Neural network models and deep learning - a primer for biologists

Abstract

Originally inspired by neurobiology, deep neural network models have become a powerful tool of machine learning and artificial intelligence, where they are used to approximate functions and dynamics by learning from examples. Here we give a brief introduction to neural network models and deep learning for biologists. We introduce feedforward and recurrent networks and explain the expressive power of this modeling framework and the backpropagation algorithm for setting the parameters. Finally, we consider how deep neural networks might help us understand the brain's computations.

14 pages, 4 figures; added references, minor corrections

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• Smooth Exact Gradient Descent Learning in Spiking Neural Networks
• Deep Recurrent Encoder: A scalable end-to-end network to model brain signals