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Table of contents
1 Introduction
1.1 Basal ganglia-thalamo-cortical network
1.1.1 Anatomy of basal ganglia-thalamo-cortical network
1.1.2 Closed loops in the BG-thalamo-cortical network
1.1.3 Neuronal dynamics and synaptic interactions in the basal ganglia
1.1.4 Functions of the basal ganglia
1.1.5 Dysfunctions of the basal ganglia
1.2 Collective dynamics in basal ganglia-thalamo-cortical network
1.2.1 Oscillations in Parkinson’s disease
1.2.2 Task-related oscillations
1.2.3 Infraslow oscillations and resting state network
1.2.4 Mathematical concepts for understanding the resting state networks
1.3 Absence seizure
1.3.1 Involvement of the basal ganglia in absence seizure
2 The role of striatal feedforward inhibition in the maintenance of absence seizures
2.1 Introduction
2.2 Results
2.2.1 The BG-thalamo-cortical network model
2.2.2 Strong striatal feedforward inhibition promotes bistability of the BG-thalamocortical network dynamics
2.2.3 The competition between feedback loops in the BG-thalamo-cortical network
2.2.4 Strong striatal feedforward inhibition promotes bistability
2.2.5 The mechanisms for bistability and suppression of MSN activity
2.2.6 Asynchronous ring and synchronous oscillations in the BG-thalamo-cortical spiking network
2.2.7 Appropriately timed excitatory stimulation of the cortex terminates seizures
2.2.8 Bistable dynamics in the network model with the GPe included
2.3 Discussion
2.3.1 Consistency of our theory with previous experimental results
2.3.2 Comparison to the thalamocortical theory
2.3.3 Perspectives and predictions
2.4 Materials and Methods
2.4.1 The rate model
2.4.2 The spiking model
2.4.3 Analysis of the rate model
2.4.4 Simulations
3 Preliminary evidence for bistable characteristics of absence seizures
3.1 Introduction
3.2 Results
3.3 Discussion
3.4 Materials and Methods
3.4.1 In vivo experiments from epileptic animals
4 Complex dynamics of basal ganglia-thalamo-cortical loops
4.1 Introduction
4.2 Discrete-time approximation of basal ganglia-thalamo-cortical network
4.2.1 Reduction to one dimensional discrete system
4.2.2 Analysis of the discrete model dynamics
4.2.3 Eects of synaptic dynamics
4.2.4 Degenerate and non-degenerate rate models
4.2.5 Slow feedback in the direct pathway
4.2.6 How the striatal feedforward inhibition enhances bistability
4.2.7 How the bistability depends on other network parameters
4.3 Complex dynamics
4.4 Discussion
4.4.1 Local and global bifurcation analysis
4.4.2 How to incorporate thalamocortical bursting in the discrete model
4.4.3 Incorporating topographic organization as coupled map systems
5 Discussion
5.1 Relation to pathological oscillations
5.1.1 Scaling of pathological oscillation frequencies
5.1.2 Scenario 1: hyperdirect feedback drives B-oscillations
5.1.3 Scenario 2: hyperdirect feedback drives SWD
5.1.4 Comparison of the two scenarios
5.1.5 Inter-species scaling of alpha and beta frequency bands
5.1.6 Are Parkinsonian oscillations multi-stable?
5.2 How to determine the oscillation driver experimentally
5.3 Functional implication of the complex dynamics
Appendix
