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Benefiting from the rapid development of electron microscopy imaging and deep learning technologies, an increasing number of brain image datasets with segmentation and synapse detection are published. Most of the automated segmentation methods label voxels rather than producing neuron skeletons directly. A further skeletonization step is necessary for quantitative morphological analysis. Currently, several tools are published for skeletonization as well as morphological and synaptic connectivity analysis using different computer languages and environments. Recently the Julia programming language, notable for elegant syntax and high performance, has gained rapid adoption in the scientific computing community. Here, we present a Julia package, called RealNeuralNetworks.jl, for efficient sparse skeletonization, morphological analysis, and synaptic connectivity analysis. Based on a large-scale Zebrafish segmentation dataset, we illustrate the software features by performing distributed skeletonization in Google Cloud, clustering the neurons using the NBLAST algorithm, combining morphological similarity and synaptic connectivity to study their relationship. We demonstrate that RealNeuralNetworks.jl is suitable for use in terabyte-scale electron microscopy image segmentation datasets.

How much can connectomes with synaptic resolution help us understand brain function? An optimistic view is that a connectome is a major determinant of brain function and a key substrate for simulating a brain. Here we investigate the explanatory power of connectomics using a wiring diagram reconstructed from a larval zebrafish brainstem. We identify modules of strongly connected neurons that turn out to be specialized for different behavioral functions, the control of eye and body movements. We then build a neural network model using a synaptic weight matrix based on the reconstructed wiring diagram. This leads to predictions that statistically match the neural coding of eye position as observed by calcium imaging. Our work shows the promise of connectome-based brain modeling to yield experimentally testable predictions of neural activity and behavior, as well as mechanistic explanations of low-dimensional neural dynamics, a widely observed phenomenon in nervous systems.

Amphetamine-associated CNS vasculitis is controversial. There are few reports but none as a tumor mimic to our knowledge. We describe a pathology-proven, amphetamine-associated CNS vasculitis resembling a tumor. A 41-year-old man presented with six weeks of progressive confusion and left-sided weakness. CT head reported a right thalamic mass with vasogenic edema. Laboratory tests were unremarkable except for cannabinoids and amphetamine in urine. MRI brain showed enhancement in right frontotemporal lobe, basal ganglia, and thalamus concerning for glioblastoma multiforme. After high-dose IV dexamethasone, an initial biopsy showed reactive gliosis, perivascular lymphocytic cuffing by CD3+, rare CD20+ cells and no infection. He continued to decline. MRI 22 days after admission showed increased T2/FLAIR hyperintensity, multifocal areas of enhancement, microhemorrhages, and ischemia. High-grade glioma, lymphoma and infectious encephalitis remained on differentials. Treatment included broad-spectrum antibiotics and acyclovir. Biopsy on 23rd day showed reactive gliosis with parenchymal macrophage infiltration and perivascular cuffing with mixed inflammatory infiltrates. CSF: slightly elevated WBCs (8/µL), elevated protein (139mg/dL), normal glucose, and no infection. MRI whole spine and CT body were unremarkable. The patient was transferred to MDACC 5.5 weeks after initial presentation. He was alert with expressive aphasia, right gaze preference, left hemiplegia, and right hemiparesis. He underwent a right anterior temporal lobectomy. Pathology showed extensive cortical laminar and white matter necrosis with macrophage infiltration and microglial activation. In areas of the preserved cortex, vasculocentric lymphocytic aggregates were present and reticulin staining showed lymphocytic infiltration of the vascular walls. Immunophenotyping (CD3, CD20) showed an almost pure T-cell population. The predominance of intramural T-lymphocytes reflected a vasculitic process. The final diagnosis was cerebral vasculitis with subacute infarction. The patient died six days later. The autopsy findings were identical to the previous resection without evidence of systemic inflammation.

For a mechanistic understanding of neuronal circuits in the brain, a detailed description of information flow is necessary. Thereby it is crucial to link neuron function to the underlying circuit structure. Multiphoton calcium imaging is the standard technique to record the activity of hundreds of neurons simultaneously. Similarly, recent advances in high-throughput electron microscopy techniques allow for the reconstruction of synaptic resolution wiring diagrams. These two methods can be combined to study both function and structure in the same specimen. Due to its small size and optical transparency, the larval zebrafish brain is one of the very few vertebrate systems where both, activity and connectivity of all neurons from entire, anatomically defined brain regions, can be analyzed. Here, we describe different methods and the tools required for combining multiphoton microscopy with dense circuit reconstruction from electron microscopy stacks of entire brain regions in the larval zebrafish.

Summary Neural integrators are involved in a variety of sensorimotor and cognitive behaviors. The oculomotor system contains a simple example, a hindbrain neural circuit that takes velocity signals as inputs and temporally integrates them to control eye position. Here we investigated the structural underpinnings of temporal integration in the larval zebrafish by first identifying integrator neurons using two-photon calcium imaging and then reconstructing the same neurons through serial electron microscopic analysis. Integrator neurons were identified as those neurons with activities highly correlated with eye position during spontaneous eye movements. Three morphological classes of neurons were observed: ipsilaterally projecting neurons located medially, contralaterally projecting neurons located more laterally, and a population at the extreme lateral edge of the hindbrain for which we were not able to identify axons. Based on their somatic locations, we inferred that neurons with only ipsilaterally projecting axons are glutamatergic, whereas neurons with only contralaterally projecting axons are largely GABAergic. Dendritic and synaptic organization of the ipsilaterally projecting neurons suggests a broad sampling from inputs on the ipsilateral side. We also observed the first conclusive evidence of synapses between integrator neurons, which have long been hypothesized by recurrent network models of integration via positive feedback.

Persistent activity in the brain is involved in working memory and motor planning. The ability of the brain to hold information ‘online' long after an initiating stimulus is a hallmark of brain areas such as the prefrontal cortex. Recurrent network loops such as the thalamocortical loop and reciprocal loops in the cortex are potential substrates that can support such activity. However, native brain circuitry makes it difficult to study mechanisms underlying such persistent activity. Here we propose a platform to study synaptic mechanisms of such persistent activity by constraining neuronal networks to a recurrent loop like geometry. Using a polymer stamping technique, adhesive proteins are transferred onto glass substrates in a precise ring shape. Primary rat hippocampal cultures were capable of forming ring-shaped networks containing 40–60 neurons. Calcium imaging of these networks show evoked persistent activity in an all-or-none manner. Blocking inhibition with bicuculline methaiodide (BMI) leads to an increase in the duration of persistent activity. These persistent phases were abolished by blockade of asynchronous neurotransmitter release by ethylene glycol tetraacetic acid (EGTA-AM).