NGC-Learn: Computational Neuroscience and NeuroAI in Python
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Updated
Jul 7, 2026 - Python
NGC-Learn: Computational Neuroscience and NeuroAI in Python
Anima: an experimental cognitive architecture that models internal state, conflict, and decision-making. Uses LLMs as an interface, not as the core.
A computational theory of consciousness: if the universe is deterministic, consciousness is the observer function, not the executor. Tested across 4 AI substrates with 11 probes and 4 controls.
Generalized Predictive Coding in Torch
Multi-timescale affective agents with theatrical control - 97K parameter architecture exploring functional correlates of consciousness
A practical canon for human behavioral neurobiology knowledge, reasoning, and AI/RAG use.
Approximate Natural Gradient Descent with precision weighted predictive coding
Emergent cognitive agent platform — complex behavior from capacity constraints, predictive processing, and homeostatic pressure. No hardcoded behaviors, no reward functions.
Abhidharma × Computational Phenomenology — a personal inquiry into attention and the non-self
The Language of Stress theory is an architectural theory of phenomenal experience based on valenced tension dynamics
A Machine-Verified Constructive Proof of Lemoine's Conjecture.
Biologically-grounded reasoning agent, numpy-only, no LLM — Kisamapa Labs Experiment 06
A conceptual architecture bridging neuroscience, psychology, and evolutionary biology
An honest, from-scratch, LLM-free instrument that implements the major scientific theories of consciousness (GWT · AST · HOT · active inference · IIT-proxy) as running code, a maximal functional attempt that never claims to be conscious.
MSc Neuroscience Research Project titled "Bridging predictive processing and EEG complexity in depression: An information-theoretic analysis"
This is the public repository for data and statistical analysis for our predictive olfaction in VR study. The published article can be found under the link below..
A first-principles model proposing consciousness as a predictive patch for causal latency. Unifies physics, philosophy of mind, and anxiety.
Consciousness substrate for AI. Unifies IIT + GWT + AST into one measurable loop. Pure Python, zero deps, 446 tests. pip install anima-kernel
This thesis presents an empirical comparison between PPM★ (Prediction by Partial Matching), a state-of-the-art statistical language modeling algorithm, and IDyOT (Information Dynamics of Thinking), a cognitive architecture designed to model human-like hierarchical learning and prediction.
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