scholarly journals Modeling the Shape of Synaptic Spines by their Actin Dynamics

2019 ◽  
Author(s):  
Mayte Bonilla-Quintana ◽  
Florentin Wörgötter ◽  
Christian Tetzlaff ◽  
Michael Fauth
Keyword(s):  
Synaptic Transmission ◽  
Actin Polymerization ◽  
Temporal Structure ◽  
Memory Storage ◽  
Biophysical Model ◽  
Large Set ◽  
Biophysical Parameters ◽  
Size And Shape ◽  
Spine Shape ◽  
Depth Analysis

AbstractDendritic spines are the morphological basis of excitatory synapses in the cortex and their size and shape correlates with functional synaptic properties. Recent experiments show that spines exhibit large shape fluctuations that are not related to activity-dependent plasticity but nonetheless might influence memory storage at their synapses. To investigate the determinants of such spontaneous fluctuations, we propose a mathematical model for the dynamics of the spine shape and analyze it in 2D — related to experimental microscopic imagery — and in 3D. We show that the spine shape is governed by a local imbalance between membrane tension and the expansive force from actin bundles that originates from discrete actin polymerization foci. Experiments have shown that only few such polymerization foci co-exist at any time in a spine, each having limited life time. The model shows that the momentarily existing set of such foci pushes the membrane along certain directions until foci are replaced and other directions may now be affected. We explore these relations in depth and use our model to predict shape and temporal characteristics of spines from the different biophysical parameters involved in actin polymerization. Reducing the model further to a single recursive equation we finally demonstrate that the temporal evolution of the number of active foci is sufficient to predict the size of the model-spines. Thus, our model provides the first platform to study the relation between molecular and morphological properties of the spine with a high degree of biophysical detail.Author summarySynaptic spines are post-synaptic contact points for pre-synaptic signals in many cortical neurons and it has been shown that synaptic transmission is correlated with spine size. However, spine size and shape can vary quite strongly on short time scales and it is currently unknown how these shape variations emerge. In this study we present a biophysical model that links spine shape fluctuations to the dynamics of the spine’s actin-based cytoskeleton. We show that shape fluctuations arise from the fact that fast actin polymerization in a spine is a discrete process happening at only few polymerization foci. Life and death of these foci determine from moment to moment how the membrane bulges or retracts. We provide an in-depth analysis of this effect for a large set of biophysical parameters and quantify the spatial-temporal structure of the spines. Our model, thus, provides a quantitative characterization of the link between spine morphology and the underlying molecular processes, which forms an essential step towards a better understanding of synaptic transmission during steady state but also during synaptic plasticity.

scholarly journals Reproducing asymmetrical spine shape fluctuations in a model of actin dynamics predicts self-organized criticality

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Mayte Bonilla-Quintana ◽  
Florentin Wörgötter ◽  
Elisa D’Este ◽  
Christian Tetzlaff ◽  
Michael Fauth
Keyword(s):  
Biophysical Model ◽  
Actin Dynamics ◽  
Circular Statistics ◽  
Size And Shape ◽  
Spine Shape ◽  
Self Organized ◽  
Temporal Intervals ◽  
Self Organized Criticality ◽  
Confocal Microscopy Image ◽  
Critical Model

AbstractDendritic spines change their size and shape spontaneously, but the function of this remains unclear. Here, we address this in a biophysical model of spine fluctuations, which reproduces experimentally measured spine fluctuations. For this, we characterize size- and shape fluctuations from confocal microscopy image sequences using autoregressive models and a new set of shape descriptors derived from circular statistics. Using the biophysical model, we extrapolate into longer temporal intervals and find the presence of 1/f noise. When investigating its origins, the model predicts that the actin dynamics underlying shape fluctuations self-organizes into a critical state, which creates a fine balance between static actin filaments and free monomers. In a comparison against a non-critical model, we show that this state facilitates spine enlargement, which happens after LTP induction. Thus, ongoing spine shape fluctuations might be necessary to react quickly to plasticity events.

scholarly journals The Astrocyte as a Gatekeeper of Synaptic Information Transfer

2007 ◽  
Vol 19 (2) ◽  
pp. 303-326 ◽  
Author(s):  
Vladislav Volman ◽  
Eshel Ben-Jacob ◽  
Herbert Levine
Keyword(s):  
Synaptic Transmission ◽  
Information Flow ◽  
Information Transfer ◽  
Calcium Concentration ◽  
Spike Timing ◽  
Biophysical Model ◽  
Testable Hypothesis ◽  
Cells In Culture

We present a simple biophysical model for the coupling between synaptic transmission and the local calcium concentration on an enveloping astrocytic domain. This interaction enables the astrocyte to modulate the information flow from presynaptic to postsynaptic cells in a manner dependent on previous activity at this and other nearby synapses. Our model suggests a novel, testable hypothesis for the spike timing statistics measured for rapidly firing cells in culture experiments.

Dendritic Spine Remodeling After Spinal Cord Injury Alters Neuronal Signal Processing

2009 ◽  
Vol 102 (4) ◽  
pp. 2396-2409 ◽  
Author(s):  
Andrew M. Tan ◽  
Jin-Sung Choi ◽  
Stephen G. Waxman ◽  
Bryan C. Hains
Keyword(s):  
Spinal Cord ◽  
Spinal Cord Injury ◽  
Synaptic Transmission ◽  
Dendritic Spines ◽  
Dendritic Spine ◽  
Nociceptive Neurons ◽  
Spine Shape ◽  
Cord Injury ◽  
Dendritic Spine Morphology ◽  
Neuronal Signal

Central sensitization, a prolonged hyperexcitability of dorsal horn nociceptive neurons, is a major contributor to abnormal pain processing after spinal cord injury (SCI). Dendritic spines are micron-sized dendrite protrusions that can regulate the efficacy of synaptic transmission. Here we used a computational approach to study whether changes in dendritic spine shape, density, and distribution can individually, or in combination, adversely modify the input–output function of a postsynaptic neuron to create a hyperexcitable neuronal state. The results demonstrate that a conversion from thin-shaped to more mature, mushroom-shaped spine structures results in enhanced synaptic transmission and fidelity, improved frequency-following ability, and reduced inhibitory gating effectiveness. Increasing the density and redistributing spines toward the soma results in a greater probability of action potential activation. Our results demonstrate that changes in dendritic spine morphology, documented in previous studies on spinal cord injury, contribute to the generation of pain following SCI.

Mastering the Digital Transformation of Sales

2020 ◽  
Vol 62 (4) ◽  
pp. 57-85 ◽  
Author(s):  
Paolo Guenzi ◽  
Johannes Habel
Keyword(s):  
Digital Transformation ◽  
Large Set ◽  
Academic Literature ◽  
International Benchmarking ◽  
Depth Analysis ◽  
Effectiveness And Efficiency

Managerial and academic literature provide only limited guidance on how to drive the digital transformation of sales. This article presents a model for in-depth analysis of sales processes, goals for each process in terms of effectiveness and efficiency, and a structured set of digital responses. For managers, it provides actionable guidelines on how to drive the digital transformation of sales, a large set of inspiring examples, and an international benchmarking opportunity.

scholarly journals The Energetics of Molecular Adaptation in Transcriptional Regulation

2019 ◽  
Author(s):  
Griffin Chure ◽  
Manuel Razo-Mejia ◽  
Nathan M. Belliveau ◽  
Tal Einav ◽  
Zofii A. Kaczmarek ◽  
...  
Keyword(s):  
Free Energy ◽  
Transcriptional Regulation ◽  
Dna Binding ◽  
Coarse Graining ◽  
Binding Domain ◽  
Biophysical Model ◽  
Model Parameters ◽  
Biophysical Parameters ◽  
Binding Domains ◽  
Laci Repressor

Mutation is a critical mechanism by which evolution explores the functional landscape of proteins. Despite our ability to experimentally inflict mutations at will, it remains difficult to link sequence-level perturbations to systems-level responses. Here, we present a framework centered on measuring changes in the free energy of the system to link individual mutations in an allosteric transcriptional repressor to the parameters which govern its response. We find the energetic effects of the mutations can be categorized into several classes which have characteristic curves as a function of the inducer concentration. We experimentally test these diagnostic predictions using the well-characterized LacI repressor of Escherichia coli, probing several mutations in the DNA binding and inducer binding domains. We find that the change in gene expression due to a point mutation can be captured by modifying only a subset of the model parameters that describe the respective domain of the wild-type protein. These parameters appear to be insulated, with mutations in the DNA binding domain altering only the DNA affinity and those in the inducer binding domain altering only the allosteric parameters. Changing these subsets of parameters tunes the free energy of the system in a way that is concordant with theoretical expectations. Finally, we show that the induction profiles and resulting free energies associated with pairwise double mutants can be predicted with quantitative accuracy given knowledge of the single mutants, providing an avenue for identifying and quantifying epistatic interactions.SummaryWe present a biophysical model of allosteric transcriptional regulation that directly links the location of a mutation within a repressor to the biophysical parameters that describe its behavior. We explore the phenotypic space of a repressor with mutations in either the inducer binding or DNA binding domains. Using the LacI repressor in E. coli, we make sharp, falsifiable predictions and use this framework to generate a null hypothesis for how double mutants behave given knowledge of the single mutants. Linking mutations to the parameters which govern the system allows for quantitative predictions of how the free energy of the system changes as a result, permitting coarse graining of high-dimensional data into a single-parameter description of the mutational consequences.

scholarly journals EEG-Based 3D Visual Fatigue Evaluation Using CNN

Electronics ◽  
2019 ◽  
Vol 8 (11) ◽  
pp. 1208 ◽  
Author(s):  
Kang Yue ◽  
Danli Wang
Keyword(s):  
Feature Extraction ◽  
Temporal Structure ◽  
Visual Fatigue ◽  
Eeg Signals ◽  
Visual Evaluation ◽  
Time Frequency ◽  
Multi Scale ◽  
Temporal Features ◽  
Depth Analysis ◽  
Fatigue Evaluation

Visual fatigue evaluation plays an important role in applications such as virtual reality since the visual fatigue symptoms always affect the user experience seriously. Existing visual evaluation methods require hand-crafted features for classification, and conduct feature extraction and classification in a separated manner. In this paper, we conduct a designed experiment to collect electroencephalogram (EEG) signals of various visual fatigue levels, and present a multi-scale convolutional neural network (CNN) architecture named MorletInceptionNet to detect visual fatigue using EEG as input, which exploits the spatial-temporal structure of multichannel EEG signals. Our MorletInceptionNet adopts a joint space-time-frequency features extraction scheme in which Morlet wavelet-like kernels are used for time-frequency raw feature extraction and inception architecture are further used to extract multi-scale temporal features. Then, the multi-scale temporal features are concatenated and fed to the fully connected layer for visual fatigue evaluation using classification. In experiment evaluation, we compare our method with five state-of-the-art methods, and the results demonstrate that our model achieve overally the best performance better performance for two widely used evaluation metrics, i.e., classification accuracy and kappa value. Furthermore, we use input-perturbation network-prediction correlation maps to conduct in-depth analysis into the reason why the proposed method outperforms other methods. The results suggest that our model is sensitive to the perturbation of β (14–30 Hz) and γ (30–40 Hz) bands. Furthermore, their spatial patterns are of high correlation with that of the corresponding power spectral densities which are used as evaluation features traditionally. This finding provides evidence of the hypothesis that the proposed model can learn the joint time-frequency-space features to distinguish fatigue levels automatically.

scholarly journals Characterization of dynamic evolution of the spatio-temporal variation of rain-field in Hong Kong

2015 ◽  
Vol 47 (2) ◽  
pp. 468-482 ◽  
Author(s):  
Peng Liu ◽  
Yeou-Koung Tung
Keyword(s):  
Hong Kong ◽  
Spatial Structure ◽  
Temporal Structure ◽  
Radar Data ◽  
Small Scale ◽  
Large Set ◽  
Time Space ◽  
Main Challenge ◽  
Geostatistical Approach ◽  
Spatio Temporal

A significant part of Hong Kong has hilly terrain with relatively short flow concentration time and, hence, is susceptible to the threat of flash floods and landslides during intense convective thunderstorms and tropical cyclones. For places like Hong Kong, a rainfall model that could adequately capture small-scale temporal and spatial variations would be highly desirable. The main challenge in rain-field modeling is to capture and describe the dynamic time-space evolution of the rainfall during rainstorm events. In this study, radar data with a high spatial (1 km2) and temporal (6 min) resolution of four rainstorm events in Hong Kong are analyzed. A geostatistical approach based on indicator variograms of rain-fields is used. The spatial structure of a rain-field is found to be highly anisotropic and should be adequately considered in the model. Variability of the spatial structure of a rain-field was described well by the main features of the variograms. Moreover, it is possible to identify whether multiple rainstorm centers exist by comparing the mean length and range. In order to establish reliable statistics on the spatial and temporal structure of rain-fields in Hong Kong, this approach could be applied to a large set of rainstorm events in this same region in the future.

scholarly journals Hippocampal Dendritic Spines Are Segregated Depending on Their Actin Polymerization

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Nuria Domínguez-Iturza ◽  
María Calvo ◽  
Marion Benoist ◽  
José Antonio Esteban ◽  
Miguel Morales
Keyword(s):  
Dendritic Spines ◽  
Hippocampal Neurons ◽  
Actin Polymerization ◽  
Close Contact ◽  
Postsynaptic Membrane ◽  
Actin Dynamics ◽  
Filamentous Actin ◽  
Virtual Absence ◽  
Spine Shape ◽  
Mobile Fraction

Dendritic spines are mushroom-shaped protrusions of the postsynaptic membrane. Spines receive the majority of glutamatergic synaptic inputs. Their morphology, dynamics, and density have been related to synaptic plasticity and learning. The main determinant of spine shape is filamentous actin. Using FRAP, we have reexamined the actin dynamics of individual spines from pyramidal hippocampal neurons, both in cultures and in hippocampal organotypic slices. Our results indicate that, in cultures, the actin mobile fraction is independently regulated at the individual spine level, and mobile fraction values do not correlate with either age or distance from the soma. The most significant factor regulating actin mobile fraction was the presence of astrocytes in the culture substrate. Spines from neurons growing in the virtual absence of astrocytes have a more stable actin cytoskeleton, while spines from neurons growing in close contact with astrocytes show a more dynamic cytoskeleton. According to their recovery time, spines were distributed into two populations with slower and faster recovery times, while spines from slice cultures were grouped into one population. Finally, employing fast lineal acquisition protocols, we confirmed the existence of loci with high polymerization rates within the spine.

Electrophysiological Properties of Rat Pontine Nuclei Neurons In Vitro II. Postsynaptic Potentials

1997 ◽  
Vol 78 (6) ◽  
pp. 3338-3350 ◽  
Author(s):  
Martin Möck ◽  
Cornelius Schwarz ◽  
Peter Thier
Keyword(s):  
Synaptic Transmission ◽  
Temporal Structure ◽  
Cerebral Peduncle ◽  
Pontine Nuclei ◽  
Postsynaptic Potentials ◽  
Electrophysiological Properties ◽  
Ampa And Nmda Receptors ◽  
Pharmacological Blockade ◽  
Electrical Stimuli

Möck, Martin, Cornelius Schwarz, and Peter Thier. Electrophysiological properties of rat pontine nuclei neurons in vitro. II. Postsynaptic potentials. J. Neurophysiol. 78: 3338–3350, 1997. We investigated the postsynaptic responses of neurons of the rat pontine nuclei (PN) by performing intracellular recordings in parasagittal slices of the pontine brain stem. Postsynaptic potentials (PSPs) were evoked by brief (0.1 ms) negative current pulses (10–250 μA) applied to either the cerebral peduncle or the pontine tegmentum. First, excitatory postsynaptic potentials (EPSPs) could be evoked readily from peduncular stimulation sites. These EPSPs exhibited short latencies, a nonlinear increment in response to increased stimulation currents, and an unconventional dependency on the somatic membrane potential. Pharmacological blockade of the synaptic transmission using 6,7-dinitroquinoxaline-2,3-dione and d,l-2-amino-5-phosphonovaleric acid, selective antagonists of the α-amino-3-hydroxy-5-methyl-4-isoxazilepropionate- (AMPA) and the N-methyl-d-aspartate (NMDA)-type glutamate receptors, showed that these EPSPs were mediated exclusively by excitatory amino acids via both AMPA and NMDA receptors. Moreover, the pharmacological experiments indicated the existence of voltage-sensitive but NMDA receptor-independent amplification of EPSPs. Second, stimulations at peduncular and tegmental sites also elicited inhibitory postsynaptic potentials (IPSPs) in a substantial proportion of pontine neurons. The short latencies of all IPSPs argued against the participation of inhibitory interneurons. Their sensitivity to bicuculline and reversal potentials around −70 mV suggested that they were mediated by γ-aminobutyric acid-A (GABAA) receptors. In addition to single PSPs, sequences consisting of two to four distinct EPSPs could be recorded after stimulation of the cerebral peduncle. Most remarkably, the onset latencies of the following EPSPs were multiples of the first one indicating the involvement of intercalated synapses. Finally, we used the classic paired-pulse paradigm to study whether the temporal structure of inputs influences the synaptic transmission onto pontine neurons. Pairs of electrical stimuli applied to the cerebral peduncle resulted in a marked enhancement of the amplitude of the second EPSP for interstimulus intervals of 10–100 ms. Delays >200 ms left the EPSP amplitude unaltered. These data provide evidence for a complex synaptic integration and an intrinsic connectivity within the PN too elaborate to support the previous notion that the PN are simply a relay station.

scholarly journals Understanding balloon-borne frost point hygrometer measurements after contamination by mixed-phase clouds

2021 ◽  
Vol 14 (1) ◽  
pp. 239-268
Author(s):  
Teresa Jorge ◽  
Simone Brunamonti ◽  
Yann Poltera ◽  
Frank G. Wienhold ◽  
Bei P. Luo ◽  
...  
Keyword(s):  
Water Vapour ◽  
High Water ◽  
Large Set ◽  
Mixing Ratios ◽  
Frost Point ◽  
Depth Analysis ◽  
Air Chemistry ◽  
Computational Fluid Dynamics Cfd ◽  
Impact Angles ◽  
Mixed Phase Clouds

Abstract. Balloon-borne water vapour measurements in the upper troposphere and lower stratosphere (UTLS) by means of frost point hygrometers provide important information on air chemistry and climate. However, the risk of contamination from sublimating hydrometeors collected by the intake tube may render these measurements unusable, particularly after crossing low clouds containing supercooled droplets. A large set of (sub)tropical measurements during the 2016–2017 StratoClim balloon campaigns at the southern slopes of the Himalayas allows us to perform an in-depth analysis of this type of contamination. We investigate the efficiency of wall contact and freezing of supercooled droplets in the intake tube and the subsequent sublimation in the UTLS using computational fluid dynamics (CFD). We find that the airflow can enter the intake tube with impact angles up to 60∘, owing to the pendulum motion of the payload. Supercooled droplets with radii > 70 µm, as they frequently occur in mid-tropospheric clouds, typically undergo contact freezing when entering the intake tube, whereas only about 50 % of droplets with 10 µm radius freeze, and droplets < 5 µm radius mostly avoid contact. According to CFD, sublimation of water from an icy intake can account for the occasionally observed unrealistically high water vapour mixing ratios (χH2O > 100 ppmv) in the stratosphere. Furthermore, we use CFD to differentiate between stratospheric water vapour contamination by an icy intake tube and contamination caused by outgassing from the balloon and payload, revealing that the latter starts playing a role only during ascent at high altitudes (p < 20 hPa).

Sign in / Sign up

Export Citation Format

Share Document