Parallels between machine and brain decoding

Authors:
Lorenzo Dell'Arciprete;Brian Murphy;Fabio Massimo Zanzotto
Affiliations:
Artificial Intelligence Research, University of Rome Tor Vergata, Rome, Italy;Machine Learning Department, Carnegie Mellon University, Pittsburgh;Artificial Intelligence Research, University of Rome Tor Vergata, Rome, Italy
Venue:
BI'12 Proceedings of the 2012 international conference on Brain Informatics
Year:
2012

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Abstract

We report some existing work, inspired by analogies between human thought and machine computation, showing that the informational state of a digital computer can be decoded in a similar way to brain decoding. We then discuss some proposed work that would leverage this analogy to shed light on the amount of information that may be missed by the technical limitations of current neuroimaging technologies.