Tiam1 coordinates synaptic structural and functional plasticity underpinning the pathophysiology of neuropathic pain

Neuropathic pain is a common, debilitating chronic pain condition caused by damage or a disease affecting the somatosensory nervous system. Understanding the pathophysiological mechanisms underlying neuropathic pain is critical for developing new therapeutic strategies to treat chronic pain effectively. Tiam1 is a Rac1 guanine nucleotide exchange factor (GEF) that promotes dendritic and synaptic growth during hippocampal development by inducing actin cytoskeletal remodeling. Here, using multiple neuropathic pain animal models, we show that Tiam1 coordinates synaptic structural and functional plasticity in the spinal dorsal horn via actin cytoskeleton reorganization and synaptic NMDAR stabilization and that these actions are essential for the initiation, transition, and maintenance of neuropathic pain. Furthermore, an antisense oligonucleotides (ASO) targeting spinal Tiam1 persistently alleviate neuropathic pain sensitivity. Our findings suggest that Tiam1-coordinated synaptic functional and structural plasticity underlies the pathophysiology of neuropathic pain and that intervention of Tiam1-mediated maladaptive synaptic plasticity has long-lasting consequences in neuropathic pain management.

Post-stroke cognitive impairment and synaptic plasticity: A review about the mechanisms and Chinese herbal drugs strategies

Post-stroke cognitive impairment, is a major complication of stroke, characterized by cognitive dysfunction, which directly affects the quality of life. Post-stroke cognitive impairment highlights the causal relationship between stroke and cognitive impairment. The pathological damage of stroke, including the increased release of excitatory amino acids, oxidative stress, inflammatory responses, apoptosis, changed neurotrophic factor levels and gene expression, influence synaptic plasticity. Synaptic plasticity refers to the activity-dependent changes in the strength of synaptic connections and efficiency of synaptic transmission at pre-existing synapses and can be divided into structural synaptic plasticity and functional synaptic plasticity. Changes in synaptic plasticity have been proven to play important roles in the occurrence and treatment of post-stroke cognitive impairment. Evidence has indicated that Chinese herbal drugs have effect of treating post-stroke cognitive impairment. In this review, we overview the influence of pathological damage of stroke on synaptic plasticity, analyze the changes of synaptic plasticity in post-stroke cognitive impairment, and summarize the commonly used Chinese herbal drugs whose active ingredient or extracts can regulate synaptic plasticity. This review will summarize the relationship between post-stroke cognitive impairment and synaptic plasticity, provide new ideas for future exploration of the mechanism of post-stroke cognitive impairment, compile evidence of applying Chinese herbal drugs to treat post-stroke cognitive impairment and lay a foundation for the development of novel formulas for treating post-stroke cognitive impairment.

Fe65: A Scaffolding Protein of Actin Regulators

The scaffolding protein family Fe65, composed of Fe65, Fe65L1, and Fe65L2, was identified as an interaction partner of the amyloid precursor protein (APP), which plays a key function in Alzheimer’s disease. All three Fe65 family members possess three highly conserved interaction domains, forming complexes with diverse binding partners that can be assigned to different cellular functions, such as transactivation of genes in the nucleus, modulation of calcium homeostasis and lipid metabolism, and regulation of the actin cytoskeleton. In this article, we rule out putative new intracellular signaling mechanisms of the APP-interacting protein Fe65 in the regulation of actin cytoskeleton dynamics in the context of various neuronal functions, such as cell migration, neurite outgrowth, and synaptic plasticity.

Levodopa Improves Cognitive Function and the Deficits of Structural Synaptic Plasticity in Hippocampus Induced by Global Cerebral Ischemia/Reperfusion Injury in Rats

The cognitive impairment caused by cerebral ischemia/reperfusion is an unsolved problem in the field of international neural rehabilitation. Not only ameliorates the consciousness level of certain patients who suffered from ischemia-reperfusion injury and were comatose for a long time period after cerebral resuscitation treatment, but levodopa also improves the symptoms of neurological deficits in rats with global cerebral ischemia-reperfusion injury. However, Levodopa has not been widely used as a brain protection drug after cardiopulmonary resuscitation, because of its unclear repair mechanism. Levodopa was used to study the neuroplasticity in the hippocampus of global cerebral ischemia/reperfusion injury rat model, established by Pulsinelli's four-vessel occlusion method. Levodopa was injected intraperitoneally at 50 mg/kg/d for 7 consecutive days after 1st day of surgery. The modified neurological function score, Morris water maze, magnetic resonance imaging, Nissl and TH staining, electron microscopy and western blot were used in the present study. The results showed that levodopa improved the neurological function and learning and memory of rats after global cerebral ischemia/reperfusion injury, improved the integrity of white matter, and density of gray matter in the hippocampus, increased the number of synapses, reduced the delayed neuronal death, and increased the expression of synaptic plasticity-related proteins (BDNF, TrkB, PSD95, and Drebrin) in the hippocampus. In conclusion, levodopa can improve cognitive function after global cerebral ischemia/reperfusion injury by enhancing the synaptic plasticity in the hippocampus.

Statistical analysis of unidirectional and reciprocal chemical connections in the C. elegans connectome

We analyze unidirectional and reciprocally connected pairs of neurons in the chemical connectomes of the male and hermaphrodite Caenorhabditis elegans, using recently published data. Our analysis reveals that reciprocal connections provide communication between most neurons with chemical synapses, and comprise on average more synapses than both unidirectional connections and the entire connectome. We further reveal that the C. elegans connectome is wired so that afferent connections onto neurons with large numbers of presynaptic neighbors (in-degree) comprise an above-average number of synapses (synaptic multiplicity). Notably, the larger the in-degree of a neuron the larger the synaptic multiplicity of its afferent connections. Finally, we show that the male forms two times fewer reciprocal connections between sex-shared neurons than the hermaphrodite, but a large number of reciprocal connections with male-specific neurons. These observations provide evidence for Hebbian structural plasticity in the C. elegans.

Analysis of Synaptic Microcircuits in the Mushroom Bodies of the Honeybee

Mushroom bodies (MBs) are multisensory integration centers in the insect brain involved in learning and memory formation. In the honeybee, the main sensory input region (calyx) of MBs is comparatively large and receives input from mainly olfactory and visual senses, but also from gustatory/tactile modalities. Behavioral plasticity following differential brood care, changes in sensory exposure or the formation of associative long-term memory (LTM) was shown to be associated with structural plasticity in synaptic microcircuits (microglomeruli) within olfactory and visual compartments of the MB calyx. In the same line, physiological studies have demonstrated that MB-calyx microcircuits change response properties after associative learning. The aim of this review is to provide an update and synthesis of recent research on the plasticity of microcircuits in the MB calyx of the honeybee, specifically looking at the synaptic connectivity between sensory projection neurons (PNs) and MB intrinsic neurons (Kenyon cells). We focus on the honeybee as a favorable experimental insect for studying neuronal mechanisms underlying complex social behavior, but also compare it with other insect species for certain aspects. This review concludes by highlighting open questions and promising routes for future research aimed at understanding the causal relationships between neuronal and behavioral plasticity in this charismatic social insect.

Neuronal Plasticity in the Mushroom-Body Calyx of Bumble Bee Workers During Early Adult Development

Division of labor among workers is a key feature of social insects and frequently characterized by an age-related transition between tasks, which is accompanied by considerable structural changes in higher brain centers. Bumble bees (Bombus terrestris), in contrast, exhibit a size-related rather than an age-related task allocation, and thus workers may already start foraging at two days of age. We ask how this early behavioral maturation and distinct size variation are represented at the neuronal level and focused our analysis on the mushroom bodies (MBs), brain centers associated with sensory integration, learning and memory. To test for structural neuronal changes related to age, light exposure, and body size, whole-mount brains of age-marked workers were dissected for synapsin immunolabeling. MB calyx volumes, densities, and absolute numbers of olfactory and visual projection neuron (PN) boutons were determined by confocal laser scanning microscopy and three-dimensional image analyses. Dark-reared bumble bee workers showed an early age-related volume increase in olfactory and visual calyx subcompartments together with a decrease in PN-bouton density during the first three days of adult life. A 12:12  h light-dark cycle did not affect structural organization of the MB calyces compared to dark-reared individuals. MB calyx volumes and bouton numbers positively correlated with body size, whereas bouton density was lower in larger workers. We conclude that, in comparison to the closely related honey bees, neuronal maturation in bumble bees is completed at a much earlier stage, suggesting a strong correlation between neuronal maturation time and lifestyle in both species.

Loss of Mecp2 Causes Atypical Synaptic and Molecular Plasticity of Parvalbumin-Expressing Interneurons Reflecting Rett Syndrome-Like Sensorimotor Defects

Rett syndrome (RTT) is caused in most cases by loss-of-function mutations in the X-linked gene encoding methyl CpG-binding protein 2 (MECP2). Understanding the pathological processes impacting sensory-motor control represents a major challenge for clinical management of individuals affected by RTT, but the underlying molecular and neuronal modifications remain unclear. We find that symptomatic male Mecp2 knockout (KO) mice show atypically elevated parvalbumin (PV) expression in both somatosensory (S1) and motor (M1) cortices together with excessive excitatory inputs converging onto PV-expressing interneurons (INs). In accordance, high-speed voltage-sensitive dye imaging shows reduced amplitude and spatial spread of synaptically induced neuronal depolarizations in S1 of Mecp2 KO mice. Moreover, motor learning-dependent changes of PV expression and structural synaptic plasticity typically occurring on PV⁺ INs in M1 are impaired in symptomatic Mecp2 KO mice. Finally, we find similar abnormalities of PV networks plasticity in symptomatic female Mecp2 heterozygous mice. These results indicate that in Mecp2 mutant mice the configuration of PV⁺ INs network is shifted toward an atypical plasticity state in relevant cortical areas compatible with the sensory-motor dysfunctions characteristics of RTT.

Structural Plasticity on the SpiNNaker Many-Core Neuromorphic System

The structural organization of cortical areas is not random, with topographic maps commonplace in sensory processing centers. This topographical organization allows optimal wiring between neurons, multimodal sensory integration, and performs input dimensionality reduction. In this work, a model of topographic map formation is implemented on the SpiNNaker neuromorphic platform, running in realtime using point neurons, and making use of both synaptic rewiring and spike-timing dependent plasticity (STDP). In agreement with Bamford et al. (2010), we demonstrate that synaptic rewiring refines an initially rough topographic map over and beyond the ability of STDP, and that input selectivity learnt through STDP is embedded into the network connectivity through rewiring. Moreover, we show the presented model can be used to generate topographic maps between layers of neurons with minimal initial connectivity, and stabilize mappings which would otherwise be unstable through the inclusion of lateral inhibition.

The Spacing Effect for Structural Synaptic Plasticity Provides Specificity and Precision in Plastic Changes

In contrast to trials of training without intervals (massed training), training trials spaced over time (spaced training) induce a more persistent memory identified as long-term memory (LTM). This phenomenon, known as the spacing effect for memory, is poorly understood. LTM is supported by structural synaptic plasticity; however, how synapses integrate spaced stimuli remains elusive. Here, we analyzed events of structural synaptic plasticity at the single-synapse level after distinct patterns of stimulation in motoneurons of Drosophila We found that the spacing effect is a phenomenon detected at synaptic level, which determines the specificity and the precision in structural synaptic plasticity. Whereas a single pulse of stimulation (massed) induced structural synaptic plasticity, the same amount of stimulation divided in three spaced stimuli completely prevented it. This inhibitory effect was determined by the length of the interstimulus intervals. The inhibitory effect of the spacing was lost by suppressing the activity of Ras or mitogen-activated protein kinase, whereas the overexpression of Ras-WT enhanced it. Moreover, dividing the same total time of stimulation into five or more stimuli produced a higher precision in the number of events of plasticity. Ras mutations associated with intellectual disability abolished the spacing effect and led neurons to decode distinct stimulation patterns as massed stimulation. This evidence suggests that the spacing effect for memory may result from the effect of the spacing in synaptic plasticity, which appears to be a property not limited to neurons involved in learning and memory. We propose a model of spacing-dependent structural synaptic plasticity.SIGNIFICANCE STATEMENT Long-term memory (LTM) induced by repeated trials spaced over time is known as the spacing effect, a common property in the animal kingdom. Altered mechanisms in the spacing effect have been found in animal models of disorders with intellectual disability, such as Noonan syndrome. Although LTM is sustained by structural synaptic plasticity, how synapses integrate spaced stimuli and decode them into specific plastic changes remains elusive. Here, we show that the spacing effect is a phenomenon detected at the synaptic level, which determines the properties of the response in structural plasticity, including precision of such response. Whereas suppressing or enhancing Ras/mitogen-activated protein kinase signaling changed how synapses decode a pattern of stimuli, a disease-related Ras allele abolished the spacing effect for plastic changes.

Matrix metalloproteinase-9 involvement in the structural plasticity of dendritic spines

Dendritic spines are the locus for excitatory synaptic transmission in the brain and thus play a major role in neuronal plasticity. The ability to alter synaptic connections includes volumetric changes in dendritic spines that are driven by scaffolds created by the extracellular matrix (ECM). Here, we review the effects of the proteolytic activity of ECM proteases in physiological and pathological structural plasticity. We use matrix metalloproteinase-9 (MMP-9) as an example of an ECM modifier that has recently emerged as a key molecule in regulating the morphology and dysmorphology of dendritic spines that underlie synaptic plasticity and neurological disorders, respectively. We summarize the influence of MMP-9 on the dynamic remodeling of the ECM via the cleavage of extracellular substrates. We discuss its role in the formation, modification, and maintenance of dendritic spines in learning and memory. Finally, we review research that implicates MMP-9 in aberrant synaptic plasticity and spine dysmorphology in neurological disorders, with a focus on morphological abnormalities of dendritic protrusions that are associated with epilepsy.

Homeostatic structural plasticity increases the efficiency of small-world networks

In networks with small-world topology, which are characterized by a high clustering coefficient and a short characteristic path length, information can be transmitted efficiently and at relatively low costs. The brain is composed of small-world networks, and evolution may have optimized brain connectivity for efficient information processing. Despite many studies on the impact of topology on information processing in neuronal networks, little is known about the development of network topology and the emergence of efficient small-world networks. We investigated how a simple growth process that favors short-range connections over long-range connections in combination with a synapse formation rule that generates homeostasis in post-synaptic firing rates shapes neuronal network topology. Interestingly, we found that small-world networks benefited from homeostasis by an increase in efficiency, defined as the averaged inverse of the shortest paths through the network. Efficiency particularly increased as small-world networks approached the desired level of electrical activity. Ultimately, homeostatic small-world networks became almost as efficient as random networks. The increase in efficiency was caused by the emergent property of the homeostatic growth process that neurons started forming more long-range connections, albeit at a low rate, when their electrical activity was close to the homeostatic set-point. Although global network topology continued to change when neuronal activities were around the homeostatic equilibrium, the small-world property of the network was maintained over the entire course of development. Our results may help understand how complex systems such as the brain could set up an efficient network topology in a self-organizing manner. Insights from our work may also lead to novel techniques for constructing large-scale neuronal networks by self-organization.