlying etiology of these disorders. We tested this idea by probing alterations in the functional and structural connectivity of both local and long-ranging neocortical circuits in the Fmr1 (-/y) mouse model of FXS. To achieve this, we combined in vivo ultrahigh-field diffusion tensor magnetic resonance imaging (MRI), functional MRI, and viral tracing approaches in adult mice. Our results show an anatomical hyperconnectivity phenotype for the primary visual cortex (V1), but a disproportional low connectivity of V1 with other neocortical regions. These structural data are supported by defects in the structural integrity of the subcortical white matter in the anterior and posterior forebrain. These anatomical alterations might contribute to the observed functional decoupling across neocortical regions. We therefore identify FXS as a "connectopathy," providing a translational model for understanding sensory processing defects and functional decoupling of neocortical areas in FXS and ASD.