Wenzao Ursuline College of Languages
Kaohsiung, Taiwan
On the Neurocognitive Basis of Syntax
Sydney Lamb
lamb@rice.edu
2010 November 12
Why is it important to consider the brain?
“I gather…that the status of linguistic theories continues
to be a difficult problem. … I would wish, cautiously, to
make the suggestion, that perhaps a further touchstone
may be added: to what esxtent does the throry tie in with
other, non-linguistic information, for example, the
anatomical aspects of language? In the end such bridges
link a theory to the broader body of scientific knowledge.”
Norman Geschwind
“The development of the brain and the evolution of language”
Georgetown Round Table on Languages and Linguistics, 1964
The two big problems of neurosyntax
How does the brain handle..
Sequencing – ordering of words in a sentence
1.
And ordering of phonemes in a word
–
2.
Categories
–
Noun, Verb, Preposition, etc.
• Subtypes of nouns, verbs, etc.
–
–
–
–
What categories are actually used in syntax?
How are syntactic categories defined?
How represented in the brain?
How does a child build up knowledge of such categories
based on just his/her ordinary language experience?
First step: accounting for sequence
• Important not just for language
– Dancing
– Eating a meal
– Events of the day, of the year, etc.
– Etc., etc.
• In language, not just syntax (lexotactics)
– Ordering of morphemes in a word
• Morphotactics
– Ordering of phonological elements in syllables
• Phonotactics
– Ordering of sememes in a thought
Neurological Structures for Sequence
• How is sequencing implemented in neural
structure?
• For an answer, consider the structure of the
cortical column
Lasting activation in minicolumn
Cell Types
Recurrent axon
branches keep
activation alive in
the column –
Until is is turned
off by inhibitory
cell
Pyramidal
Spiny
Stellate
Inhibitory
Connections to
neighboring
columns not
shown
Subcortical
locations
The ‘Wait’ Element
1
2
www.ruf.rice.edu/~lngbrain/neel
Lasting activation in minicolumn
Cell Types
Recurrent axon
branches keep
activation alive in
the column –
Until is is turned
off by inhibitory
cell
Pyramidal
Spiny
Stellate
Inhibitory
Connections to
neighboring
columns not
shown
Subcortical
locations
Simple notation for lasting activation
Thick border for a node
that stays active for a
relatively long time
Thin border for a node
that stays active for a
relatively short time
N.B.: Nodes are implemented as cortical columns
Recognizing items in sequence
This link
stays
active
This node
recognizes the
sequence ab
c
a
b
Node c is satisfied by activation from both a and b
If satisfied it sends activation to output connections
Node a keeps itself active for a while
Suppose that node b is activated after node a
Then c will recognize the sequence ab
Example: eat apple
(structure for recognition)
(Just labels,
not part of the
structure)
eat apple
eat
apple
Example: eat apple, eat banana
(structure for recognition)
eat apple
eat
apple
eat banana
banana
Producing items in sequence
Wait element
ab
a
b
First a, then b
How does the delay element work?
• Remember: each node is implemented as a cortical column
– Within the column are 75-110 neurons
• Enough for considerable internal structure
• When node ab receives activation, it
– Sends activation on down to node a
– And to the delay element, which
• Waits for activation from clock timer or feedback
– Will come in on line labeled ‘f’ in diagram
• Upon receiving this signal, sends activation on to node b
Producing items in sequence
Delay element
ab
a
f
b
Carries feedback
or clock signal
Producing items in sequence
May be within one
cortical column
ab
a
f
b
Producing items in sequence
a different means
a
b
f
This would apply for items ‘a’ and ‘b’ in
sequence where there is no ‘ab’ to be
recognized as a unit.
Example: Adjectives of size precede
adjectives of color, which precede
adjectives of material in the English noun
phrase, as in big brown wooden box
Two different network notations
Narrow notation
•
•
•
•
Nodes represent cortical columns
Links represent neural fibers
Uni-directional
Close to neurological structure
eat apple
eat
apple
Abstract notation
•
•
•
•
Nodes show type of relationship (OR,
AND)
Easier for representing linguistic
relationships
Bidirectional
Not as close to neurological structure
eat apple
eat
apple
Two different network notations
Narrow notation
b
a
ab
Upward
b
f
a
ab
Abstract notation

Bidirectional
a
b
Downward
b
Constructions have meanings and functions
• They are also signs
Meaning/Function
Form/Expression
The sign
relationship:
a (neural)
connection
The difference is that for a construction the
expression is variable rather than fixed
The transitive verb phrase construction
Semantic
function
Syntactic
function
CLAUSE
DO-TO-SMTHG
Transitive verb phrase
Variable
expression
Vt
NP
Linked constructions
The clause
construction
CL
DO-TO-SMTHG
NP
Transitive verb phrase
Vt
NP
Add a few more connections
ACTOR-DO
CL
DO-TO-SMTHG
Transitive verb phrase
Vt
NP
Add other types of predicate
THING-DESCR
CL
BE-SMTHG
DO-TO-SMTHG
Vi
(A rough first
approximation)
Vt
be
Adj
NP
Loc
The other big problem for syntax
• Categories
• Problems of categories are considered in a separate
presentation
– “Categories in the Brain”
• Lexotactics uses very broad categories
– We can say, e.g., “tried to eat a truck”
• For narrower categories, Semotactics
– So the prototypical goals of EAT are edible objects