Brain dump: How publicly available fMRI can help inform neuronal network architecture

Towards the Cognitive Informatics of Natural Language

“…As the bulk of the paper below will demonstrate, the success of computational humor depends in large part on fusing information from numerous sources, both of a linguistic and extra-linguistic nature, including implicit information available to a human from his/her knowledge of a specific situation and of the world, in general, including multimodality (cf., again, Sun et al 2013, Paolercio et al 2013. Humor research in general goes well beyond natural language into images (Hempelmann 2008), music, physical comedy, non-verbal stand-up acts, etc. An integral part of cognitive informatics, aggressively claiming a pretty central place to natural language as the best window to the mind that researchers have, our research is also closely related to cognitive computing (see, for instance, Wang , 2012Rao 2013, Borg et al 2006, accepting the premise that natural language computing should be informed by what we discover about the structure and functioning of the brain, even as the latest fMRI data pretty much break down the initial naïve modular structure of the brain, especially as far as natural language is concerned: the new results bring in more and more fine-grained data on much more complexity of language activities (see, for instance, Fariello 2013, Deen & Saxe 2012, Dufour et al 2012, Jara-Ettinger et al 2012, Crowder et al 2012.…”

Perspectives on Cognitive Computers and Knowledge Processors

“…Philosophers of Epistemology from Plato (1978) to Hume (1749) and Kant (1901), to Dennett (1749) have long wrestled with questions of just how accurate our knowledge representations of the world really can be and how we are able to learn, develop, or construct accurate knowledge representations; with no settled answers yet. As we move further in the development of cognitive informatics models of neural activity and the brain such as those presented in keynotes at the ICCI*CC2013 conference by Wang (2013) for denotational mathematical and logical models of the brain and cognitive activity and by Fariello (2013) and Rao (2013) for neural connectivity and functional neural networks, this central question of purpose is critical to trying to understand and model the brain.…”