AACIMP 2010 Summer School lecture by Anton Chizhov. "Physics, Chemistry and Living Systems" stream. "Neuron-Computer Interface in Dynamic-Clamp Experiments. Models of Neuronal Populations and Visual Cortex" course. Part 2.
More info at http://summerschool.ssa.org.ua
AACIMP 2010 Summer School lecture by Anton Chizhov. "Physics, Chemistry and Living Systems" stream. "Neuron-Computer Interface in Dynamic-Clamp Experiments. Models of Neuronal Populations and Visual Cortex" course. Part 3.
More info at http://summerschool.ssa.org.ua
There is nowadays a growing need for sensing devices offering rapid and portable analytical functionality in real-time as well as massively parallel capabilities with very high sensitivity at the molecular level. Such devices are essential to facilitate research and foster advances in fields such as drug discovery, proteomics, medical diagnostics, systems biology or environmental monitoring.
In this context, an ideal solution is an ion-sensitive field-effect transistor sensor platform based on silicon nanowires to be integrated in a CMOS architecture. Indeed, in addition to the expected high sensitivity and superior signal quality, such nanowire sensors could be mass manufactured at reasonable costs, and readily integrated into electronic diagnostic devices to facilitate bed-site diagnostics and personalized medicine. Moreover, their small size makes them ideal candidates for future implanted sensing devices. While promising biosensing experiments based on silicon nanowire field-effect transistors have been reported, real-life applications still require improved control, together with a detailed understanding of the basic sensing mechanisms. For instance, it is crucial to optimize the geometry of the wire, a still rather unexplored aspect up to now, as well as its surface functionalization or its selectivity to the targeted analytes.
This project seeks to develop a modular, scalable and integrateable sensor platform for the electronic detection of analytes in solution. The idea is to integrate silicon nanowire field-effect transistors as a sensor array and combine them with state-of-the-art microfabricated interface electronics as well as with microfluidic channels for liquid handling. Such sensors have the potential to be mass manufactured at reasonable costs, allowing their integration as the active sensor part in electronic point-of-care diagnostic devices to facilitate, for instance, bed-side diagnostics and personalized medicine. Another important field is systems biology, where many substances need to be quantitatively detected in parallel at very low concentrations: in these situations, the platform being developed fulfills the requirements ideally and will have a strong impact and provide new insights, e.g. into the metabolic processes of cells, organisms or organs.
Expert Design & Empirical Test Strategies for Practical Transformer DevelopmentRAF Tabtronics LLC
Expert Design & Empirical Test Strategies for Practical Transformer Development presented by Mr. Victor QUINN of RAF Tabtronics LLC at the 2012 Applied Power Electronics Conference (APEC).
Automatic Processing of Emotionally Salient Imageshschwimmer
This study investigated whether the effect of emotional valence on the P300 event-related potential is automatic or attentional. Researchers recorded EEG data from participants performing a perceptual task with frequent neutral images and infrequent positive, negative, or neutral images. Results showed no main effect of emotional valence on P300 amplitude. However, there was an interaction between valence and electrode laterality—positive images produced larger P300s in the left hemisphere, while negative images produced larger P300s in the right hemisphere. This suggests emotional valence is processed automatically rather than through attention allocation.
The document discusses a workshop on smart sensor systems held by Delft Institute of Microelectronics. It provides an overview of various lectures on topics related to silicon sensors and smart sensor design, including applications, measurement techniques, calibration, sensor types, interfaces and more. The goal is to discuss specifications, design and development of smart silicon sensor systems.
TeraHertz three-dimensional plasma resonances in InGaAs diodes: a hydrodynami...Christophe Palermo
This document studies terahertz plasma resonances in InGaAs diodes using numerical hydrodynamic modeling. It finds that doped regions exhibit resonances at the expected 3D plasma frequency, while intermediate regions show coupled modes with frequencies between the doped and intermediate regions. Increasing the doping ratio or doping concentration strengthens the coupling. Geometry also influences coupling, with longer intermediate regions weakening it. The work aims to understand these effects to enable tuning device resonances for terahertz applications.
This document discusses calibration of the SMOS (Soil Moisture and Ocean Salinity) Earth Explorer mission. SMOS uses an interferometric radiometer called MIRAS to measure brightness temperatures. MIRAS requires comprehensive calibration to correct for measurement errors. The calibration scheme involves internal noise injection, external sky views by a reference radiometer, and ground characterization. The goal is to parameterize errors, measure coefficients, extract errors through calibration, and assess residuals to iteratively refine the error model.
Graded Patterns in Attractor Networks explores how noise can exist in large neural networks like the brain. The study introduces graded firing patterns, where neuron firing rates vary across populations, rather than being uniform. Simulations found graded patterns decreased reaction times and increased variability compared to uniform patterns. This suggests graded firing represents increased noise but may play a functional role in neural processing like memory retrieval.
AACIMP 2010 Summer School lecture by Anton Chizhov. "Physics, Chemistry and Living Systems" stream. "Neuron-Computer Interface in Dynamic-Clamp Experiments. Models of Neuronal Populations and Visual Cortex" course. Part 3.
More info at http://summerschool.ssa.org.ua
There is nowadays a growing need for sensing devices offering rapid and portable analytical functionality in real-time as well as massively parallel capabilities with very high sensitivity at the molecular level. Such devices are essential to facilitate research and foster advances in fields such as drug discovery, proteomics, medical diagnostics, systems biology or environmental monitoring.
In this context, an ideal solution is an ion-sensitive field-effect transistor sensor platform based on silicon nanowires to be integrated in a CMOS architecture. Indeed, in addition to the expected high sensitivity and superior signal quality, such nanowire sensors could be mass manufactured at reasonable costs, and readily integrated into electronic diagnostic devices to facilitate bed-site diagnostics and personalized medicine. Moreover, their small size makes them ideal candidates for future implanted sensing devices. While promising biosensing experiments based on silicon nanowire field-effect transistors have been reported, real-life applications still require improved control, together with a detailed understanding of the basic sensing mechanisms. For instance, it is crucial to optimize the geometry of the wire, a still rather unexplored aspect up to now, as well as its surface functionalization or its selectivity to the targeted analytes.
This project seeks to develop a modular, scalable and integrateable sensor platform for the electronic detection of analytes in solution. The idea is to integrate silicon nanowire field-effect transistors as a sensor array and combine them with state-of-the-art microfabricated interface electronics as well as with microfluidic channels for liquid handling. Such sensors have the potential to be mass manufactured at reasonable costs, allowing their integration as the active sensor part in electronic point-of-care diagnostic devices to facilitate, for instance, bed-side diagnostics and personalized medicine. Another important field is systems biology, where many substances need to be quantitatively detected in parallel at very low concentrations: in these situations, the platform being developed fulfills the requirements ideally and will have a strong impact and provide new insights, e.g. into the metabolic processes of cells, organisms or organs.
Expert Design & Empirical Test Strategies for Practical Transformer DevelopmentRAF Tabtronics LLC
Expert Design & Empirical Test Strategies for Practical Transformer Development presented by Mr. Victor QUINN of RAF Tabtronics LLC at the 2012 Applied Power Electronics Conference (APEC).
Automatic Processing of Emotionally Salient Imageshschwimmer
This study investigated whether the effect of emotional valence on the P300 event-related potential is automatic or attentional. Researchers recorded EEG data from participants performing a perceptual task with frequent neutral images and infrequent positive, negative, or neutral images. Results showed no main effect of emotional valence on P300 amplitude. However, there was an interaction between valence and electrode laterality—positive images produced larger P300s in the left hemisphere, while negative images produced larger P300s in the right hemisphere. This suggests emotional valence is processed automatically rather than through attention allocation.
The document discusses a workshop on smart sensor systems held by Delft Institute of Microelectronics. It provides an overview of various lectures on topics related to silicon sensors and smart sensor design, including applications, measurement techniques, calibration, sensor types, interfaces and more. The goal is to discuss specifications, design and development of smart silicon sensor systems.
TeraHertz three-dimensional plasma resonances in InGaAs diodes: a hydrodynami...Christophe Palermo
This document studies terahertz plasma resonances in InGaAs diodes using numerical hydrodynamic modeling. It finds that doped regions exhibit resonances at the expected 3D plasma frequency, while intermediate regions show coupled modes with frequencies between the doped and intermediate regions. Increasing the doping ratio or doping concentration strengthens the coupling. Geometry also influences coupling, with longer intermediate regions weakening it. The work aims to understand these effects to enable tuning device resonances for terahertz applications.
This document discusses calibration of the SMOS (Soil Moisture and Ocean Salinity) Earth Explorer mission. SMOS uses an interferometric radiometer called MIRAS to measure brightness temperatures. MIRAS requires comprehensive calibration to correct for measurement errors. The calibration scheme involves internal noise injection, external sky views by a reference radiometer, and ground characterization. The goal is to parameterize errors, measure coefficients, extract errors through calibration, and assess residuals to iteratively refine the error model.
Graded Patterns in Attractor Networks explores how noise can exist in large neural networks like the brain. The study introduces graded firing patterns, where neuron firing rates vary across populations, rather than being uniform. Simulations found graded patterns decreased reaction times and increased variability compared to uniform patterns. This suggests graded firing represents increased noise but may play a functional role in neural processing like memory retrieval.
1. Population models describe the activity of groups of similar neurons receiving common input. They include firing-rate models and the probability density approach.
2. The refractory density approach models populations using a hazard function that describes the probability of individual neurons firing. It can accurately model both stationary and non-stationary activity.
3. Conductance-based refractory density and firing-rate models can simulate the responses of coupled neuronal populations to different input patterns and reproduce experimental observations of population-level activity.
The document appears to be a website URL for www.gazzetta.gr. As there is no other contextual information provided, a 3 sentence summary cannot be generated that captures the high level or essential information from just a website URL on its own.
Dream it tonight achieve it tomorrow - presentationdmjohn100
The document discusses the importance of accountants for business success and outlines the services of a particular accounting firm. It notes that 80% of businesses fail within 5 years due to poor financial advice, capitalization, and planning. Most business owners rely on their accountant for advice. The accounting firm offers a range of services including financial statements, tax preparation, consulting, and packages starting at $85 per month.
Algebra of equivalent instances and its applicationsSSA KPI
AACIMP 2010 Summer School lecture by Dmitry Krushinsky. "Applied Mathematics" stream. "The p-Median Problem and Its Applications" course. Part 3.
More info at http://summerschool.ssa.org.ua
Need To Get Your Mojo Back? Keeping You and Your Team Motivated!Multifamily Insiders
You started off the year with a bang, now your sizzle has turned into a bit of a fizzle! Find yourself In need of a Mojo adjustment? This presentation is for you! We all need our Mojo to keep us motivated and growing in both our professional and personal lives!
Heart of healing korea hma 2010-ardy roberto - upload for delegatesArdy Roberto
The document discusses the importance of hope and optimism in healing. It notes that a leader's attitude can impact health outcomes through the placebo and nocebo effects. The story of a man named Nick illustrates how negative expectations from a perceived threat of freezing to death actually caused his body to freeze due to the nocebo effect of his thoughts.
Physical wellness means making your whole body healthy by doing good things for your body like getting plenty of exercise, eating healthy foods, getting a good night's rest, and visiting the dentist regularly. If you take care of your body with these healthy habits, your body will take care of you in return.
Back to School Webinar: A Crash Course In Digital Marketing Opportunities You...Michael Zarcone
Capitalize on Back-to-School spending this year by leveraging PointRoll's research into consumer buying behavior. Join PointRoll and ShopLocal during this free, interactive webinar to learn about:
• Untapped opportunities to reach interested and engaged customers
• Correlations between advertising and activity on marketers' sites
• Valuable insights into consumer behavior and consumer profiles
While many marketers' 2010 back-to-school marketing plans are already underway, these findings can be put into play with existing campaigns for incremental gains.
Join Jamie Ray, VP of Retail for PointRoll/ShopLocal, and Adam Harris, Manager of Business Development and Analytics at PointRoll, for this deep dive into consumer behavior during back-to-school season.
This document outlines key concepts in e-marketing, including important metrics and performance pricing models. It discusses Google Analytics presentations on metrics and cookies. Case studies on using Google Analytics are recommended. Students are instructed to create their own website using tools like Google Sites or Weebly to start e-marketing. The next session will discuss assigned case studies on metrics, knowing customers, e-marketing strategies, and include a quiz.
This CV summarizes Timothy Knell's experience in IT project coordination and technical support roles over the past 15 years. It lists his key achievements in project management, technical direction, and communication. It then details his professional history working on projects such as operating systems upgrades, network installations, audits, and display home technology setup. The CV provides 3 pages of descriptions of Timothy's roles, responsibilities, and outcomes across various employers in both private and public sectors.
How good are interior point methods? Klee–Minty cubes tighten iteration-compl...SSA KPI
This document summarizes a paper that examines the performance of interior point methods for solving linear optimization problems. It presents a refined version of the Klee-Minty cubes problem that forces the central path of interior point methods to visit all 2n vertices of an n-dimensional cube.
The key results are:
1) For this problem, the central path must make at least 2n-2 turns before converging to the optimal solution, providing a lower bound on the iteration complexity of interior point methods.
2) The upper bound on iteration complexity for this problem is O(2n*n5/2), nearly matching the lower bound and showing interior point methods can perform close to worst-case on this
Tiga kalimat ringkasan dokumen tersebut adalah:
1. Dokumen tersebut membahas tentang konsep-konsep dasar yang berkaitan dengan pengetahuan diri dan presentasi diri seperti self presentation, self knowledge, identitas, self esteem, dan social comparison.
2. Konsep-konsep tersebut dijelaskan dalam rangka menjawab pertanyaan mengenai bagaimana kita dapat mengetahui siapa diri kita sebenarnya dan bagaimana perilaku kita dapat berbeda di
This short document promotes creating presentations using Haiku Deck, a tool for making slideshows. It encourages the reader to get started making their own Haiku Deck presentation and sharing it on SlideShare. In just one sentence, it pitches the idea of using Haiku Deck to easily create engaging slideshows.
Neuron-Computer Interface in Dynamic-Clamp Experiments. Models of Neuronal P...SSA KPI
The document discusses several applications of neuron-computer interfaces using dynamic-clamp experiments. It summarizes models of single neurons and neuronal populations used in such experiments. It also describes how dynamic clamp can be used to inject artificial synaptic or intrinsic currents to study neuronal properties, estimate synaptic conductances in vivo, and interface real and modeled neurons.
Benchmark Calculations of Atomic Data for Modelling ApplicationsAstroAtom
This document summarizes benchmark calculations of atomic data for modeling applications. It discusses numerical methods like close-coupling and distorted-wave approaches for calculating atomic collision data. It provides selected results on energy levels, oscillator strengths, and electron-impact excitation cross sections. It also discusses applications to modeling neon discharges and takes a closer look at ionization calculations and examples. The document concludes by discussing the production and assessment of atomic data and outlines challenges in obtaining reliable data from both experiments and calculations.
Neuron-computer interface in Dynamic-Clamp experimentsSSA KPI
AACIMP 2010 Summer School lecture by Anton Chizhov. "Physics, Chemistry and Living Systems" stream. "Neuron-Computer Interface in Dynamic-Clamp Experiments. Models of Neuronal Populations and Visual Cortex" course. Part 1.
More info at http://summerschool.ssa.org.ua
The document discusses detecting dark matter through its annihilation signals across the electromagnetic spectrum. It describes how neutralinos and sterile neutrinos could produce gamma rays, x-rays, and radio emission through various processes. Specific targets are mentioned, including the Galactic center, dwarf galaxies, and galaxy clusters. Future instruments like CTA, SKA, and NuSTAR may help constrain dark matter properties or detect its signals.
Coercivity weighted Langevin magnetisation: A new approach to interpret super...Dhanesh Rajan
This document summarizes a new approach called "coercivity weighted Langevin magnetization" that more accurately models the superparamagnetic and nonsuperparamagnetic behavior of single domain magnetic nanoparticles. It presents results showing how coercivity and remanence in the single domain regime can be predicted as functions of particle size, temperature, and measurement frequency. The new model combines steady and time-varying magnetization dynamics and considers factors affecting the superparamagnetic state. It defines the transition between superparamagnetic and nonsuperparamagnetic states more precisely and allows direct calculation of coercivity-weighted magnetization and susceptibility.
1. Population models describe the activity of groups of similar neurons receiving common input. They include firing-rate models and the probability density approach.
2. The refractory density approach models populations using a hazard function that describes the probability of individual neurons firing. It can accurately model both stationary and non-stationary activity.
3. Conductance-based refractory density and firing-rate models can simulate the responses of coupled neuronal populations to different input patterns and reproduce experimental observations of population-level activity.
The document appears to be a website URL for www.gazzetta.gr. As there is no other contextual information provided, a 3 sentence summary cannot be generated that captures the high level or essential information from just a website URL on its own.
Dream it tonight achieve it tomorrow - presentationdmjohn100
The document discusses the importance of accountants for business success and outlines the services of a particular accounting firm. It notes that 80% of businesses fail within 5 years due to poor financial advice, capitalization, and planning. Most business owners rely on their accountant for advice. The accounting firm offers a range of services including financial statements, tax preparation, consulting, and packages starting at $85 per month.
Algebra of equivalent instances and its applicationsSSA KPI
AACIMP 2010 Summer School lecture by Dmitry Krushinsky. "Applied Mathematics" stream. "The p-Median Problem and Its Applications" course. Part 3.
More info at http://summerschool.ssa.org.ua
Need To Get Your Mojo Back? Keeping You and Your Team Motivated!Multifamily Insiders
You started off the year with a bang, now your sizzle has turned into a bit of a fizzle! Find yourself In need of a Mojo adjustment? This presentation is for you! We all need our Mojo to keep us motivated and growing in both our professional and personal lives!
Heart of healing korea hma 2010-ardy roberto - upload for delegatesArdy Roberto
The document discusses the importance of hope and optimism in healing. It notes that a leader's attitude can impact health outcomes through the placebo and nocebo effects. The story of a man named Nick illustrates how negative expectations from a perceived threat of freezing to death actually caused his body to freeze due to the nocebo effect of his thoughts.
Physical wellness means making your whole body healthy by doing good things for your body like getting plenty of exercise, eating healthy foods, getting a good night's rest, and visiting the dentist regularly. If you take care of your body with these healthy habits, your body will take care of you in return.
Back to School Webinar: A Crash Course In Digital Marketing Opportunities You...Michael Zarcone
Capitalize on Back-to-School spending this year by leveraging PointRoll's research into consumer buying behavior. Join PointRoll and ShopLocal during this free, interactive webinar to learn about:
• Untapped opportunities to reach interested and engaged customers
• Correlations between advertising and activity on marketers' sites
• Valuable insights into consumer behavior and consumer profiles
While many marketers' 2010 back-to-school marketing plans are already underway, these findings can be put into play with existing campaigns for incremental gains.
Join Jamie Ray, VP of Retail for PointRoll/ShopLocal, and Adam Harris, Manager of Business Development and Analytics at PointRoll, for this deep dive into consumer behavior during back-to-school season.
This document outlines key concepts in e-marketing, including important metrics and performance pricing models. It discusses Google Analytics presentations on metrics and cookies. Case studies on using Google Analytics are recommended. Students are instructed to create their own website using tools like Google Sites or Weebly to start e-marketing. The next session will discuss assigned case studies on metrics, knowing customers, e-marketing strategies, and include a quiz.
This CV summarizes Timothy Knell's experience in IT project coordination and technical support roles over the past 15 years. It lists his key achievements in project management, technical direction, and communication. It then details his professional history working on projects such as operating systems upgrades, network installations, audits, and display home technology setup. The CV provides 3 pages of descriptions of Timothy's roles, responsibilities, and outcomes across various employers in both private and public sectors.
How good are interior point methods? Klee–Minty cubes tighten iteration-compl...SSA KPI
This document summarizes a paper that examines the performance of interior point methods for solving linear optimization problems. It presents a refined version of the Klee-Minty cubes problem that forces the central path of interior point methods to visit all 2n vertices of an n-dimensional cube.
The key results are:
1) For this problem, the central path must make at least 2n-2 turns before converging to the optimal solution, providing a lower bound on the iteration complexity of interior point methods.
2) The upper bound on iteration complexity for this problem is O(2n*n5/2), nearly matching the lower bound and showing interior point methods can perform close to worst-case on this
Tiga kalimat ringkasan dokumen tersebut adalah:
1. Dokumen tersebut membahas tentang konsep-konsep dasar yang berkaitan dengan pengetahuan diri dan presentasi diri seperti self presentation, self knowledge, identitas, self esteem, dan social comparison.
2. Konsep-konsep tersebut dijelaskan dalam rangka menjawab pertanyaan mengenai bagaimana kita dapat mengetahui siapa diri kita sebenarnya dan bagaimana perilaku kita dapat berbeda di
This short document promotes creating presentations using Haiku Deck, a tool for making slideshows. It encourages the reader to get started making their own Haiku Deck presentation and sharing it on SlideShare. In just one sentence, it pitches the idea of using Haiku Deck to easily create engaging slideshows.
Neuron-Computer Interface in Dynamic-Clamp Experiments. Models of Neuronal P...SSA KPI
The document discusses several applications of neuron-computer interfaces using dynamic-clamp experiments. It summarizes models of single neurons and neuronal populations used in such experiments. It also describes how dynamic clamp can be used to inject artificial synaptic or intrinsic currents to study neuronal properties, estimate synaptic conductances in vivo, and interface real and modeled neurons.
Benchmark Calculations of Atomic Data for Modelling ApplicationsAstroAtom
This document summarizes benchmark calculations of atomic data for modeling applications. It discusses numerical methods like close-coupling and distorted-wave approaches for calculating atomic collision data. It provides selected results on energy levels, oscillator strengths, and electron-impact excitation cross sections. It also discusses applications to modeling neon discharges and takes a closer look at ionization calculations and examples. The document concludes by discussing the production and assessment of atomic data and outlines challenges in obtaining reliable data from both experiments and calculations.
Neuron-computer interface in Dynamic-Clamp experimentsSSA KPI
AACIMP 2010 Summer School lecture by Anton Chizhov. "Physics, Chemistry and Living Systems" stream. "Neuron-Computer Interface in Dynamic-Clamp Experiments. Models of Neuronal Populations and Visual Cortex" course. Part 1.
More info at http://summerschool.ssa.org.ua
The document discusses detecting dark matter through its annihilation signals across the electromagnetic spectrum. It describes how neutralinos and sterile neutrinos could produce gamma rays, x-rays, and radio emission through various processes. Specific targets are mentioned, including the Galactic center, dwarf galaxies, and galaxy clusters. Future instruments like CTA, SKA, and NuSTAR may help constrain dark matter properties or detect its signals.
Coercivity weighted Langevin magnetisation: A new approach to interpret super...Dhanesh Rajan
This document summarizes a new approach called "coercivity weighted Langevin magnetization" that more accurately models the superparamagnetic and nonsuperparamagnetic behavior of single domain magnetic nanoparticles. It presents results showing how coercivity and remanence in the single domain regime can be predicted as functions of particle size, temperature, and measurement frequency. The new model combines steady and time-varying magnetization dynamics and considers factors affecting the superparamagnetic state. It defines the transition between superparamagnetic and nonsuperparamagnetic states more precisely and allows direct calculation of coercivity-weighted magnetization and susceptibility.
Hodgkin-Huxley & the nonlinear dynamics of neuronal excitabilitySSA KPI
The document discusses the Hodgkin-Huxley model of neuronal excitability and its analysis using nonlinear dynamics and phase plane methods. It describes how the Hodgkin-Huxley model dissects the action potential into fast and slow processes. It also discusses models of repetitive and phasic firing, including the Morris-Lecar model, and references software tools for neuronal modeling and simulation.
This lecture discusses synaptic learning rules in neural networks. It introduces the basic anatomy and physiology of synapses and different coding schemes neurons use, such as rate coding and spike timing coding. It then covers several synaptic plasticity rules, including Hebbian learning, spike-timing dependent plasticity (STDP), and the Bienenstock-Cooper-Munro (BCM) rule. It also discusses modeling synapses using the conductance-based model and implementations of STDP learning through online learning rules and weight dependence mechanisms.
There is nowadays a growing need for sensing devices offering rapid and portable analytical functionality in real-time as well as massively parallel capabilities with very high sensitivity at the molecular level. Such devices are essential to facilitate research and foster advances in fields such as drug discovery, proteomics, medical diagnostics, systems biology or environmental monitoring.
In this context, an ideal solution is an ion-sensitive field-effect transistor sensor platform based on silicon nanowires to be integrated in a CMOS architecture. Indeed, in addition to the expected high sensitivity and superior signal quality, such nanowire sensors could be mass manufactured at reasonable costs, and readily integrated into electronic diagnostic devices to facilitate bed-site diagnostics and personalized medicine. Moreover, their small size makes them ideal candidates for future implanted sensing devices. While promising biosensing experiments based on silicon nanowire field-effect transistors have been reported, real-life applications still require improved control, together with a detailed understanding of the basic sensing mechanisms. For instance, it is crucial to optimize the geometry of the wire, a still rather unexplored aspect up to now, as well as its surface functionalization or its selectivity to the targeted analytes.
This project seeks to develop a modular, scalable and integrateable sensor platform for the electronic detection of analytes in solution. The idea is to integrate silicon nanowire field-effect transistors as a sensor array and combine them with state-of-the-art microfabricated interface electronics as well as with microfluidic channels for liquid handling. Such sensors have the potential to be mass manufactured at reasonable costs, allowing their integration as the active sensor part in electronic point-of-care diagnostic devices to facilitate, for instance, bed-side diagnostics and personalized medicine. Another important field is systems biology, where many substances need to be quantitatively detected in parallel at very low concentrations: in these situations, the platform being developed fulfills the requirements ideally and will have a strong impact and provide new insights, e.g. into the metabolic processes of cells, organisms or organs.
Normal Modes Analysis can be used to estimate full 2D velocity vectors from radial CODAR measurements in tidal channels. It models flow as a series of eigenfunctions satisfying the boundary conditions. By fitting the radial radar data to the Normal Modes solutions, coefficients for each mode can be determined via least squares. This allows reconstruction of the full velocity field and visualization of particle trajectories over time, providing insight into tidal flow dynamics. Future work aims to validate the method against direct measurements during flow reversals and determine the optimal number of modes.
Introduction to Modern Methods and Tools for Biologically Plausible Modelling...SSA KPI
This document provides an overview of modern methods and tools for biologically plausible modeling of neural structures in the brain. It discusses modeling at different levels, from the system level looking at the brain as a whole, down to the subcellular and molecular levels examining individual neurons and ion channels. At each level, it outlines key research methods used to study the brain experimentally and different modeling approaches, including population and dynamical models, formal neural networks, and detailed single-cell models. The document also reviews seminal work in neuroscience like Hodgkin and Huxley's equations for modeling ion channel dynamics and spike generation in neurons.
Tutorial in calculation of IR & NMR spectra (i.e. measuring nuclear vibrations and spins) using the GAUSSIAN03 computational chemistry package.
Following an introduction to spectroscopy in general, each of the two measurement types is presented in sequence. For each one, we review the theory before presenting the calculation scheme. We then present the relative strengths and limitations (with respect to other measurements), and then compare the calculation method with experimentation. We close each of the two subjects with an advanced topic: Raman IR spectroscopy (and depolarization ratio), and indirect dipole coupling (a.k.a. spin-spin coupling). I've also made the last part available as a standalone presentation: http://www.slideshare.net/InonSharony/nmr-spinspin-splitting-using-gaussian03.
The document provides an introduction and overview of the Power Electronics 2 module. It discusses typical AC/DC/AC power conversion systems using line-side and motor-side converters. The module aims to provide knowledge of power electronics technologies including three-phase rectification, resonant converters, inverters, and high power converter structures. It outlines the lecture topics, recommendations, and reviews three-phase voltage supplies.
Rotating Wave Approximation (RWA) breaks down for few-cycle pulses. Using Gaussian pulses, quantum logic gates like NOT and Hadamard can be implemented, but their effectiveness decreases for pulses with a small frequency compared to the transition frequency between levels. Attosecond pulses cannot be used to study ultrafast phenomena in biology due to limitations of RWA - the required x-ray or gamma ray frequencies would damage living cells. The document examines how RWA breakdown affects population dynamics in a two-level system interacting with femtosecond and attosecond pulses.
The document discusses an approach to measuring the electric dipole moment (EDM) of the neutron. It aims to increase the statistical sensitivity to below 10-27 e·cm and systematic sensitivity to below 10-27 e·cm through several methods including increasing UCN density, using a buffer gas to suppress nuclear spin relaxation, using a spherical coil geometry, and implementing various shielding techniques. It also acknowledges collaborators from other institutions. The key ideas are to measure the neutron EDM through Ramsey's method of separated oscillatory fields in a static electric field, and to improve statistical and systematic uncertainties through technical upgrades and experimental design choices.
This document summarizes research on the open-circuit voltage (Voc) in organic solar cells. Key points include:
- Voc is defined as the voltage when the current is zero under illumination but non-zero under dark conditions.
- Polaron pair dissociation can generate free charge carriers even at zero electric field and Voc, contributing to power conversion efficiency.
- Bulk recombination of free charges follows Langevin dynamics and limits Voc at room temperature. Surface "recombination" is better described as the charge extraction rate at electrodes.
- Voc decreases with increasing temperature as the charge carrier concentration n(T) also decreases with temperature based on thermal generation and recombination processes.
Introduction to modern methods and tools for biologically plausible modeling ...SSA KPI
AACIMP 2010 Summer School lecture by Ruben Tikidji-Hamburyan. "Physics, Chemistry and Living Systems" stream. "Introduction to Modern Methods and Tools for Biologically Plausible Modeling of Neurons and Neural Networks" course. Part 1.
More info at http://summerschool.ssa.org.ua
1. The document describes experiments and models of visual cortex neurons and their responses to visual stimuli.
2. A 2-dimensional continuum model of visual cortex is presented, with excitatory and inhibitory neuron populations in different layers and types of synapses between them.
3. The model is able to simulate responses of neurons to changes in orientation of visual stimuli and capture effects of adaptation and stimulus contrast. Comparisons are made to experimental data.
Envelope coding in the cochlear nucleus: a data mining approachAlbanLevy
This document analyzes spike train data from the cochlear nucleus using data mining techniques to better understand envelope coding. It finds that modern machine learning methods can extract modulation frequency from spike patterns without strong assumptions. Classification accuracy varies by neuron type and is highest for onset units, consistent with their role in encoding periodicity. Optimal timescales are sub-millisecond, and different preprocessing methods like interspike interval features or spike timing yield similar results. The analysis characterizes neurons' modulation transfer functions and suggests they act as low-pass filters for envelope information.
The document summarizes key developments in nuclear magnetic resonance (NMR) spectroscopy from its theoretical prediction in the 1930s to modern applications. It describes Pauli's prediction of nuclear spin in 1926, the detection of nuclear magnetic moments in the 1930s-1940s, and the awarding of Nobel Prizes to scientists who developed NMR techniques. It then discusses chemical shifts, spin properties of different nuclei, interactions such as Zeeman and J-coupling that provide structural information, and experimental aspects like magic angle spinning.
This document provides an overview of various medical imaging modalities including their physics principles, capabilities, limitations and artifacts. It discusses x-rays/radiography, CT, and MRI. For each modality, it explains how images are generated, advantages, limitations including radiation dose for CT and need for patient cooperation/stillness for MRI. It emphasizes understanding limitations to avoid "wishful thinking" and making diagnoses from suboptimal studies.
This document discusses student organizations and the university system in Germany. It provides an overview of the different types of higher education institutions in Germany, including universities, universities of applied sciences, and arts universities. It describes the degree system including bachelor's, master's, and Ph.D. programs. It also outlines the systems of student participation at universities, using the examples of Leipzig and Hanover. Student councils, departments, and faculty student organizations are discussed.
The document discusses grand challenges in energy and perspectives on moving towards more sustainable systems. It notes that while global energy demand and CO2 emissions rebounded in 2010 after the economic downturn, urgent changes are still needed. It explores perspectives on changing direction, including overcoming barriers like technologies, economies, management, and mindsets. The document advocates a systems approach and backcasting from desirable futures to identify pathways for transitioning between states.
Engineering can play an important role in sustainable development by focusing on meeting human needs over wants and prioritizing projects that serve the most vulnerable populations. Engineers should consider how their work impacts sustainability, affordability, and accessibility. A socially sustainable product is manufactured sustainably and also improves people's lives. Engineers are not neutral and should strive to serve societal needs rather than just generate profits. They can help redefine commerce and an engineering culture focused on meeting needs sustainably through services rather than creating unnecessary products and infrastructure.
Consensus and interaction on a long term strategy for sustainable developmentSSA KPI
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Chapter wise All Notes of First year Basic Civil Engineering.pptxDenish Jangid
Chapter wise All Notes of First year Basic Civil Engineering
Syllabus
Chapter-1
Introduction to objective, scope and outcome the subject
Chapter 2
Introduction: Scope and Specialization of Civil Engineering, Role of civil Engineer in Society, Impact of infrastructural development on economy of country.
Chapter 3
Surveying: Object Principles & Types of Surveying; Site Plans, Plans & Maps; Scales & Unit of different Measurements.
Linear Measurements: Instruments used. Linear Measurement by Tape, Ranging out Survey Lines and overcoming Obstructions; Measurements on sloping ground; Tape corrections, conventional symbols. Angular Measurements: Instruments used; Introduction to Compass Surveying, Bearings and Longitude & Latitude of a Line, Introduction to total station.
Levelling: Instrument used Object of levelling, Methods of levelling in brief, and Contour maps.
Chapter 4
Buildings: Selection of site for Buildings, Layout of Building Plan, Types of buildings, Plinth area, carpet area, floor space index, Introduction to building byelaws, concept of sun light & ventilation. Components of Buildings & their functions, Basic concept of R.C.C., Introduction to types of foundation
Chapter 5
Transportation: Introduction to Transportation Engineering; Traffic and Road Safety: Types and Characteristics of Various Modes of Transportation; Various Road Traffic Signs, Causes of Accidents and Road Safety Measures.
Chapter 6
Environmental Engineering: Environmental Pollution, Environmental Acts and Regulations, Functional Concepts of Ecology, Basics of Species, Biodiversity, Ecosystem, Hydrological Cycle; Chemical Cycles: Carbon, Nitrogen & Phosphorus; Energy Flow in Ecosystems.
Water Pollution: Water Quality standards, Introduction to Treatment & Disposal of Waste Water. Reuse and Saving of Water, Rain Water Harvesting. Solid Waste Management: Classification of Solid Waste, Collection, Transportation and Disposal of Solid. Recycling of Solid Waste: Energy Recovery, Sanitary Landfill, On-Site Sanitation. Air & Noise Pollution: Primary and Secondary air pollutants, Harmful effects of Air Pollution, Control of Air Pollution. . Noise Pollution Harmful Effects of noise pollution, control of noise pollution, Global warming & Climate Change, Ozone depletion, Greenhouse effect
Text Books:
1. Palancharmy, Basic Civil Engineering, McGraw Hill publishers.
2. Satheesh Gopi, Basic Civil Engineering, Pearson Publishers.
3. Ketki Rangwala Dalal, Essentials of Civil Engineering, Charotar Publishing House.
4. BCP, Surveying volume 1
Chapter wise All Notes of First year Basic Civil Engineering.pptx
Models of neuronal populations
1. Models of neuronal populations
Anton V. Chizhov
Ioffe Physico-Technical Institute of RAS,
St.-Petersburg
Definitions:
Population is a great number of similar neurons
receiving similar input
Population activity (=population firing rate) is the
number of spikes per unit time per total number of
neurons
3. Overview
• Experimental evidences of population firing rate coding
• Conductance-based neuron model
• Probability Density Approach (PDA)
• Conductance-Based Refractory Density approach (CBRD)
- threshold neuron
- t*-parameterization
- Hazard-function for white noise
- Hazard-function for colored noise
• Simulations of coupled populations
• Firing-Rate model
• Hierarchy of visual cortex models
4. • What can be modeled on population level?
• Which details are important?
• What kinds of population models do exist?
• Which one to choose?
5. Commonly information
is coded by firing rate
[R.M.Bruno, B.Sakmann // Science 312:1622-1627, 2006]
Population PSTH of thalamic neurons’
responses to a 2-Hz sinusoidal deflection of their
[E.Aksay, R.Baker, H.S.Seung, D.W.Tank
Activity of a
J.Neurophysiol. 84:1035-1049, 2000]
respective principal whiskers (n = 40 cells).
position neuron during spontaneous
saccades and fixations in the dark. A:
horizontal eye position (top 2 traces),
extracellular recording (middle), and firing
rate (bottom) of an area I position neuron
during a scanning pattern of horizontal eye
movements.
6. Commonly populations are
localized in cortical space
Whole-cell (WC) recording of a layer
2/3 neuron of the C2 cortical barrel
column was performed simultaneously
with measurement of VSD
fluorescence under conventional optics
in a urethane anesthetized mouse.
7. Pure population events
observed in experiments:
• Evoked responses
• Oscillations
•Traveling waves
Voltage-sensitive Dye Optical Imaging
[W.Tsau, L.Guan, J.-Y.Wu, 1999]
8. • What can be modeled on population level?
• Which details are important?
• What kinds of population models do exist?
• Which one to choose?
9. Synaptic
conductance
kinetics
GABA-IPSC AMPA-EPSC
AMPA-EPSC GABA-IPSC
Membrane
GABA-IPSP AMPA-EPSP equations
AMPA-EPSP GABA-IPSP
PSP
PSP
Threshold criterium
Spike
Spike
Population model
Firing rate
Firing rate
Eq. for spatial
connections
10. • ionic channel kinetics
• input signal is 2-d Model of a pyramidal neuron
dV
C = − I Na − I DR − I A − I M − I H − I L − I AHP − s(t ) (V − V0 ) + u(t ) + η (t )
dt
u(t ) = ∑S g S (t ) (VS − V0 ) + I electrode (t )
I ... = g... x p (t ) y q (t ) (V (t ) − V... ) s(t ) = ∑S g S (t )
dx x∞ (U ) − x
= ,
dt τ x (U )
dy y∞ (U ) − y
=
dt τ y (U )
Approximations for
I Na , I DR , I A , I M , I H
are
from [L.Graham, 1999]; EXPЕRIМЕNТ
IAHP is from [N.Kopell et al., 2000]
MODEL
Color noise model
(Ornstein-Uhlenbeck
process):
dη
τ = −η + 2τ σξ (t )
dt
12. • neuron is spatially distributed A
2-comp. neuron with synaptic currents at somas
15
0 B
PSC, exp.
PSP, exp. Vd
-50 PSP, model 2 10
PSP, model 1
PSP, mV
PSC, pA
Vd
-100
Vs Is
5
-150
-200 0
0 5 10
t, ms
15 C
Two boundary problems: ∂V ∂V g=Id/(Vd-Vrev) Vd
A) current-clamp to register PSP: ∂X = R Gs V + ;
X =0 ∂T
B) voltage-clamp to register PSC: V (T ,0) = 0; Vd
∂V
Vd Is
= R I S (T ) Vs
∂X X =L
V0 [F.Pouille,
∂V ∂ V 2 M.Scanziani
− +V = 0 //Nature, 2004]
∂T ∂X 2
X=0 X=L Figure Transient activation of somatic and delayed
Solution: activation of dendritic inhibitory conductances in
dV I [A.V.Chizhov //
τm = −(V − V rest ) + ρ (Vd − V ) − S Biophysics 2004]
experiment (solid lines) and in the model (small circles).
dt Gs A, Experimental configuration.
dV 1 ∂I d B, Responses to alveus stimulation without (left) and with
τ m d = −(Vd − V rest ) − (2 + ρ )(Vd − V ) − τ m
+ 3I d
(right) somatic V-clamp.
dt ρ Gs ∂t C, In a different cell, responses to dynamic current injection
Parameters of the model: in the dendrite; conductance time course (g) in green, 5-nS
τm= 33 ms, ρ = 3.5, Gs= 6 nS in B and 2.4 nS in C peak amplitude, Vrev=-85 mV.
13. • spatial structure of connections
1 mm
Эксперимент. Зрительная кора. Карта
ориентационной избирательности
активности нейронов.
Модель “Pinwheels” карты
ориентационной
избирательности входных
сигналов.
Модель. Ответ зрительной коры на полосу горизонтальной,
а затем вертикальной ориентации.
14. • What can be modeled on population level?
• Which details are important?
• What kinds of population models do exist?
• Which one to choose?
15. Population models
• Definition
A population is a set of similar neurons
receiving a common input and dispersed due
to noise and intrinsic parameter distribution.
• Common assumptions:
– Input – synaptic current (+conductance)
– Infinite number of neurons
– Output – population firing rate (4000)
1 nact (t; t + ∆t )
ν (t ) = lim lim
∆t →0 N →∞ ∆t N
16. Direct Monte-Carlo simulation
of individual neurons: Types of population models
∂V
C = I − g L (V − VL ) + σ I ξ (t )
∂t
если V > V T , т V = Vreset и спайк
1 nact ( t + ∆t )
ν (t ) =
∆t N
Firing-rate:
ν (t ) = f ( I (t )) f “f-I-curve”
dν
or τ = −ν + f ( I (t ))
dt
dU
or C = I − g L (U − VL ),
dt I
ν (t ) = ~(U (t ))
f
Assumption. Neurons are de-synchronized.
Probability Density Approach (PDA):
(4000)
RD модель :
∂ρ ∂ρ
+ = − ρH
∂t ∂t *
∂U ∂U
C + = I − g L (U − VL )
∂t ∂t *
1
H (U ( t , t*)) = ( A(U ) + B(U , dU / dt ))
τm
∞
v (t ) = ρ (t ,0) = ∫ ρ H dt *
+0
17. Idea of Probability Density Approach (PDA)
Single neuron equation (e.g. H-H model)
r
dX
= F(X ) + S
r r r
dt
r
where F is the common deterministic part,
r
S is the noisy term.
X = (V , m, h, n )
r
For classical H-H:
ρ ( X , t)
r
Eq. for neural density
∂ρ
∂t
=−
∂
∂X
r r
( ∂
r ⋅ F(X ) ρ + r
∂X
) t ∂ρ
⋅ W r
∂X [B.Knight 1972]
t r
where the matrix W represents the influence of noise S
Problem! The equation is multi-dimensional.
Particular cases are [A.Omurtag et al. 2000]
X ≡V - membrane potential [D.Nykamp, D.Tranchina 2000]
[N.Brunel, V.Hakim 1999], …
X ≡ t* - time passed since the last spike [J.Eggert, JL.Hemmen 2001]
[А.Чижов, А.Турбин 2003]
X ≡τ - time till the next spike [A.Turbin 2003]
18. ρ
Simplest 1-d PDAs
• Kolmogorov-Fokker-Planck eq. for ρ(t,V)
Hz
Leaky Integrate-and-Fire (LIF) neuron:
dV
τm = −V + RI (t ) + η (t ),
dt
if V > V T then V = Vreset 0 Vreset VT
< η (t ) >= 0, < η (t ) η (t ' ) >= τ m σ 2 δ (t − t ' ) ν
∂ρ ∂ σ 2 ∂2ρ
τm = [(V − RI ) ρ ] + + ν ⋅ δ (V − Vreset )
∂t ∂V 2 ∂V 2 Hz
σ 2 ∂ρ Problem! Voltage can not
ν (t ) = uniquely characterize
2 ∂V V =V T neuron’s state. 0 t
• Refractory density ρ(t,t*) for SRM - neurons
∂ρ ∂ρ ∞
+ ∗ = −ρ H ρ (t ,0) ≡ ν (t ) = ∫ ρ (t , t * ) dt *
∂t ∂t 0
H = H (U (t , t*), V T )
Spike Response Model (SRM):
U (t , t * ) = η (t * ) + ∫ k (t * , t ') I (t ' ) dt '
t*
[W.Gerstner, W.Kistler, 2002]
0
19. 1-D Refractory Density
Approach for conductance-
based neurons (CBRD)
[A.V.Chizhov, L.J.Graham // Phys. Rev. E 2007, 2008]
1. Threshold single-neuron model
2. Refractory density approach (t* -
parameterization)
3. Hazard-function t* is the time since the last spike;
H ≈ A+ B ∂ρ ∂ρ
+ = −ρ H
∂t ∂t ∗
∂U ∂U
C + * = − I DR − I A − I M − I H − I L − I AHP − I i
H(U) = ‘frozen stationary’ + ‘self-similar’ ∂t ∂t
solutions of Kolmogorov-Fokker-Planck eq. ∂x ∂x x (U ) − x
+ * = ∞ , ∞
∂t ∂t τ x (U )
for I&F neuron with white or color v (t ) = ρ H dt *
∫
noise-current ∂y ∂y y ∞ (U ) − y
+ = +0
∂t ∂t * τ y (U )
20. 1. Threshold neuron model
Full single neuron model dV
C = − I Na − I DR − I A − I M − I H − I L − I AHP − I i
dt
Approximations for I Na , I DR , I A , I M , I H are taken from [L.Graham, 1999]; IAHP is from [N.Kopell et al., 2000]
Threshold model dU
C = − I Na − I DR − I A − I M − I H − I L − I AHP − I i
dt
dx x∞ (U ) − x dy y∞ (U ) − y
= , =
dt τ x (U ) dt τ y (U )
if U > V T then U = U reset = −40 mV
for I DR : x = x reset = 0.262, y = y reset = 0.473;
for IA : x = x reset = 0.743, y = y reset = 0.691;
for IH : y = y reset = 0.002;
for IM : x = x + ∆ x reset , ∆ x reset = 0.18 (1 − x );
for I AHP : w = w + ∆ w reset , ∆ w reset = 0.018 (1 − w).
21.
22. 2. Refractory density approach (t* - parameterization)
t* is the time since the last spike;
ρ = ρ (t , t * ), U = U (t , t * ), x = x (t , t * ), y = y (t , t * )
∂ρ ∂ρ d • ∂ • dt * ∂ • ∂ • ∂ •
+ ∗ = −ρ H = + = +
∂t dt ∂t * ∂t ∂t *
∂t ∂t
dt
∂U ∂U
C + * = − I DR − I A − I M − I H − I L − I AHP − I i
∂t ∂t
∂x ∂x x∞ (U ) − x
+ *= ,
∂t ∂t τ x (U ) I ... = g ... x y (U − V... )
for I DR , I A , I M , I H , I AHP
∂y ∂y y∞ (U ) − y
+ =
∂t ∂t * τ y (U )
H (U ) = 1 τ m ( A(U ) + B (U , dU dt ) ) -- Hazard function
τ m = C /( g DR (t , t * ) + g A (t , t * ) + g M (t , t * ) + g H (t, t * ) + g L + g AHP (t , t * ))
Boundary conditions:
A(U ) = exp(6.1 ⋅ 10−3 − 1.12 T − 0.257 T 2 − 0.072 T 3 − 0.0117 T 4 ). ∞
B (U ) = -τ m 2
dT ~
F (T ), T=
U −U
T
, ~
F (T ) =
2 exp( −T ) 2
ρ (t ,0) = ∫ ρ F dt ∗ ≡ ν (t ) -- firing rate
dt σ π 1 + erf (T ) +0
U (t ,0) = U reset
x (t ,0) = x reset , y (t ,0) = y reset for I DR , I A , I H ;
Application x (t ,0) = x (t , t *T ) + ∆ x reset for I M ;
w(t ,0) = w(t , t *T ) + ∆ w reset for I AHP ;
t *T : U (t , t *T ) = U T ( dU (t , t *T ) dt ).
23. 3. Hazard-function in the case of white noise-current
(First-time passage problem)
A – solution in case of steady stimulation (self-similar);
Approximation: H ≈ A+ B
B – solution in case of abrupt excitation
Single LIF neuron - Langevin equation
dV < η (t ) > = 0
τm = −V + U (t ) + η (t ) < η (t )η (t ' ) >= σ 2 τ m δ (t − t ' )
dt
if V < UT then spike
Fokker-Planck equation
~ ∂
∂ρ ~
σ 2 ∂ρ
τm ~−
+ (U (t ) − V ) ρ 2 ∂V = 0 ρ (t,U T ) = 0
~
∂t ∂V ρ (t ,−∞) = 0
~
σ 2 ∂ρ~
exp (− (V − U ) 2 σ 2 )
H (t ) ≡ − ~ 1
ρ (0,V ) =
2τ m ∂V V =U T πσ
u (t ) = (V (t ) − U (t )) σ
ˆ
T (t ) = (U T − U (t )) σ
ˆ
~ ~ ρ (t , T (t )) = 0
~
∂ρ ∂ ~ − 1 ∂ρ = 0
τm + −uρ ρ (t ,−∞) = 0
~
∂t ∂u 2 ∂u
exp(− u 2 )
~ 1
ρ (0, u ) =
~ 1 ∂ρ ~ π
H (t ) ≡ H (t ) / τ m = −
2τ m ∂u u =T ( t )
24. Self-similar solution (T=const)
Equivalent formulation:
~
ρ ( t , u ) = ρ (t ) p (t , u )
T (t )
where ρ (t ) = ∫ ~
ρ (t , u ) du
−∞
ρ (t ) − amplitude , p(t , u ) − shape
p (t , T ) = 0
∂p ∂ 1 ∂p ~ ~ 1 ∂p
τm + − u p − = H (t ) ⋅ p where H (t ) = − p(t ,−∞) = 0
∂t ∂u 2 ∂u
2 ∂u u = T exp(− u 2 )
1
p(0, u ) =
dρ ~ π
τm = − ρ H (t ),
dt
~
Assumption. U(t)=const (or T(t)=const). Notation: A ≡ H
~
Then the shape of ρ , which is p(t , u) , is invariable.
∂ 1 ∂p 1 ∂p p (t , T ) = 0
−u p− = A(t ) ⋅ p where A(t ) = −
∂u 2 ∂u 2 ∂u u =T p(t ,−∞) = 0
dρ
τm = − ρ A(T )
dt
25. Frozen Gaussian distribution (dT/dt = ∞)
Assumption. T(t) decreases fast.
The initial Gaussian distribution remains almost unchanged except
cutting at u=T.
The hazard function in this case is H=B(T,dT/dt).
dρ
τm = −ρ B
T (t )
where ρ (t ) = ∫ ~
ρ (t , u ) du
dt −∞
τ m dρ τ dρ dT
or B=− =− m
ρ dt ρ dT dt +
U(t) UT
~(t , u ) = π exp(− u ), if
1
For the simplicity, we consider the case of 2
u ( t ) < T (t )
arbitrary but monotonically increasing T(t) and ρ
the Gaussian distribution
0, otherwise
τ m dρ dT dT ~
B=− = −τ m 2 F (T )
ρ dT dt +
dt +
~ 2 exp( −T 2 )
where F (T ) =
π 1 + erf(T )
[x]+ for x>0 and zero otherwise
26. Approximation of hazard function in arbitrary case
~
∂ρ ∂ ~ ρ (t , T (t )) = 0
~ где T (t ) = (U T − U (t )) σ
τm + ~ − 1 ∂ρ = 0
−uρ
ˆ
∂t ∂u 2 ∂u ρ (t ,−∞) = 0
~
exp(− u 2 )
~ 1
1 ∂ρ ~ ρ (0, u ) =
H=
ˆ π
2τ m ∂u u =T ( t )
A – solution in case of steady stimulation (self-similar);
Approximation: H ≈ A+ B
B – solution in case of abrupt excitation
Weak stimulus Strong stimulus
Approximation of H by A is green, by B is blue, by A+B is red, exact solution is black. ν (t ) = ∂ρ ∂t
27. 3. Hazard-function in the case of colored noise
dU Langevin equation
Without noise: C = − I tot (U , t ) U < UT
dt
dV du ~
With noise: C = − I tot (V , t ) + η (t ) V < UT τ m (U , t ) = −u + q(t ), u < T (t )
dt dt
dη dq
τ = −η + 2τ σ ξ (t ) or τ = − q + 2τ ξ (t )
dt dt
< ξ (t ) > = 0 где u = gtot (U , t )(V − U ) / σ , q = η (t ) / σ ,
< ξ (t ) ξ (t ' ) >= τ δ (t − t ' ) ~
T (t ) = g (U , t )(U T − U ) / σ
tot
Fokker-Planck eq.
∂ρ ∂ − u + q ~ ∂ q ~ 1 ∂ ρ
~ ~ 2
ρ (t, u = ∞, q) = ρ (t , u, q = −∞) =
~ ~
+ τ ρ + − ρ − =0
∂t ∂u m ∂q τ τ ∂q
2 ~ ~ ~ ~
= ρ (t, u, q = +∞) = ρ (t , u = T , q ≤ T ) = 0
~ 1 ∞
~ ~ ~ ρ (t = 0, u, q) =
~ 1+ k
2π k
1+ k
exp [
− (1 + k )u 2 − q 2 + 2 qu ]
H (U (t )) ≡
ρT
~
∫ ( q − T ) ρ (t, T , q) dq, k (U , t ) ≡ τ m (U , t )/τ
2k
or ~
T ∞
∞
ρ ( t , u, q ) = ρ ( t ) p ( t , u, q )
T (t )
~ where ∫−∞ dq ∫− ∞ p (t , u, q ) du = 1 ρ (t ) = ∫ ∫ ρ (t, u, q) dq du.
~
ρ (t ) − amplitude , p(t , u ) − shape −∞−∞
dρ ~ ∞
τm = − ρ H (t ), where ~ ~ ~
H (U (t )) ≡ ∫ ( q − T ) p (t , T , q ) dq
dt ~
T
∂p ∂ ∂ ∂2 p ~ p(t , u = ∞, q) = p(t , u, q = −∞) =
τm = (u − q) p + k qp + 2 + H (t ) p
∂t ∂u ∂q ∂q ~ ~
= p(t , u, q = +∞) = p(t , u = T (t ), q ≤ T (t )) = 0
28. Self-similar solution (T=const)
Assumption. U(t) (or T(t)) is constant or slow.
~
Then the shape of ρ , which is p(t , u, q), is invariable.
∂ ∂ ∂2 p p(t, u = ∞, q) = p(t, u, q = −∞) =
(u − q) p + k qp + 2 + A p = 0 ~ ~
∂u ∂q ∂q = p(t , u, q = +∞) = p(t, u = T , q ≤ T ) = 0
∞
~ ~
A = ∫ ( q − T ) p (t , T , q ) dq
where ~ 1+ k
T =T
~
T 2
q
u
A ∞ (T) = exp(0.0061 - 1.12 T - 0.257 T 2 - 0.072 T 3 - 0.0117 T 4 )
29. Hazard function in arbitrary case H ≈ A+ B
K=1: Weak stimulus Strong stimulus
K=8: Weak stimulus Strong stimulus
Approximation of H
by A is green,
by B is blue,
by A+B is red,
exact solution is black.
ν (t ) = ∂ρ ∂t
30. CBRD Single cell level
t* is the time since the last spike
∂ρ ∂ρ
+ ∗ = −ρ H
∂t ∂t
∂U ∂U
C + = − I DR − I A − I M − I H − I L − I AHP − I i
∂t ∂t *
∂x ∂x x∞ (U ) − x Populations
+ *= , I ... = g ... x y (U − V... )
∂t ∂t τ x (U )
for I DR , I A , I M , I H , I AHP
∂y ∂y y∞ (U ) − y
+ *=
∂t ∂t τ y (U )
∞
ρ (t ,0) = ∫ ρ F dt ∗ ≡ ν (t )
+0
Large-scale simulations
(NMM & FR-models
for EEG & MRI)
36. Simulations. Constant current stimulation.
Color noise.
Comparison with analytical solution.
−1 (*)
a u ' τ m H (u )
ν = τ m ∫0 exp − ∫0 du /(a − u ′) du′
a−u
a = I a /g L (U T − VL )
dots – Monte-Carlo
solid – eq.(*)
dash – adiabatic approach
[Moreno-Bote, Parga 2004]
Firing rate depends on the noise
time constant.
37. Interconnected populations
Synaptic current
kinetics
GABA-IPSC AMPA-EPSC
AMPA-EPSC GABA-IPSC
Membrane
GABA-IPSP AMPA-EPSP equations
AMPA-EPSP GABA-IPSP
PSP
PSP
Threshold criterium
Spike
Spike
Population model
Firing rate
Firing rate
38. Pyramidal neurons
Approximations of synaptic currents 200 AMPA-PSC 40 NMDA-PSC
(with PTX, APV) (with PTX, CNQX)
150 20
Vh=-40 mV
Vh=-80 mV experiment
model 0
PSC, pA
100
PSC, pA
experiment
model
Excitatory synaptic current: -20
50
iE = i AMPA + i NMDA Vh=-40 mV
-40
i AMPA = g AMPA m AMPA (t ) (V − V AMPA ) 0
Vh=+20 mV -60
Vh=+20 mV
iNMDA = g NMDAm NMDA (t ) f NMDA (V ) (V − VNMDA ) -50
-80
0 10 20 30 40 50 0 25 50 75 100
t, ms t, ms
gj - maximum specific conductance, 0
0
mj - non-dimensional conductance GABA-PSC
(with CNQX, D-AP5)
Vj - reversal potential -100
f NMDA (V ) = 1 /(1 + Mg / 3.57 exp( −0.062V )) -50 Vh=-64 mV fast GABA-A -IPSC
PSC, pA
(with CNQX, D,L-APV)
PSC, pA
-200
Vh=-60 mV
Inhibitory synaptic current:
-300
i I = g GABAmGABA (t ) (V − VGABA ) -100
experiment
model experiment
Non-dimensional synaptic conductances: -400 model
d 2m j dm j
ττ + (τ rj + τ d ) + m j = S (ν j ),
r d 0 10 20 30 40 50 -500
0 10 20 30 40 50
j j j t, ms t, ms
dt 2 dt
Interneurons
j = AMPA , GABA , NMDA 500 AMPA-PSC
(with PTX, APV) 150 NMDA-PSC
where S ( ν j ) = 2 ( 1 + exp( −2τ ν j ) ) − 1 τ = 1 µs 400
(with PTX, CNQX)
τ r , τ d - rise and decay time constants
j j experiment
100
Vh=-40 mV
300 Vh=-80 mV
ν j (t ) - firing rate on j-type axonal terminals model
PSC, pA
50
PSC, pA
200 experiment
0 model
100 -50
Vh=-40 mV
0 -100 Vh=+20 mV
Vh=+20 mV
-100 -150
0 10 20 30 40 50 0 25 50 75 100
t, ms t, ms
39. Simulations. Interictal activity. Recurrent network of pyramidal cells,
including all-to-all connectivity by excitatory synapses.
I i (t ) = I ext (t ) + I S (t ), Model
with IM and IAHP
I S (t ) = g S (t ) (U (t ) − VS ),
2
2 d g S (t ) dg (t )
τS + 2τ S S + g S (t ) = g S τ ρ (t ,0)
dt 2 dt
Experiment I = 150 pA
ext
τ S = 5.4 ms,
τ = 1 ms,
VS = 5 mV,
g S = 1 mS/cm 2
σ V = 2 mV ( at rest )
[S.Karnup, A.Stelzer 2001]
40. Simulations. Gamma rhythm. Recurrent network of interneurons,
including all-to-all connectivity by inhibitory synapses
τ S = 3ms,
d 2 g S (t ) dg (t )
I i (t ) = I ext (t ) + I S (t ), τ2
S + 2τ S S + g S (t ) = g S τ ν (t − τ d ) τ d = 1ms,
dt 2 dt τ = 1ms,
I S (t ) = g S (t ) (U (t ) − VS ), for density approach ν (t ) = ρ (t , t * = 0) VS = -80mV,
g S = 7mS/cm 2
41. Model Experiments Oscillations
Control (“Kainate”) +“Bicuculline”
All the simulations were done with a
single set of parameters. All the
parameters except synaptic maximum
conductances have been obtained by
fitting to experimental registration of
elementary events such as patch-
electrode current-induced traces,
Spikes in single neurons spike trains and monosynaptic
responses .
Conductances The model reproduces the following
characteristics of gamma-oscillations :
frequency of population spikes
a single pyramidal cell does not fire
Power Spectrum of Extracellular Potentials every cycle
every interneuron fires every cycle
bic
con amplitude of EPSC is less than that
of IPSC
blockage of GABA-A receptors
[Khazipov, Holmes, 2003] reduces the frequency
Kainate-induced oscillations [A.Fisahn et al., 1998]
in CA3. Cholinergically induced
oscillations in CA3
peak of pyramidal cell’s firing
frequency corresponds to the
descending phase of EPSC and the
ascending phase of IPSC
firing of interneurons follows the
firing of pyramidal cells
gamma-oscillations are
[N.Hajos, J.Palhalmi, E.O.Mann, B.Nemeth, homogeneous in space along the
Spike timing of pyramidal and inhibitory cells. O.Paulsen, and T.F.Freund. J.Neuroscience, cortical surface (data not shown)
24(41):9127–9137, 2004]
42. Spatial connections
ϕij (t , x, y ) = ∫ ∫ ν i (t − d ( x, y , X , Y ) / c, X , Y ) W ( x, y , X , Y ) dX dY ,
d ( x, y , X , Y ) = ( x − X ) 2 + ( y − Y ) 2 Experiment:
φ ( t , x , y ) - firing rate on presynaptic terminals;
ν ( t , x , y ) - firing rate on somas.
Assumption: distances from soma to synapses have exponentially decreasing
distribution p(x) [B.Hellwig 2000].
d ( x , y , X ,Y )
−
W ( x, y , X , Y ) = e λ
∂ 2φ ∂φ 2 ∂ φ
2
∂ 2φ 2 ∂
+ 2γ + γ φ − c 2 + 2 = γ + γ ν (t , x, y )
2
∂x
∂t 2 ∂t ∂y
∂t
[V.Jirsa, G.Haken 1996]
where γ = c/λ; c – the average velocity of spike [P.Nunez 1995]
propagation along the cortex surface by axons; [J.Wright, P.Robinson 1995]
λ – characteristic axon length. [D.Contreras, R.Llinas 2001]
43. Model Experiments Evoked responses
A B
The model reproduces postsynaptic currents
and postsynaptic potentials registered on
somas of pyramidal cells, namely:
monosynaptic EPSCs and EPSPs
[S.Karnup, A.Stelzer
1999] Effects of GABA-A disynaptic IPSC/Ps followed be EPSC/Ps
receptor blockade on
orthodromic potentials in CA1 polysynaptic EPSC/Ps
pyramidal cells. Superimposed
C
responses in a pyramidal cell
reduction of delays in polysynaptic EPSCs
soma before and after decay of excitation after II component of
application of picrotoxin (PTX,
100 muM). Control and PTX poly-EPSCs in presence of GABA-A receptor
recordings were obtained at V block.
rest (-64 mV; 150 muA
stimulation intensities; 1 mm The model predicts that the evoked responses
distance between stratum [B.Mlinar, are essentially non-homogeneous in space:
radiatum stimulation site and A.M.Pugliese,
perpendicular line through
stratum pyramidale recording R.Corradetti
site). The recordings were 2001] Components of
carried out in ‘minislices’ in complex synaptic
which the CA3 region was cut responses evoked in CA1
off by dissection. pyramidal neurones in the
presence of GABAA
receptor block.
PSPs and PSCs evoked by
extracellular stimulation and registered
at 3.5cm away, w/ and w/o kainate.
[V.Crepel, R.Khazipov,
Y.Ben-Ari, 1997]
In normal concentrations of Mg and in the
absence of CNQX, block of GABA-A Spatial profiles of membrane potential and
receptors induced a late synaptic response. firing rate in pyramids.
44. Model Experiments Waves
In the case of reduced GABA-reversal
potential VGABA= -50mV and stimulation Waves with unchanging chape and
by extracellular electrode we obtain a velocity are observed in cortical tissue
traveling wave of stable amplitude and in disinhibiting or overexciting
velocity 0.15 m/s. The velocity is much conditions. The waves are produced
less than the axon propagation velocity by complex interaction of pyramidal
(1m/s) and is A determined mostly by cells and interneurons. That is
synaptic interactions. confirmed by much lower speed of the
wave propagation comparing with the
140 voltage, pyramids
axon propagation velocity which is the
voltage, interneurons
120 firing rate, pyramids
firing rate, interneurons
coefficient in the wave-like equation.
100
80
-40 Analysis of wave solutions and more
mV
Hz
60 B detailed comparison with experiments
40
20 -60
are expected in future.
0
0 25 50 75 100
ms
[Leinekugel et al. 1998]. Spontaneous GDPs
propagate synchronously in both hippocampi from septal to
120 voltage, pyramids
temporal poles. Multiple extracellular field recordings from the CA3
100
voltage, interneurons
firing rate, pyramids region of the intact bilateral septohippocampal complex.
firing rate, interneurons
0.15m/s -40 Simultaneous extracellular field recordings at the four recording
80
sites indicated in the scheme. Corresponding electrophysiological
mV
Hz
60
traces (1–4) showing propagation of a GDP at a large time scale.
40
-60
20
0
10 20 30 40
mm
Fig.5. Wave propagating from the site
of extracellular stimulation at right
border of the “slice”.
A, Evoked responses of pyramidal
cells and interneurons at the site of
stimulation.
B, Profiles of mean voltage and firing
rate in pyramidal cells and
interneurons at the time 200 ms after
the stimulus. [D.Golomb, Y.Amitai, 1997]
Propagation of discharges in disinhibited
neocortical slices.
49. Частотная модель популяции
адаптивных нейронов:
«интериктальная» активность
I AHP (ν ), I M (ν )
I
E
I S (ν )
FR модель :
∂V
C = I − I AHP (ν ) − I M (ν ) − g L (V − VL ) − I S (ν )
∂t
I S = g S (t )(V − VS )
d 2 g S (t ) d g S (t )
τS 2
2
+ 2τ S + g S (t ) = g Sτv(t )
dt dt
ν (t ) = A(U ) + B(U , dU / dt )
50. • What can be modeled on population level?
• Which details are important?
• What kinds of population models do exist?
• Which one to choose?
51. Monte-Carlo conventional
simulations: Firing-Rate modified Firing-Rate CBRD:
model: model (non-
Метод Монте − Карло :
∂V FR модель : stationary and RD модель :
C = I − ( g L + g S )(V − VL ) + σ I ξ ( t )
∂t adaptive): ∂ρ ∂ρ
dU + = − ρH
если V > V T , т V = Vreset и спайк C = I − ( g L + g S )(U − VL ) ∂t ∂t *
dt
1 nact ( t + ∆ t ) ν (t ) = A(U ) + B (U , dU / dt )
FR модель : ∂U ∂U
ν (t ) = C + = I − ( g L + g S )(U − VL )
∆t ∂V ∂t ∂t *
N C = I − ( g L + g S )(V − VL ) − I M (ν ) − I AHP (ν )
∂t 1
2 H (U (t , t*)) = ( A(U ) + B(U , dU / dt ))
τS 2 d g S (t )
+ 2τ S
d g S (t )
+ g S (t ) = g Sτv (t ) τm
dt 2 dt ∞
ν (t ) = A(U ) + B (U , dU / dt ) v (t ) = ρ (t ,0) = ∫ ρ H dt *
+0
Mathematical complexity:
104 ODEs 1 ODE a few ODEs 1-d PDEs
Precision:
4 2 3 5
Precision for non-stationary problems:
5 2 4 5
Precision for adaptive neurons :
5 1 3 4
Computational efficiency:
2 5 5 4
Mathematical analyzability:
1 5 4 4