Intro

My approach to brain simulation

1. Identify a list of computational modules in the brain
2. For each module
   1. Understand what it computes: input -> output
   2. Get training data (synthetic or real-world)
   3. Train artificial neural networks to replicate its functionality
3. Combine modules

Why?

• Biological plausibility is a trap, simulating spikes and neurotransmitters does not help us understand how brain generates intelligence

• Analogy: considering transistor physics is irrelevant to understanding how a computer computes a + b -- they are on different isolated levels of abstractions, they do not depend on one another to work

• Current works in AI are mainly focused on solving daily-life tasks (text, image/video, game playing) -- I want to use these technologies to understand the brain

• It is well proven that ANNs can produce intelligence (LLMs, RL agents) -- making them qualified to model modules in the brain

List of implemented modules

pip install brain-modules

1. Hippocampal Place Cells (2014 Nobel Prize)