Last updated 6Jan2003
The text that describes my model does not contain references, because the relevant references are all the data that we have about human behavior and about the human brain. Even if a very restricted definition of the term 'data' is used (e.g only controlled experiments) this is far too much. This leaves two options:
The problem with the first option, (apart from requiring more work and making the text larger), is that it introduce a bias towards consideration of the included references, and ignoring others. This is bad, because I don't think any reference is more important than others. In fact, I believe one of the major failures of many other models is that they concentrate on explaining some data, and ignore the rest. A model of human cognition has to explain (be compatible with) all the data about human cognition.
Instead of listing references, I invite the reader to pick up what he/she thinks the most important data, and see if it is compatible with the model. This relies on the user knowing enough about cognitive psychology, neurobiology and related areas to find the data himself/herself.
For readers that feel less safe in any of these areas, here are my recommendations of the right approach for further reading. These relies on the reader to be ready to put significant amount of effort in the subject.
[18Feb2002] The reasonability of textbooks in neuroscience is not absolute. Some imaginary concepts do succeed to enter them, and it is not always easy to figure it out. For example, the "columnar organization" of the cortex appear in most new books, even though it is mostly fictitious (Example).
[4Jan2003] It is getting worse. Here is an example of a straightforward false statement, accompanied by a figure that makes the false concept very clear.
[6 Nov 2004] for a non-nonsense research on how the cerebral cortex actually looks, without imposing "theoretical" (i.e. prejudicial) biases, Kathleen Rockalnd research is the best that I can find (latest pubished article, Ichinohe and Rockland, Cerebral Cortex 2004 14(11):1173-1184; Note that they use 'modularity' to mean 'patchiness').
That shouldn't stop you from trying to find good models, mainly because it is a good practice of critical reading, and also on the off-chance that there is any useful model around. If you find a model that is neurobiologically plausible, and explains anything more interesting that eye blinking, let me know. You can also try to see how many of the reasoning errors that I list in the Reasoning Errors page applies to it.
However, it is important to note that acquaintance with computers is far from being sufficient for developing this skill. This is because the translation between complex and simple operators is different in different systems. Learning the translation in one system does not guarantee a better understanding of the translation in a different system. The important thing to learn is the principles which are involved in the translation, and most of people, including computer scientists, don't understand this.