Reconciling Predictive Coding and Biased Competition Models of Cortical Function. Spratling, M. W Frontiers in Computational Neuroscience, Frontiers, 2008. ![Reconciling Predictive Coding and Biased Competition Models of Cortical Function [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex A simple variation of the standard biased competition model is shown, via some trivial mathematical manipulations, to be identical to predictive coding. Specifically, it is shown that a particular implementation of the biased competition model, in which nodes compete via inhibition that targets the inputs to a cortical region, is mathematically equivalent to the linear predictive coding model. This observation demonstrates that these two important and influential rival theories of cortical function are minor variations on the same underlying mathematical model.
@article{Spratling:2008bg,
author = {Spratling, Michael W},
title = {{Reconciling Predictive Coding and Biased Competition Models of Cortical Function}},
journal = {Frontiers in Computational Neuroscience},
year = {2008},
volume = {2},
publisher = {Frontiers},
keywords = {predictive coding},
doi = {10.3389/neuro.10.004.2008},
language = {English},
read = {Yes},
rating = {4},
date-added = {2018-01-31T20:26:03GMT},
date-modified = {2018-01-31T20:39:52GMT},
abstract = {A simple variation of the standard biased competition model is shown, via some trivial mathematical manipulations, to be identical to predictive coding. Specifically, it is shown that a particular implementation of the biased competition model, in which nodes compete via inhibition that targets the inputs to a cortical region, is mathematically equivalent to the linear predictive coding model. This observation demonstrates that these two important and influential rival theories of cortical function are minor variations on the same underlying mathematical model.},
url = {http://journal.frontiersin.org/article/10.3389/neuro.10.004.2008/abstract},
local-url = {file://localhost/Users/yimengzh/Documents/Papers3_revised/Library.papers3/Articles/2008/Spratling/Front.%20Comput.%20Neurosci.%202008%20Spratling.pdf},
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uri = {\url{papers3://publication/doi/10.3389/neuro.10.004.2008}}
}
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