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Replicate brain modules' computations with Artificial Neural Networks

Project description

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. Place Cells (incomplete, deprecated)
  2. Brain's GPS System (Head Direction Cells, Grid Cells, Place Cells)

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