scholarly journals Reconstruction and Simulation of a Scaffold Model of the Cerebellar Network

2019 ◽  
Author(s):  
Stefano Casali ◽  
Elisa Marenzi ◽  
Chaitanya Medini ◽  
Claudia Casellato ◽  
Egidio D’Angelo
Keyword(s):  
Computational Models ◽  
Mossy Fiber ◽  
Molecular Layer ◽  
Cerebellar Nuclei ◽  
Neuronal Morphology ◽  
Inhibitory Synapses ◽  
Structural Constraints ◽  
Neuron Models ◽  
Cellular Mechanisms ◽  
The Impact

AbstractReconstructing neuronal microcircuits through computational models is fundamental to simulate local neuronal dynamics. Here a scaffold model of the cerebellum has been developed in order to flexibly place neurons in space, connect them synaptically and endow neurons and synapses with biologically-grounded mechanisms. The scaffold model can keep neuronal morphology separated from network connectivity, which can in turn be obtained from convergence/divergence ratios and axonal/dendritic field 3D geometries. We first tested the scaffold on the cerebellar microcircuit, which presents a challenging 3D organization, at the same time providing appropriate datasets to validate emerging network behaviors. The scaffold was designed to integrate the cerebellar cortex with deep cerebellar nuclei (DCN), including different neuronal types: Golgi cells, granule cells, Purkinje cells, stellate cells, basket cells and DCN principal cells. Mossy fiber (mf) inputs were conveyed through the glomeruli. An anisotropic volume (0.077 mm3) of mouse cerebellum was reconstructed, in which point-neuron models were tuned toward the specific discharge properties of neurons and were connected by exponentially decaying excitatory and inhibitory synapses. Simulations using pyNEST and pyNEURON showed the emergence of organized spatio-temporal patterns of neuronal activity similar to those revealed experimentally in response to background noise and burst stimulation of mossy fiber bundles. Different configurations of granular and molecular layer connectivity consistently modified neuronal activation patterns, revealing the importance of structural constraints for cerebellar network functioning. The scaffold provided thus an effective workflow accounting for the complex architecture of the cerebellar network. In principle, the scaffold can incorporate cellular mechanisms at multiple levels of detail and be tuned to test different structural and functional hypotheses. A future implementation using detailed 3D multi-compartment neuron models and dynamic synapses will be needed to investigate the impact of single neuron properties on network computation.

scholarly journals Model Simulations Unveil The Structure-Function-Dynamics Relationship of The Cerebellar Cortical Microcircuit

2021 ◽  
Author(s):  
Robin De Schepper ◽  
Alice Geminiani ◽  
Stefano Masoli ◽  
Martina Francesca Rizza ◽  
Alberto Antonietti ◽  
...  
Keyword(s):  
Structure Function ◽  
Molecular Layer ◽  
Mossy Fibers ◽  
Ground Truth ◽  
Signal Propagation ◽  
Neuron Models ◽  
Cellular Mechanisms ◽  
Modeling Framework ◽  
The Impact

Abstract The cerebellar network is renowned for its regular architecture that has inspired foundational computational theories. However, the relationship between circuit structure, function and dynamics remained elusive. To tackle the issue, we have developed an advanced computational modeling framework that allowed us to reconstruct and simulate the structure and function of the mouse cerebellar cortex using morphologically realistic multi-compartmental neuron models. The cerebellar connectome was generated through appropriate connection rules, unifying a collection of scattered experimental data into a coherent construct and providing a new model-based ground-truth about circuit organization. Naturalistic background and sensory-burst stimulation were then used for functional validation against recordings in vivo, monitoring the impact of cellular mechanisms on signal propagation and spatio-temporal processing. Our simulations show, for the first time, how mossy fibers entrain the local neuronal microcircuit boosting the formation of columns of activity travelling from the granular to the molecular layer providing a new resource for the investigation of cerebellar computation.

A Mechanistic Motor-Clutch Model That Explains Cell Shape Dynamics to Cyclic Stretch

2022 ◽  
Author(s):  
Benjamin W. Scandling ◽  
Jia Gou ◽  
Jessica Thomas ◽  
Jacqueline Xuan ◽  
Chuan Xue ◽  
...  
Keyword(s):  
Computational Model ◽  
Computational Models ◽  
The Body ◽  
Cyclic Stretch ◽  
Substrate Stiffness ◽  
Cell Alignment ◽  
Cellular Mechanisms ◽  
Actin Bundles ◽  
The Impact

Many cells in the body experience cyclic mechanical loading, which can impact cellular processes and morphology. In vitro studies often report that cells reorient in response to cyclic stretch of their substrate. To explore cellular mechanisms involved in this reorientation, a computational model was developed by utilizing the previous computational models of the actin-myosin-integrin motor-clutch system developed by others. The computational model predicts that under most conditions, actin bundles align perpendicular to the direction of applied cyclic stretch, but under specific conditions, such as low substrate stiffness, actin bundles align parallel to the direction of stretch. The model also predicts that stretch frequency impacts the rate of reorientation, and that proper myosin function is critical in the reorientation response. These computational predictions are consistent with reports from the literature and new experimental results presented here. The model suggests that the impact of different stretching conditions (stretch type, amplitude, frequency, substrate stiffness, etc.) on the direction of cell alignment can largely be understood by considering their impact on cell-substrate detachment events, specifically whether detachment occurs during stretching or relaxing of the substrate.

Plasticity of Both Excitatory and Inhibitory Synapses Is Associated With Seizures Induced by Removal of Chronic Blockade of Activity in Cultured Hippocampus

2006 ◽  
Vol 96 (4) ◽  
pp. 2151-2167 ◽  
Author(s):  
Suzanne B. Bausch ◽  
Shuijin He ◽  
Yelena Petrova ◽  
Xiao-Min Wang ◽  
James O. McNamara
Keyword(s):  
Granule Cell ◽  
Granule Cells ◽  
Mossy Fiber ◽  
Field Potential ◽  
Inhibitory Synapses ◽  
Current Frequency ◽  
Synaptic Circuits ◽  
Acquired Epilepsy ◽  
The Impact ◽  
Excitatory And Inhibitory Synapses

One factor common to many neurological insults that can lead to acquired epilepsy is a loss of afferent neuronal input. Neuronal activity is one cellular mechanism implicated in transducing deafferentation into epileptogenesis. Therefore the effects of chronic activity blockade on seizure susceptibility and its underlying mechanisms were examined in organotypic hippocampal slice cultures treated chronically with the sodium channel blocker, tetrodotoxin (TTX), or the N-methyl-d-aspartate receptor (NMDAR) antagonist, d-2-amino-5-phosphonovaleric acid (d-APV). Granule cell field potential recordings in physiological buffer revealed spontaneous electrographic seizures in 83% of TTX-, 9% of d-APV-, but 0% of vehicle-treated cultures. TTX-induced seizures were not associated with membrane property alterations that would elicit granule cell hyperexcitability. Seizures were blocked by glutamate receptor antagonists, suggesting that plasticity in excitatory synaptic circuits contributed to seizures. The morphology of granule cells and their mossy fiber axons remained largely unchanged, and the number of synapses onto granule cells measured immunohistochemically was not increased in TTX- or d-APV-treated cultures. However, voltage-clamp recordings revealed that miniature excitatory postsynaptic current frequency and kinetics were increased and miniature inhibitory postsynaptic current kinetics were decreased in d-APV- and TTX-treated cultures compared with vehicle. Changes were more profound and qualitatively different in TTX- compared with d-APV-treated cultures, consistent with the dramatic effects of TTX treatment on seizure expression. We propose that chronic blockade of action potentials by TTX induces homeostatic responses including plasticity of both excitatory and inhibitory synapses. Removal of TTX unmasks the impact of these synaptic plasticities on local circuit excitability, resulting in spontaneous seizures.

A Simulation Study Investigating the Impact of Dendritic Morphology and Synaptic Topology on Neuronal Firing Patterns

2010 ◽  
Vol 22 (4) ◽  
pp. 1086-1111 ◽  
Author(s):  
Jen-Yung Chen
Keyword(s):  
Information Processing ◽  
Computational Models ◽  
Dendritic Morphology ◽  
Neuronal Firing ◽  
Membrane Properties ◽  
Neuron Models ◽  
Spatial And Temporal Scales ◽  
Brain Functions ◽  
Scaling Analyses ◽  
The Impact

In the brain, complex information interactions among neurons span several spatial and temporal scales, making it extremely difficult to identify the principles governing neural information processing. In this study, we used computational models to investigate the impact of dendritic morphology and synaptic topology on patterns of neuronal firing. We first constructed Hodgkin-Huxley-type neuron models that possessed dendrites with different morphological features. We then simulated the responses of these neurons to a number of spatiotemporal input patterns. The similarity between neuronal responses to different patterned inputs was effectively evaluated by a novel combination of metric space analysis and multidimensional scaling analyses. The results showed that neurons with different morphological or anatomical features exhibit differences in stimulus-specific temporal encoding and firing reliability. These findings support the idea that in addition to biophysical membrane properties, the dendritic morphology and the synaptic topology of a neuron can play a significant role in neuronal information processing and may directly contribute to various brain functions.

scholarly journals The relationship between birth timing, circuit wiring, and physiological response properties of cerebellar granule cells

2021 ◽  
Vol 118 (23) ◽  
pp. e2101826118
Author(s):  
S. Andrew Shuster ◽  
Mark J. Wagner ◽  
Nathan Pan-Doh ◽  
Jing Ren ◽  
Sophie M. Grutzner ◽  
...  
Keyword(s):  
Granule Cells ◽  
Cerebellar Granule Cells ◽  
Mossy Fiber ◽  
Molecular Layer ◽  
Cerebellar Nuclei ◽  
Birth Timing ◽  
Imaging Data ◽  
Cerebellar Granule ◽  
Virus Tracing

Cerebellar granule cells (GrCs) are usually regarded as a uniform cell type that collectively expands the coding space of the cerebellum by integrating diverse combinations of mossy fiber inputs. Accordingly, stable molecularly or physiologically defined GrC subtypes within a single cerebellar region have not been reported. The only known cellular property that distinguishes otherwise homogeneous GrCs is the correspondence between GrC birth timing and the depth of the molecular layer to which their axons project. To determine the role birth timing plays in GrC wiring and function, we developed genetic strategies to access early- and late-born GrCs. We initiated retrograde monosynaptic rabies virus tracing from control (birth timing unrestricted), early-born, and late-born GrCs, revealing the different patterns of mossy fiber input to GrCs in vermis lobule 6 and simplex, as well as to early- and late-born GrCs of vermis lobule 6: sensory and motor nuclei provide more input to early-born GrCs, while basal pontine and cerebellar nuclei provide more input to late-born GrCs. In vivo multidepth two-photon Ca2+ imaging of axons of early- and late-born GrCs revealed representations of diverse task variables and stimuli by both populations, with modest differences in the proportions encoding movement, reward anticipation, and reward consumption. Our results suggest neither organized parallel processing nor completely random organization of mossy fiber→GrC circuitry but instead a moderate influence of birth timing on GrC wiring and encoding. Our imaging data also provide evidence that GrCs can represent generalized responses to aversive stimuli, in addition to recently described reward representations.

scholarly journals Valproic acid-exposed astrocytes impair inhibitory synapse formation and function

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kotomi Takeda ◽  
Takuya Watanabe ◽  
Kohei Oyabu ◽  
Shuntaro Tsukamoto ◽  
Yuki Oba ◽  
...  
Keyword(s):  
Valproic Acid ◽  
Synaptic Transmission ◽  
Neurodevelopmental Disorders ◽  
Synapse Formation ◽  
Autism Spectrum ◽  
Vital Role ◽  
Neuronal Morphology ◽  
Inhibitory Neurons ◽  
Inhibitory Synapses ◽  
The Impact

AbstractValproic acid (VPA) is widely prescribed to treat epilepsy. Maternal VPA use is, however, clinically restricted because of the severe risk that VPA may cause neurodevelopmental disorders in offspring, such as autism spectrum disorder. Understanding the negative action of VPA may help to prevent VPA-induced neurodevelopmental disorders. Astrocytes play a vital role in neurodevelopment and synapse function; however, the impact of VPA on astrocyte involvement in neurodevelopment and synapse function has not been examined. In this study, we examined whether exposure of cultured astrocytes to VPA alters neuronal morphology and synapse function of co-cultured neurons. We show that synaptic transmission by inhibitory neurons was small because VPA-exposed astrocytes reduced the number of inhibitory synapses. However, synaptic transmission by excitatory neurons and the number of excitatory synapses were normal with VPA-exposed astrocytes. VPA-exposed astrocytes did not affect the morphology of inhibitory neurons. These data indicate that VPA-exposed astrocytes impair synaptogenesis specifically of inhibitory neurons. Our results indicate that maternal use of VPA would affect not only neurons but also astrocytes and would result in perturbed astrocyte-mediated neurodevelopment.

scholarly journals Morphologically constrained modeling of spinous inhibition in the somato-sensory cortex

2020 ◽  
Author(s):  
Olivier Gemin ◽  
Pablo Serna ◽  
Nora Assendorp ◽  
Matteo Fossati ◽  
Philippe Rostaing ◽  
...  
Keyword(s):  
Dendritic Spines ◽  
Computational Models ◽  
Pyramidal Neurons ◽  
Inhibitory Synapses ◽  
Brain Circuits ◽  
Basal Dendrites ◽  
Dendritic Shaft ◽  
Intact Brain ◽  
Neuronal Types ◽  
The Impact

ABSTRACTPyramidal neurons are covered by thousands of dendritic spines receiving excitatory synaptic inputs. The ultrastructure of dendritic spines shapes signal compartmentalization but ultrastructural diversity is rarely taken into account in computational models of synaptic integration. Here, we developed a 3D correlative light-electron microscopy (3D-CLEM) approach allowing the analysis of specific populations of synapses in genetically defined neuronal types in intact brain circuits. We used it to reconstruct segments of basal dendrites of layer 2/3 pyramidal neurons of adult mouse somatosensory cortex and quantify spine ultrastructural diversity. We found that 10% of spines were dually-innervated and 38% of inhibitory synapses localized to spines. Using our morphometric data to constrain a model of synaptic signal compartmentalization, we assessed the impact of spinous versus dendritic shaft inhibition. Our results indicate that spinous inhibition is locally more efficient than shaft inhibition and that it can decouple voltage and calcium signaling, potentially impacting synaptic plasticity.

scholarly journals A strategy for mapping biophysical to abstract neuronal network models applied to primary visual cortex

2021 ◽  
Author(s):  
Anton V. Chizhov ◽  
Lyle J. Graham
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Neuronal Network ◽  
Receptive Fields ◽  
Network Models ◽  
Neuron Models ◽  
Cellular Mechanisms ◽  
Neural Network Models ◽  
Theoretical Approaches ◽  
The Impact

AbstractA fundamental challenge for the theoretical study of neuronal networks is to make the link between complex biophysical models based directly on experimental data, to progressively simpler mathematical models that allow the derivation of general operating principles. We present a strategy that successively maps a relatively detailed biophysical population model, comprising conductance-based Hodgkin-Huxley type neuron models with connectivity rules derived from anatomical data, to various representations with fewer parameters, finishing with a firing rate network model that permits analysis. We apply this methodology to primary visual cortex of higher mammals, focusing on the functional property of stimulus orientation selectivity of receptive fields of individual neurons. The mapping produces compact expressions for the parameters of the abstract model that clearly identify the impact of specific electrophysiological and anatomical parameters on the analytical results, in particular as manifested by specific functional signatures of visual cortex, including input-output sharpening, conductance invariance, virtual rotation and the tilt after effect. Importantly, qualitative differences between model behaviours point out consequences of various simplifications. The strategy may be applied to other neuronal systems with appropriate modifications.Author summaryA hierarchy of theoretical approaches to study a neuronal network depends on a tradeoff between biological fidelity and mathematical tractibility. Biophysically-detailed models consider cellular mechanisms and anatomically defined synaptic circuits, but are often too complex to reveal insights into fundamental principles. In contrast, increasingly abstract reduced models facilitate analytical insights. To better ground the latter to the underlying biology, we describe a systematic procedure to move across the model hierarchy that allows understanding how changes in biological parameters - physiological, pathophysiological, or because of new data - impact the behaviour of the network. We apply this approach to mammalian primary visual cortex, and examine how the different models in the hierarchy reproduce functional signatures of this area, in particular the tuning of neurons to the orientation of a visual stimulus. Our work provides a navigation of the complex parameter space of neural network models faithful to biology, as well as highlighting how simplifications made for mathematical convenience can fundamentally change their behaviour.

scholarly journals Unique properties of dually innervated dendritic spines in pyramidal neurons of the somatosensory cortex uncovered by 3D correlative light and electron microscopy

PLoS Biology ◽  
2021 ◽  
Vol 19 (8) ◽  
pp. e3001375
Author(s):  
Olivier Gemin ◽  
Pablo Serna ◽  
Joseph Zamith ◽  
Nora Assendorp ◽  
Matteo Fossati ◽  
...  
Keyword(s):  
Electron Microscopy ◽  
Somatosensory Cortex ◽  
Dendritic Spines ◽  
Computational Models ◽  
Pyramidal Neurons ◽  
Light And Electron Microscopy ◽  
Inhibitory Synapses ◽  
Dendritic Shaft ◽  
Intact Brain ◽  
The Impact

Pyramidal neurons (PNs) are covered by thousands of dendritic spines receiving excitatory synaptic inputs. The ultrastructure of dendritic spines shapes signal compartmentalization, but ultrastructural diversity is rarely taken into account in computational models of synaptic integration. Here, we developed a 3D correlative light–electron microscopy (3D-CLEM) approach allowing the analysis of specific populations of synapses in genetically defined neuronal types in intact brain circuits. We used it to reconstruct segments of basal dendrites of layer 2/3 PNs of adult mouse somatosensory cortex and quantify spine ultrastructural diversity. We found that 10% of spines were dually innervated and 38% of inhibitory synapses localized to spines. Using our morphometric data to constrain a model of synaptic signal compartmentalization, we assessed the impact of spinous versus dendritic shaft inhibition. Our results indicate that spinous inhibition is locally more efficient than shaft inhibition and that it can decouple voltage and calcium signaling, potentially impacting synaptic plasticity.

scholarly journals Evaluation of the impact of compliance of precast discs of overlapping on the work of the frame of a multi-storey building

2019 ◽  
Vol 97 ◽  
pp. 04022
Author(s):  
Nikolay Trekin ◽  
Emil Kodysh ◽  
Alexander Bybka ◽  
Alexander Yamalov ◽  
Nikita Konkov
Keyword(s):  
Economic Performance ◽  
Computational Models ◽  
Precast Concrete ◽  
Building Frames ◽  
Frame Building ◽  
Numerical Studies ◽  
Frame Buildings ◽  
The Impact ◽  
Structural Solutions ◽  
Storey Building

The article provides an analysis and justification of the need to take into account the compliance of discs of overlapping and coatings when calculating frames from precast concrete structures. Previously conducted full-scale experiments showed that the rigidity of the precast overlapping with full filling of the seams, in comparison with the monolithic overlapping, decreases by 3-15 times due to the ductility of the joints. The use of refined computational models of structural solutions for frames, which take into account the compliance of the conjugations of elements, makes it possible to trace possible redistribution of efforts. Such an approach when reconstructing, it is possible to optimally select and calculate the enforcement of structure, and on new designing, to increase reliability and / or improve the economic performance of frame buildings. According to the results of analytical studies, formulas were adopted for the parameters that allow one to take into account the overall compliance of overlapping disks and coatings in computational models of building frames. Numerical studies on the computational model of a frame building made it possible to evaluate the effect of accounting for compliance on the stress-strain state of a multi-storey frame.

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