Dendritic Tree Research Articles

N-WASP-Arp2/3 signaling controls multiple steps of dendrite maturation in Purkinje cells in vivo.

During neural development, the actin filament network must be precisely regulated to form elaborate neurite structures. N-WASP tightly controls actin polymerization dynamics by activating an actin nucleator Arp2/3. However, the importance of N-WASP-Arp2/3 signaling in the assembly of neurite architecture in vivo has not been clarified. Here, we demonstrate that N-WASP-Arp2/3 signaling plays a crucial role in the maturation of cerebellar Purkinje cell (PC) dendrites in vivo in mice. N-WASP was expressed and activated in developing PCs. Inhibition of Arp2/3 and N-WASP from the beginning of dendrite formation severely disrupted the establishment of a single stem dendrite, which is a characteristic basic structure of PC dendrites. Inhibition of Arp2/3 after stem dendrite formation resulted in hypoplasia of the PC dendritic tree. Cdc42, an upstream activator of N-WASP, is required for N-WASP-Arp2/3 signaling-mediated PC dendrite maturation. In addition, overactivation of N-WASP is also detrimental to dendrite formation in PCs. These findings reveal that proper activation of N-WASP-Arp2/3 signaling is crucial for multiple steps of PC dendrite maturation in vivo.

The Tripod neuron: a minimal structural reduction of the dendritic tree.

Neuron models with explicit dendritic dynamics have shed light on mechanisms for coincidence detection, pathway selection and temporal filtering. However, it is still unclear which morphological and physiological features are required to capture these phenomena. In this work, we introduce the Tripod neuron model and propose a minimal structural reduction of the dendritic tree that is able to reproduce these computations. The Tripod is a three-compartment model consisting of two segregated passive dendrites and a somatic compartment modelled as an adaptive, exponential integrate-and-fire neuron. It incorporates dendritic geometry, membrane physiology and receptor dynamics as measured in human pyramidal cells. We characterize the response of the Tripod to glutamatergic and GABAergic inputs and identify parameters that support supra-linear integration, coincidence-detection and pathway-specific gating through shunting inhibition. Following NMDA spikes, the Tripod neuron generates plateau potentials whose duration depends on the dendritic length and the strength of synaptic input. When fitted with distal compartments, the Tripod encodes previous activity into a dendritic depolarized state. This dendritic memory allows the neuron to perform temporal binding, and we show that it solves transition and sequence detection tasks on which a single-compartment model fails. Thus, the Tripod can account for dendritic computations previously explained only with more detailed neuron models or neural networks. Due to its simplicity, the Tripod neuron can be used efficiently in simulations of larger corticalcircuits. KEY POINTS: We present a neuron model, called the Tripod, with two segregated dendritic branches that are connected to an axosomatic compartment. Each branch implements inhibitory GABAergic and excitatory glutamatergic synaptic transmission, including voltage-gated NMDA receptors. Dendrites are modelled on relevant geometric and physiological parameters measured in human pyramidal cells. The neuron reproduces classical dendritic computations, such as coincidence detection and pathway selection via shunting inhibition, that are beyond the scope of point-neuron models. Under some conditions, dendritic NMDA spikes cause plateau potentials, and we show that they provide a form of short-term memory which is useful for sequence recognition. The dendritic structure of the Tripod neuron is sufficiently simple to be integrated into efficient network simulations and studied in a broad functional context.

Repetitively burst-spiking neurons in reeler mice show conserved but also highly variable morphological features of layer Vb-fated "thick-tufted" pyramidal cells.

Reelin is a large extracellular glycoprotein that is secreted by Cajal-Retzius cells during embryonic development to regulate neuronal migration and cell proliferation but it also seems to regulate ion channel distribution and synaptic vesicle release properties of excitatory neurons well into adulthood. Mouse mutants with a compromised reelin signaling cascade show a highly disorganized neocortex but the basic connectional features of the displaced excitatory principal cells seem to be relatively intact. Very little is known, however, about the intrinsic electrophysiological and morphological properties of individual cells in the reeler cortex. Repetitive burst-spiking (RB) is a unique property of large, thick-tufted pyramidal cells of wild-type layer Vb exclusively, which project to several subcortical targets. In addition, they are known to possess sparse but far-reaching intracortical recurrent collaterals. Here, we compared the electrophysiological properties and morphological features of neurons in the reeler primary somatosensory cortex with those of wild-type controls. Whereas in wild-type mice, RB pyramidal cells were only detected in layer Vb, and the vast majority of reeler RB pyramidal cells were found in the superficial third of the cortical depth. There were no obvious differences in the intrinsic electrophysiological properties and basic morphological features (such as soma size or the number of dendrites) were also well preserved. However, the spatial orientation of the entire dendritic tree was highly variable in the reeler neocortex, whereas it was completely stereotyped in wild-type mice. It seems that basic quantitative features of layer Vb-fated RB pyramidal cells are well conserved in the highly disorganized mutant neocortex, whereas qualitative morphological features vary, possibly to properly orient toward the appropriate input pathways, which are known to show an atypical oblique path through the reeler cortex. The oblique dendritic orientation thus presumably reflects a re-orientation of dendritic input domains toward spatially highly disorganized afferent projections.

Gestational protein restriction alters early amygdala neurochemistry in male offspring

ABSTRACT Background Gestational protein intake restriction-induced long-lasting harmful outcomes in the offspring's organs and systems. However, few studies have focused on this event's impact on the brain's structures and neurochemical compounds. Aim The present study investigated the effects on the amygdala neurochemical composition and neuronal structure in gestational protein-restricted male rats' offspring. Methods Dams were maintained on isocaloric standard rodent laboratory chow with regular protein [NP, 17%] or low protein content [LP, 6%]. Total cells were quantified using the Isotropic fractionator method, Neuronal 3D reconstruction, and dendritic tree analysis using the Golgi–Cox technique. Western blot and high-performance liquid chromatography performed neurochemical studies. Results The gestational low-protein feeding offspring showed a significant decrease in birth weight up to day 14, associated with unaltered brain weight in youth or adult progenies. The amygdala cell numbers were unchanged, and the dendrites length and dendritic ramifications 3D analysis in LP compared to age-matched NP progeny. However, the current study shows reduced amygdala content of norepinephrine, epinephrine, and dopamine in LP progeny. These offspring observed a significant reduction in the amygdala glucocorticoid (GR) and mineralocorticoid (MR) receptor protein levels. Also corticotrophin-releasing factor (CRF) amygdala protein content was reduced in 7 and 14-day-old LP rats. Conclusion The observed amygdala neurochemical changes may represent adaptation during embryonic development in response to elevated fetal exposure to maternal corticosteroid levels. In this way, gestational malnutrition stress can alter the amygdala's neurochemical content and may contribute to known behavioral changes induced by gestational protein restriction.

Models of Purkinje cell dendritic tree selection during early cerebellar development

Models of Purkinje cell dendritic tree selection during early cerebellar development

Models of Purkinje cell dendritic tree selection during early cerebellar development

Models of Purkinje cell dendritic tree selection during early cerebellar development

Morpho-functional analysis of the early changes induced in retinal ganglion cells by the onset of diabetic retinopathy: The effects of a neuroprotective strategy

PurposeRetinal ganglion cells (RGCs) are highly susceptible to diabetes-induced metabolic stress. This study describes the early responses of RGCs to hyperglycemia and examines the effects of the neuroprotective somatostatin analog octreotide (OCT). MethodsThy1-green fluorescent protein (GFP)-M transgenic mice were used, which express GFP in a number of RGCs. OCT was intravitreally injected in mice with streptozotocin (STZ)-induced diabetes. A longitudinal electroretinography (ERG) analysis was performed up to 2 weeks from STZ treatment. RGC density was measured and extensive morphometric analyses were performed on identified RGC subtypes. ResultsSTZ treatment caused a decline of RGC function, which was counteracted by OCT. No differences in RGC density were recorded, indicating that impaired activity was unlikely to be related to RGC death. Different GFP-labeled RGC subtypes were identified and analyzed. Overall, large RGCs were mostly affected by diabetes and responded to OCT treatment, while those with smaller dendritic arborizations were less involved. Interestingly, depending on the complexity of the dendritic tree, OCT could completely rescue RGC morphometric parameters or increase the effects of hyperglycemia. ConclusionsThere is an early response of RGCs to diabetes, which involves specific morpho-functional deficits but not overt cell death. OCT induces adaptive changes that, although different among RGC subtypes, contribute to RGC functionality in the presence of metabolic stress. These results highlight the importance of neuronal protection in the early phases of diabetic retinopathy, when cell loss has not yet started and RGC morphology can be preserved or adjusted to maintain RGC physiology.

Dendritic Branching of Retinal Ganglion Cells as a Biomarker of Glaucomatous Optic Neuropathy and Alzheimer’s Disease and a Target of Neuroprotective Therapy

Irreversible damage to the structure of axons and death of the retinal ganglion cell (RGC) soma in primary open-angle glaucoma (POAG) and Alzheimer’s disease (AD) develop against the background of the already existing clinical manifestation, which is preceded by a slow period of progressive loss of synapses and dendrites of the RGCs. Recent studies have shown that the integrity of the RGC’s dendritic branching can serve as both a target of neuroprotective therapy and a sensitive marker of retinal degeneration in AD and glaucoma. To develop methods of complex neuroprotective therapy, it is necessary to substantiate the targets and tactics of affecting the dendritic tree of the RGCs, the remodeling of which, according to modern concepts, can be closely and antagonistically related to the regeneration of the axon after its damage in trauma and neurodegenerative diseases. RGCs are highly capable of functional modification. Currently, it has been proven that the use of neuroprotective drugs and neurotrophins is promising for maintaining the adaptive plasticity of RGCs and restoring their synaptic contacts at the level of the retina and brain. Understanding the features of the adaptive plasticity of RGCs in AD and glaucoma will make it possible to use technologies to activate the internal potential of neuronal remodeling, including the modification of dendritic branching of RGCs and regeneration of their axons, in the preclinical stages of these diseases. Increasing knowledge about the sequence and mechanisms of early events in the retina’s inner plexiform layer will contribute to the development of targeted neuroprotective therapy and new technologies to detect early POAG, AD, and, possibly, other systemic and local neurodegenerative conditions.

High-fidelity dendritic sodium spike generation in human layer 2/3 neocortical pyramidal neurons.

Dendritic spikes function as cardinal components of rodent neocortical circuit computations. Recently, the biophysical properties of human pyramidal neurons (PNs) have been reported to be divergent, raising the question of whether dendritic spikes have homologous roles in the human neocortex. To directly address this, we made electrical recordings from the soma and apical dendrites of human and rat layer 2/3 PNs of the temporal cortex. In both species, dendritic excitatory input led to the initiation of sodium-channel-mediated dendritic spikes. Dendritic sodium spikes could be generated across a wide input range, exhibited a similar frequency range of activation, and forward-propagated with high-fidelity to implement stereotyped computations in human and rat PNs. However, the physical expansion and complexification of the apical dendritic trees of human PNs allowed the enriched expression of dendritic spike generation. The computational capacity of human PNs is therefore enhanced by the widespread implementation of a conserved dendritic integration mechanism.

Synaptic Plasticity Is Predicted by Spatiotemporal Firing Rate Patterns and Robust to In Vivo-like Variability.

Synaptic plasticity, the experience-induced change in connections between neurons, underlies learning and memory in the brain. Most of our understanding of synaptic plasticity derives from in vitro experiments with precisely repeated stimulus patterns; however, neurons exhibit significant variability in vivo during repeated experiences. Further, the spatial pattern of synaptic inputs to the dendritic tree influences synaptic plasticity, yet is not considered in most synaptic plasticity rules. Here, we investigate how spatiotemporal synaptic input patterns produce plasticity with in vivo-like conditions using a data-driven computational model with a plasticity rule based on calcium dynamics. Using in vivo spike train recordings as inputs to different size clusters of spines, we show that plasticity is strongly robust to trial-to-trial variability of spike timing. In addition, we derive general synaptic plasticity rules describing how spatiotemporal patterns of synaptic inputs control the magnitude and direction of plasticity. Synapses that strongly potentiated have greater firing rates and calcium concentration later in the trial, whereas strongly depressing synapses have hiring firing rates early in the trial. The neighboring synaptic activity influences the direction and magnitude of synaptic plasticity, with small clusters of spines producing the greatest increase in synaptic strength. Together, our results reveal that calcium dynamics can unify diverse plasticity rules and reveal how spatiotemporal firing rate patterns control synaptic plasticity.

Endogenous PTEN-Induced Kinase 1 Regulates Dendritic Architecture and Spinogenesis.

Mutations in PTEN-induced kinase 1 (PINK1) contribute to autosomal recessive Parkinson's disease with cognitive and neuropsychiatric comorbidities. Disturbances in dendritic and spine architecture are hallmarks of neurodegenerative and neuropsychiatric conditions, but little is known of the impact of PINK1 on these structures. We used Pink1 -/- mice to study the role of endogenous PINK1 in regulating dendritic architecture, spine density, and spine maturation. Pink1 -/- cortical neurons of unknown sex showed decreased dendritic arborization, affecting both apical and basal arbors. Dendritic simplification in Pink1 -/- neurons was primarily driven by diminished branching with smaller effects on branch lengths. Pink1 -/- neurons showed reduced spine density with a shift in morphology to favor filopodia at the expense of mushroom spines. Electrophysiology revealed significant reductions in miniature EPSC (mEPSC) frequency in Pink1 -/- neurons, consistent with the observation of decreased spine numbers. Transfecting with human PINK1 rescued changes in dendritic architecture, in thin, stubby, and mushroom spine densities, and in mEPSC frequency. Diminished spine density was also observed in Golgi-Cox stained adult male Pink1 -/- brains. Western blot study of Pink1 -/- brains of either sex revealed reduced phosphorylation of NSFL1 cofactor p47, an indirect target of PINK1. Transfection of Pink1 -/- neurons with a phosphomimetic p47 plasmid rescued dendritic branching and thin/stubby spine density with a partial rescue of mushroom spines, implicating a role for PINK1-regulated p47 phosphorylation in dendrite and spine development. These findings suggest that PINK1-dependent synaptodendritic alterations may contribute to the risk of cognitive and/or neuropsychiatric pathologies observed in PINK1-mutated families.SIGNIFICANCE STATEMENT Loss of PINK1 function has been implicated in both familial and sporadic neurodegenerative diseases. Yet surprisingly little is known of the impact of PINK1 loss on the fine structure of neurons. Neurons receive excitatory synaptic signals along a complex network of projections that form the dendritic tree, largely at tiny protrusions called dendritic spines. We studied cortical neurons and brain tissues from mice lacking PINK1. We discovered that PINK1 deficiency causes striking simplification of dendritic architecture associated with reduced synaptic input and decreased spine density and maturation. These changes are reversed by reintroducing human PINK1 or one of its downstream mediators into PINK1-deficient mouse neurons, indicating a conserved function, whose loss may contribute to neurodegenerative processes.

Functional and structural features of L2/3 pyramidal cells continuously covary with pial depth in mouse visual cortex.

Pyramidal cells of neocortical layer 2/3 (L2/3 PyrCs) integrate signals from numerous brain areas and project throughout the neocortex. These PyrCs show pial depth-dependent functional and structural specializations, indicating participation in different functional microcircuits. However, whether these depth-dependent differences result from separable PyrC subtypes or whether their features display a continuum correlated with pial depth is unknown. Here, we assessed the stimulus selectivity, electrophysiological properties, dendritic morphology, and excitatory and inhibitory connectivity across the depth of L2/3 in the binocular visual cortex of mice. We find that the apical, but not the basal dendritic tree structure, varies with pial depth, which is accompanied by variation in subthreshold electrophysiological properties. Lower L2/3 PyrCs receive increased input from L4, while upper L2/3 PyrCs receive a larger proportion of intralaminar input. In vivo calcium imaging revealed a systematic change in visual responsiveness, with deeper PyrCs showing more robust responses than superficial PyrCs. Furthermore, deeper PyrCs are more driven by contralateral than ipsilateral eye stimulation. Importantly, the property value transitions are gradual, and L2/3 PyrCs do not display discrete subtypes based on these parameters. Therefore, L2/3 PyrCs' multiple functional and structural properties systematically correlate with their depth, forming a continuum rather than discrete subtypes.

Dendritic Morphology Affects the Velocity and Amplitude of Back-propagating Action Potentials

The back-propagating action potential (bpAP) is crucial for neuronal signal integration and synaptic plasticity in dendritic trees. Its properties (velocity and amplitude) can be affected by dendritic morphology. Due to limited spatial resolution, it has been difficult to explore the specific propagation process of bpAPs along dendrites and examine the influence of dendritic morphology, such as the dendrite diameter and branching pattern, using patch-clamp recording. By taking advantage of Optopatch, an all-optical electrophysiological method, we made detailed recordings of the real-time propagation of bpAPs in dendritic trees. We found that the velocity of bpAPs was not uniform in a single dendrite, and the bpAP velocity differed among distinct dendrites of the same neuron. The velocity of a bpAP was positively correlated with the diameter of the dendrite on which it propagated. In addition, when bpAPs passed through a dendritic branch point, their velocity decreased significantly. Similar to velocity, the amplitude of bpAPs was also positively correlated with dendritic diameter, and the attenuation patterns of bpAPs differed among different dendrites. Simulation results from neuron models with different dendritic morphology corresponded well with the experimental results. These findings indicate that the dendritic diameter and branching pattern significantly influence the properties of bpAPs. The diversity among the bpAPs recorded in different neurons was mainly due to differences in dendritic morphology. These results may inspire the construction of neuronal models to predict the propagation of bpAPs in dendrites with enormous variation in morphology, to further illuminate the role of bpAPs in neuronal communication.

Df(h22q11)/+ mouse model exhibits reduced binding levels of GABAA receptors and structural and functional dysregulation in the inhibitory and excitatory networks of hippocampus

The 22q11.2 hemizygous deletion confers high risk for multiple neurodevelopmental disorders. Inhibitory signaling, largely regulated through GABAA receptors, is suggested to serve a multitude of brain functions that are disrupted in the 22q11.2 deletion syndrome.We investigated the putative deficit of GABAA receptors and the potential substrates contributing to the inhibitory and excitatory dysregulations in hippocampal networks of the Df(h22q11)/+ mouse model of the 22q11.2 hemizygous deletion. The Df(h22q11)/+ mice exhibited impairments in several hippocampus-related functional domains, represented by impaired spatial memory and sensory gating functions. Autoradiography using the [3H]muscimol tracer revealed a significant reduction in GABAA receptor binding in the CA1 and CA3 subregions, together with a loss of GAD67+ interneurons in CA1 of Df(h22q11)/+ mice. Furthermore, electrophysiology recordings exhibited significantly higher neuronal activity in CA3, in response to the GABAA receptor antagonist, bicuculline, as compared with wild type mice. Density and volume of dendritic spines in pyramidal neurons were reduced and Sholl analysis also showed a reduction in the complexity of basal dendritic tree in CA1 and CA3 subregions of Df(h22q11)/+ mice.Overall, our findings demonstrate that hemizygous deletion in the 22q11.2 locus leads to dysregulations in the inhibitory circuits, involving reduced binding levels of GABAA receptors, in addition to functional and structural modulations of the excitatory networks of hippocampus.

Inferring monosynaptic connections from paired dendritic spine Ca2+ imaging and large-scale recording of extracellular spiking

Objective: Techniques to identify monosynaptic connections between neurons have been vital for neuroscience research, facilitating important advancements concerning network topology, synaptic plasticity, and synaptic integration, among others. Approach: Here, we introduce a novel approach to identify and monitor monosynaptic connections using high-resolution dendritic spine Ca2+ imaging combined with simultaneous large-scale recording of extracellular electrical activity by means of high-density microelectrode arrays. Main results: We introduce an easily adoptable analysis pipeline that associates the imaged spine with its presynaptic unit and test it on in vitro recordings. The method is further validated and optimized by simulating synaptically-evoked spine Ca2+ transients based on measured spike trains in order to obtain simulated ground-truth connections. Significance: The proposed approach offers unique advantages as (a) it can be used to identify monosynaptic connections with an accurate localization of the synapse within the dendritic tree, (b) it provides precise information of presynaptic spiking, and (c) postsynaptic spine Ca2+ signals and, finally, (d) the non-invasive nature of the proposed method allows for long-term measurements. The analysis toolkit together with the rich data sets that were acquired are made publicly available for further exploration by the research community.

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.

All neurons can perform linearly non-separable computations.

Multiple studies have shown how dendrites enable some neurons to perform linearly non-separable computations. These works focus on cells with an extended dendritic arbor where voltage can vary independently, turning dendritic branches into local non-linear subunits. However, these studies leave a large fraction of the nervous system unexplored. Many neurons, e.g. granule cells, have modest dendritic trees and are electrically compact. It is impossible to decompose them into multiple independent subunits. Here, we upgraded the integrate and fire neuron to account for saturation due to interacting synapses. This artificial neuron has a unique membrane voltage and can be seen as a single layer. We present a class of linearly non-separable computations and how our neuron can perform them. We thus demonstrate that even a single layer neuron with interacting synapses has more computational capacity than without. Because all neurons have one or more layer, we show that all neurons can potentially implement linearly non-separable computations.

Compartmental spiking neuron model CSNM

The purpose of this work is to develop a compartment spiking neuron model as an element of growing neural networks. Methods. As part of the work, the CSNM is compared with the Leaky Integrate-and-Fire model by comparing the reactions of point models to a single spike. The influence of hyperparameters of the proposed model on neuron excitation is also investigated. All the described experiments were carried out in the Simulink environment using the tools of the proposed library. Results. It was concluded that the proposed model is able to qualitatively reproduce the reaction of the point classical model, and the tuning of hyperparameters allows reproducing the following patterns of signal propagation in a biological neuron: a decrease in the maximum potential and an increase in the delay between input and output spikes with an increase in the size of the neuron or the length of the dendrite, as well as an increase in the potential with an increase in the number of active synapses. Conclusion. The proposed compartment spiking neuron model allows to describe the behavior of biological neurons at the level of pulse signal conversion. The hyperparameters of the model allow tuning the neuron responses at fixed other neuron parameters. The model can be used as a part of spiking neural networks with details at the level of compartments of neurons dendritic trees.

Granule cell dispersion in two mouse models of temporal lobe epilepsy and reeler mice is associated with changes in dendritic orientation and spine distribution.

Temporal lobe epilepsy is characterized by hippocampal neuronal death in CA1 and hilus. Dentate gyrus granule cells survive but show dispersion of the compact granule cell layer. This is associated with decrease of the glycoprotein Reelin, which regulates neuron migration and dendrite outgrow. Reelin-deficient (reeler) mice show no layering, their granule cells are dispersed throughout the dentate gyrus. We studied granule cell dendritic orientation and distribution of postsynaptic spines in reeler mice and two mouse models of temporal lobe epilepsy, namely the p35 knockout mice, which show Reelin-independent neuronal migration defects, and mice with unilateral intrahippocampal kainate injection. Granule cells were Golgi-stained and analyzed, using a computerized camera lucida system. Granule cells in naive controls exhibited a vertically oriented dendritic arbor with a small bifurcation angle if positioned proximal to the hilus and a wider dendritic bifurcation angle, if positioned distally. P35 knockout- and kainate-injected mice showed a dispersed granule cell layer, granule cells showed basal dendrites with wider bifurcation angles, which lost position-specific differences. Reeler mice lacked dendritic orientation. P35 knockout- and kainate-injected mice showed increased dendritic spine density in the granule cell layer. Molecular layer dendrites showed a reduced spine density in kainate-injected mice only, whereas in p35 knockouts no reduced spine density was seen. Reeler mice showed a homogenous high spine density. We hypothesize that granule cells migrate in temporal lobe epilepsy, develop new dendrites which show a spread of the dendritic tree, create new spines in areas proximal to mossy fiber sprouting, which is present in p35 knockout- and kainate-injected mice and loose spines on distal dendrites if mossy cell death is present, as it was in kainate-injected mice only. These results are in accordance with findings in epilepsy patients.

A 3D Tubular Flux Model for Centerline Extraction in Neuron Volumetric Images.

Digital morphology reconstruction from neuron volumetric images is essential for computational neuroscience. The centerline of the axonal and dendritic tree provides an effective shape representation and serves as a basis for further neuron reconstruction. However, it is still a challenge to directly extract the accurate centerline from the complex neuron structure with poor image quality. In this paper, we propose a neuron centerline extraction method based on a 3D tubular flux model via a two-stage CNN framework. In the first stage, a 3D CNN is used to learn the latent neuron structure features, namely flux features, from neuron images. In the second stage, a light-weight U-Net takes the learned flux features as input to extract the centerline with a spatial weighted average strategy to constrain the multi-voxel width response. Specifically, the labels of flux features in the first stage are generated by the 3D tubular model which calculates the geometric representations of the flux between each voxel in the tubular region and the nearest point on the centerline ground truth. Compared with self-learned features by networks, flux features, as a kind of prior knowledge, explicitly take advantage of the contextual distance and direction distribution information around the centerline, which is beneficial for the precise centerline extraction. Experiments on two challenging datasets demonstrate that the proposed method outperforms other state-of-the-art methods by 18% and 35.1% in F1-measurement and average distance scores at the most, and the extracted centerline is helpful to improve the neuron reconstruction performance.