This section contains lectures which were provided by several HBP PIs.
Future Computing
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W3 Gerstner Wulfram: Derivation of the Cable Equation
Lecture: Gerstner Wulfram (EPFL) - Derivation of the Cable Equation
Neuronal Dynamics - Computational Neuroscience of Single Neurons (Online Course 2013)
Week 3: Synapses, dendrites and the cable equation
Duration: 10min
Future Medicine
Future Neuroscience
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Born Jan: Sleep's critical role for memory
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Dehaene Ghislaine: Origins of the human mind in the infant braint
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Dehaene Stanislas: "Reading in the Brain"
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Dehaene Stanislas: Recent Advances in Understanding the Brain Mechanisms of Consciousness
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Einevoll Gaute: From cellular/network models to tissue simulation
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Einevoll Gaute: What can we learn from multielectrode recordings of extracellular potentials in the brain?
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Goebel Rainer: Functional Brain Imaging and Brain-Computer Interfaces: Past, present, Future
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Grant Seth: The Problem of synapse complexity
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Grün Sonja: Data driven analysis of spatio-temporal cortical interaction
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Lachaux Jean-Philippe: 1998 - 2013: the new wave of human intra-cranial electrophysiology
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Lachaux Jean-Philippe: Attention, distraction and the war in our brain: Jean-Philippe Lachaux at TEDxEMLYON
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Maass Wolfgang: Does the brain play dice?
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Mortone Maryann: Where do we go from here: databases and ontologies
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Pavone Francesco: Brain research aims to advance neuromorphic computing
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Pavone Francesco: Journey into the Brain: from Single Synapse to Whole Brain Anatomy
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Segev Idan: Design principles for dendritic inhibition
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W1 Gerstner Wulfram: Generalized Integrate and Fire Models
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W1 Gerstner Wulfram: Leaky Integrate- and- Fire Model
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W1 Gerstner Wulfram: Linear differential equation
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W1 Gerstner Wulfram: Neurons and Synapses: Overview
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W1 Gerstner Wulfram: Quality of Integrate-and-Fire Models
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W1 Gerstner Wulfram: The Passive Membrane
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W2 Gerstner Wulfram: Biophysics of neurons
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W2 Gerstner Wulfram: Detailed Biophysical Models
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W2 Gerstner Wulfram: Hodgkin-Huxley Model
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W2 Gerstner Wulfram: Reversal potential and Nernst equation
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W2 Gerstner Wulfram: Threshold in the Hodgkin Huxley Model
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W3 Gerstner Wulfram: Cable equation
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W3 Gerstner Wulfram: Compartmental Models
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W3 Gerstner Wulfram: Dendrite as a Cable
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W3 Gerstner Wulfram: Derivation of the Cable Equation
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W3 Gerstner Wulfram: Synapses
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W3 Gerstner Wulfram: Synaptic short term plasticity
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W4 Gerstner Wulfram: Analysis of a 2D neuron model - constant input
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W4 Gerstner Wulfram: Analysis of a 2D neuron model - pulse input
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W4 Gerstner Wulfram: Exploiting similarities
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W4 Gerstner Wulfram: Firing threshold in 2D models
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W4 Gerstner Wulfram: From Hodgkin Huxley to 2D
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W4 Gerstner Wulfram: Nonlinear Integrate-and-Fire Model
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W4 Gerstner Wulfram: Phase Plane Analysis
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W4 Gerstner Wulfram: Separation of time scales
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W4 Gerstner Wulfram: Stability of fixed points
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W4 Gerstner Wulfram: Type I and Type II Neuron Models
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W5 Gerstner Wulfram: Membrane potential fluctuations
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W5 Gerstner Wulfram: Poisson Model
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W5 Gerstner Wulfram: Sources of Variability?
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W5 Gerstner Wulfram: Stochastic spike arrival
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W5 Gerstner Wulfram: Stochastic spike firing in integrate and fire models
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W5 Gerstner Wulfram: Three definitions of rate code
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W5 Gerstner Wulfram: Variability of spike trains
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W6 Gerstner Wulfram: Comparison of noise models
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W6 Gerstner Wulfram: Escape noise
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W6 Gerstner Wulfram: From diffuse noise to escape noise
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W6 Gerstner Wulfram: Interspike intervals & renewal processes
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W6 Gerstner Wulfram: Likelihood of a spike train
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W6 Gerstner Wulfram: Rate Codes versus Temporal Codes
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W7 Gerstner Wulfram: AdEx: Adaptive exponential integrate-and-fire
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W7 Gerstner Wulfram: Firing patterns and phase plane analysis
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W7 Gerstner Wulfram: Generalized Linear Model (GLM)
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W7 Gerstner Wulfram: Helping Humans
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W7 Gerstner Wulfram: Modeling in vitro data
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W7 Gerstner Wulfram: Models and data
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W7 Gerstner Wulfram: Parameter estimation
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W7 Gerstner Wulfram: Parameter estimation for spike times
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W7 Gerstner Wulfram: Spike Response Model (SRM)