NEURON | OpenAGI

THE BREAKTHROUGH

Traditional AI relies on static weights and biases. At OpenAGI, we realized the path to True Artificial General Intelligence wasn't in adding more layers, but in perfecting the unit.

Neuron is not a mathematical abstraction. It is a biological simulation. It breathes. It consumes energy. It repairs itself. It learns via Hebbian Plasticity, not backpropagation.

This is the atomic unit of the next generation of intelligence.

Hodgkin-Huxley Dynamics

Real-time calculation of ion channel gating (Na+, K+, Ca2+) and membrane potential.

Metabolic System

Simulated mitochondria convert Glucose and O2 into ATP. Without energy, the neuron dies.

Synaptic Plasticity

True Hebbian learning (LTP/LTD) based on spike timing and chemical traces.

TECHNICAL SPECIFICATIONS

Bio-Physics Engine

The core loop runs at 0.1ms resolution, solving differential equations for membrane voltage and ion concentration gradients in real-time.

Genetic Regulation

The code simulates simplistic gene expression. The neuron effectively "decides" when to strengthen connections based on protein availability.

Training Data

Neuron requires no pre-training. It learns from input spikes dynamically, associating patterns just like a human brain cell.

            class Membrane:

              def tick(self, I_syn):

                # Hodgkin-Huxley Equation Integration

                g_Na = 120.0 * (self.m**3) * self.h

                i_na = g_Na * (v - self.nernst("Na"))

                self.voltage += (i_total / Cm) * dt