# Neuro-Inspired Architecture Research Program — 2026-03-09

## Pat's Vision
Not "brain-like" AI. Actually replicate the human brain's processes:
- Down to synapse-level dynamics
- Neurotransmitter systems (dopamine, serotonin, norepinephrine, GABA, glutamate)
- Synaptic plasticity (Hebbian learning, LTP/LTD, spike-timing dependent plasticity)
- Dendritic computation (not just point neurons)
- Hormonal modulation (slow global state changes)
- Cortical column structure
- Thalamic gating (attention routing)
- Basal ganglia (action selection, reinforcement)
- Default mode network (idle thought, creativity)
- Sleep/consolidation cycles (memory reorganization)

## Goal
1. Study real neuroscience → understand mechanisms
2. Implement as multi-agent swarm (tiny models as neurons/clusters)
3. Iterate: observe emergent behavior, refine architecture
4. Long-term: design a novel AI architecture based on brain principles
5. Not mimicry — actual process replication

## Research Questions
- How does synaptic plasticity map to connection weight updates between agents?
- Can neurotransmitter dynamics (reward/punishment signals) improve agent coordination?
- Does thalamic gating (selective attention routing) improve efficiency?
- Can sleep/consolidation cycles improve long-term memory?
- Does dendritic computation (agents processing multiple inputs non-linearly) outperform simple message passing?

## Starting Point
- Phase 1: Literature review (brain architecture, computational neuroscience)
- Phase 2: Map brain structures to agent architecture with real mechanisms
- Phase 3: Build v2 brain simulation with neuroscience-grounded dynamics
- Phase 4: Run experiments, measure emergence, iterate
- Phase 5: Design novel architecture based on findings