Graphical models for cognition

The following visuals should help to communicate my thoughts on cognitive models based on the coordination class model for concepts with added influence from neuroscience research on neuron and neural network characteristics.

Cognition has components...

Some components of cognition have smaller, nested components...

The components of cognition are linked...

Nested components of cognition are linked...

The activity of and relationships among components of cognition are not fully deterministic...


Your feedback is most welcome. I've touched on some of the ways I think this model (stochastic scale-free coordination class) can be supported by experience in the classroom, such as concepts within concepts and student questions that seem "random". What other aspects of cognition and learning do you think this model can support? What aspects of cognition and learning have only limited, if any, representation within this model?

Teaching machines to predict brain states

The semantic web gets a boost from functional MRIs (Lee @ Ars technica)

I'm recommending that you take a moment to read the above-linked interesting post over at Ars technica on an article recently published in Science. The post discusses the research in the article, which involved training a neural network to create a sense of meaning for a variety of nouns and verbs, and then linking the neural network's meaning for those words with fMRI brain scans of humans thinking about those words. The neural network was then challenged to predict fMRI patterns of brain activation associated with the words it had developed meanings for, but hadn't already linked with existing fMRI scans - it performed quite well, and continued to perform better than random chance would suggest as the prediction task became less linked to the original word set.