ResearchPad - dendritic-structure https://www.researchpad.co Default RSS Feed en-us © 2020 Newgen KnowledgeWorks <![CDATA[Low-rate firing limit for neurons with axon, soma and dendrites driven by spatially distributed stochastic synapses]]> https://www.researchpad.co/article/elastic_article_13830 Neurons are extended cells with multiple branching dendrites, a cell body and an axon. In an active neuronal network, neurons receive vast numbers of incoming synaptic pulses throughout their dendrites and cell body that each exhibit significant variability in amplitude and arrival time. The resulting synaptic input causes voltage fluctuations throughout their structure that evolve in space and time. The dynamics of how these signals are integrated and how they ultimately trigger outgoing spikes have been modelled extensively since the late 1960s. However, until relatively recently the majority of the mathematical formulae describing how fluctuating synaptic drive triggers action potentials have been applicable only for small neurons with the dendritic and axonal structure ignored. This has been largely due to the mathematical complexity of including the effects of spatially distributed synaptic input. Here we show that in a physiologically relevant, low-firing-rate regime, an approximate level-crossing approach can be used to provide an estimate for the neuronal firing rate even when the dendrites and axons are included. We illustrate this approach using basic neuronal morphologies that capture the fundamentals of neuronal structure. Though the models are simple, these preliminary results show that it is possible to obtain useful formulae that capture the effects of spatially distributed synaptic drive. The generality of these results suggests they will provide a mathematical framework for future studies that might require the structure of neurons to be taken into account, such as the effect of electrical fields or multiple synaptic input streams that target distinct spatial domains of cortical pyramidal cells.

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<![CDATA[Different operators and histologic techniques in the assessment of germinal center-like structures in primary Sjögren’s syndrome minor salivary glands]]> https://www.researchpad.co/article/5c644913d5eed0c484c2f56d

Objective

A standardization of minor salivary gland (MSG) histopathology in primary Sjögren’s syndrome (pSS) has been recently proposed. Although there is strong agreement that germinal center (GC)-like structures should be routinely identified, due to their prognostic value, a consensus regarding the best protocol is still lacking. Aim of this study was to compare the performance of different histological techniques and operators to identify GC-like structures in pSS MSGs. MSG biopsies from 50 pSS patients were studied.

Methods

Three blinded operators (one pathologist and two rheumatologists with different years of experience in pSS MSG assessment) assessed 50 MSGs of which one slide was stained with haematoxylin and eosin (H&E) and consecutive slides were processed to investigate CD3/CD20, CD21 and Bcl-6 expression.

Results

By assessing 225 foci, the best agreement was between H&E-stained sections evaluated by the rheumatologist with more years of experience in pSS MSG assessment and CD3/CD20 segregation. In the foci with CD21 positivity, the agreement further increased. Bcl-6- foci could display a GC, detected with other staining, but not vice versa.

Conclusion

GC assessment on H&E-stained sections should be performed with caution, being operator-dependent. The combination of H&E with CD3/CD20 and CD21 staining should be recommended as it is reliable, feasible, able to overcome the bias of operator experience and easily transferrable into routine practice.

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<![CDATA[Hierarchical elimination selection method of dendritic river network generalization]]> https://www.researchpad.co/article/5c0ed773d5eed0c484f1417c

Dendritic river networks are fundamental elements in cartography, and the generalization of these river networks directly influences the quality of cartographic generalization. Automatic selection is a difficult and important process for river generalization that requires the consideration of semantic, geometric, topological, and structural characteristics. However, owing to a lack of effective use of river features, most existing methods lose important spatial distribution characteristics of rivers, thus affecting the selection result. Therefore, a hierarchical elimination selection method of dendritic river networks is proposed that consists of three steps. First, a directed topology tree (DTT) is investigated to realize the organization of river data and the intelligent identification of river structures. Second, based on the “180° hypothesis” and “acute angle hypothesis”, each river is traced in the upstream direction from its estuary to create the stroke connections of dendritic river networks based on a consideration of the river semantics, length, and angle features, and the hierarchical relationships of a dendritic river network are then determined. Finally, by determining the total number of selected rivers, a hierarchical elimination algorithm that accounts for density differences is proposed. The reliability of the proposed method was verified using sample data tests, and the rationality and validity of the method were demonstrated in experiments using actual data.

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<![CDATA[Full reconstruction of large lobula plate tangential cells in Drosophila from a 3D EM dataset]]> https://www.researchpad.co/article/5c08419cd5eed0c484fca32f

With the advent of neurogenetic methods, the neural basis of behavior is presently being analyzed in more and more detail. This is particularly true for visually driven behavior of Drosophila melanogaster where cell-specific driver lines exist that, depending on the combination with appropriate effector genes, allow for targeted recording, silencing and optogenetic stimulation of individual cell-types. Together with detailed connectomic data of large parts of the fly optic lobe, this has recently led to much progress in our understanding of the neural circuits underlying local motion detection. However, how such local information is combined by optic flow sensitive large-field neurons is still incompletely understood. Here, we aim to fill this gap by a dense reconstruction of lobula plate tangential cells of the fly lobula plate. These neurons collect input from many hundreds of local motion-sensing T4/T5 neurons and connect them to descending neurons or central brain areas. We confirm all basic features of HS and VS cells as published previously from light microscopy. In addition, we identified the dorsal and the ventral centrifugal horizontal, dCH and vCH cell, as well as three VSlike cells, including their distinct dendritic and axonal projection area.

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<![CDATA[The effects of aging on neuropil structure in mouse somatosensory cortex—A 3D electron microscopy analysis of layer 1]]> https://www.researchpad.co/article/5b4a08df463d7e3fbe689132

This study has used dense reconstructions from serial EM images to compare the neuropil ultrastructure and connectivity of aged and adult mice. The analysis used models of axons, dendrites, and their synaptic connections, reconstructed from volumes of neuropil imaged in layer 1 of the somatosensory cortex. This shows the changes to neuropil structure that accompany a general loss of synapses in a well-defined brain region. The loss of excitatory synapses was balanced by an increase in their size such that the total amount of synaptic surface, per unit length of axon, and per unit volume of neuropil, stayed the same. There was also a greater reduction of inhibitory synapses than excitatory, particularly those found on dendritic spines, resulting in an increase in the excitatory/inhibitory balance. The close correlations, that exist in young and adult neurons, between spine volume, bouton volume, synaptic size, and docked vesicle numbers are all preserved during aging. These comparisons display features that indicate a reduced plasticity of cortical circuits, with fewer, more transient, connections, but nevertheless an enhancement of the remaining connectivity that compensates for a generalized synapse loss.

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<![CDATA[An open-source tool for analysis and automatic identification of dendritic spines using machine learning]]> https://www.researchpad.co/article/5b4a192f463d7e428027f892

Synaptic plasticity, the cellular basis for learning and memory, is mediated by a complex biochemical network of signaling proteins. These proteins are compartmentalized in dendritic spines, the tiny, bulbous, post-synaptic structures found on neuronal dendrites. The ability to screen a high number of molecular targets for their effect on dendritic spine structural plasticity will require a high-throughput imaging system capable of stimulating and monitoring hundreds of dendritic spines in various conditions. For this purpose, we present a program capable of automatically identifying dendritic spines in live, fluorescent tissue. Our software relies on a machine learning approach to minimize any need for parameter tuning from the user. Custom thresholding and binarization functions serve to “clean” fluorescent images, and a neural network is trained using features based on the relative shape of the spine perimeter and its corresponding dendritic backbone. Our algorithm is rapid, flexible, has over 90% accuracy in spine detection, and bundled with our user-friendly, open-source, MATLAB-based software package for spine analysis.

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<![CDATA[Heterogeneous firing responses predict diverse couplings to presynaptic activity in mice layer V pyramidal neurons]]> https://www.researchpad.co/article/5989db5aab0ee8fa60bdf258

In this study, we present a theoretical framework combining experimental characterizations and analytical calculus to capture the firing rate input-output properties of single neurons in the fluctuation-driven regime. Our framework consists of a two-step procedure to treat independently how the dendritic input translates into somatic fluctuation variables, and how the latter determine action potential firing. We use this framework to investigate the functional impact of the heterogeneity in firing responses found experimentally in young mice layer V pyramidal cells. We first design and calibrate in vitro a simplified morphological model of layer V pyramidal neurons with a dendritic tree following Rall's branching rule. Then, we propose an analytical derivation for the membrane potential fluctuations at the soma as a function of the properties of the synaptic input in dendrites. This mathematical description allows us to easily emulate various forms of synaptic input: either balanced, unbalanced, synchronized, purely proximal or purely distal synaptic activity. We find that those different forms of dendritic input activity lead to various impact on the somatic membrane potential fluctuations properties, thus raising the possibility that individual neurons will differentially couple to specific forms of activity as a result of their different firing response. We indeed found such a heterogeneous coupling between synaptic input and firing response for all types of presynaptic activity. This heterogeneity can be explained by different levels of cellular excitability in the case of the balanced, unbalanced, synchronized and purely distal activity. A notable exception appears for proximal dendritic inputs: increasing the input level can either promote firing response in some cells, or suppress it in some other cells whatever their individual excitability. This behavior can be explained by different sensitivities to the speed of the fluctuations, which was previously associated to different levels of sodium channel inactivation and density. Because local network connectivity rather targets proximal dendrites, our results suggest that this aspect of biophysical heterogeneity might be relevant to neocortical processing by controlling how individual neurons couple to local network activity.

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<![CDATA[Biophysical model of the role of actin remodeling on dendritic spine morphology]]> https://www.researchpad.co/article/5989db4fab0ee8fa60bdb8c7

Dendritic spines are small membranous structures that protrude from the neuronal dendrite. Each spine contains a synaptic contact site that may connect its parent dendrite to the axons of neighboring neurons. Dendritic spines are markedly distinct in shape and size, and certain types of stimulation prompt spines to evolve, in fairly predictable fashion, from thin nascent morphologies to the mushroom-like shapes associated with mature spines. It is well established that the remodeling of spines is strongly dependent upon the actin cytoskeleton inside the spine. A general framework that details the precise role of actin in directing the transitions between the various spine shapes is lacking. We address this issue, and present a quantitative, model-based scenario for spine plasticity validated using realistic and physiologically relevant parameters. Our model points to a crucial role for the actin cytoskeleton. In the early stages of spine formation, the interplay between the elastic properties of the spine membrane and the protrusive forces generated in the actin cytoskeleton propels the incipient spine. In the maturation stage, actin remodeling in the form of the combined dynamics of branched and bundled actin is required to form mature, mushroom-like spines. Importantly, our model shows that constricting the spine-neck aids in the stabilization of mature spines, thus pointing to a role in stabilization and maintenance for additional factors such as ring-like F-actin structures. Taken together, our model provides unique insights into the fundamental role of actin remodeling and polymerization forces during spine formation and maturation.

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<![CDATA[A Single Vector Platform for High-Level Gene Transduction of Central Neurons: Adeno-Associated Virus Vector Equipped with the Tet-Off System]]> https://www.researchpad.co/article/5989daf0ab0ee8fa60bc0da7

Visualization of neurons is indispensable for the investigation of neuronal circuits in the central nervous system. Virus vectors have been widely used for labeling particular subsets of neurons, and the adeno-associated virus (AAV) vector has gained popularity as a tool for gene transfer. Here, we developed a single AAV vector Tet-Off platform, AAV-SynTetOff, to improve the gene-transduction efficiency, specifically in neurons. The platform is composed of regulator and response elements in a single AAV genome. After infection of Neuro-2a cells with the AAV-SynTetOff vector, the transduction efficiency of green fluorescent protein (GFP) was increased by approximately 2- and 15-fold relative to the conventional AAV vector with the human cytomegalovirus (CMV) or human synapsin I (SYN) promoter, respectively. We then injected the AAV vectors into the mouse neostriatum. GFP expression in the neostriatal neurons infected with the AAV-SynTetOff vector was approximately 40-times higher than that with the CMV or SYN promoter. By adding a membrane-targeting signal to GFP, the axon fibers of neostriatal neurons were clearly visualized. In contrast, by attaching somatodendritic membrane-targeting signals to GFP, axon fiber labeling was mostly suppressed. Furthermore, we prepared the AAV-SynTetOff vector, which simultaneously expressed somatodendritic membrane-targeted GFP and membrane-targeted red fluorescent protein (RFP). After injection of the vector into the neostriatum, the cell bodies and dendrites of neostriatal neurons were labeled with both GFP and RFP, whereas the axons in the projection sites were labeled only with RFP. Finally, we applied this vector to vasoactive intestinal polypeptide-positive (VIP+) neocortical neurons, one of the subclasses of inhibitory neurons in the neocortex, in layer 2/3 of the mouse primary somatosensory cortex. The results revealed the differential distribution of the somatodendritic and axonal structures at the population level. The AAV-SynTetOff vector developed in the present study exhibits strong fluorescence labeling and has promising applications in neuronal imaging.

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<![CDATA[The Structural Correlates of Statistical Information Processing during Speech Perception]]> https://www.researchpad.co/article/5989db0dab0ee8fa60bcabc0

The processing of continuous and complex auditory signals such as speech relies on the ability to use statistical cues (e.g. transitional probabilities). In this study, participants heard short auditory sequences composed either of Italian syllables or bird songs and completed a regularity-rating task. Behaviorally, participants were better at differentiating between levels of regularity in the syllable sequences than in the bird song sequences. Inter-individual differences in sensitivity to regularity for speech stimuli were correlated with variations in surface-based cortical thickness (CT). These correlations were found in several cortical areas including regions previously associated with statistical structure processing (e.g. bilateral superior temporal sulcus, left precentral sulcus and inferior frontal gyrus), as well other regions (e.g. left insula, bilateral superior frontal gyrus/sulcus and supramarginal gyrus). In all regions, this correlation was positive suggesting that thicker cortex is related to higher sensitivity to variations in the statistical structure of auditory sequences. Overall, these results suggest that inter-individual differences in CT within a distributed network of cortical regions involved in statistical structure processing, attention and memory is predictive of the ability to detect structural structure in auditory speech sequences.

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<![CDATA[Interactions between the breast cancer-associated MUC1 mucins and C-type lectin characterized by optical tweezers]]> https://www.researchpad.co/article/5989db52ab0ee8fa60bdc8e0

Carbohydrate–protein interactions govern many crucial processes in biological systems including cell recognition events. We have used the sensitive force probe optical tweezers to quantify the interactions occurring between MGL lectins and MUC1 carrying the cancer-associated glycan antigens mucins Tn and STn. Unbinding forces of 7.6 pN and 7.1 pN were determined for the MUC1(Tn)—MGL and MUC1(STn)—MGL interactions, at a force loading rate of ~40 pN/s. The interaction strength increased with increasing force loading rate, to 27 and 37 pN at a force loading rate of ~ 310 pN/s. No interactions were detected between MGL and MUC1(ST), a glycoform of MUC1 also expressed by breast carcinoma cells. Interestingly, this glycan (ST) can be found on proteins expressed by normal cells, although in this case not on MUC1. Additionally, GalNAc decorated polyethylene glycol displayed similar rupture forces as observed for MUC1(Tn) and MUC1(STn) when forced to unbind from MGL, indicating that GalNAc is an essential group in these interactions. Since the STn glycan decoration is more frequently found on the surface of carcinomas than the Tn glycan, the binding of MUC1 carrying STn to MGL may be more physiologically relevant and may be in part responsible for some of the characteristics of STn expressing tumours.

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<![CDATA[Abnormal dendritic maturation of developing cortical neurons exposed to corticotropin releasing hormone (CRH): Insights into effects of prenatal adversity?]]> https://www.researchpad.co/article/5989db5fab0ee8fa60be12b1

Corticotropin releasing hormone (CRH) produced by the hypothalamus initiates the hypothalamic-pituitary-adrenal (HPA) axis, which regulates the body’s stress response. CRH levels typically are undetectable in human plasma, but during pregnancy the primate placenta synthesizes and releases large amounts of CRH into both maternal and fetal circulations. Notably, placental CRH synthesis increases in response to maternal stress signals. There is evidence that human fetal exposure to high concentrations of placental CRH is associated with behavioral consequences during infancy and into childhood, however the direct effects on of the peptide on the human brain are unknown. In this study, we used a rodent model to test the plausibility that CRH has direct effects on the developing cortex. Because chronic exposure to CRH reduces dendritic branching in hippocampal neurons, we tested the hypothesis that exposure to CRH would provoke impoverishment of dendritic trees in cortical neurons. This might be reflected in humans as cortical thinning. We grew developing cortical neurons in primary cultures in the presence of graded concentrations of CRH. We then employed Sholl analyses to measure dendritic branching and total dendritic length of treated cells. A seven-day exposure to increasing levels of CRH led to a significant, dose-dependent impoverishment of the branching of pyramidal-like cortical neurons. These results are consistent with the hypothesis that, rather than merely being a marker of prenatal stress, CRH directly decreases dendritic branching. Because dendrites comprise a large portion of cortical volume these findings might underlie reduced cortical thickness and could contribute to the behavioral consequences observed in children exposed to high levels of CRH in utero.

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<![CDATA[Optimal Current Transfer in Dendrites]]> https://www.researchpad.co/article/5989da10ab0ee8fa60b79509

Integration of synaptic currents across an extensive dendritic tree is a prerequisite for computation in the brain. Dendritic tapering away from the soma has been suggested to both equalise contributions from synapses at different locations and maximise the current transfer to the soma. To find out how this is achieved precisely, an analytical solution for the current transfer in dendrites with arbitrary taper is required. We derive here an asymptotic approximation that accurately matches results from numerical simulations. From this we then determine the diameter profile that maximises the current transfer to the soma. We find a simple quadratic form that matches diameters obtained experimentally, indicating a fundamental architectural principle of the brain that links dendritic diameters to signal transmission.

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<![CDATA[Scanning Ultrasound (SUS) Causes No Changes to Neuronal Excitability and Prevents Age-Related Reductions in Hippocampal CA1 Dendritic Structure in Wild-Type Mice]]> https://www.researchpad.co/article/5989da14ab0ee8fa60b7a7fa

Scanning ultrasound (SUS) is a noninvasive approach that has recently been shown to ameliorate histopathological changes and restore memory functions in an Alzheimer's disease mouse model. Although no overt neuronal damage was reported, the short- and long-term effects of SUS on neuronal excitability and dendritic tree morphology had not been investigated. To address this, we performed patch-clamp recordings from hippocampal CA1 pyramidal neurons in wild-type mice 2 and 24 hours after a single SUS treatment, and one week and 3 months after six weekly SUS treatments, including sham treatments as controls. In both treatment regimes, no changes in CA1 neuronal excitability were observed in SUS-treated neurons when compared to sham-treated neurons at any time-point. For the multiple treatment groups, we also determined the dendritic morphology and spine densities of the neurons from which we had recorded. The apical trees of sham-treated neurons were reduced at the 3 month time-point when compared to one week; however, surprisingly, no longitudinal change was detected in the apical dendritic trees of SUS-treated neurons. In contrast, the length and complexity of the basal dendritic trees were not affected by SUS treatment at either time-point. The apical dendritic spine densities were reduced, independent of the treatment group, at 3 months compared to one week. Collectively, these data suggest that ultrasound can be employed to prevent an age-associated loss of dendritic structure without impairing neuronal excitability.

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<![CDATA[Tracking the Fragile X Mental Retardation Protein in a Highly Ordered Neuronal RiboNucleoParticles Population: A Link between Stalled Polyribosomes and RNA Granules]]> https://www.researchpad.co/article/5989da5aab0ee8fa60b8fc75

Local translation at the synapse plays key roles in neuron development and activity-dependent synaptic plasticity. mRNAs are translocated from the neuronal soma to the distant synapses as compacted ribonucleoparticles referred to as RNA granules. These contain many RNA-binding proteins, including the Fragile X Mental Retardation Protein (FMRP), the absence of which results in Fragile X Syndrome, the most common inherited form of intellectual disability and the leading genetic cause of autism. Using FMRP as a tracer, we purified a specific population of RNA granules from mouse brain homogenates. Protein composition analyses revealed a strong relationship between polyribosomes and RNA granules. However, the latter have distinct architectural and structural properties, since they are detected as close compact structures as observed by electron microscopy, and converging evidence point to the possibility that these structures emerge from stalled polyribosomes. Time-lapse video microscopy indicated that single granules merge to form cargoes that are transported from the soma to distal locations. Transcriptomic analyses showed that a subset of mRNAs involved in cytoskeleton remodelling and neural development is selectively enriched in RNA granules. One third of the putative mRNA targets described for FMRP appear to be transported in granules and FMRP is more abundant in granules than in polyribosomes. This observation supports a primary role for FMRP in granules biology. Our findings open new avenues for the study of RNA granule dysfunctions in animal models of nervous system disorders, such as Fragile X syndrome.

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<![CDATA[Ultrastructure and morphology of antennal sensilla of the adult diving beetle Cybister japonicus Sharp]]> https://www.researchpad.co/article/5989db52ab0ee8fa60bdc6b4

The morphology and distribution of the antennal sensilla of adult diving beetle Cybister japonicus Sharp (Dytiscidae, Coleoptera), have been examined. Five types of sensilla on the antennae were identified by scanning electron microscope (SEM) and transmission electron microscope (TEM). Sensilla placodea and elongated s. placodea are the most abundant types of sensilla, distributing only on the flagellum. Both these types of sensilla carry multiple pore systems with a typical function as chemoreceptors. Three types of s. coeloconica (Type I–III) were also identified, with the characterization of the pit-in-pit style, and carrying pegs externally different from each other. Our data indicated that both type I and type II of s. coleconica contain two bipolar neurons, while the type III of s. coleconica contains three dendrites in the peg. Two sensory dendrites in the former two sensilla are tightly embedded inside the dendrite sheath, with no space left for sensilla lymph. There are no specific morphological differences in the antennal sensilla observed between males and females, except that the males have longer antennae and more sensilla than the females.

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<![CDATA[Improved Simulation of Electrodiffusion in the Node of Ranvier by Mesh Adaptation]]> https://www.researchpad.co/article/5989dac7ab0ee8fa60bb2e83

In neural structures with complex geometries, numerical resolution of the Poisson-Nernst-Planck (PNP) equations is necessary to accurately model electrodiffusion. This formalism allows one to describe ionic concentrations and the electric field (even away from the membrane) with arbitrary spatial and temporal resolution which is impossible to achieve with models relying on cable theory. However, solving the PNP equations on complex geometries involves handling intricate numerical difficulties related either to the spatial discretization, temporal discretization or the resolution of the linearized systems, often requiring large computational resources which have limited the use of this approach. In the present paper, we investigate the best ways to use the finite elements method (FEM) to solve the PNP equations on domains with discontinuous properties (such as occur at the membrane-cytoplasm interface). 1) Using a simple 2D geometry to allow comparison with analytical solution, we show that mesh adaptation is a very (if not the most) efficient way to obtain accurate solutions while limiting the computational efforts, 2) We use mesh adaptation in a 3D model of a node of Ranvier to reveal details of the solution which are nearly impossible to resolve with other modelling techniques. For instance, we exhibit a non linear distribution of the electric potential within the membrane due to the non uniform width of the myelin and investigate its impact on the spatial profile of the electric field in the Debye layer.

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<![CDATA[Fractal Dimension Analysis of Subcortical Gray Matter Structures in Schizophrenia]]> https://www.researchpad.co/article/5989da1cab0ee8fa60b7d192

A failure of adaptive inference—misinterpreting available sensory information for appropriate perception and action—is at the heart of clinical manifestations of schizophrenia, implicating key subcortical structures in the brain including the hippocampus. We used high-resolution, three-dimensional (3D) fractal geometry analysis to study subtle and potentially biologically relevant structural alterations (in the geometry of protrusions, gyri and indentations, sulci) in subcortical gray matter (GM) in patients with schizophrenia relative to healthy individuals. In particular, we focus on utilizing Fractal Dimension (FD), a compact shape descriptor that can be computed using inputs with irregular (i.e., not necessarily smooth) surfaces in order to quantify complexity (of geometrical properties and configurations of structures across spatial scales) of subcortical GM in this disorder. Probabilistic (entropy-based) information FD was computed based on the box-counting approach for each of the seven subcortical structures, bilaterally, as well as the brainstem from high-resolution magnetic resonance (MR) images in chronic patients with schizophrenia (n = 19) and age-matched healthy controls (n = 19) (age ranges: patients, 22.7–54.3 and healthy controls, 24.9–51.6 years old). We found a significant reduction of FD in the left hippocampus (median: 2.1460, range: 2.07–2.18 vs. median: 2.1730, range: 2.15–2.23, p<0.001; Cohen’s effect size, U3 = 0.8158 (95% Confidence Intervals, CIs: 0.6316, 1.0)), the right hippocampus (median: 2.1430, range: 2.05–2.19 vs. median: 2.1760, range: 2.12–2.21, p = 0.004; U3 = 0.8421 (CIs: 0.5263, 1)), as well as left thalamus (median: 2.4230, range: 2.40–2.44, p = 0.005; U3 = 0.7895 (CIs: 0.5789, 0.9473)) in schizophrenia patients, relative to healthy individuals. Our findings provide in-vivo quantitative evidence for reduced surface complexity of hippocampus, with reduced FD indicating a less complex, less regular GM surface detected in schizophrenia.

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<![CDATA[Dendritic overgrowth and elevated ERK signaling during neonatal development in a mouse model of autism]]> https://www.researchpad.co/article/5989db5eab0ee8fa60be0b35

Autism spectrum disorder (hereafter referred to as “ASD”) is a heterogeneous neurodevelopmental condition characterized by impaired social communication and interactions, and restricted, repetitive activities or interests. Alterations in network connectivity and memory function are frequently observed in autism patients, often involving the hippocampus. However, specific changes during early brain development leading to disrupted functioning remain largely unclear. Here, we investigated the development of dendritic arbor of hippocampal CA1 pyramidal neurons in the BTBR T+tf/J (BTBR) mouse model of autism. BTBR mice display the defining behavioural features of autism, and also exhibit impaired learning and memory. We found that compared to control C57BL/6J (B6) animals, the lengths of both apical and basal dendrites were significantly greater in neonatal BTBR animals. Further, basal dendrites in the BTBR mice had higher branching complexity. In contrast, cross-sectional area of the soma was unchanged. In addition, we observed a similar density of CA1 pyramidal neurons and thickness of the neuronal layer between the two strains. Thus, there was a specific, compartmentalized overgrowth of dendrites during early development in the BTBR animals. Biochemical analysis further showed that the extracellular signal-regulated kinases (ERK) pathway was up-regulated in the hippocampus of neonatal BTBR animals. Since dendritic structure is critical for information integration and relay, our data suggest that altered development of dendrites could potentially contribute to impaired hippocampal function and behavior observed in the BTBR model, and that this might be related to increased activation of the ERK pathway.

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<![CDATA[Somato-dendritic Synaptic Plasticity and Error-backpropagation in Active Dendrites]]> https://www.researchpad.co/article/5989dae5ab0ee8fa60bbd0d2

In the last decade dendrites of cortical neurons have been shown to nonlinearly combine synaptic inputs by evoking local dendritic spikes. It has been suggested that these nonlinearities raise the computational power of a single neuron, making it comparable to a 2-layer network of point neurons. But how these nonlinearities can be incorporated into the synaptic plasticity to optimally support learning remains unclear. We present a theoretically derived synaptic plasticity rule for supervised and reinforcement learning that depends on the timing of the presynaptic, the dendritic and the postsynaptic spikes. For supervised learning, the rule can be seen as a biological version of the classical error-backpropagation algorithm applied to the dendritic case. When modulated by a delayed reward signal, the same plasticity is shown to maximize the expected reward in reinforcement learning for various coding scenarios. Our framework makes specific experimental predictions and highlights the unique advantage of active dendrites for implementing powerful synaptic plasticity rules that have access to downstream information via backpropagation of action potentials.

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