Volume 18 — Collapse Neural Systems
Neural Architectures in Golden-Base Reality
This volume develops neural network theory within φ-constrained systems. Neurons become trace nodes, synapses are valid transitions, and learning emerges from structural adaptation while maintaining the no-11 constraint.
Chapter Index
Chapter 288: NeuroCollapse
Trace Firing Patterns in Collapse Neural Models
Neural activation as trace collapse events.
Chapter 289: TensorActivate
Activation Flow in Collapse Tensor Fields
Activation functions in trace space.
Chapter 290: PlasticCollapse
Adaptive Restructuring of Collapse Pathways
Synaptic plasticity via trace modification.
Chapter 291: ObsAttention
Observer-Centered φ-Trace Reinforcement Dynamics
Attention mechanisms through observers.
Chapter 292: GradientTrace
Collapse Learning via Trace Gradient Descent
Backpropagation in trace networks.
Chapter 293: MemoryLoop
Information Encoding via Collapse Cycle Trace Loops
Memory formation in cyclic traces.
Chapter 294: SynapticWeighting
Collapse Weight Adjustment as Learning Mechanism
Weight updates preserving constraints.
Chapter 295: NeuroEntropy
Trace Complexity as Cognitive Entropy Load
Information processing limits.
Chapter 296: ZetaSpecialize
Trace Pathway Specialization via ζ-Resonance
Spectral specialization of neurons.
Chapter 297: NeuroModularity
Module Structure in φ-Neural Trace Graphs
Modular neural architectures.
Chapter 298: CompressRecall
Trace Collapse Compression for Memory Recall
Memory compression and retrieval.
Chapter 299: NeuroOsc
Collapse Oscillations in Synchronized Tensor Networks
Neural oscillations and synchrony.
Chapter 300: ConceptCollapse
φ-Trace Concept Formation through Path Collapse Integration
Concept learning in trace space.
Chapter 301: PlasticityIndex
φ-Neural Plasticity Index for Observer Networks
Measuring learning capacity.
Chapter 302: TraceReconstruct
Collapse-Based Neural Memory Reconstruction
Pattern completion from partial traces.
Chapter 303: NeuroCode
Structural Collapse Encoding for AGI Neural Interfaces
Neural coding for AGI systems.
Key Concepts Introduced
- Neural Traces: Neurons as trace nodes
- Plastic Pathways: Adaptive learning
- Observer Attention: Focus mechanisms
- Trace Memory: Cyclic encoding
- Neural Oscillations: Synchrony patterns
- Concept Formation: Abstract learning
Dependencies
- Volume 7: Observer systems
- Volume 8: Information theory
- Volume 11: Computation models
Next Steps
- Volume 21: AGI applications
- Volume 22: Evolution of networks
- Volume 28: Memory systems
"In neural traces, mind emerges from constraint."