This volume moves from individual assemblies to dynamics over time. The question changes from "what fired?" to "where does activity go next?"
It covers:
- memorizing short stimulus sequences
- inspecting recall with Long-Range Inhibition (LRI)
- running deterministic finite-state utilities
- sampling probabilistic automata
01_sequence_memory_lri.ipynb: sequence memorization, overlap diagnostics, animated LRI recall, and winner-turnover inspection under one seeded parameter setting.02_fsm_and_pfa.ipynb: parity withFSMNetworkand independent samples from a smallPFANetwork.03_lri_parameter_lab.ipynb: sweep refractory period and inhibition strength, then inspect one detailed LRI recall trace.
These notebooks demonstrate package utilities. The full theoretical results belong to the cited assembly-calculus literature.
Treat the outputs as traces from a small machine: trajectories, overlap matrices, and sample counts. If a sequence recall run is short or noisy, that is part of the lesson. The mechanism is visible enough to debug rather than hidden behind a single success/failure label.