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Biology
Neurobiology/Neuroscience
Computational Neuroscience
1. Introduction to Computational Neuroscience
2. Foundations in Neuroscience
3. Mathematical and Physical Foundations
4. Modeling Single Neurons
5. Synaptic Plasticity and Learning
6. Neural Coding
7. Modeling Neural Networks
8. Models of Learning and Memory
9. Models of Sensory and Motor Systems
10. Models of Higher Cognitive Functions
11. Tools and Techniques
Synaptic Plasticity and Learning
Short-Term Plasticity
Synaptic Facilitation
Mechanisms
Residual calcium hypothesis
Calcium sensor proteins
Functional significance
Temporal filtering
Information processing
Mathematical models
Facilitation dynamics
Recovery kinetics
Synaptic Depression
Mechanisms
Vesicle depletion
Calcium channel inactivation
Functional significance
Adaptation
Gain control
Mathematical models
Depression dynamics
Resource depletion
Short-Term Plasticity Interactions
Facilitation-depression interplay
Frequency-dependent filtering
Computational roles
Long-Term Plasticity
Long-Term Potentiation
Induction protocols
High-frequency stimulation
Theta burst stimulation
Molecular mechanisms
NMDA receptor activation
Calcium signaling
Protein synthesis
Expression mechanisms
AMPA receptor trafficking
Structural changes
Long-Term Depression
Induction protocols
Low-frequency stimulation
Paired-pulse protocols
Molecular mechanisms
Metabotropic glutamate receptors
Calcium signaling
Protein phosphatases
Expression mechanisms
AMPA receptor internalization
Spine shrinkage
Metaplasticity
Plasticity of plasticity
Sliding thresholds
BCM theory
Hebbian Learning
Fire Together Wire Together Principle
Correlation-based learning
Activity-dependent plasticity
Covariance-Based Learning Rules
Covariance detection
Decorrelation learning
Correlation-Based Learning Rules
Correlation functions
Temporal correlations
Competitive Hebbian learning
Winner-take-all dynamics
Feature competition
BCM Rule
Sliding threshold
Selectivity development
Spike-Timing-Dependent Plasticity
Causal Spike Pairing
Pre-before-post timing
Potentiation window
Anti-Causal Spike Pairing
Post-before-pre timing
Depression window
STDP Learning Windows
Temporal precision
Asymmetric windows
Symmetric windows
Mathematical models of STDP
Exponential kernels
Power-law kernels
Triplet rules
Functional consequences
Temporal sequence learning
Causality detection
Competitive dynamics
Homeostatic Plasticity
Synaptic Scaling
Global scaling mechanisms
Activity sensors
Scaling factors
Intrinsic Plasticity
Excitability regulation
Ion channel regulation
Firing rate homeostasis
Network stability mechanisms
Excitation-inhibition balance
Critical dynamics
Avalanche dynamics
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6. Neural Coding