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

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.

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Scaffold modelling captures the structure-function-dynamics relationship in brain microcircuits

10.1101/2021.07.30.454314 ◽

2021 ◽

Author(s):

Robin Gilbert De Schepper ◽

Alice Geminiani ◽

Stefano Masoli ◽

Martina Francesca Rizza ◽

Alberto Antonietti ◽

...

Keyword(s):

Ground Truth ◽

Signal Propagation ◽

Neuron Models ◽

Modeling Framework ◽

Multiple Strategies ◽

Spatio Temporal ◽

Cell Placement ◽

Flexible Management ◽

The Impact

Modelling brain networks with complex configuration and cellular properties requires a set of neuroinformatic tools and an organized staged workflow. We have therefore developed the Brain Scaffold Builder (BSB), a new modeling framework embedding multiple strategies for cell placement and connectivity and a flexible management of cellular and network mechanisms. With BSB, for the first time, the mouse cerebellar cortex was reconstructed and simulated at cellular resolution, using morphologically realistic multi-compartmental single-neuron models. Embedded connection rules allowed BSB to generate the cerebellar connectome, unifying a collection of scattered experimental data into a coherent construct. Naturalistic background and sensory-burst stimulation were used for functional validation against recordings in vivo, monitoring the impact of subcellular mechanisms on signal propagation and spatio-temporal processing and providing a new ground-truth about circuit organization for the prediction of neural dynamics.

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Reconstruction and Simulation of a Scaffold Model of the Cerebellar Network

10.1101/532515 ◽

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.

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PalaCell2D: A framework for detailed tissue morphogenesis

10.1101/2021.01.30.428940 ◽

2021 ◽

Author(s):

Raphaël Conradin ◽

Christophe Coreixas ◽

Jonas Latt ◽

Bastien Chopard

Keyword(s):

Internal Pressure ◽

Tissue Growth ◽

Cellular Mechanisms ◽

Simple Description ◽

Biologically Relevant ◽

In Vivo Experiments ◽

Cell Shapes ◽

And Migration ◽

The Impact

AbstractIn silico, cell based approaches for modeling biological morphogenesis are used to test and validate our understanding of the biological and mechanical process that are at work during the growth and the organization of multi-cell tissues. As compared to in vivo experiments, computer based frameworks dedicated to tissue modeling allow us to easily test different hypotheses, and to quantify the impact of various biophysically relevant parameters.Here, we propose a formalism based on a detailed, yet simple, description of cells that accounts for intra-, inter- and extra-cellular mechanisms. More precisely, the cell growth and division is described through the space and time evolution of the membrane vertices. These vertices follow a Newtonian dynamics, meaning that their evolution is controlled by different types of forces: a membrane force (spring and bending), an adherence force (inter-cellular spring), external and internal pressure forces. Different evolution laws can be applied on the internal pressure, depending on the intra-cellular mechanism of interest. In addition to the cells dynamics, our formalism further relies on a lattice Boltzmann method, using the Palabos library, to simulate the diffusion of chemical signals. The latter aims at driving the growth and migration of a tissue by simply changing the state of the cells.All of this leads to an accurate description of the growth and division of cells, with realistic cell shapes and where membranes can have different properties. While this work is mainly of methodological nature, we also propose to validate our framework through simple, yet biologically relevant benchmark tests at both single-cell and full tissue scales. This includes free and chemically controlled cell tissue growth in an unbounded domain. The ability of our framework to simulate cell migration, cell compression and morphogenesis under external constraints is also investigated in a qualitative manner.

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Network feedback regulates motor output across a range of modulatory neuron activity

Journal of Neurophysiology ◽

10.1152/jn.01112.2015 ◽

2016 ◽

Vol 115 (6) ◽

pp. 3249-3263 ◽

Cited By ~ 4

Author(s):

Robert M. Spencer ◽

Dawn M. Blitz

Keyword(s):

Neuron Activity ◽

Projection Neurons ◽

Activity Levels ◽

Cellular Mechanisms ◽

Physiological Range ◽

Network Activation ◽

Network Output ◽

The Impact

Modulatory projection neurons alter network neuron synaptic and intrinsic properties to elicit multiple different outputs. Sensory and other inputs elicit a range of modulatory neuron activity that is further shaped by network feedback, yet little is known regarding how the impact of network feedback on modulatory neurons regulates network output across a physiological range of modulatory neuron activity. Identified network neurons, a fully described connectome, and a well-characterized, identified modulatory projection neuron enabled us to address this issue in the crab ( Cancer borealis) stomatogastric nervous system. The modulatory neuron modulatory commissural neuron 1 (MCN1) activates and modulates two networks that generate rhythms via different cellular mechanisms and at distinct frequencies. MCN1 is activated at rates of 5–35 Hz in vivo and in vitro. Additionally, network feedback elicits MCN1 activity time-locked to motor activity. We asked how network activation, rhythm speed, and neuron activity levels are regulated by the presence or absence of network feedback across a physiological range of MCN1 activity rates. There were both similarities and differences in responses of the two networks to MCN1 activity. Many parameters in both networks were sensitive to network feedback effects on MCN1 activity. However, for most parameters, MCN1 activity rate did not determine the extent to which network output was altered by the addition of network feedback. These data demonstrate that the influence of network feedback on modulatory neuron activity is an important determinant of network output and feedback can be effective in shaping network output regardless of the extent of network modulation.

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Effect of Neuritic Cables on Conductance Estimates for Remote Electrical Synapses

Journal of Neurophysiology ◽

10.1152/jn.00956.2002 ◽

2003 ◽

Vol 89 (4) ◽

pp. 2215-2224 ◽

Cited By ~ 10

Author(s):

Astrid A. Prinz ◽

Peter Fromherz

Keyword(s):

Signal Propagation ◽

Synaptic Conductance ◽

Electrical Synapse ◽

Protein Patterns ◽

Electrical Synapses ◽

Snail Neurons ◽

Cable Properties ◽

The Impact ◽

Synaptic Conductances

The conductance of electrical synapses is usually estimated from voltage recordings at the neuronal somata under the assumption that each cell is isopotential. This approach neglects effects of intervening neurites. For a cell pair with unbranched neurites and an electrical synapse at their ends, we used cable theory to derive an analytical expression that relates the synaptic conductance to voltage recordings at the cell bodies and to the neurite properties. The equation implies that the conventional method significantly underestimates the actual synapse conductance if the neurite length is comparable to the electrotonic length constant and if the synaptic conductance is similar to the serial neurite conductance. For an experimental test, we cultured pairs of snail neurons on protein patterns, resulting in a geometry that matched the theoretical model. Using the isopotential theory, we estimated the synapse conductances and found them to be rather weak. To obtain the cable properties, we recorded spatiotemporal maps of signal propagation in the neurites using a voltage-sensitive dye. Fits of these maps to a passive cable model showed that the snail neurons are electrotonically rather compact. Given these features of our experimental system, the synaptic conductances derived with the nonisopotential model deviated from the estimates of the isopotential theory by about 13%. This discrepancy, although small, shows that even in electrotonically compact neurons coupled by weak synapses the impact of the neuritic cables on conductance estimates cannot be neglected. When applied to less compact and more strongly coupled cell pairs in vivo, our approach can supply the realistic estimates of synaptic conductances that are necessary for a better understanding of the role of electrical coupling in neural systems.

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

10.1101/2021.04.28.441749 ◽

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.

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Experimental Study of the Impact of Alisma plantago-aquatica Secretions on Pathogenic Bacteria

Agricultural science and practice ◽

10.15407/agrisp1.03.003 ◽

2014 ◽

Vol 1 (3) ◽

pp. 3-7

Author(s):

O. Zhukorskyy ◽

O. Hulay

Keyword(s):

Pathogenic Bacteria ◽

Initial Density ◽

Biologically Active ◽

Erysipelothrix Rhusiopathiae ◽

Natural Focus ◽

Test Species ◽

Popula Tions ◽

And Control ◽

The Impact

Aim. To estimate the impact of in vivo secretions of water plantain (Alisma plantago-aquatica) on the popula- tions of pathogenic bacteria Erysipelothrix rhusiopathiae. Methods. The plants were isolated from their natural conditions, the roots were washed from the substrate residues and cultivated in laboratory conditions for 10 days to heal the damage. Then the water was changed; seven days later the selected samples were sterilized using fi lters with 0.2 μm pore diameter. The dilution of water plantain root diffusates in the experimental samples was 1:10–1:10,000. The initial density of E. rhusiopathiae bacteria populations was the same for both experimental and control samples. The estimation of the results was conducted 48 hours later. Results. When the dilution of root diffusates was 1:10, the density of erysipelothrixes in the experimental samples was 11.26 times higher than that of the control, on average, the dilution of 1:100 − 6.16 times higher, 1:1000 – 3.22 times higher, 1:10,000 – 1.81 times higher, respectively. Conclusions. The plants of A. plantago-aquatica species are capable of affecting the populations of E. rhusiopathiae pathogenic bacteria via the secretion of biologically active substances into the environment. The consequences of this interaction are positive for the abovementioned bacteria, which is demon- strated by the increase in the density of their populations in the experiment compared to the control. The intensity of the stimulating effect on the populations of E. rhusiopathiae in the root diffusates of A. plantago-aquatica is re- ciprocally dependent on the degree of their dilution. The investigated impact of water plantain on erysipelothrixes should be related to the topical type of biocenotic connections, the formation of which between the test species in the ecosystems might promote maintaining the potential of natural focus of rabies. Keywords: Alisma plantago-aquatica, in vivo secretions, Erysipelothrix rhusiopathiae, population density, topical type of connections.

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The efficiency of application of virtual cross-sections method and hypotheses MELS in problems of wave signal propagation in elastic waveguides with rough surfaces

JOURNAL OF ADVANCES IN PHYSICS ◽

10.24297/jap.v11i5.344 ◽

2016 ◽

pp. 3564-3575 ◽

Cited By ~ 1

Author(s):

Ara Sergey Avetisyan

Keyword(s):

Half Space ◽

Cross Sections ◽

Classical Method ◽

Signal Propagation ◽

Elastic Half Space ◽

Layered Systems ◽

Surface Layers ◽

Inhomogeneous Surface ◽

Wave Signal ◽

The Impact

The efficiency of virtual cross sections method and MELS (Magneto Elastic Layered Systems) hypotheses application is shown on model problem about distribution of wave field in thin surface layers of waveguide when plane wave signal is propagating in it. The impact of surface non-smoothness on characteristics of propagation of high-frequency horizontally polarized wave signal in isotropic elastic half-space is studied. It is shown that the non-smoothness leads to strong distortion of the wave signal over the waveguide thickness and along wave signal propagation direction as well. Â Numerical comparative analysis of change in amplitude and phase characteristics of obtained wave fields against roughness of weakly inhomogeneous surface of homogeneous elastic half-space surface is done by classical method and by proposed approach for different kind of non-smoothness.

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Curcumin-containing Silver Nanoparticles prevent carbon tetrachlorideinduced hepatotoxicity in mice

Combinatorial Chemistry & High Throughput Screening ◽

10.2174/1386207323666201211100830 ◽

2020 ◽

Vol 23 ◽

Author(s):

Hossam Ebaid ◽

Mohamed Habila ◽

Iftekhar Hassan ◽

Jameel Al-Tamimi ◽

Mohamed S. Omar ◽

...

Keyword(s):

Dna Damage ◽

Silver Nanoparticles ◽

Nuclear Dna ◽

Liquid Paraffin ◽

Tail Length ◽

Hepatic Tissue ◽

Tissue Destruction ◽

Group 2 ◽

The Impact

Background: Hepatotoxicity remains an important clinical challenge. Hepatotoxicity observed in response to toxins and hazardous chemicals may be alleviated by delivery of the curcumin in silver nanoparticles (AgNPs-curcumin). In this study, we examined the impact of AgNPs-curcumin in a mouse model of carbon tetrachloride (CCl4)-induced hepatic injury. Methods: Male C57BL/6 mice were divided into three groups (n=8 per group). Mice in group 1 were treated with vehicle control alone, while mice in Group 2 received a single intraperitoneal injection of 1 ml/kg CCl4 in liquid paraffin (1:1 v/v). Mice in group 3 were treated with 2.5 mg/kg AgNPs-curcumin twice per week for three weeks after the CCl4 challenge. Results: Administration of CCL4 resulted in oxidative dysregulation, including significant reductions in reduced glutathione and concomitant elevations in the level of malondialdehyde (MDA). CCL4 challenge also resulted in elevated levels of serum aspartate transaminase (AST) and alanine transaminase (ALT); these findings were associated with the destruction of hepatic tissues. Treatment with AgNPs-curcumin prevented oxidative imbalance, hepatic dysfunction, and tissue destruction. A comet assay revealed that CCl4 challenge resulted in significant DNA damage as documented by a 70% increase in nuclear DNA tail-length; treatment with AgNPs-curcumin inhibited the CCL4-mediated increase in nuclear DNA tail-length by 34%. Conclusion: Administration of AgNPs-curcumin resulted in significant antioxidant activity in vivo. This agent has the potential to prevent the hepatic tissue destruction and DNA damage that results from direct exposure to CCL4.

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