Complex Dendritic Trees Research Articles

Catalpol rescues LPS-induced cognitive impairment via inhibition of NF-Κb-regulated neuroinflammation and up-regulation of TrkB-mediated BDNF secretion in mice

Ethnopharmacological relevanceSeptic-associated encephalopathy (SAE) is a key manifestation of sepsis. Nevertheless, specific treatment for SAE is still lacking. Catalpol is an active component derived from Rehmanniae Radix, and has been demonstrated to be a potential neuroprotective agent. However, its effect on SAE still needs to be fully explored. AimTo address the benefits of catalpol on post-sepsis cognitive deterioration and related mechanisms. Materials and methodsNovel object recognition test, temporal order task, histopathology, and immunochemistry were applied to address the benefits of catalpol on LPS-triggered post-sepsis cognitive decline in mice. Xuebijing injection (10 ml/kg) has been utilized as a positive control in the above animal studies. After treatment, the catalpol content in the hippocampus was determined using LC-MS/MS. Finally, the mechanisms of catalpol were further assessed in BV2 and PC12 cells in vitro using Western blot, RT-PCR, flow cytometry, molecular docking tests, thermal shift assay, transmission electron microscopy, and immunofluorescence analysis. ResultsBehavior tests showed that catalpol therapy could lessen the cognitive impairment induced by LPS damage. HE, Nissl, immunofluorescence, transmission electron microscopy, and Golgi staining further reflected that catalpol treatment could restore lymphocyte infiltration, blood-brain barrier (BBB) degradation, and the decreasing complexity of dendritic trees. According to LC-MS/MS analysis, catalpol had a 136 ng/mg concentration in the hippocampus. In vitro investigation showed that catalpol could inhibit microglia M1 polarization via blocking NF-κB phosphorylation, translocation and then reducing inflammatory cytokine release in BV2 microglia cells. Brain-derived neurotrophic factor (BDNF) release up-regulation and TrkB pathway activation were observed in the catalpol treatment group in vivo and in vitro. The effect of catalpol on enhancing BDNF expression was inhibited by the specific inhibitor of TrkB (GNF-5837) in PC12 cells. Further molecular docking tests showed that catalpol formed weak hydrophobic bonds with TrkB. Besides, thermal shift assay also reflected that catalpol incubation caused a considerable change in the melting temperature of the TrkB. ConclusionCatalpol alleviates LPS-triggered post-sepsis cognitive impairment by reversing neuroinflammation via blocking the NF-κB pathway, up-regulating neurotrophic factors via the activation of TrkB pathway, and preserving BBB integrity.

Meshed neuronal mitochondrial networks empowered by AI-powered classifiers and immersive VR reconstruction.

Mitochondrial networks are defined as a continuous matrix lumen, but the morphological feature of neuronal mitochondrial networks is not clear due to the lack of suitable analysis techniques. The aim of the present study is to develop a framework to capture and analyze the neuronal mitochondrial networks by using 4-step process composed of 2D and 3D observation, primary and secondary virtual reality (VR) analysis, with the help of artificial intelligence (AI)-powered Aivia segmentation an classifiers. In order to fulfill this purpose, we first generated the PCs-Mito-GFP mice, in which green fluorescence protein (GFP) could be expressed on the outer mitochondrial membrane specifically on the cerebellar Purkinje cells (PCs), thus all mitochondria in the giant neuronal soma, complex dendritic arborization trees and long projection axons of Purkinje cells could be easily detected under a laser scanning confocal microscope. The 4-step process resolved the complicated neuronal mitochondrial networks into discrete neuronal mitochondrial meshes. Second, we measured the two parameters of the neuronal mitochondrial meshes, and the results showed that the surface area (μm2) of mitochondrial meshes was the biggest in dendritic trees (45.30 ± 53.21), the smallest in granular-like axons (3.99 ± 1.82), and moderate in soma (27.81 ± 22.22) and silk-like axons (17.50 ± 15.19). These values showed statistically different among different subcellular locations. The volume (μm3) of mitochondrial meshes was the biggest in dendritic trees (9.97 ± 12.34), the smallest in granular-like axons (0.43 ± 0.25), and moderate in soma (6.26 ± 6.46) and silk-like axons (3.52 ± 4.29). These values showed significantly different among different subcellular locations. Finally, we found both the surface area and the volume of mitochondrial meshes in dendritic trees and soma within the Purkinje cells in PCs-Mito-GFP mice after receiving the training with the simulating long-term pilot flight concentrating increased significantly. The precise reconstruction of neuronal mitochondrial networks is extremely laborious, the present 4-step workflow powered by artificial intelligence and virtual reality reconstruction could successfully address these challenges.

Facial nerve axotomy induces morphological changes in hippocampal pyramidal neurons.

Facial nerve injury in rats have been widely used to study functional and structural changes that occur in the injured motoneurons and other central nervous system structures related with sensorimotor processing. A decrease in long-term potentiation of hippocampal CA3-to-CA1 commissural synapse has recently been reported related to this peripheral injury. Additionally, it has been found increased corticosterone plasmatic levels, impairment in spatial memory consolidation, and hippocampal microglial activation in animals with facial nerve axotomy. In this work, we analyzed the neuronal morphology of hippocampal CA1 and CA3 pyramidal neurons in animals with either reversible or irreversible facial nerve injury. For this purpose, brain tissues of injured animals sacrificed at different postlesion times, were stained with the Golgi-Cox method and compared with control brains. It was found that both reversible and irreversible facial nerve injury-induced significant decreases in dendritic tree complexity, dendritic length, branch points, and spine density of hippocampal neurons. However, such changes' timing varied according to hippocampal area (CA1 vs. CA3), dendritic area (apical vs. basal), and lesion type (reversible vs. irreversible). In general, the observed changes were transient when animals had the possibility of motor recovery (reversible injury), but perdurable if the recovery from the lesion was impeded (irreversible injury). CA1 apical and CA3 basal dendritic tree morphology were more sensible to irreversible injury. It is concluded that facial nerve injury induced significant changes in hippocampal CA1 and CA3 pyramidal neurons morphology, which could be related to LTP impairments and microglial activation in the hippocampal formation, previously described.

Genome-wide translation control analysis of developing human neurons

During neuronal differentiation, neuroprogenitor cells become polarized, change shape, extend axons, and form complex dendritic trees. While growing, axons are guided by molecular cues to their final destination, where they establish synaptic connections with other neuronal cells. Several layers of regulation are integrated to control neuronal development properly. Although control of mRNA translation plays an essential role in mammalian gene expression, how it contributes temporarily to the modulation of later stages of neuronal differentiation remains poorly understood. Here, we investigated how translation control affects pathways and processes essential for neuronal maturation, using H9-derived human neuro progenitor cells differentiated into neurons as a model. Through Ribosome Profiling (Riboseq) combined with RNA sequencing (RNAseq) analysis, we found that translation control regulates the expression of critical hub genes. Fundamental synaptic vesicle secretion genes belonging to SNARE complex, Rab family members, and vesicle acidification ATPases are strongly translationally regulated in developing neurons. Translational control also participates in neuronal metabolism modulation, particularly affecting genes involved in the TCA cycle and glutamate synthesis/catabolism. Importantly, we found translation regulation of several critical genes with fundamental roles regulating actin and microtubule cytoskeleton pathways, critical to neurite generation, spine formation, axon guidance, and circuit formation. Our results show that translational control dynamically integrates important signals in neurons, regulating several aspects of its development and biology.

Common Microscale and Macroscale Principles of Connectivity in the Human Brain.

The brain requires efficient information transfer between neurons and large-scale brain regions. Brain connectivity follows predictable organizational principles. At the cellular level, larger supragranular pyramidal neurons have larger, more branched dendritic trees, more synapses, and perform more complex computations; at the macroscale, region-to-region connections display a diverse architecture with highly connected hub areas facilitating complex information integration and computation. Here, we explore the hypothesis that the branching structure of large-scale region-to-region connectivity follows similar organizational principles as the neuronal scale. We examine microscale connectivity of basal dendritic trees of supragranular pyramidal neurons (300+) across 10 cortical areas in five human donor brains (1 male, 4 female). Dendritic complexity was quantified as the number of branch points, tree length, spine count, spine density, and overall branching complexity. High-resolution diffusion-weighted MRI was used to construct white matter trees of corticocortical wiring. Examining complexity of the resulting white matter trees using the same measures as for dendritic trees shows heteromodal association areas to have larger, more complex white matter trees than primary areas (p < 0.0001) and macroscale complexity to run in parallel with microscale measures, in terms of number of inputs (r = 0.677, p = 0.032), branch points (r = 0.797, p = 0.006), tree length (r = 0.664, p = 0.036), and branching complexity (r = 0.724, p = 0.018). Our findings support the integrative theory that brain connectivity follows similar principles of connectivity at neuronal and macroscale levels and provide a framework to study connectivity changes in brain conditions at multiple levels of organization.SIGNIFICANCE STATEMENT Within the human brain, cortical areas are involved in a wide range of processes, requiring different levels of information integration and local computation. At the cellular level, these regional differences reflect a predictable organizational principle with larger, more complexly branched supragranular pyramidal neurons in higher order regions. We hypothesized that the 3D branching structure of macroscale corticocortical connections follows the same organizational principles as the cellular scale. Comparing branching complexity of dendritic trees of supragranular pyramidal neurons and of MRI-based regional white matter trees of macroscale connectivity, we show that macroscale branching complexity is larger in higher order areas and that microscale and macroscale complexity go hand in hand. Our findings contribute to a multiscale integrative theory of brain connectivity.

Properties and Computational Consequences of Fast Dendritic Spikes during Natural Behavior

The dendritic membrane potential was recently measured for the first time in drug-free, naturally behaving rats over several days. These showed that neuronal dendrites generate a lot of sodium spikes, up to ten times as many as the somatic spikes. These key experimental findings are reviewed here, along with a discussion of computational models, and computational consequences of such intense spike traffic in dendrites. We overview the experimental techniques that enabled these measurements as well as a variety of models, ranging from conceptual models to detailed biophysical models. The biophysical models suggest that the intense dendritic spiking activity can arise from the biophysical properties of the dendritic voltage-dependent and synaptic ion channels, and delineate some computational consequences of fast dendritic spike activity. One remarkable aspect is that in the model, with fast dendritic spikes, the efficacy of synaptic strength in terms of driving the somatic activity is much less dependent on the position of the synapse in dendrites. This property suggests that fast dendritic spikes is a way to confer to neurons the possibility to grow complex dendritic trees with little computational loss for the distal most synapses, and thus form very complex networks with high density of connections, such as typically in the human brain. Another important consequence is that dendritically localized spikes can allow simultaneous but different computations on different dendritic branches, thereby greatly increasing the computational capacity and complexity of neuronal networks.

Jacob, a Synapto-Nuclear Protein Messenger Linking N-methyl-D-aspartate Receptor Activation to Nuclear Gene Expression.

Pyramidal neurons exhibit a complex dendritic tree that is decorated by a huge number of spine synapses receiving excitatory input. Synaptic signals not only act locally but are also conveyed to the nucleus of the postsynaptic neuron to regulate gene expression. This raises the question of how the spatio-temporal integration of synaptic inputs is accomplished at the genomic level and which molecular mechanisms are involved. Protein transport from synapse to nucleus has been shown in several studies and has the potential to encode synaptic signals at the site of origin and decode them in the nucleus. In this review, we summarize the knowledge about the properties of the synapto-nuclear messenger protein Jacob with special emphasis on a putative role in hippocampal neuronal plasticity. We will elaborate on the interactome of Jacob, the signals that control synapto-nuclear trafficking, the mechanisms of transport, and the potential nuclear function. In addition, we will address the organization of the Jacob/NSMF gene, its origin and we will summarize the evidence for the existence of splice isoforms and their expression pattern.

Diverse processing underlying frequency integration in midbrain neurons of barn owls.

Emergent response properties of sensory neurons depend on circuit connectivity and somatodendritic processing. Neurons of the barn owl’s external nucleus of the inferior colliculus (ICx) display emergence of spatial selectivity. These neurons use interaural time difference (ITD) as a cue for the horizontal direction of sound sources. ITD is detected by upstream brainstem neurons with narrow frequency tuning, resulting in spatially ambiguous responses. This spatial ambiguity is resolved by ICx neurons integrating inputs over frequency, a relevant processing in sound localization across species. Previous models have predicted that ICx neurons function as point neurons that linearly integrate inputs across frequency. However, the complex dendritic trees and spines of ICx neurons raises the question of whether this prediction is accurate. Data from in vivo intracellular recordings of ICx neurons were used to address this question. Results revealed diverse frequency integration properties, where some ICx neurons showed responses consistent with the point neuron hypothesis and others with nonlinear dendritic integration. Modeling showed that varied connectivity patterns and forms of dendritic processing may underlie observed ICx neurons’ frequency integration processing. These results corroborate the ability of neurons with complex dendritic trees to implement diverse linear and nonlinear integration of synaptic inputs, of relevance for adaptive coding and learning, and supporting a fundamental mechanism in sound localization.

Short high fat diet triggers reversible and region specific effects in DCX+ hippocampal immature neurons of adolescent male mice

Adolescence represents a crucial period for maturation of brain structures involved in cognition. Early in life unhealthy dietary patterns are associated with inferior cognitive outcomes at later ages; conversely, healthy diet is associated with better cognitive results. In this study we analyzed the effects of a short period of hypercaloric diet on newborn hippocampal doublecortin+ (DCX) immature neurons in adolescent mice. Male mice received high fat diet (HFD) or control low fat diet (LFD) from the 5th week of age for 1 or 2 weeks, or 1 week HFD followed by 1 week LFD. After diet supply, mice were either perfused for immunohistochemical (IHC) analysis or their hippocampi were dissected for biochemical assays. Detailed morphometric analysis was performed in DCX+ cells that displayed features of immature neurons. We report that 1 week-HFD was sufficient to dramatically reduce dendritic tree complexity of DCX+ cells. This effect occurred specifically in dorsal and not ventral hippocampus and correlated with reduced BDNF expression levels in dorsal hippocampus. Both structural and biochemical changes were reversed by a return to LFD. Altogether these studies increase our current knowledge on potential consequences of hypercaloric diet on brain and in particular on dorsal hippocampal neuroplasticity.

Studying Synaptically Evoked Cortical Responses ex vivo With Combination of a Single Neuron Recording (Whole-Cell) and Population Voltage Imaging (Genetically Encoded Voltage Indicator).

In a typical electrophysiology experiment, synaptic stimulus is delivered in a cortical layer (1–6) and neuronal responses are recorded intracellularly in individual neurons. We recreated this standard electrophysiological paradigm in brain slices of mice expressing genetically encoded voltage indicators (GEVIs). This allowed us to monitor membrane voltages in the target pyramidal neurons (whole-cell), and population voltages in the surrounding neuropil (optical imaging), simultaneously. Pyramidal neurons have complex dendritic trees that span multiple cortical layers. GEVI imaging revealed areas of the brain slice that experienced the strongest depolarization on a specific synaptic stimulus (location and intensity), thus identifying cortical layers that contribute the most afferent activity to the recorded somatic voltage waveform. By combining whole-cell with GEVI imaging, we obtained a crude distribution of activated synaptic afferents in respect to the dendritic tree of a pyramidal cell. Synaptically evoked voltage waves propagating through the cortical neuropil (dendrites and axons) were not static but rather they changed on a millisecond scale. Voltage imaging can identify areas of brain slices in which the neuropil was in a sustained depolarization (plateau), long after the stimulus onset. Upon a barrage of synaptic inputs, a cortical pyramidal neuron experiences: (a) weak temporal summation of evoked voltage transients (EPSPs); and (b) afterhyperpolarization (intracellular recording), which are not represented in the GEVI population imaging signal (optical signal). To explain these findings [(a) and (b)], we used four voltage indicators (ArcLightD, chi-VSFP, Archon1, and di-4-ANEPPS) with different optical sensitivity, optical response speed, labeling strategy, and a target neuron type. All four imaging methods were used in an identical experimental paradigm: layer 1 (L1) synaptic stimulation, to allow direct comparisons. The population voltage signal showed paired-pulse facilitation, caused in part by additional recruitment of new neurons and dendrites. “Synaptic stimulation” delivered in L1 depolarizes almost an entire cortical column to some degree.

Automatic Identification of Dendritic Branches and their Orientation

The structure of neuronal dendritic trees plays a key role in the integration of synaptic inputs in neurons. Therefore, characterization of the morphology of dendrites is essential for a better understanding of neuronal function. However, the complexity of dendritic trees, both when isolated and especially when located within neuronal networks, has not been completely understood. We developed a new computational tool, SOA (Segmentation and Orientation Analysis), which allows automatic measurement of the orientation of dendritic branches from fluorescence images of 2D neuronal cultures. SOA, written in Python, uses segmentation to distinguish dendritic branches from the image background and accumulates a database on the spatial direction of each branch. The database is then used to calculate morphological parameters such as the directional distribution of dendritic branches in a network and the prevalence of parallel dendritic branch growth. The data obtained can be used to detect structural changes in dendrites in response to neuronal activity and to biological and pharmacological stimuli.

Mapping complex cell morphology in the grey matter with double diffusion encoding MR: A simulation study

This paper investigates the impact of cell body (namely soma) size and branching of cellular projections on diffusion MR imaging (dMRI) and spectroscopy (dMRS) signals for both standard single diffusion encoding (SDE) and more advanced double diffusion encoding (DDE) measurements using numerical simulations. The aim is to investigate the ability of dMRI/dMRS to characterize the complex morphology of brain cells focusing on these two distinctive features of brain grey matter.To this end, we employ a recently developed computational framework to create three dimensional meshes of neuron-like structures for Monte Carlo simulations, using diffusion coefficients typical of water and brain metabolites. Modelling the cellular structure as realistically connected spherical soma and cylindrical cellular projections, we cover a wide range of combinations of sphere radii and branching order of cellular projections, characteristic of various grey matter cells. We assess the impact of spherical soma size and branching order on the b-value dependence of the SDE signal as well as the time dependence of the mean diffusivity (MD) and mean kurtosis (MK). Moreover, we also assess the impact of spherical soma size and branching order on the angular modulation of DDE signal at different mixing times, together with the mixing time dependence of the apparent microscopic anisotropy (μA), a promising contrast derived from DDE measurements.The SDE results show that spherical soma size has a measurable impact on both the b-value dependence of the SDE signal and the MD and MK diffusion time dependence for both water and metabolites. On the other hand, we show that branching order has little impact on either, especially for water. In contrast, the DDE results show that spherical soma size has a measurable impact on the DDE signal's angular modulation at short mixing times and the branching order of cellular projections significantly impacts the mixing time dependence of the DDE signal's angular modulation as well as of the derived μA, for both water and metabolites.Our results confirm that SDE based techniques may be sensitive to spherical soma size, and most importantly, show for the first time that DDE measurements may be more sensitive to the dendritic tree complexity (as parametrized by the branching order of cellular projections), paving the way for new ways of characterizing grey matter morphology, non-invasively using dMRS and potentially dMRI.

Neuron tracing and quantitative analyses of dendritic architecture reveal symmetrical three-way-junctions and phenotypes of git-1 in C. elegans.

Complex dendritic trees are a distinctive feature of neurons. Alterations to dendritic morphology are associated with developmental, behavioral and neurodegenerative changes. The highly-arborized PVD neuron of C. elegans serves as a model to study dendritic patterning; however, quantitative, objective and automated analyses of PVD morphology are missing. Here, we present a method for neuronal feature extraction, based on deep-learning and fitting algorithms. The extracted neuronal architecture is represented by a database of structural elements for abstracted analysis. We obtain excellent automatic tracing of PVD trees and uncover that dendritic junctions are unevenly distributed. Surprisingly, these junctions are three-way-symmetrical on average, while dendritic processes are arranged orthogonally. We quantify the effect of mutation in git-1, a regulator of dendritic spine formation, on PVD morphology and discover a localized reduction in junctions. Our findings shed new light on PVD architecture, demonstrating the effectiveness of our objective analyses of dendritic morphology and suggest molecular control mechanisms.

Classification by morphology of multipolar neurons of the human principal olivary nucleus

The principal olivary nucleus is the largest part of the inferior olivary complex and is involved in the spatial and temporal organization of movement and motor learning. Nearly all neurons in this nucleus is multipolar along with having a highly complex dendritic tree and significant asymmetry in shape. In this study, we updated the current classification scheme, examined morphological differences between the proposed groups, and investigated age-related morphological changes. Histological preparations were digitized by a light microscope and a sample of 259 images of neurons was analyzed by 17 computationally generated parameters of morphology. These were reduced to the four variables of principal component analysis and the sample was classified by k-means method of clustering into three clusters. The differences between clusters were documented and for medium-sized neurons the relationship between four morphological parameters and age were investigated. Finally, for two of the age groups the changes in the morphology were explored. This study includes a detailed and robust classification of the PON neurons and the findings improve upon past qualitative work.

Melatonin Modulates Dendrite Maturation and Complexity in the Dorsal- and Ventral- Dentate Gyrus Concomitantly with Its Antidepressant-Like Effect in Male Balb/C Mice.

Adult neurogenesis occurs in the dentate gyrus (DG) of the hippocampus. New neurons help to counteract the effects of stress and several interventions including antidepressant drugs, environmental modifications and internal factors act pro-neurogenic with consequences in the dorsal and ventral DG. Melatonin, the main product synthesized by the pineal gland, induces antidepressant-like effects and modulates several events of the neurogenic process. However, the information related to the capability of melatonin to modulate dendrite maturation and complexity in the dorsal and ventral regions of the DG and their correlation with its antidepressant-like effect is absent. Thus, in this study, we analyzed the impact of melatonin (0, 0.5, 1, 2.5, 5 or 10 mg/kg) administered daily for fourteen days on the number, dendrite complexity and distribution of doublecortin (DCX)-cells in the dorsal-ventral regions of the DG in male Balb/C mice. Doublecortin is a microtubule-associated protein that is expressed during the course of dendritic maturation of newborn neurons. Also, we analyzed the impact of melatonin on despair-like behavior in the forced swim test. We first found a significant increase in the number and higher dendrite complexity, mainly with the doses of 2.5, 5 and 10 mg/kg of melatonin (81%, 122%, 78%). These cells showed more complex dendritic trees in the ventral- and the dorsal- DG. Concomitantly, the doses of 5 and 10 mg/kg of melatonin decreased depressant-like behavior (76%, 82%). Finally, the data corroborate the antidepressant-like effect of melatonin and the increasing number of doublecortin-associated cells. Besides, the data indicate that melatonin favors the number and dendrite complexity of DCX-cells in the dorsal- and ventral- region of the DG, which may explain part of the antidepressant-like effect of melatonin.

Neuropathic Pain Causes Memory Deficits and Dendrite Tree Morphology Changes in Mouse Hippocampus.

IntroductionNeuropathic pain manifests in a diverse combination of sensory symptoms and disorders of higher nervous activity, such as memory deficiency, anxiety, depression, anhedonia, etc. This suggests the participation of brain structures, including the hippocampus, in the pathogenesis of neuropathic pain. The elucidation of central sensitization mechanisms underlying neuropathic pain cognitive and affective symptoms may be useful in the development of new and effective treatments for these common disorders. The study aims to elucidate the effect of chronic neuropathic pain on cognitive function and underlying neuronal plasticity in the hippocampus.MethodsChronic constriction injury of mouse right hind limb sciatic nerve was used as a model of neuropathic pain. The presence of neuropathic pain was confirmed by the thermal and mechanical allodynia. The morphology of the CA1 pyramidal neurons and the dentate gyrus (DG) granule neurons were studied using Golgi-Cox staining. The hippocampal proteins concentration was determined by immunohistochemistry and ELISA.ResultsBehavioral testing revealed reduced locomotor activity as well as impaired working and long-term memory in mice with a ligated nerve. We revealed changes in the dendritic tree morphology in CA1 and the dentate gyrus hippocampal subregions. We found the atrophy of the CA1 pyramidal neurons and an increase in the dendritic tree complexity in DG. Moreover, changes in the density of dendritic spines were observed in these regions. In addition, we revealed increased expression of the Arc protein in DG granule neurons and decreased surface expression of AMPA receptors within the hippocampus. Decreased AMPA receptors expression underlies observed altered dendrite arborization and dendritic spines morphology.DiscussionWe found that pain information entering the hippocampus causes neuronal plasticity changes. The changes in neurite arborization, dendritic length and dendritic spines morphology as well as protein expression are observed within the hippocampal regions involved in the processing of pain information. Moreover, changes in the dendrite morphology in hippocampal subregions are different due to the anatomical and functional heterogeneity of the hippocampus. Apparently, the detected morphological and biochemical changes can underlie the observed hippocampus-dependent behavioral and cognitive impairment in animals with neuropathic pain.

Experience-Dependent Structural Plasticity of Adult-Born Neurons in the Aging Hippocampus.

Synaptic modification in cortical structures underlies the acquisition of novel information that results in learning and memory formation. In the adult dentate gyrus, circuit remodeling is boosted by the generation of new granule cells (GCs) that contribute to specific aspects of memory encoding. These forms of plasticity decrease in the aging brain, where both the rate of adult neurogenesis and the speed of morphological maturation of newly generated neurons decline. In the young-adult brain, a brief novel experience accelerates the integration of new neurons. The extent to which such degree of plasticity is preserved in the aging hippocampus remains unclear. In this work, we characterized the time course of functional integration of adult-born GCs in middle-aged mice. We performed whole-cell recordings in developing GCs from Ascl1CreERT2;CAGfloxStopTom mice and found a late onset of functional excitatory synaptogenesis, which occurred at 4 weeks (vs. 2 weeks in young-adult mice). Overall mature excitability and maximal glutamatergic connectivity were achieved at 10 weeks. In contrast, large mossy fiber boutons (MFBs) in CA3 displayed mature morphological features including filopodial extensions at 4 weeks, suggesting that efferent connectivity develops faster than afference. Notably, new GCs from middle-aged mice exposed to enriched environment for 7 days showed an advanced degree of maturity at 3 weeks, revealed by the high frequency of excitatory postsynaptic responses, complex dendritic trees, and large size of MFBs with filopodial extensions. These findings demonstrate that adult-born neurons act as sensors that transduce behavioral stimuli into major network remodeling in the aging brain.

Coding Capacity of Purkinje Cells With Different Schemes of Morphological Reduction.

The brain as a neuronal system has very complex structures with a large diversity of neuronal types. The most basic complexity is seen from the structure of neuronal morphology, which usually has a complex tree-like structure with dendritic spines distributed in branches. To simulate a large-scale network with spiking neurons, the simple point neuron, such as the integrate-and-fire neuron, is often used. However, recent experimental evidence suggests that the computational ability of a single neuron is largely enhanced by its morphological structure, in particular, by various types of dendritic dynamics. As the morphology reduction of detailed biophysical models is a classic question in systems neuroscience, much effort has been taken to simulate a neuron with a few compartments to include the interaction between the soma and dendritic spines. Yet, novel reduction methods are still needed to deal with the complex dendritic tree. Here, using 10 individual Purkinje cells of the cerebellum from three species of guinea-pig, mouse and rat, we consider four types of reduction methods and study their effects on the coding capacity of Purkinje cells in terms of firing rate, timing coding, spiking pattern, and modulated firing under different stimulation protocols. We found that there is a variation of reduction performance depending on individual cells and species, however, all reduction methods can preserve, to some degree, firing activity of the full model of Purkinje cell. Therefore, when stimulating large-scale network of neurons, one has to choose a proper type of reduced neuronal model depending on the questions addressed. Among these reduction schemes, Branch method, that preserves the geometrical volume of neurons, can achieve the best balance among different performance measures of accuracy, simplification, and computational efficiency, and reproduce various phenomena shown in the full morphology model of Purkinje cells. Altogether, these results suggest that the Branch reduction scheme seems to provide a general guideline for reducing complex morphology into a few compartments without the loss of basic characteristics of the firing properties of neurons.

Amot and Yap1 regulate neuronal dendritic tree complexity and locomotor coordination in mice.

The angiomotin (Amot)–Yes-associated protein 1 (Yap1) complex plays a major role in regulating the inhibition of cell contact, cellular polarity, and cell growth in many cell types. However, the function of Amot and the Hippo pathway transcription coactivator Yap1 in the central nervous system remains unclear. We found that Amot is a critical mediator of dendritic morphogenesis in cultured hippocampal cells and Purkinje cells in the brain. Amot function in developing neurons depends on interactions with Yap1, which is also indispensable for dendrite growth and arborization in vitro. The conditional deletion of Amot and Yap1 in neurons led to a decrease in the complexity of Purkinje cell dendritic trees, abnormal cerebellar morphology, and impairments in motor coordination. Our results indicate that the function of Amot and Yap1 in dendrite growth does not rely on interactions with TEA domain (TEAD) transcription factors or the expression of Hippo pathway–dependent genes. Instead, Amot and Yap1 regulate dendrite development by affecting the phosphorylation of S6 kinase and its target S6 ribosomal protein.

Methods to Study the Roles of Rho GTPases in Dendritic Tree Complexity.

Most neurons elaborate a characteristic dendritic arbor which is physiologically important for receiving and processing of synaptic inputs. Pathologically, disturbances in the regulation of dendritic tree complexity are often associated with mental retardation and other neurological deficits. Rho GTPases are major players in the regulation of dendritic tree complexity. They are involved in many signal transduction cascades, activated at the neuronal plasma membrane, and relayed to intracellular proteins that directly rearrange the cytoskeleton. The use of siRNA technology combined with morphometric and imaging techniques allows the roles of individual Rho GTPases, such as Rac1, in dendritic branching to be examined. In this chapter we describe the establishment, transfection, and processing of a primary hippocampal cell culture. Methods to assess the complexity of dendritic arbors like the Sholl analysis, and techniques to investigate Rac1 activity in hippocampal cells, and specifically in neuronal dendrites, such as fluorescence resonance energy transfer (FRET) imaging are presented.