CST Neural Connection Training Simulator

Disclaimer

This is a theoretical educational demo, not a medical test, IQ test, diagnosis, or neuroscience measurement device. It does not measure real neurons or synapses.

This model follows CST-based neural efficiency theory where intelligence depends on connection quality, not brain percentage usage.

Short Theory Explanation

Intelligence is not based on neuron quantity (~86 billion), but on neural efficiency, organization, and synchronization over time.

CST defines intelligence as a time-evolving network optimization process driven by repeated activation, environmental adaptation, and learning feedback.

Growth Model: Practice × Recall × Feedback × Sleep × Challenge

Core Rule

You do not upgrade intelligence by increasing total connections.

You upgrade performance by improving efficiency, organization, and timing of neural pathways.

Training Variables

Practice

Recall

Feedback

Sleep

Challenge

Training Guidance

Use recall instead of rereading
Correct mistakes immediately
Sleep consolidates memory
Use moderate challenge
Repeat tests to improve

Efficiency Estimate

Network Efficiency

Connection Quality