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Hierarchical anti-Hebbian network model for the formation of spatial cells in 3D (Soman et al 2019)
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<html> <p>This is the readme for the MATLAB models associated with the paper: </p> <p>Karthik Soman, Srinivasa Chakravarthy, Michael M Yartsev, "A hierarchical anti-Hebbian network model for the formation of spatial cells in three-dimensional space", Nature Communications (2018) 9:4046 DOI: <a href="http://doi.org/10.1038/s41467-018-06441-5">10.1038/s41467-018-06441-5</a> </p> <p>This model was contributed by Karthik Soman. </p> <p>This model shows how spatial representations in 3D space could emerge using unsupervised neural networks. Model is a hierarchical one which means that it has multiple layers, where each layer has a specific function to achieve. This architecture is more of a generalised one i.e. it gives rise to different kinds of spatial representations after training. </p> Usage:<br/> ------<br/> <p>After extracting this archive cd to the new folder and type "main_code" at the matlab command prompt. After a minute or two, 28 figures should appear including these: </p> <img src="./images/screenshot.png" alt="screenshot 1" width="550"><p/> <img src="./images/screenshot2.png" alt="screenshot 2" width="550"><p/> <img src="./images/screenshot3.png" alt="screenshot 3" width="550"><p/> </html>
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Hierarchical anti-Hebbian network model for the formation of spatial cells in 3D (Soman et al 2019)
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