# From Artificial Intelligence to Brain Intelligence: The basis learning and memory algorithm for brain-like intelligence

Source: [From Artificial Intelligence to Brain Intelligence: The basis learning and memory algorithm for brain-like intelligence](<https://www.sota2.com/research/paper/68fa689d1e209131cea1d19b>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-25T22:40:59.400Z

Authors: Yifei Mao

Published: 2020-10-07T14:25:05.000Z

## Abstract

The algorithm of brain learning and memory is still undetermined. The backpropagation algorithm of artificial neural networks was thought not suitable for brain cortex, and there is a lack of algorithm for memory engram. We designed a brain version of backpropagation algorithm, which are biologically plausible and could be implemented with virtual neurons to complete image classification task. An encoding algorithm that can automatically allocate engram cells is proposed, which is an algorithm implementation for memory engram theory, and could simulate how hippocampus achieve fast associative memory. The role of the LTP and LTD in the cerebellum is also explained in algorithm level. Our results proposed a method for the brain to deploy backpropagation algorithm, and sparse coding method for memory engram theory.

## Recorded benchmark results

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## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2010.14617>)

[PDF](<https://arxiv.org/pdf/2010.14617.pdf>)