Neurothena
A Backprop-Free Cognitive System Built on Hebbian Plasticity and Biological Learning Principles
Neurothena is the evolution of Project Athena — a research-first, neuro-aligned cognition system that replaces gradient descent with pure local learning rules. Every concept is born organically through neurogenesis. Every synapse strengthens through repetition. No backpropagation. No loss functions. Just neurons, plasticity, and emergent intelligence.
Why Backprop-Free?
Biological brains don't compute gradients. They learn through local signals — neurons that fire together wire together. Neurothena takes this literally: every learning rule is local, online, and biologically plausible.
Hebbian/STDP Learning — Synaptic weights update based on temporal co-activation, not error gradients propagated backwards through layers.
Online Learning — No batches, no epochs, no training/inference split. The system learns continuously from each experience, exactly like a biological organism.
Pure Neurogenesis — Concepts aren't pre-allocated. Every neuron is born organically when the system encounters genuine novelty — like a developing brain forming new neural assemblies.
Dual-Process Architecture
Aligned with Kahneman's System 1 / System 2 framework:
System 2 — Thinking
ThoughtEngine: a recurrent attractor network that iterates until distributional KL stabilizes. Free energy minimization drives convergence.
System 1 — Acting
MotorCortex: graph-based replay engine where high-level concepts drive concrete motor actions via vertical grounding.
The 8-Layer Cognitive Stack
Each layer maps to a biological brain structure. Together they form a complete cognitive agent.
Multimodal Fovea
Thalamic Integration
Text and vision are fused into a unified holographic workspace of parallel slots — preserving spatial geometry like a biological visual field.
Causal Graph
Asymmetric STDP
Directed synaptic edges learn temporal cause-and-effect sequences. "Fire" causes "Smoke" — not just symmetric association, but true causality.
The Oracle
Predictive Coding
A world model predicts future mental states. Surprise is the delta between prediction and reality, grounding reasoning in external data.
Knowledge Tree
Vertical Grounding
Bidirectional links between abstract concepts (System 2) and motor actions (System 1). Ideas drive speech — top-down cortical control.
Executive Controller
Prefrontal Cortex
Maintains high-level goal vectors across long timescales, overriding immediate reactive biases for strategic persistence and planning.
The Chunker
Cortical Consolidation
Fuses frequent token sequences into macro-symbols — emergent symbol formation that deepens the temporal window for higher-order reasoning.
Homeostatic Regulator
Metabolic Drive
Internal drives (energy, dopamine, surprise) replace objective functions. Cognitive load scales with thinking depth — pressure for efficient thought.
Social Brain
Theory of Mind
Distinguishes between inputs from Self, Users, and Data. Dedicated memory slots model different agents and their beliefs.
Research Progress
94.4%
Full charset mastery (72 characters) via pure Hebbian learning
23+
Iterative research versions since January 2026
0
Backpropagation operations — fully local learning
Current Capabilities
Cortical Column Vision — Text and visual pathways learn independently via VICReg self-supervised learning. Cross-modal associations form through Hebbian temporal co-occurrence, not fused gradients.
Multimodal Lectures — Every learning exposure presents text and EMNIST handwritten images simultaneously. Concepts are born multimodal from the start.
Competency-Based Curriculum — Self-paced learning through Letters → Words → Stream phases. The system must achieve true mastery before advancing — no shortcuts.
3D Brain Viewer — Real-time visualization of the emergent neuron/synapse structure as a force-directed graph. Watch concepts form and connections strengthen live.
Audio Modality (Planned) — A third cortical column for auditory processing is on the roadmap. Audio will learn independently and bind to text/vision concepts through the same Hebbian co-occurrence mechanism.
Evolution from Project Athena
Project Athena explored diffusion-based cognitive architecture with embodied cognition in the Genesis physics simulator. That research revealed a fundamental insight: real intelligence doesn't need backpropagation. Neurothena carries Athena's core philosophy forward — applied cognition, tripartite memory, dual-process reasoning — but rebuilds the foundation on biologically plausible Hebbian learning.
Read about Project Athena's foundational research →Interested in Neurothena?
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