Artificial neural networks for neuroscientists: A primer
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Artificial neural networks (ANNs) are essential tools in machine learning that are increasingly used for building computational models in neuroscience. Besides being powerful techniques for data analysis, ANNs provide a new approach for neuroscientists to build models that capture complex behaviors, neural activity and connectivity, as well as to explore optimization in neural systems. In this pedagogical Primer, we introduce conventional ANNs and demonstrate how they have been deployed to study neuroscience questions. Next, we detail how to customize the analysis, structure, and learning of ANNs to better address a wide range of challenges in brain research. To help the readers garner hands-on experience, this Primer is accompanied with tutorial-style code in PyTorch and Jupyter Notebook, covering major topics.
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