Abstract
Neuroscience has tight connections with machine learning, but this relationship isnt so clear in deep learning. This review explores the bidirectional bridge between deep learning and neuroscience. It reveals how deep learning helps interpret the basic mechanisms of neuroscience and how neuroscience inspires AI scientists to improve algorithms. We review research using deep learning to investigate cognition portions, like grid cells, neuron-astrocytes, and hippocampus. Also, deep learning, mainly Transformers, is improved by modifying and combining with other models. Inspired by neurons, even a new model known as Thousand Brains is set up. Finally, we discuss the limitations revealed in how to translate biology action into algorithms. In the future, it is convinced combination of biology function and deep learning which is used to test multiple tasks is a feasible method to explore the basic mechanism of neuroscience and improve algorithms.
Published Version
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