1. Linking cognitive neuroscience and computation with language.

Our old questions: how come we turned out like we did and not otherwise? More technically: what is the nature of the neurocognitive (visual, memory, language...) machine?

Neurocognitive answers:

domain-specificity, modularity, encapsulation, innateness, shallow/rich code, minimal knowledge (just enough to make a mind)...

Computational answers:

memories, input/output differences, hardware/software relations, intelligence vs. intentionality, learnability...

2. Some cognitive science questions for language:

Is language modular? (yes) Is language represented in code? (yes: if computational learning is understood as the relation between computable input, a machine, and the programs the machine outputs [I ---> M ---> P], then linguists usually study the language programs the machine outputs: grammars) Is language computational intelligence or intentionality (both: syntax and phonology concern the former; meaning concerns the latter)

3. So, the cognitive science questions for meaning:

How do expressions as forms get interpretations? How are expressions about the world? What does the interpretation module of language look like? Even more technically: how does the neurocognitive machine compute interpretations for formal linguistic structures?

4. Two kinds of aboutness: pragmatic (language brings about the world: significance), semantic (language depicts the world: truth).

5. Pragmatic meaning can be seen in a mechanistic way (rules of conversation, speech acts and inferences about speakers' and hearers intentional states).

But pragmatic meaning seems to vary significantly with context. Is it therefore core for the interpretation of expressions? In varying, it also seems to lack psychobiological plausibility (though see the work of John Tooby and Leah Cosmides on how the structure of exchange -- the basis of pragmatics -- might be evolutionarily conditioned.)

6. The other kind of intentionality: semantics.

How do we use meaning to get at truth? Basic ideas:

reference vs. sense (intenSionality)

semantic intuitions

meaning-form connections

Two facets of core semantic meaning:

intentionality: minimal content (= conceptual content?)

computational intelligence: minimal semantic form) (= logic?)

7. Some final worries:

Are these computationally feasible?

Could they be part of the factory installed equipment of the neurocognitive machine?