Intracellular recordings in awake and naturally sleeping animals

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Table of contents

1 Introduction 
1.1 Preface
1.2 Computational neuroscience
1.2.1 Models with a single state variable
1.2.2 Models with multiple state variables
1.3 The point-conductance model
1.4 The dynamic-clamp technique
1.4.1 Overview
1.4.2 The AEC-method
1.5 Spike-triggered averages
1.6 Outline of the thesis
2 Inhibitory conductance dynamics in cortical neurons during activated states
2.1 Abstract
2.2 Introduction
2.3 Spike-triggered averages during activated states
2.4 Discussion
2.5 References
3 Calculating event-triggered average synaptic conductances from the membrane potential 
3.1 Abstract
3.2 Introduction
3.3 Material and Methods
3.3.1 Models
3.3.2 In vitro experiments
3.4 Results
3.4.1 Method to extract conductance STA
3.4.2 Test of the accuracy of the method using numerical simulations
3.4.3 Test of the method in real neurons
3.5 Discussion
3.6 Acknowledgments
3.7 References
4 Inhibition determines membrane potential dynamics and controls action potential generation in awake and sleeping cat cortex 
4.1 Abstract
4.2 Introduction
4.3 Materials and Methods
4.3.1 Intracellular recordings in awake and naturally sleeping animals
4.3.2 Analysis and computational models
4.4 Results
4.4.1 Intracellular recordings in awake and naturally sleeping animals
4.4.2 Synaptic conductances in wakefulness and natural sleep .
4.4.3 Conductance time course during up and down state transitions
4.4.4 Dynamics of spike initiation during activated states .
4.5 Discussion
4.5.1 Supplementary Information
4.6 References
5 Characterizing synaptic conductance fluctuations in cortical neurons and their influence on spike generation 
5.1 Abstract
5.2 Introduction
5.3 Methods
5.3.1 Computational methods
5.3.2 Biological preparation
5.3.3 Electrophysiology
5.3.4 Data analysis
5.4 Results
5.4.1 The VmD method for extracting synaptic conductance parameters
5.4.2 Estimating time constants from Vm power spectral density
5.4.3 Estimating spike-triggering conductance configurations .
5.4.4 Estimating spike-triggered averages of synaptic conductances from the Vm
5.5 Discussion
5.6 References
6 Which model best captures the spiking response of cortical neurons to excitatory inputs? 
6.1 Abstract
6.2 Introduction
6.3 Materials and Methods
6.3.1 In vitro experiments
6.3.2 Models
6.3.3 Integrate-and-fire models
6.3.4 The 2–state–variable models
6.3.5 The Hodgkin-Huxley model
6.3.6 The protocol
6.3.7 The optimisation
6.4 Results
6.5 Discussion
6.6 References
7 General Conclusions 
7.1 Summary
7.2 Outlook
A Estimating conductance parameters fromthemembrane potential time course 
A.1 Synopsis
A.2 The Method
A.3 Application to model data
A.4 Application to in vitro data
A.5 Discussion
Bibliography