Activity-dependent switches between dynamic regimes of extracellular matrix expression

Exploring neuro-glial interaction mechanisms in myelin plasticity for learning and memory enhancement

Neural plasticity was considered as the principal mechanism for learning and memory many decades ago. So our study aims to figure out the underlying mechanisms of myelin plasticity associated with learning and memory. Myelin was considered for a long time as static, inert insulator, irrelevant to learning. But recent studies showed that myelination is dynamically changed to enhance neuronal plasticity. The study was conducted on 24 rats, divided into 3 groups, with 8 rats in each: Group 1: control in cages; Group 2: control untrained; and Group 3: rats were trained using Barnez maze behavior test. The gene expression analysis for Sox10, Myrf, Nrg1, Bdnf, Serpine2 and Mbp was evaluated by qRT-PCR in hippocampus tissues with correlation assessment, and histopathological and immunohistochemistry assessment were done. The present study showed improved spatial memory with increased myelination in the trained group, in addition to high expression of Sox10, Myrf, Nrg1 and Bdnf in the trained group compared to all others (P < 0.001). Serpine2 and GFAP as markers of astrocytes showed high expression in the trained group in comparison with other groups (P < 0.001) with strong positive correlation between Serpine2 and Mbp (r = 0.76, P = 0.02). Myelin plasticity as one of the crucial learning mechanisms, was influenced by different neural and environmental signals. In addition, there was a significant role of astrocytes in promoting such myelination effect.

Linking epileptic phenotypes and neural extracellular matrix remodeling signatures in mouse models of epilepsy

Epilepsies are multifaceted neurological disorders characterized by abnormal brain activity, e.g. caused by imbalanced synaptic excitation and inhibition. The neural extracellular matrix (ECM) is dynamically modulated by physiological and pathophysiological activity and critically involved in controlling the brain's excitability. We used different epilepsy models, i.e. mice lacking the presynaptic scaffolding protein Bassoon at excitatory, inhibitory or all synapse types as genetic models for rapidly generalizing early-onset epilepsy, and intra-hippocampal kainate injection, a model for acquired temporal lobe epilepsy, to study the relationship between epileptic seizures and ECM composition. Electroencephalogram recordings revealed Bassoon deletion at excitatory or inhibitory synapses having diverse effects on epilepsy-related phenotypes. While constitutive Bsn mutants and to a lesser extent GABAergic neuron-specific knockouts (BsnDlx5/6cKO) displayed severe epilepsy with more and stronger seizures than kainate-injected animals, mutants lacking Bassoon solely in excitatory forebrain neurons (BsnEmx1cKO) showed only mild impairments. By semiquantitative immunoblotting and immunohistochemistry we show model-specific patterns of neural ECM remodeling, and we also demonstrate significant upregulation of the ECM receptor CD44 in null and BsnDlx5/6cKO mutants. ECM-associated WFA-binding chondroitin sulfates were strongly augmented in seizure models. Strikingly, Brevican, Neurocan, Aggrecan and link proteins Hapln1 and Hapln4 levels reliably predicted seizure properties across models, suggesting a link between ECM state and epileptic phenotype.

STDP-Driven Rewiring in Spiking Neural Networks under Stimulus-Induced and Spontaneous Activity

Mathematical and computer simulation of learning in living neural networks have typically focused on changes in the efficiency of synaptic connections represented by synaptic weights in the models. Synaptic plasticity is believed to be the cellular basis for learning and memory. In spiking neural networks composed of dynamical spiking units, a biologically relevant learning rule is based on the so-called spike-timing-dependent plasticity or STDP. However, experimental data suggest that synaptic plasticity is only a part of brain circuit plasticity, which also includes homeostatic and structural plasticity. A model of structural plasticity proposed in this study is based on the activity-dependent appearance and disappearance of synaptic connections. The results of the research indicate that such adaptive rewiring enables the consolidation of the effects of STDP in response to a local external stimulation of a neural network. Subsequently, a vector field approach is used to demonstrate the successive "recording" of spike paths in both functional connectome and synaptic connectome, and finally in the anatomical connectome of the network. Moreover, the findings suggest that the adaptive rewiring could stabilize network dynamics over time in the context of activity patterns' reproducibility. A universal measure of such reproducibility introduced in this article is based on similarity between time-consequent patterns of the special vector fields characterizing both functional and anatomical connectomes.

Information Encoding in Bursting Spiking Neural Network Modulated by Astrocytes

We investigated a mathematical model composed of a spiking neural network (SNN) interacting with astrocytes. We analysed how information content in the form of two-dimensional images can be represented by an SNN in the form of a spatiotemporal spiking pattern. The SNN includes excitatory and inhibitory neurons in some proportion, sustaining the excitation-inhibition balance of autonomous firing. The astrocytes accompanying each excitatory synapse provide a slow modulation of synaptic transmission strength. An information image was uploaded to the network in the form of excitatory stimulation pulses distributed in time reproducing the shape of the image. We found that astrocytic modulation prevented stimulation-induced SNN hyperexcitation and non-periodic bursting activity. Such homeostatic astrocytic regulation of neuronal activity makes it possible to restore the image supplied during stimulation and lost in the raster diagram of neuronal activity due to non-periodic neuronal firing. At a biological point, our model shows that astrocytes can act as an additional adaptive mechanism for regulating neural activity, which is crucial for sensory cortical representations.

Bioinspired micro- and nano-structured neural interfaces

The development of a functional nervous system requires neurons to interact with and promptly respond to a wealth of biochemical, mechanical and topographical cues found in the neural extracellular matrix (ECM). Among these, ECM topographical cues have been found to strongly influence neuronal function and behavior. Here, we discuss how the blueprint of the architectural organization of the brain ECM has been tremendously useful as a source of inspiration to design biomimetic substrates to enhance neural interfaces and dictate neuronal behavior at the cell-material interface. In particular, we focus on different strategies to recapitulate cell-ECM and cell-cell interactions. In order to mimic cell-ECM interactions, we introduce roughness as a first approach to provide informative topographical biomimetic cues to neurons. We then examine 3D scaffolds and hydrogels, as softer 3D platforms for neural interfaces. Moreover, we will discuss how anisotropic features such as grooves and fibers, recapitulating both ECM fibrils and axonal tracts, may provide recognizable paths and tracks that neuron can follow as they develop and establish functional connections. Finally, we show how isotropic topographical cues, recapitulating shapes, and geometries of filopodia- and mushroom-like dendritic spines, have been instrumental to better reproduce neuron-neuron interactions for applications in bioelectronics and neural repair strategies. The high complexity of the brain architecture makes the quest for the fabrication of create more biologically relevant biomimetic architectures in continuous and fast development. Here, we discuss how recent advancements in two-photon polymerization and remotely reconfigurable dynamic interfaces are paving the way towards to a new class of smart biointerfaces forin vitroapplications spanning from neural tissue engineering as well as neural repair strategies.

Toward Reflective Spiking Neural Networks Exploiting Memristive Devices

The design of modern convolutional artificial neural networks (ANNs) composed of formal neurons copies the architecture of the visual cortex. Signals proceed through a hierarchy, where receptive fields become increasingly more complex and coding sparse. Nowadays, ANNs outperform humans in controlled pattern recognition tasks yet remain far behind in cognition. In part, it happens due to limited knowledge about the higher echelons of the brain hierarchy, where neurons actively generate predictions about what will happen next, i.e., the information processing jumps from reflex to reflection. In this study, we forecast that spiking neural networks (SNNs) can achieve the next qualitative leap. Reflective SNNs may take advantage of their intrinsic dynamics and mimic complex, not reflex-based, brain actions. They also enable a significant reduction in energy consumption. However, the training of SNNs is a challenging problem, strongly limiting their deployment. We then briefly overview new insights provided by the concept of a high-dimensional brain, which has been put forward to explain the potential power of single neurons in higher brain stations and deep SNN layers. Finally, we discuss the prospect of implementing neural networks in memristive systems. Such systems can densely pack on a chip 2D or 3D arrays of plastic synaptic contacts directly processing analog information. Thus, memristive devices are a good candidate for implementing in-memory and in-sensor computing. Then, memristive SNNs can diverge from the development of ANNs and build their niche, cognitive, or reflective computations.

Bistability and Chaos Emergence in Spontaneous Dynamics of Astrocytic Calcium Concentration

In this work, we consider a mathematical model describing spontaneous calcium signaling in astrocytes. Based on biologically relevant principles, this model simulates experimentally observed calcium oscillations and can predict the emergence of complicated dynamics. Using analytical and numerical analysis, various attracting sets were found and investigated. Employing bifurcation theory analysis, we examined steady state solutions, bistability, simple and complicated periodic limit cycles and also chaotic attractors. We found that astrocytes possess a variety of complex dynamical modes, including chaos and multistability, that can further provide different modulations of neuronal circuits, enhancing their plasticity and flexibility.

The Role of the Extracellular Matrix in Neural Progenitor Cell Proliferation and Cortical Folding During Human Neocortex Development

Extracellular matrix (ECM) has long been known to regulate many aspects of neural development in many different species. However, the role of the ECM in the development of the human neocortex is not yet fully understood. In this review we discuss the role of the ECM in human neocortex development and the different model systems that can be used to investigate this. In particular, we will focus on how the ECM regulates human neural stem and progenitor cell proliferation and differentiation, how the ECM regulates the architecture of the developing human neocortex and the effect of mutations in ECM and ECM-associated genes in neurodevelopmental disorders.

Lesion-induced changes of brevican expression in the perineuronal net of the superior vestibular nucleus

Damage to the vestibular sense organs evokes static and dynamic deficits in the eye movements, posture and vegetative functions. After a shorter or longer period of time, the vestibular function is partially or completely restored via a series of processes such as modification in the efficacy of synaptic inputs. As the plasticity of adult central nervous system is associated with the alteration of extracellular matrix, including its condensed form, the perineuronal net, we studied the changes of brevican expression in the perineuronal nets of the superior vestibular nucleus after unilateral labyrinth lesion. Our results demonstrated that the unilateral labyrinth lesion and subsequent compensation are accompanied by the changing of brevican staining pattern in the perineuronal nets of superior vestibular nucleus of the rat. The reduction of brevican in the perineuronal nets of superior vestibular nucleus may contribute to the vestibular plasticity by suspending the non-permissive role of brevican in the restoration of perineuronal net assembly. After a transitory decrease, the brevican expression restored to the control level parallel to the partial restoration of impaired vestibular function. The bilateral changing in the brevican expression supports the involvement of commissural vestibular fibers in the vestibular compensation. All experimental procedures were approved by the ‘University of Debrecen – Committee of Animal Welfare’ (approval No. 6/2017/DEMAB) and the ‘Scientific Ethics Committee of Animal Experimentation’ (approval No. HB/06/ÉLB/2270-10/2017; approved on June 6, 2017).

Blood-brain barrier dysfunction as a potential therapeutic target for neurodegenerative disorders

The blood-brain barrier (BBB) is composed of specific tight junction proteins and transporters expressed on the lining of endothelial cells of the vasculature in the brain. The structural and functional integrity of the BBB is one of the most critical factors for maintaining brain homeostasis and is mainly regulated by complex interactions between various cell types, such as endothelial cells, pericytes, and astrocytes, which are shaped by their differential responses to changes in microenvironments. Alterations in these cellular components have been implicated in neurodegenerative disorders. Although it has long been considered that BBB dysfunction is a mere ramification of pathological phenomena, emerging evidence supports its critical role in the pathogenesis of various disorders. In epilepsy, heightened BBB permeability has been found to be associated with increased occurrence of spontaneous seizures. Additionally, exaggerated inflammatory responses significantly correlate with increased BBB permeability during healthy aging. Furthermore, it has been previously reported that BBB disruption can be an early marker for predicting cognitive impairment in the progression of Alzheimer's disease. We herein review a potential role of the major cellular components of the BBB, with a focus on the contribution of BBB disruption, in neurodegenerative disease progression.

Unraveling Myelin Plasticity

Plasticity in the central nervous system (CNS) allows for responses to changing environmental signals. While the majority of studies on brain plasticity focus on neuronal synapses, myelin plasticity has now begun to emerge as a potential modulator of neuronal networks. Oligodendrocytes (OLs) produce myelin, which provides fast signal transmission, allows for synchronization of neuronal inputs, and helps to maintain neuronal function. Thus, myelination is also thought to be involved in learning. OLs differentiate from oligodendrocyte precursor cells (OPCs), which are distributed throughout the adult brain, and myelination continues into late adulthood. This process is orchestrated by numerous cellular and molecular signals, such as axonal diameter, growth factors, extracellular signaling molecules, and neuronal activity. However, the relative importance of, and cooperation between, these signaling pathways is currently unknown. In this review, we focus on the current knowledge about myelin plasticity in the CNS. We discuss new insights into the link between this type of plasticity, learning and behavior, as well as mechanistic aspects of myelin formation that may underlie myelin plasticity, highlighting OPC diversity in the CNS.