ABSTRACT Clark makes a convincing case for the merits of conceptualizing brains as hierarchical prediction machines. This perspective has the potential to provide an elegant and powerful general theory of brain function, but it will ultimately stand or fall with evidence from basic neuroscience research. Here, we characterize the status quo of that evidence and highlight important avenues for future investigations.
%0 Journal Article
%1 BBS:8918821
%A Egner, Tobias
%A Summerfield, Christopher
%D 2013
%J Behavioral and Brain Sciences
%K cognition cognitive neuroscience predictivecoding
%N 03
%P 210--211
%R 10.1017/S0140525X1200218X
%T Grounding predictive coding models in empirical neuroscience research
%U http://journals.cambridge.org/article_S0140525X1200218X
%V 36
%X ABSTRACT Clark makes a convincing case for the merits of conceptualizing brains as hierarchical prediction machines. This perspective has the potential to provide an elegant and powerful general theory of brain function, but it will ultimately stand or fall with evidence from basic neuroscience research. Here, we characterize the status quo of that evidence and highlight important avenues for future investigations.
@article{BBS:8918821,
abstract = { ABSTRACT Clark makes a convincing case for the merits of conceptualizing brains as hierarchical prediction machines. This perspective has the potential to provide an elegant and powerful general theory of brain function, but it will ultimately stand or fall with evidence from basic neuroscience research. Here, we characterize the status quo of that evidence and highlight important avenues for future investigations. },
added-at = {2013-06-14T13:03:44.000+0200},
author = {Egner, Tobias and Summerfield, Christopher},
biburl = {https://www.bibsonomy.org/bibtex/2bb02c0b7143db25be0354d8df8098260/yish},
doi = {10.1017/S0140525X1200218X},
interhash = {2387b0b31e747dd92751165c4256385e},
intrahash = {bb02c0b7143db25be0354d8df8098260},
issn = {1469-1825},
journal = {Behavioral and Brain Sciences},
keywords = {cognition cognitive neuroscience predictivecoding},
month = {5},
number = 03,
numpages = {2},
pages = {210--211},
timestamp = {2013-06-14T13:05:30.000+0200},
title = {Grounding predictive coding models in empirical neuroscience research},
url = {http://journals.cambridge.org/article_S0140525X1200218X},
volume = 36,
year = 2013
}