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Perineuronal nets (PNN) are a special highly structured type of extracellular matrix encapsulating synapses on large populations of CNS neurons. PNN undergo structural changes in schizophrenia, epilepsy, Alzheimer's disease, stroke, post-traumatic conditions, and some other brain disorders. The functional role of the PNN microstructure in brain pathologies has remained largely unstudied until recently. Here, we review recent research implicating PNN microstructural changes in schizophrenia and other disorders. We further concentrate on high-resolution studies of the PNN mesh units surrounding synaptic boutons to elucidate fine structural details behind the mutual functional regulation between the ECM and the synaptic terminal. We also review some updates regarding PNN as a potential pharmacological target. Artificial intelligence (AI)-based methods are now arriving as a new tool that may have the potential to grasp the brain's complexity through a wide range of organization levels—from synaptic molecular events to large scale tissue rearrangements and the whole-brain connectome function. This scope matches exactly the complex role of PNN in brain physiology and pathology processes, and the first AI-assisted PNN microscopy studies have been reported. To that end, we report here on a machine learning-assisted tool for PNN mesh contour tracing. [ABSTRACT FROM AUTHOR]

The brain synaptic circuitry is formed as a result of pre-defined genetic programs and sensory experience during postnatal development. Perineuronal nets ensheath synaptic boutons and control several crucial features of the synapse physiology. Formation of the perineuronal net microstructure during the brain development remains largely unstudied. Here we provide a detailed quantitative description of the 3-dimensional geometry of the synapse and the surrounding perineuronal net in the mouse somatosensory cortex layer IV. We compare the morphology of the synapse+perineuronal net complex in the adult brain formed under normal conditions or in the whisker shaving model of somatosensory deprivation. We demonstrate that the sensory deprivation causes flattening of the 3D PNN mesh geometry and reduction of the VGAT-positive cluster volume in presynaptic boutons. These results reveal a mechanism of the sensory input-dependent synapse morphogenesis during the brain development. • Here we propose new methods for quantitative analysis of the 3D microstructure of perineuronal nets. • Somatosensory deprivation via whisker shaving causes flattening of the perineuronal nets. • Somatosensory deprivation also affects microstructure of the GABAergic synapses surrounded by perineuronal nets as shown by reduction of the volume of VGAT-positive clusters. [ABSTRACT FROM AUTHOR]

Perineuronal nets (PNNs) represent a highly condensed specialized form of brain extracellular matrix (ECM) enwrapping mostly parvalbumin‐positive interneurons in the brain in a mesh‐like fashion. PNNs not only regulate the onset and completion of the critical period during postnatal brain development, control cell excitability, and synaptic transmission but are also implicated in several brain disorders including schizophrenia. Holes in the perineuronal nets, harboring the synaptic contacts, along with hole‐surrounding ECM barrier can be viewed as PNN compartmentalization units that might determine the properties of synapses and heterosynaptic communication. In this study, we developed a novel open‐source script for Fiji (ImageJ) to semi‐automatically quantify structural alterations of PNNs such as the number of PNN units, area, mean intensity of PNN marker expression in 2D and 3D, shape parameters of PNN units in the ketamine‐treated Sprague–Dawley rat model of schizophrenia using high‐resolution confocal microscopic images. We discovered that the mean intensity of ECM within PNN units is inversely correlated with the area and the perimeter of the PNN holes. The intensity, size, and shape of PNN units proved to be three major principal factors to describe their variability. Ketamine‐treated rats had more numerous but smaller and less circular PNN units than control rats. These parameters allowed to correctly classify individual PNNs as derived from control or ketamine‐treated groups with ≈85% reliability. Thus, the proposed multidimensional analysis of PNN units provided a robust and comprehensive morphometric fingerprinting of fine ECM structure abnormalities in the experimental model of schizophrenia. [ABSTRACT FROM AUTHOR]

Perineuronal nets (PNN) ensheath GABAergic and glutamatergic synapses on neuronal cell surface in the central nervous system (CNS), have neuroprotective effect in animal models of Alzheimer disease and regulate synaptic plasticity during development and regeneration. Crucial insights were obtained recently concerning molecular composition and physiological importance of PNN but the microstructure of the network remains largely unstudied. Here we used histochemistry, fluorescent microscopy and quantitative image analysis to study the PNN structure in adult mouse and rat neurons from layers IV and VI of the somatosensory cortex. Vast majority of meshes have quadrangle, pentagon or hexagon shape with mean mesh area of 1.29 µm 2 in mouse and 1.44 µm 2 in rat neurons. We demonstrate two distinct patterns of chondroitin sulfate distribution within a single mesh – with uniform (nonpolar) and node-enriched (polar) distribution of the Wisteria floribunda agglutinin-positive signal. Vertices of the node-enriched pattern match better with local maxima of chondroitin sulfate density as compared to the uniform pattern. PNN is organized into clusters of meshes with distinct morphologies on the neuronal cell surface. Our findings suggest the role for the PNN microstructure in the synaptic transduction and plasticity. [ABSTRACT FROM AUTHOR]