scholarly journals How does the presence of neural probes affect extracellular potentials?

2018 ◽  
Author(s):  
Alessio Paolo Buccino ◽  
Miroslav Kuchta ◽  
Karoline Horgmo Jæger ◽  
Torbjørn Vefferstad Ness ◽  
Pierre Berthet ◽  
...  
Keyword(s):  
Extracellular Space ◽  
Mechanistic Modeling ◽  
Accurate Estimation ◽  
Extracellular Potential ◽  
Cable Equation ◽  
Electrode Arrays ◽  
Neural Probes ◽  
Modeling Framework ◽  
Extracellular Recordings ◽  
Extracellular Potentials

AbstractObjectiveMechanistic modeling of neurons is an essential component of computational neuroscience that enables scientists to simulate, explain, and explore neural activity. The conventional approach to simulation of extracellular neural recordings first computes transmembrane currents using the cable equation and then sums their contribution to model the extracellular potential. This two-step approach relies on the assumption that the extracellular space is an infinite and homogeneous conductive medium, while measurements are performed using neural probes. The main purpose of this paper is to assess to what extent the presence of the neural probes of varying shape and size impacts the extracellular field and how to correct for them.ApproachWe apply a detailed modeling framework allowing explicit representation of the neuron and the probe to study the effect of the probes and thereby estimate the effect of ignoring it. We use meshes with simplified neurons and different types of probe and compare the extracellular action potentials with and without the probe in the extracellular space. We then compare various solutions to account for the probes’ presence and introduce an efficient probe correction method to include the probe effect in modeling of extracellular potentials.Main resultsOur computations show that microwires hardly influence the extracellular electric field and their effect can therefore be ignored. In contrast, Multi-Electrode Arrays (MEAs) significantly affect the extracellular field by magnifying the recorded potential. While MEAs behave similarly to infinite insulated planes, we find that their effect strongly depends on the neuron-probe alignment and probe orientation.SignificanceIgnoring the probe effect might be deleterious in some applications, such as neural localization and parameterization of neural models from extracellular recordings. Moreover, the presence of the probe can improve the interpretation of extracellular recordings, by providing a more accurate estimation of the extracellular potential generated by neuronal models.

Hyperexcitability of entorhinal cortex and hippocampus after application of aminooxyacetic acid (AOAA) to layer III of the rat medial entorhinal cortex in vitro

1996 ◽  
Vol 76 (5) ◽  
pp. 2986-3001 ◽  
Author(s):  
H. E. Scharfman
Keyword(s):  
Nmda Receptor ◽  
Evoked Potentials ◽  
Entorhinal Cortex ◽  
Pyramidal Cells ◽  
Aminooxyacetic Acid ◽  
Field Potentials ◽  
Medial Entorhinal Cortex ◽  
Extracellular Recordings ◽  
Extracellular Potentials

1. Injection of aminooxyacetic acid (AOAA) into the entorhinal cortex in vivo produces acute seizures and cell loss in medial entorhinal cortex. To understand these effects, AOAA was applied directly to the medial entorhinal cortex in slices containing both the entorhinal cortex and hippocampus. Extracellular and intracellular recordings were made in both the entorhinal cortex and hippocampus to study responses to angular bundle stimulation and spontaneous activity. 2. AOAA was applied focally by leak from a micropipette or by pressure ejection. Evoked potentials increased gradually within 5 min of application, particularly the late, negative components. Evoked potentials continued to increase for up to 1 h, and these changes persisted for the remainder of the experiment (up to 5 h after drug application). 3. Paired pulse facilitation (100-ms interval) was also enhanced after AOAA application. Increasing stimulus frequency to 1-10 Hz increased evoked potentials further, and after several seconds of such stimulation multiple field potentials occurred. When stimulation was stopped at this point, repetitive field potentials occurred spontaneously for 1-2 min. These recordings, and simultaneous extracellular recordings in different layers, indicated that spontaneous synchronous activity occurred in entorhinal neurons. Intracellularly labeled cortical pyramidal cells depolarized and discharged during spontaneous and evoked field potentials. 4. The effects of AOAA were blocked reversibly by bath application of the N-methyl-D-aspartate (NMDA) receptor antagonist D-amino-5-phosphonovalerate (D-APV; 25 microM) or focal application of D-APV to the medial entorhinal cortex. 5. Simultaneous extracellular recordings from the entorhinal cortex and hippocampus demonstrated that spontaneous synchronous activity in layer III was often followed within several milliseconds by negative field potentials in the terminal zones of the perforant path (stratum moleculare of the dentate gyrus and stratum lacunosum-moleculare of area CA1). The extracellular potentials recorded in the dentate gyrus corresponded to excitatory postsynaptic potentials and action potentials in dentate granule cells. However, extracellular potentials in area CA1 were small and rarely correlated with discharge in CA1 pyramidal cells. 6. The results demonstrate that AOAA application leads to an NMDA-receptor-dependent enhancement of evoked potentials in medial entorhinal cortical neurons, which appears to be irreversible. The potentials can be facilitated by repetitive stimulation, and lead to synchronized discharges of entorhinal neurons. The discharges invade other areas such as the hippocampus, indicating how seizure activity may spread after AOAA injection in vivo. These data suggest that AOAA may be a useful tool to study longlasting changes in NMDA receptor function that lead to epileptiform activity and neurodegeneration.

scholarly journals The Bayesian Covariance Structure Model for Testlets

2020 ◽  
pp. 107699862094120
Author(s):  
Jean-Paul Fox ◽  
Jeremias Wenzel ◽  
Konrad Klotzke
Keyword(s):  
Random Effects ◽  
Random Effect ◽  
Covariance Structure ◽  
Accurate Estimation ◽  
Model Parameters ◽  
Random Effects Model ◽  
Structure Model ◽  
Modeling Framework ◽  
Irt Models ◽  
Covariance Structure Model

Standard item response theory (IRT) models have been extended with testlet effects to account for the nesting of items; these are well known as (Bayesian) testlet models or random effect models for testlets. The testlet modeling framework has several disadvantages. A sufficient number of testlet items are needed to estimate testlet effects, and a sufficient number of individuals are needed to estimate testlet variance. The prior for the testlet variance parameter can only represent a positive association among testlet items. The inclusion of testlet parameters significantly increases the number of model parameters, which can lead to computational problems. To avoid these problems, a Bayesian covariance structure model (BCSM) for testlets is proposed, where standard IRT models are extended with a covariance structure model to account for dependences among testlet items. In the BCSM, the dependence among testlet items is modeled without using testlet effects. This approach does not imply any sample size restrictions and is very efficient in terms of the number of parameters needed to describe testlet dependences. The BCSM is compared to the well-known Bayesian random effects model for testlets using a simulation study. Specifically for testlets with a few items, a small number of test takers, or weak associations among testlet items, the BCSM shows more accurate estimation results than the random effects model.

scholarly journals A mechanistic modeling framework for gas-phase adsorption kinetics and fixed-bed transport

AIChE Journal ◽  
2017 ◽  
Vol 63 (11) ◽  
pp. 5029-5043 ◽  
Author(s):  
Austin P. Ladshaw ◽  
Sotira Yiacoumi ◽  
Ronghong Lin ◽  
Yue Nan ◽  
Lawrence L. Tavlarides ◽  
...  
Keyword(s):  
Gas Phase ◽  
Adsorption Kinetics ◽  
Fixed Bed ◽  
Mechanistic Modeling ◽  
Modeling Framework ◽  
Gas Phase Adsorption

scholarly journals A practical guide to mechanistic systems modeling in biology using a logic-based approach

2020 ◽  
Author(s):  
Anna Niarakis ◽  
Tomáš Helikar
Keyword(s):  
Computational Modeling ◽  
Computational Models ◽  
Regulatory System ◽  
Mechanistic Modeling ◽  
Lac Operon ◽  
Modeling Framework ◽  
Validation Criteria ◽  
Hands On ◽  
Modeling Software ◽  
Logical Modeling

Abstract Mechanistic computational models enable the study of regulatory mechanisms implicated in various biological processes. These models provide a means to analyze the dynamics of the systems they describe, and to study and interrogate their properties, and provide insights about the emerging behavior of the system in the presence of single or combined perturbations. Aimed at those who are new to computational modeling, we present here a practical hands-on protocol breaking down the process of mechanistic modeling of biological systems in a succession of precise steps. The protocol provides a framework that includes defining the model scope, choosing validation criteria, selecting the appropriate modeling approach, constructing a model and simulating the model. To ensure broad accessibility of the protocol, we use a logical modeling framework, which presents a lower mathematical barrier of entry, and two easy-to-use and popular modeling software tools: Cell Collective and GINsim. The complete modeling workflow is applied to a well-studied and familiar biological process—the lac operon regulatory system. The protocol can be completed by users with little to no prior computational modeling experience approximately within 3 h.

scholarly journals Using the Mutation-Selection Framework to Characterize Selection on Protein Sequences

Genes ◽  
2018 ◽  
Vol 9 (8) ◽  
pp. 409 ◽  
Author(s):  
Ashley Teufel ◽  
Andrew Ritchie ◽  
Claus Wilke ◽  
David Liberles
Keyword(s):  
Protein Sequences ◽  
Original Model ◽  
Mechanistic Modeling ◽  
Mathematical Framework ◽  
Conditional Probabilities ◽  
Modeling Framework ◽  
Mutational Pressure ◽  
Generative Process ◽  
Different Types ◽  
Selection Framework

When mutational pressure is weak, the generative process of protein evolution involves explicit probabilities of mutations of different types coupled to their conditional probabilities of fixation dependent on selection. Establishing this mechanistic modeling framework for the detection of selection has been a goal in the field of molecular evolution. Building on a mathematical framework proposed more than a decade ago, numerous methods have been introduced in an attempt to detect and measure selection on protein sequences. In this review, we discuss the structure of the original model, subsequent advances, and the series of assumptions that these models operate under.

scholarly journals SDE based Unified Scheme for Developing Entropy Prediction Models for OSS

2020 ◽  
Vol 6 (1) ◽  
pp. 207-222
Author(s):  
Deepika Deepika ◽  
Ompal Singh ◽  
Adarsh Anand ◽  
Jagvinder Singh
Keyword(s):  
Prediction Models ◽  
Removal Rate ◽  
Three Dimensional ◽  
Real Life ◽  
Accurate Estimation ◽  
Modeling Framework ◽  
Software Complex ◽  
Wiener Processes ◽  
Code Changes ◽  
Experimental Findings

Today, so as to meet the user's requirement, modification of software is necessarily required. But at the same time, to incorporate these modifications and requirements there are enormous changes which are made to the coding of the software and over a period of time these changes make the software complex. Largely there are three types of code changes occur in the source code namely, bug repair, feature enhancement & addition of new features, but these changes bring the uncertainty in the bug removal rate. In this paper, these uncertainties have been explicitly modeled and using three-dimensional wiener processes that define the three types of fluctuation; we have come up with an entropy prediction modeling framework with a unified approach. The analytical solution of the equation is interpreted using Itô’s process. The models are fitted on three real life projects namely Avro, Hive and Pig of Apache open source software (OSS) The experimental findings show that present models exhibit accurate estimation results and have strong prediction skills.

scholarly journals Development and Evaluation of a Holistic and Mechanistic Modeling Framework for Chemical Emissions, Fate, Exposure, and Risk

2021 ◽  
Vol 129 (12) ◽  
Author(s):  
Li Li ◽  
Alessandro Sangion ◽  
Frank Wania ◽  
James M. Armitage ◽  
Liisa Toose ◽  
...  
Keyword(s):  
Mechanistic Modeling ◽  
Modeling Framework

scholarly journals Mechanistic Multilayer Quantitative Model for Nonlinear Pharmacokinetics, Target Occupancy and Pharmacodynamics (PK/TO/PD) Relationship of D-Amino Acid Oxidase Inhibitor, TAK-831 in Mice

2020 ◽  
Vol 37 (8) ◽  
Author(s):  
Tomoki Yoneyama ◽  
Sho Sato ◽  
Andy Sykes ◽  
Rosa Fradley ◽  
Stuart Stafford ◽  
...  
Keyword(s):  
Amino Acid ◽  
Dose Range ◽  
Quantitative Model ◽  
Clinical Development ◽  
Mechanistic Modeling ◽  
Binding Kinetics ◽  
Acid Oxidase ◽  
Brain Distribution ◽  
Modeling Framework ◽  
Amino Acid Oxidase

Abstract Purpose TAK-831 is a highly selective and potent inhibitor of D-amino acid oxidase (DAAO) currently under clinical development for schizophrenia. In this study, a mechanistic multilayer quantitative model that parsimoniously connects pharmacokinetics (PK), target occupancy (TO) and D-serine concentrations as a pharmacodynamic (PD) readout was established in mice. Methods PK, TO and PD time-profiles were obtained in mice and analyzed by mechanistic binding kinetics model connected with an indirect response model in a step wise fashion. Brain distribution was investigated to elucidate a possible mechanism driving the hysteresis between PK and TO. Results The observed nonlinear PK/TO/PD relationship was well captured by mechanistic modeling framework within a wide dose range of TAK-831 in mice. Remarkably different brain distribution was observed between target and reference regions, suggesting that the target-mediated slow binding kinetics rather than slow penetration through the blood brain barrier caused the observed distinct kinetics between PK and TO. Conclusion A quantitative mechanistic model for concentration- and time-dependent nonlinear PK/TO/PD relationship was established for TAK-831 in mice with accounting for possible rate-determining process. The established mechanistic modeling framework will provide a quantitative means for multilayer biomarker-assisted clinical development in multiple central nervous system indications.

scholarly journals Effects of fibrosis on the extracellular potential based on 3D reconstructions from histological sections of heart tissue

2016 ◽  
Vol 2 (1) ◽  
pp. 675-678 ◽  
Author(s):  
Markus Rottmann ◽  
Jannik Zürn ◽  
Ufuk Arslan ◽  
Karin Klingel ◽  
Olaf Dössel
Keyword(s):  
Atrial Fibrillation ◽  
Sinus Rhythm ◽  
Heart Tissue ◽  
Extracellular Potential ◽  
Central Question ◽  
3D Reconstructions ◽  
Excitation Wave ◽  
Tissue Sections ◽  
Clinical Systems ◽  
Extracellular Potentials

AbstractAtrial fibrillation is the most common arrhythmia. However, the mechanisms of AF are not completely understood. It is known that fractionated signals are measured in AF but the etiology of fractionated signals is still not clear. The central question is to evaluate the effects of segmented fibrotic areas in histological tissue sections on the extracellular potential in a simulation study. We calculated the transmembrane voltages and extracellular potentials from the excitation wave front around a 3D fibrotic area from mouse hearts that were reconstructed from histological tissue sections. Extracellular potentials resulted in fragmented signals and differed strongly by stimulations from different directions. The transmural angle of the excitation waves had a significantly influence on the signal morphologies. We suggest for future clinical systems to implement the possibility for substrate mapping by stimulations from different directions in sinus rhythm.

scholarly journals Dextran as a Resorbable Coating Material for Flexible Neural Probes

Micromachines ◽  
2019 ◽  
Vol 10 (1) ◽  
pp. 61 ◽  
Author(s):  
Dries Kil ◽  
Marta Bovet Carmona ◽  
Frederik Ceyssens ◽  
Marjolijn Deprez ◽  
Luigi Brancato ◽  
...  
Keyword(s):  
Immunological Response ◽  
Scar Tissue ◽  
Coating Material ◽  
Dissolution Time ◽  
Electrode Arrays ◽  
Neural Probes ◽  
Neuron Density ◽  
Flexible Polymer ◽  
In Vivo Testing

In the quest for chronically reliable and bio-tolerable brain interfaces there has been a steady evolution towards the use of highly flexible, polymer-based electrode arrays. The reduced mechanical mismatch between implant and brain tissue has shown to reduce the evoked immune response, which in turn has a positive effect on signal stability and noise. Unfortunately, the low stiffness of the implants also has practical repercussions, making surgical insertion extremely difficult. In this work we explore the use of dextran as a coating material that temporarily stiffens the implant, preventing buckling during insertion. The mechanical properties of dextran coated neural probes are characterized, as well as the different parameters which influence the dissolution rate. Tuning parameters, such as coating thickness and molecular weight of the used dextran, allows customization of the stiffness and dissolution time to precisely match the user’s needs. Finally, the immunological response to the coated electrodes was analyzed by performing a histological examination after four months of in vivo testing. The results indicated that a very limited amount of glial scar tissue was formed. Neurons have also infiltrated the area that was initially occupied by the dissolving dextran coating. There was no noticeable drop in neuron density around the site of implantation, confirming the suitability of the coating as a temporary aid during implantation of highly flexible polymer-based neural probes.

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