Computational Neuroscience - book notes
Chap 1: Intro
- Some phenomena
- Computation
- Emergent phenomena
- Why care?
- AI,ML,Neuroscience
- How to read + resources
Chap 2: Neurons
- Basic biology
- Dynamics
- Activation outputs
- Math
- Individual neurons
- Detector review
- Appendix
Chap 3: Networks
- Neocortex biology
- Categorization | Distributed representations
- Bidirectional dynamics
- Inhibition | Regulation
- Appendix
Chap 4: Learning
- Synaptic Plasticity
- XCAL model
- Self-organized learning
- Error-driven learning
- Leabra (framework)
- Appendix
Chap 5: Areas of the Brain
- Anatomy navigation
- Major areas
- Perception | attention
- Motor control - motor cortext - basal ganglia - cerebellum
- Memory - temporal cortex and hippocampus
- Language
- Executive functions
Chap 8: Memory
- Episodic
- Hippocampus - patterns
- Complementary learning systems
- Familiarity - recognition
- Priming
- Appendix
Chap 9: Language
- Biology
- Reading | Dyslexia
- Spelling to sound maps
- Latent semantics
- Sentence gestalt
- Language modeling - next steps
Chap 10-Executive Function
- PFC/BG biology
- Phasic DA | temporal credit assignment
- PBWM computation model
- Stroop model
- A-not-B
- SIR model
- N-Back task
- Hierarchical organization
- Affective influences
- More functions
- Alternates
- Summary
