Biophysically Realistic Neuron Models for Simulation of Cortical Stimulation

1.AbstractObjectiveWe implemented computational models of human and rat cortical neurons for simulating the neural response to cortical stimulation with electromagnetic fields.ApproachWe adapted model neurons from the library of Blue Brain models to reflect biophysical and geometric properties of both adult rat and human cortical neurons and coupled the model neurons to exogenous electric fields (E-fields). The models included 3D reconstructed axonal and dendritic arbors, experimentally-validated electrophysiological behaviors, and multiple, morphological variants within cell types. Using these models, we characterized the single-cell responses to intracortical microstimulation (ICMS) and uniform E-field with dc as well as pulsed currents.Main resultsThe strength-duration and current-distance characteristics of the model neurons to ICMS agreed with published experimental results, as did the subthreshold polarization of cell bodies and axon terminals by uniform dc E-fields. For all forms of stimulation, the lowest threshold elements were terminals of the axon collaterals, and the dependence of threshold and polarization on spatial and temporal stimulation parameters was strongly affected by morphological features of the axonal arbor, including myelination, diameter, and branching.SignificanceThese results provide key insights into the mechanisms of cortical stimulation. The presented models can be used to study various cortical stimulation modalities while incorporating detailed spatial and temporal features of the applied E-field.

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Comparative AAV-eGFP Transgene Expression Using Vector Serotypes 1–9, 7m8, and 8b in Human Pluripotent Stem Cells, RPEs, and Human and Rat Cortical Neurons

Stem Cells International ◽

10.1155/2019/7281912 ◽

2019 ◽

Vol 2019 ◽

pp. 1-11 ◽

Cited By ~ 6

Author(s):

Thu T. Duong ◽

James Lim ◽

Vidyullatha Vasireddy ◽

Tyler Papp ◽

Hung Nguyen ◽

...

Keyword(s):

Cortical Neurons ◽

Transgene Expression ◽

Fluorescent Protein ◽

Ex Vivo ◽

Cell Types ◽

Egfp Expression ◽

Cell Type ◽

Egfp Gene ◽

Rat Cortical Neurons

Recombinant adeno-associated virus (rAAV), produced from a nonpathogenic parvovirus, has become an increasing popular vector for gene therapy applications in human clinical trials. However, transduction and transgene expression of rAAVs can differ acrossin vitroand ex vivo cellular transduction strategies. This study compared 11 rAAV serotypes, carrying one reporter transgene cassette containing a cytomegalovirus immediate-early enhancer (eCMV) and chicken beta actin (CBA) promoter driving the expression of an enhanced green-fluorescent protein (eGFP) gene, which was transduced into four different cell types: human iPSC, iPSC-derived RPE, iPSC-derived cortical, and dissociated embryonic day 18 rat cortical neurons. Each cell type was exposed to three multiplicity of infections (MOI: 1E4, 1E5, and 1E6 vg/cell). After 24, 48, 72, and 96 h posttransduction, GFP-expressing cells were examined and compared across dosage, time, and cell type. Retinal pigmented epithelium showed highest AAV-eGFP expression and iPSC cortical the lowest. At an MOI of 1E6 vg/cell, all serotypes show measurable levels of AAV-eGFP expression; moreover, AAV7m8 and AAV6 perform best across MOI and cell type. We conclude that serotype tropism is not only capsid dependent but also cell type plays a significant role in transgene expression dynamics.

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Nckβ Adapter Controls Neuritogenesis by Maintaining the Cellular Paxillin Level

Molecular and Cellular Biology ◽

10.1128/mcb.01807-06 ◽

2007 ◽

Vol 27 (17) ◽

pp. 6001-6011 ◽

Cited By ~ 16

Author(s):

Shengxi Guan ◽

Mei Chen ◽

David Woodley ◽

Wei Li

Keyword(s):

Pc12 Cells ◽

Cortical Neurons ◽

State Level ◽

Cell Types ◽

Steady State Level ◽

Down Regulation ◽

Evolutionarily Conserved ◽

Rat Cortical Neurons ◽

Interfering Rna

ABSTRACT The SH2/SH3 adapter Nck has an evolutionarily conserved role in neurons, linking the cell surface signals to actin cytoskeleton-mediated responses. The mechanism, however, remains poorly understood. We have investigated the role of Nck/Nckα/Nck1 versus Grb4/Nckβ/Nck2 side-by-side in the process of mammalian neuritogenesis. Here we show that permanent genetic silencing of Nckβ, but not Nckα, completely blocked nerve growth factor-induced neurite outgrowth in PC12 cells and dramatically disrupted the axon and dendrite tree in primary rat cortical neurons. By screening for changes among the components reportedly present in complex with Nck, we found that the steady-state level of paxillin was significantly reduced in Nckβ knockdown, but not Nckα knockdown, neurons. Interestingly, Nckβ knockdown did not affect the paxillin level in glial cells and several other cell types of various tissue origins. Genetic silencing of paxillin blocked neuritogenesis, just like Nckβ knockdown. Reintroducing a nondegradable Nckβ into Nckβ short interfering RNA-expressing PC12 cells rescued paxillin from down-regulation and allowed the resumption of neuritogenesis. Forced expression of paxillin in Nckβ knockdown PC12 also rescued its capacity for neuritogenesis. Finally, Nckβ, but not Nckα, binds strongly to paxillin and treatment of the neurons with proteosome inhibitors prevented paxillin down-regulation in Nckβ knockdown neurons. Thus, Nckβ maintains paxillin stability during neuritogenesis.

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Epigenomic Diversity of Cortical Projection Neurons in the Mouse Brain

10.1101/2020.04.01.019612 ◽

2020 ◽

Cited By ~ 3

Author(s):

Zhuzhu Zhang ◽

Jingtian Zhou ◽

Pengcheng Tan ◽

Yan Pang ◽

Angeline Rivkin ◽

...

Keyword(s):

Single Cell ◽

Cortical Neurons ◽

Neuronal Cell ◽

Cell Types ◽

Molecular Properties ◽

Projection Neurons ◽

Long Distance ◽

Cortical Projection ◽

Axon Terminals ◽

Projection Properties

SummaryNeuronal cell types are classically defined by their molecular properties, anatomy, and functions. While recent advances in single-cell genomics have led to high-resolution molecular characterization of cell type diversity in the brain, neuronal cell types are often studied out of the context of their anatomical properties. To better understand the relationship between molecular and anatomical features defining cortical neurons, we combined retrograde labeling with single-nucleus DNA methylation sequencing to link epigenomic properties of cell types to neuronal projections. We examined 11,827 single neocortical neurons from 63 cortico-cortical (CC) and cortico-subcortical long-distance projections. Our results revealed unique epigenetic signatures of projection neurons that correspond to their laminar and regional location and projection patterns. Based on their epigenomes, intra-telencephalic (IT) cells projecting to different cortical targets could be further distinguished, and some layer 5 neurons projecting to extra-telencephalic targets (L5-ET) formed separate subclusters that aligned with their axonal projections. Such separation varied between cortical areas, suggesting area-specific differences in L5-ET subtypes, which were further validated by anatomical studies. Interestingly, a population of CC projection neurons clustered with L5-ET rather than IT neurons, suggesting a population of L5-ET cortical neurons projecting to both targets (L5-ET+CC). We verified the existence of these neurons by labeling the axon terminals of CC projection neurons and observed clear labeling in ET targets including thalamus, superior colliculus, and pons. These findings highlight the power of single-cell epigenomic approaches to connect the molecular properties of neurons with their anatomical and projection properties.

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Selective Recruitment of Cortical Neurons by Electrical Stimulation

10.1101/213017 ◽

2017 ◽

Cited By ~ 1

Author(s):

Maxim Komarov ◽

Paola Malerba ◽

Paul Nunez ◽

Eric Halgren ◽

Maxim Bazhenov

Keyword(s):

Cortical Neurons ◽

Cell Activation ◽

Cell Types ◽

Cortical Stimulation ◽

Local Network ◽

Analytical Estimate ◽

Axonal Arborization ◽

Novel Approach ◽

Type Layer ◽

Layer I

AbstractDespite its critical importance in experimental and clinical neuroscience, at present there is no systematic method to predict which neural elements will be activated by a given stimulation regime. Here we develop a novel approach to model the effect of cortical stimulation on spiking probability of neurons in a volume of tissue, by applying an analytical estimate of stimulation-induced activation of different cell types across cortical layers. We utilize the morphology and properties of axonal arborization profiles obtained from publicly available anatomical reconstructions of the twelve main categories of neocortical neurons to derive the dependence of activation probability on cell type, layer and distance from the source. We then propagate this activity through the local network incorporating connectivity, synaptic and cellular properties. Our work predicts that (a) intracranial cortical stimulation induces selective activation across cell types and layers; (b) superficial anodal stimulation is more effective than cathodal at cell activation; (c) cortical surface stimulation focally activates layer I axons, and (d) an optimal stimulation intensity exists capable of eliciting cell activation lasting beyond the end of stimulation.

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Biophysically realistic neuron models for simulation of cortical stimulation

Journal of Neural Engineering ◽

10.1088/1741-2552/aadbb1 ◽

2018 ◽

Vol 15 (6) ◽

pp. 066023 ◽

Cited By ~ 26

Author(s):

Aman S Aberra ◽

Angel V Peterchev ◽

Warren M Grill

Keyword(s):

Cortical Stimulation ◽

Neuron Models ◽

Realistic Neuron

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Astrocytes Exhibit a Protective Role in Neuronal Firing Patterns under Chemically Induced Seizures in Neuron–Astrocyte Co-Cultures

International Journal of Molecular Sciences ◽

10.3390/ijms222312770 ◽

2021 ◽

Vol 22 (23) ◽

pp. 12770

Author(s):

Annika Ahtiainen ◽

Barbara Genocchi ◽

Jarno M. A. Tanskanen ◽

Michael T. Barros ◽

Jari A. K. Hyttinen ◽

...

Keyword(s):

Cortical Neurons ◽

Microelectrode Arrays ◽

Cell Types ◽

Protective Role ◽

Neuronal Firing ◽

Neuronal Homeostasis ◽

Chemically Induced ◽

Rat Cortical Neurons

Astrocytes and neurons respond to each other by releasing transmitters, such as γ-aminobutyric acid (GABA) and glutamate, that modulate the synaptic transmission and electrochemical behavior of both cell types. Astrocytes also maintain neuronal homeostasis by clearing neurotransmitters from the extracellular space. These astrocytic actions are altered in diseases involving malfunction of neurons, e.g., in epilepsy, Alzheimer’s disease, and Parkinson’s disease. Convulsant drugs such as 4-aminopyridine (4-AP) and gabazine are commonly used to study epilepsy in vitro. In this study, we aim to assess the modulatory roles of astrocytes during epileptic-like conditions and in compensating drug-elicited hyperactivity. We plated rat cortical neurons and astrocytes with different ratios on microelectrode arrays, induced seizures with 4-AP and gabazine, and recorded the evoked neuronal activity. Our results indicated that astrocytes effectively counteracted the effect of 4-AP during stimulation. Gabazine, instead, induced neuronal hyperactivity and synchronicity in all cultures. Furthermore, our results showed that the response time to the drugs increased with an increasing number of astrocytes in the co-cultures. To the best of our knowledge, our study is the first that shows the critical modulatory role of astrocytes in 4-AP and gabazine-induced discharges and highlights the importance of considering different proportions of cells in the cultures.

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Numerical uncertainty can critically affect simulations of mechanistic models in neuroscience

10.1101/2021.04.27.441605 ◽

2021 ◽

Author(s):

Jonathan Oesterle ◽

Nicholas Krämer ◽

Philipp Hennig ◽

Philipp Berens

Keyword(s):

Differential Equations ◽

Ordinary Differential Equations ◽

Computational Models ◽

Large Population ◽

Neural System ◽

Neuron Models ◽

True Solution ◽

Sample Paths ◽

The Central Nervous System ◽

Realistic Neuron

AbstractUnderstanding neural computation on the mechanistic level requires biophysically realistic neuron models. To analyze such models one typically has to solve systems of coupled ordinary differential equations (ODEs), which describe the dynamics of the underlying neural system. These ODEs are solved numerically with deterministic ODE solvers that yield single solutions with either no or only a global scalar bound on precision. To overcome this problem, we propose to use recently developed probabilistic solvers instead, which are able to reveal and quantify numerical uncertainties, for example as posterior sample paths. Importantly, these solvers neither require detailed insights into the kinetics of the models nor are they difficult to implement. Using these probabilistic solvers, we show that numerical uncertainty strongly affects the outcome of typical neuroscience simulations, in particular due to the non-linearity associated with the generation of action potentials. We quantify this uncertainty in individual single Izhikevich neurons with different dynamics, a large population of coupled Izhikevich neurons, single Hodgkin-Huxley neuron and a small network of Hodgkin-Huxley-like neurons. For commonly used ODE solvers, we find that the numerical uncertainty in these models can be substantial, possibly jittering spikes by milliseconds or even adding or removing individual spikes from the simulation altogether.Author summaryComputational neuroscience is built around computational models of neurons that allow the simulation and analysis of signal processing in the central nervous system. These models come typically in the form of ordinary differential equations (ODEs). The solution of these ODEs is computed using solvers with finite accuracy and, therefore, the computed solutions deviate from the true solution. If this deviation is too large but goes unnoticed, this can potentially lead to wrong scientific conclusions.A field in machine learning called probabilistic numerics has recently developed a set of probabilistic solvers for ODEs, which not only produce a single solution of unknown accuracy, but instead yield a distribution over simulations. Therefore, these tools allow one to address the problem state above and quantitatively analyze the numerical uncertainty inherent in the simulation process.In this study, we demonstrate how such solvers can be used to quantify numerical uncertainty in common neuroscience models. We study both Hodgkin-Huxley and Izhikevich neuron models and show that the numerical uncertainty in these models can be substantial, possibly jittering spikes by milliseconds or even adding or removing individual spikes from the simulation altogether. We discuss the implications of this finding and discuss how our methods can be used to select simulation parameters to trade off accuracy and speed.

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The Protective Effects of Jatrorrhizine on β-Amyloid (25-35)-Induced Neurotoxicity in Rat Cortical Neurons

CNS & Neurological Disorders - Drug Targets ◽

10.2174/1871527311211080013 ◽

2013 ◽

Vol 11 (8) ◽

pp. 1030-1037 ◽

Cited By ~ 17

Author(s):

Tao Luo ◽

Wei Jiang ◽

Yan Kong ◽

Sheng Li ◽

Feng He ◽

...

Keyword(s):

Cortical Neurons ◽

Protective Effects ◽

Rat Cortical Neurons ◽

Β Amyloid

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Neuron-specific activation of necroptosis signaling in multiple sclerosis cortical grey matter

Acta Neuropathologica ◽

10.1007/s00401-021-02274-7 ◽

2021 ◽

Vol 141 (4) ◽

pp. 585-604 ◽

Cited By ~ 1

Author(s):

Carmen Picon ◽

Anusha Jayaraman ◽

Rachel James ◽

Catriona Beck ◽

Patricia Gallego ◽

...

Keyword(s):

Multiple Sclerosis ◽

Signaling Pathway ◽

Cortical Neurons ◽

Grey Matter ◽

Molecular Mechanisms ◽

Fold Increase ◽

Cell Types ◽

Meningeal Inflammation ◽

Cortical Grey Matter

AbstractSustained exposure to pro-inflammatory cytokines in the leptomeninges is thought to play a major role in the pathogenetic mechanisms leading to cortical pathology in multiple sclerosis (MS). Although the molecular mechanisms underlying neurodegeneration in the grey matter remain unclear, several lines of evidence suggest a prominent role for tumour necrosis factor (TNF). Using cortical grey matter tissue blocks from post-mortem brains from 28 secondary progressive MS subjects and ten non-neurological controls, we describe an increase in expression of multiple steps in the TNF/TNF receptor 1 signaling pathway leading to necroptosis, including the key proteins TNFR1, FADD, RIPK1, RIPK3 and MLKL. Activation of this pathway was indicated by the phosphorylation of RIPK3 and MLKL and the formation of protein oligomers characteristic of necrosomes. In contrast, caspase-8 dependent apoptotic signaling was decreased. Upregulation of necroptotic signaling occurred predominantly in macroneurons in cortical layers II–III, with little expression in other cell types. The presence of activated necroptotic proteins in neurons was increased in MS cases with prominent meningeal inflammation, with a 30-fold increase in phosphoMLKL+ neurons in layers I–III. The density of phosphoMLKL+ neurons correlated inversely with age at death, age at progression and disease duration. In vivo induction of chronically elevated TNF and INFγ levels in the CSF in a rat model via lentiviral transduction in the meninges, triggered inflammation and neurodegeneration in the underlying cortical grey matter that was associated with increased neuronal expression of TNFR1 and activated necroptotic signaling proteins. Exposure of cultured primary rat cortical neurons to TNF induced necroptosis when apoptosis was inhibited. Our data suggest that neurons in the MS cortex are dying via TNF/TNFR1 stimulated necroptosis rather than apoptosis, possibly initiated in part by chronic meningeal inflammation. Neuronal necroptosis represents a pathogenetic mechanism that is amenable to therapeutic intervention at several points in the signaling pathway.

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