8 November 2010
Words in the Brain
The Mental Lexicon
Sydney Lamb
Rice University
lamb@rice.edu
National Taiwan University
Information about a word
• In ordinary dictionaries
– an entry for each word
– all the information pertaining to that word is given there
• Phonological, graphic, grammatical, semantic
– all together in one place
• In the brain
– The situation is entirely different
• Each word is represented as a large network
• Different kinds of information in different locations
• So also each phrase that is learned as a unit
Why is this interesting?
• Knowledge of how words are represented in the brain provides
– the key to understanding linguistic structure
– sheds light on how the brain works in general
• Surprisingly, neuroscientists can’t tell us how the brain
processes information
– To ask them is like asking an electronic engineer how a
computer calculates the orbit of a satellite or how a
computer translates a weather report from Mandarin to
English
• For the latter question it is better to ask a linguist
– Similarly, if you want to know how the human processes
language, better to ask a neurocognitive linguist
Two views of the lexical entry
• 1 – The compact entry (as in ordinary dictionaries)
• All the information is there in one place – the lexical entry
– Accessing the information
• Retrieval
– First, locate the information (requires searching)
– Then “read” it
• 2 – The distributed entry
• The information is distributed among different locations
– Accessing the information
• Activation
– Follow the connections (no search required)
The compact lexical entry
(in an external lexicon)
• Heading
– Needed to locate the entry
– A graphic representation
• Exposition – the information – other than graphic
– Phonological
– Grammatical (e.g., Noun, Verb transitive)
– Semantic – meanings
– (also, etymological information)
The distributed “entry”
(a functional web)
• “Entry” is not the best term, since it is too closely
associated with the familiar compact entry
• Better: “Functional Web” (term from Pulvermüller 2002)
• Kinds of information – in different parts of the web
– Conceptual
– Perceptual
– Grammatical
– Phonological
• Production
• Recognition
• All of these are interconnected
Topics in this presentation
•
•
•
•
•
Introductory neuroanatomy
Functional webs
Phonology in the brain
Hierarchy and Cardinal Nodes
Nouns and verbs
Topics
•
•
•
•
•
Introductory neuroanatomy
Functional webs
Phonology in the brain
Hierarchy and Cardinal Nodes
Nouns and verbs
The brain
•
•
•
•
•
Medulla oblongata – Myelencephalon
Pons and Cerebellum – Metencephalon
Midbrain – Mesencephalon
Thalamus and hypothalamus – Diencephalon
Cerebral hemispheres – Telencephalon
– Cerebral cortex
– Basal ganglia
– Basal forebrain nuclei
– Amygdaloid nucleus
Two hemispheres
Left
Interhemispheric fissure
(a.k.a. longitudinal
fissure)
Right
Corpus Callosum Connects Hemispheres
Corpus
Callosum
Major Left Hemisphere landmarks
Central Sulcus
Sylvian fissure
Major landmarks and the four lobes
Central Sulcus
Frontal
Lobe
Sylvian fissure
Parietal
Lobe
Temporal
Lobe
Occipital
Lobe
Primary Areas
Central Sulcus
Primary Somatosensory Area
Primary
Motor Area
Primary Auditory
Area
Sylvian fissure
Primary
Visual Area
Divisions of Primary Motor and Somatic Areas
Leg
Primary
Motor Area
Primary Somatosensory Area
Trunk
Arm
Hand
Fingers
Mouth
Primary Auditory
Area
Primary
Visual Area
Higher level motor areas
Actions perFormed by leg
Actions
performed
by hand
Leg
Primary Somatosensory Area
Trunk
Arm
Hand
Fingers
Actions
performed
by mouth
Mouth
Primary Auditory
Area
Primary
Visual Area
Hierarchy in cortical development
Coronal Section
Gray
matter
White
matter
The gray matter
• Color: gray
• About 3 mm thick
• Consists of columns of cell bodies 3 mm long
– “Cortical columns”
– Each column extends from top to bottom
of the gray matter
• Therefore, the gray matter, topologically, is a
two-dimensional array of cortical columns
Layers of the Cortex
From top
to bottom,
about 3
mm
The White Matter
• Provides long-distance connections
Some long-distance fiber bundles
(schematic)
Topological essence of cortical structure
(known facts from neuroanatomy)
• The thickness of the cortex is entirely accounted for by the columns
• Hence, the cortex is an array of nodes
– A two-dimensional structure of interconnected nodes (columns)
• Third dimension for
– Internal structure of the nodes (columns)
– Cortico-cortical connections (white matter)
Dimensionality of the cortex
• Two dimensions: The array of nodes
• The third dimension:
– The length (depth) of each column (through
the six cortical layers)
– The cortico-cortical connections (white matter)
Some things that are now well established
• The brain is a network
– Composed, ultimately, of neurons
• Neurons are interconnected
– Axons (with branches)
– Dendrites (with branches)
• Activity travels along neural pathways
– Cortical neurons are clustered in columns
• Columns come in different sizes
– The smallest: minicolumn – 70-110 neurons
• Each minicolumn acts as a unit
– When it becomes active all its neurons are active
• Locations of various kinds of “information”
– Visual, auditory, tactile, motor, …
Deductions from known facts
• All the information in the brain has the form of a
network
– (the “human information system”)
• Therefore a person’s linguistic and conceptual
system is a network
– (part of the information system)
• Every lexeme and every concept is a sub-network
– Term: functional web (Pulvermüller 2002)
Topics
•
•
•
•
•
Introductory neuroanatomy
Functional webs
Phonology in the brain
Hierarchy and Cardinal Nodes
Nouns and verbs
Hypothesis I: Functional Webs
•
•
A word is represented in the cortex as a functional web
Spread over a wide area of cortex
– Includes perceptual information
– As well as specifically conceptual information
• For nominal concepts, mainly in
– Angular gyrus
– (?) For some, middle temporal gyrus
– (?) For some, supramarginal gyrus
– Plus phonological information
Example: The concept DOG
• We know what a dog looks like
– Visual information, in occipital lobe
• We know what its bark sounds like
– Auditory information, in temporal lobe
• We know what its fur feels like
– Somatosensory information, in parietal lobe
• All of the above..
– constitute perceptual information
– are subwebs with many nodes each
– have to be interconnected into a larger web
– along with further web structure for conceptual information
Building a model of a functional web:
First steps
Each node in this diagram
represents the cardinal node* of a
subweb of properties
T
C
M
For example
V
*to be defined in a moment!
Add phonological recognition
For example, FORK
C
T
M
P
V
These are all
cardinal nodes –
each is supported
by a subweb
Labels for Properties:
C – Conceptual
M – Motor
P – Phonological image
T – Tactile
V – Visual
The phonological image
of the spoken form [fork]
(in Wernicke’s area)
Add node in primary auditory area
For example, FORK
C
T
M
P
PA
V
Labels for Properties:
C – Conceptual
M – Motor
P – Phonological image
PA – Primary Auditory
T – Tactile
V – Visual
Primary Auditory: the cortical structures in the primary
auditory cortex that are activated when the ears receive
the vibrations of the spoken form [fork]
Add node for phonological production
For example, FORK
C
T
M
P
PP
PA
Arcuate fasciculus
V
Labels for Properties:
C – Conceptual
M – Motor
P – Phonological image
PA – Primary Auditory
PP – Phonological Production
T – Tactile
V – Visual
Part of the functional web for DOG
(showing cardinal nodes only)
Each
node
shown
here is
the
cardinal
node of
a
subweb
T
M
PP
C
P
PA
V
For example,
the cardinal
node of the
visual subweb
An activated functional web
(with two subwebs partly shown)
T
C
PP
PR
PA
M
C – Cardinal concept node
M – Memories
PA – Primary auditory
PP – Phonological production
PR – Phonological recognition
T – Tactile
V – Visual
V
Visual features
Ignition of a functional web from visual input
T
C
PR
Art
PA
M
V
Ignition of a functional web from visual input
T
C
PR
Art
PA
M
V
Ignition of a functional web from visual input
T
C
PR
Art
PA
M
V
Ignition of a functional web from visual input
T
C
PR
Art
PA
M
V
Ignition of a functional web from visual input
T
C
PR
Art
PA
M
V
Ignition of a functional web from visual input
T
C
PR
Art
PA
M
V
Ignition of a functional web from visual input
T
C
PR
Art
PA
M
V
Ignition of a functional web from visual input
T
C
PR
Art
PA
M
V
Ignition of a functional web from visual input
T
C
PR
Art
PA
M
V
Ignition of a functional web from visual input
T
C
PR
Art
PA
M
V
Ignition of a functional web from visual input
T
C
PR
Art
PA
M
V
Ignition of a functional web from visual input
T
C
PR
Art
PA
M
V
Ignition of a functional web from visual input
T
C
PR
Art
PA
M
V
Ignition of a functional web from visual input
T
C
PR
Art
PA
M
V
Speaking as a response to ignition of a web
T
C
PR
Art
PA
M
V
Speaking as a response to ignition of a web
T
C
PR
Art
PA
M
V
Speaking as a response to ignition of a web
T
C
PR
Art
PA
M
From here (via subcortical
structures) to the muscles that
control the organs of articulation
V
An MEG study from Max Planck Institute
Hypothesis II:
Nodes as Cortical Columns
• Nodes are implemented as cortical columns
• Information is represented in the cortex in the form of
functional webs (Hypothesis I)
– A functional web is a network within the cortical
network as a whole
• consisting of nodes and their interconnections
– connections represented in graphs as lines
• The interconnections are represented by inter-columnar
neural connections and synapses
– Axonal fibers
– Dendritic fibers
The node as a cortical column
• The properties of the cortical column are approximately
those described by Vernon Mountcastle
– Mountcastle, Perceptual Neuroscience, 1998
• Additional properties of columns and functional webs can
be derived from Mountcastle’s treatment together with
neurolinguistic findings
– Method: “connecting the dots”
• Hypothesis IV: (Coming Soon!)
“[T]he effective unit of operation…is not the
single neuron and its axon, but bundles or
groups of cells and their axons with similar
functional properties and anatomical
connections.”
Vernon Mountcastle, Perceptual
Neuroscience (1998), p. 192
Evidence for columns
• Experiments on living cats, monkeys, rats
• Microelectrode penetrations in cortex
• If perpendicular to cortical surface
– Neurons all of same response properties
• If not perpendicular
– Neurons of different response properties
• Conclusion: All neurons of a single column respond to stimuli
– alike
– and differently from those of adjacent columns
Microelectrode penetrations in the
paw area of a cat’s cortex
Columns for orientation of lines (visual cortex)
Microelectrode
penetrations
K. Obermayer & G.G. Blasdell, 1993
The (Mini)Column
• Width is about (or just larger than) the diameter of a single
pyramidal cell
– About 30–50 m in diameter
• Extends thru the six cortical layers
– Three to six mm in length
– The entire thickness of the cortex is accounted for by the
columns
• Roughly cylindrical in shape
• If expanded by a factor of 100, the dimensions would correspond
to a tube with diameter of 4 mm and length of 30 – 40 cm
Cortical Column Structure
• Minicolumn 30-50 microns diameter
• Recurrent axon collaterals of pyramidal neurons activate
other neurons in same column
• Inhibitory neurons can inhibit neurons of neighboring
columns
– Function: contrast
• Excitatory connections can activate neighboring columns
– In this case we get a bundle of contiguous columns
acting as a unit
Another Quotation
“Every cellular study of the auditory
cortex in cat and monkey has
provided direct evidence for its
columnar organization.”
Vernon Mountcastle (1998:181)
Cortical minicolumns: Quantities
•
•
•
•
•
•
Diameter of minicolumn: 30 - 40 microns
Neurons per minicolumn: 70-110 (avg. 75-80)
Minicolumns/mm2 of cortical surface: 1460
Minicolumns/cm2 of cortical surface: 146,000
Neurons under 1 sq mm of cortical surface: 110,000
Approximate number of minicolumns in Wernicke’s
area: 2,920,000 (at 20 sq cm for Wernicke’s area)
Adapted from Mountcastle 1998: 96
Nodal interconnections
(known facts from neuroanatomy)
• Nodes (columns) are connected to
– Nearby nodes
– Distant nodes
• Connections to nearby nodes are either excitatory or inhibitory
– Via horizontal axons (through gray matter)
• Connections to distant nodes are excitatory only
– Via long (myelinated) axons of pyramidal neurons
Local and distal connections
excitatory
inhibitory
Findings relating to columns
(Mountcastle, Perceptual Neuroscience, 1998)
• The column is the fundamental module of
perceptual systems
– probably also of motor systems
• Perceptual functions are very highly localized
– Each column has a very specific local function
• This columnar structure is found in all
mammals that have been investigated
• The theory is confirmed by detailed studies of
visual, auditory, and somatosensory perception
in living cat and monkey brains
Hypothesis III: Nodal Specificity
in functional webs
• Every node in a functional web has a specific function
• The nodes in each area of a functional web
– Constitute a subweb
– Their function fits the portion of cortex in which they
are located
• For example,
– Phonological recognition in Wernicke’s area
– Visual subweb in occipital and lower temporal lobe
– Tactile subweb in parietal lobe
– Each node of a subweb also has a specific function
within that of the subweb
Support for Nodal Specificity: the paw
area of a cat’s cortex
Column (node) represents
specific location on paw
Support for Nodal Specificity:
Columns for orientation of lines (visual cortex)
Microelectrode
penetrations
K. Obermayer & G.G. Blasdell, 1993
Hypothesis III(a): Adjacency
• Nodes of related function are in adjacent
locations
– More closely related function, more closely
adjacent
• Examples:
– Adjacent locations on cat’s paw
represented by adjacent cortical locations
– Similar line orientations represented by
adjacent cortical locations
Support for Nodal adjacency: the paw
area of a cat’s cortex
Adjacent column in cortex
for adjacent location on paw
Extrapolation to Language?
• Our knowledge of cortical columns comes mostly from studies
of perception in cats, monkeys, and rats
• Such studies haven’t been done for language
– Cats and monkeys don’t have language
– That kind of neurosurgical experiment isn’t done on human
beings
• Are they relevant to language anyway?
– Relevant if language uses similar cortical structures
– Relevant if linguistic functions are like perceptual functions
Hypothesis IV: Extrapolation to Humans
• Hypothesis: The findings about cortical structure and
function from experiments on cats, monkeys, and rats can
be extrapolated to human cortical structure and function
• In fact, this hypothesis is simply assumed to be valid by
neuroscientists
• Why? We know from neuroanatomy that, locally,
– Cortical structure is relatively uniform across mammals
– Cortical function is relatively uniform across mammals
Hypothesis IV(a):
Linguistic and conceptual structure
• Hypothesis IV(a): The extrapolation can be extended to
linguistic and conceptual structures and functions
• Why?
– Local uniformity of cortical structure and function across
all human cortical areas except for primary areas
• Primary visual and primary auditory are known to
have specialized structures, across mammals
• Higher level areas are – locally – highly uniform
Objection
• Cats and monkeys don’t have language
• Therefore language must have unique properties of its
structural representation in the cortex
• Answer: Yes, language is different, but
– The differences are a consequence not of different
(local) structure but differences of connectivity
– The network does not have different kinds of
structure for different kinds of information
• Rather, different connectivities
Uniformity of cortical structure
• What distinguishes one kind of information from
another is what it is connected to
• Lines and nodes are approximately the same all over
• Similarly, uniformity of cortical structure
– Same kinds of columnar structure
– Same kinds of neurons
– Same kinds of connections
• Different areas have different functions because of
what they are connected to
Topics
•
•
•
•
•
Introductory neuroanatomy
Functional webs
Phonology in the brain
Hierarchy and cardinal nodes
Nouns and verbs
The phonological forms of words in the brain:
in symbolic form?
• Let us suppose that they are stored in some
kind of symbolic form
• What form?
– Written symbols as in a dictionary?
• If written, there would have to be..
– something in there that can read them
– something in there that can write them
– something in there that can move them
around, from one place to another
– something in there to compare them with
forms entering the brain as it hears
someone speaking – otherwise, how can
an incoming word be recognized?
There must be another way
The alternative
• The information is in operational form
• For a syllable, two operations
– Recognition: Activation of the subweb
representing the phonological image
– Production: Activation of the motor image
• to produce it
How the brain operates
• It is a network
• Operation consists of activation traveling along
pathways of the network
– From node (column) to node, along neural fibers
• The operation is controlled by the individual nodes
– Integration: A node receives activation from
connecting fibers
– Broadcasting: when activated, it sends activation
out along its output fibers (axons)
Functions of Cortical Columns
• Integration: A column is activated if it receives
enough activation from
– Other columns
– Thalamus
• Can be activated to varying degrees
• Can keep activation alive for a period of time
• Broadcasting: An activated column transmits
activation to other columns
– Exitatory
– Inhibitory
• Learning : adjustment of connection strengths
and thresholds
Integration and Broadcasting
 Broadcasting
• To multiple locations
• In parallel
 Integration
Integration and Broadcasting
Broadcasting
Integration
Now I’ll tell my friends!
Wow, I got activated!
Operations in relational networks
• Activation moves along lines and through nodes
– Integration
– Broadcasting
• Connection strengths are variable
– A connection becomes stronger with repeated
successful use
– A stronger connection can carry greater activation
Primary Areas in LH
Primary Somatosensory Area
Primary
Motor Area
Primary Auditory
Area
Primary
Visual Area
Speech Recognition in the Left Hemisphere
Phonological
Production
Primary Auditory
Area
Wernicke’s Area
How a syllable is recognized
• Prerequisite: you need knowledge of the phonology
– A functional subweb for phonological recognition
– In Wernicke’s area – posterior superior temporal gyrus
– It represents the phonological image of the syllable
• Activation travels from the primary auditory area to the
phonological image
Speech Production in the Left Hemisphere
Speech
Production
Broca’s Area
Phonological
Recognition
Wernicke’s Area
Broca’s area, Wernicke’s area,
and Arcuate Fasciculus
www.rice.edu/langbrain
The arcuate fasciculus consists of several hundred thousand axons
Topics
•
•
•
•
•
Introductory neuroanatomy
Functional webs: Six Hypotheses
Phonology in the brain
Hierarchy and cardinal nodes
Nouns and verbs
Hypothesis V:
Hierarchy in functional webs
• A functional web is hierarchically organized
– Bottom levels in primary areas
– Lower levels closer to primary areas
– Higher (more abstract) levels in
• Associative areas – e.g., angular gyrus
• Executive areas – prefrontal
• These higher areas are much larger in
humans than in other mammals
• Hypothesis V(a): Each subweb is likewise
hierarchically organized
Properties of Hierachy
• Each level has fewer nodes than
lower levels, more than higher levels
– Compare the organization of
management of a corporation
• Top level has just one node
– Compare the “CEO”
Hypothesis VI: Cardinal nodes
• Every functional web has a cardinal node
– At the top of the entire functional web
– Unique to that concept
– For example, C/cat/ at “top” of the web for CAT
• Hypothesis VI(a):
– Each subweb likewise has a cardinal node
• At the top level of the subweb
• Unique to that subweb
• For example, V/cat/
– At the top of the visual subweb
Cardinal nodes of a functional web
Some of the cortical structure relating to fork
Each
node
shown
here is
the
cardinal
node of
a
subweb
Cardinal
node of the
whole web
T
M
PP
C
P
PA
V
Cardinal
node of
the visual
subweb
(Part of) the functional web for CAT
The cardinal node for the
entire functional web
T
C
P
A
M
V
Cardinal nodes of
the subwebs
Support for cardinal nodes
Example: FORK
• The distributed network as a whole represents the
•
•
concept of forks
The whole can evidently be activated by any part of
the network
– From seeing a fork
– From eating with a fork
– Etc.
The cardinal node provides the coordinated
organization that makes such reactivation possible
Reactivating the functional web
• When the cardinal node (the integrating node) is activated,
it can activate the whole (distributed) functional web
– Without it, how would that be possible?
– E.g., activating conceptual and perceptual properties of
cat upon hearing the word cat
– From phonological recognition to concepts
– From visual image to phonological representation
Cardinal nodes and the linguistic sign
•
•
Connection of conceptual to phonological representation
Consider two possibilities
1. A cardinal node for the concept connected to a
cardinal node for the phonological image
2. No cardinal nodes: multiple connections between
concept representation and phonological image
• supported by Pulvermüller (2002)
Implications of possibility 2
•
•
•
•
No cardinal nodes: multiple connections between
concept representation and phonological image
I.e., different parts of meaning connected to
different parts of phonological image
Consider fork
– Maybe /f-/ connects to the shape?
– Maybe /-or-/ connects to the feeling of holding
a fork in the hand?
– Maybe /-k/ connects to the knowledge that
fork is related to knife?
Conclusion: Possibility 2 must be rejected
Topics
•
•
•
•
•
Introductory neuroanatomy
Functional webs: Six Hypotheses
Phonology in the brain
Hierarchy and cardinal nodes
Nouns and verbs
Broca’s Aphasia
•
•
•
•
Damage to frontal lobe
Largely intact comprehension
Nonfluent, agrammatic speech
“Telegraphic speech” –
– Abundance of content words (e.g., nouns)
– Lack of function words (e.g. prepositions)
• Impaired verb processing
Wernicke’s Aphasia
• Damage to temporal lobe (and/or angular
gyrus and/or SMG)
• Impaired comprehension
• Fluent, grammatical, neologistic speech
• Impaired noun processing
Evidence from Chinese (Bates et al. 1991)
• Chinese has virtually no inflectional morphology for
nouns or verbs
• Therefore, if the noun-verb dissociation occurs in the
speech of Chinese-speaking Broca’s and Wernicke’s
aphasics, the dissociation cannot be due to a
difference in nominal and verbal morphology
Bates, E., Chen, S., Tzeng, O., Li, P., & Opie, M. (1991). The nounverb problem in Chinese aphasia. Brain and Language, 41, 203-233.
Study by Sylvia Chen
• Sylvia Chen, a graduate student of Elizabeth
Bates at UC San Diego
• Subjects:
– Ten Broca aphasics
• Reduced fluency and phrase length
• Tendency to omit function words
– Ten Wernicke aphasics
• Impaired comprehension
• Fluent or hyperfluent speech
• Marked word-finding difficulties
• Semantic paraphasias
Nouns and Verbs in Chinese
• Most nouns and verbs are disyllabic
– Most morphemes are monosyllabic
– Therefore, the nouns and verbs are compounds
– Common types: V-N, N-N
• Many have more than two syllables
• Such compounds are learned as units
– Like complex lexemes in any language
• Cf. hot dog, Zhong-guo
Chen’s experiment
• Patients were tested in their ability to name
– Pictures of objects (nominal compounds)
– Pictures of common actions (verbal compounds)
• All of the compounds have the form V-N
– 13 verbal V-N compounds
– 28 nominal V-N compounds
Chinese V-N Compounds
• The experiment was concerned with
disyllabic compounds of form V-N
• Some are nouns, some are verbs
• fei v. ‘to fly’ + ji n. ‘machine’
– feiji n. ‘airplane’
• chi v. ‘to eat’ + fan n. ‘rice’
– chifan v. ‘to have a meal’
The Experimental Task
• 10 Broca’s aphasics, 10 Wernicke’s aphasics
• Test with nominal compounds
– Produce a word to describe a picture of an object
• Test with verbal compounds
– Produce a word to describe a picture of an action
(Sylvia Chen – UCSD dissertation)
Typical Errors of Broca aphasics
(for nominal compounds)
Target
Components
Response
fei-ji
‘airplane’
fei ‘to fly’
ji ‘machine’
ji
wan-ju
wan ‘play’
‘toy’
ju ‘instrument’
shui-yi
shui ‘to sleep’
yi ‘clothes’
‘pajamas’
wei-qi
‘go (game)’
wei ‘to surround’
qi ‘chess’
ju
yi
qi-lu
(lu ‘strategy’)
Summary of findings
• Broca aphasics
– Difficulty producing verbal components for both verbal
and nominal compounds
• Wernicke aphasics
– Difficulty with noun components of verbal compounds
– More general and varied difficulties with nominal
compounds
• Responses did not indicate that patients had trouble with
the semantics of the target items
• This despite the fact that these are compounds and are
doubtless learned as units by speakers of Chinese
“Potency” of components of compounds
1. Semantic potency
• Q: Do the meanings of the constituents have a bearing
on the meaning of the composite?
– understand
– hot dog
– blackboard
– bluebird
• A: Sometimes yes, sometimes no
– Complex lexemes have a scale of transparency
• From transparent (bluebird)
• To opaque (understand)
– Opaque lexemes are known as ‘idioms’
Potency of constituents of compunds
2. Grammatical potency
• Q: Do the grammatical categories of the constituents of a
compound have a bearing on properties of the composite?
• Evidence for positive answer:
– In Chinese aphasics with impaired verb access,
nominal compounds are also affected if they have
verbal components
Evidence for intact semantics
• The subjects did not have difficulty with the semantics of the pictures,
but only with the means of providing linguistic representations
• Example:
– Target: jiao-hua v. ‘to water flowers
• jiao v. ‘to water’ + hua n. ‘flower’
– Response: *hua-shui (shui n. ‘water’)
– Indicates that the (Broca’s aphasic) patient understood the
meaning while failing to produce the verbal component of the
standard compound
Sylvia Chen (UCSD dissertation)
Errors of Broca aphasics
(for nominal compounds)
Target
Components
fei-ji
‘airplane’
fei ‘to fly’
ji ‘machine’
wan-ju
wan ‘play’
‘toy’
ju ‘instrument’
shui-yi
shui ‘to sleep’
yi ‘clothes’
‘pajamas’
wei-qi
‘go (game)’
wei ‘to surround’
qi ‘chess’
Response
ji
ju
yi
qi-lu
(lu ‘strategy’)
Conclusions of Chen’s Experiment
• Verb components and noun components
are represented differently in the cortex
• This differential representation of the
components is independent of the
representation of the compound as a
whole, even for compounds that are wellestablished and frequently occurring (i.e.
well entrenched)
Why is this interesting?
• If a lexeme is learned as a unit, why should
the components make a difference?
– If lexemes are stored as units, the
grammatical categories of their
components shouldn’t matter
• If it is a noun, why should a Broca aphasic
have trouble with it?
– Of course, we know from the experiment
that it is because it has a verbal
component
• Moreover, some of these compounds are
well-entrenched
• How to explain?
Inferences from Chen’s Experiment
• Verbal components of compounds are represented in the
frontal lobe, even when they are components of nominal
compounds (like ‘airplane’) that, as nouns, are presumably
represented in the posterior cortex
• The situation can only be understood in the context of a
distributed network (rather than symbolic) representation of
the linguistic information
Cortical representation of a compound
Anterior
Posterior
fei-ji n. ‘airplane’
delay
fei v. ‘fly’
ji n. ‘machine’
Cortical representation of a compound
Anterior
Posterior
wan-ju n. ‘toy’
delay
wan v. ‘play’
ju n. ‘thing’
Nodes for phonological recognition
(presumably in Wernicke’s area)
wan ‘to play’
wan
wa-
demisyllables
-an
Nodes for phonological production
(presumably in Broca’s area)
wan ‘to play’
PPwan
w-
-an
Phonological nodes for wan ‘to play’
PPwan
w-
-an
PRwan
wa-
Internal feedback nodes
from PP to PR not shown
-an
Add (cardinal) concept node for wan
PLAY
PRwan
PPwan
w-
-an
wa-
-an
Add node for wan-ju ‘toy’
Anterior
But this proposal looks
too simple
Posterior
wan-ju
PLAY
ju
PPwan
w-
PRwan
-an
wa-
-an
Why wouldn’t it work instead like this?
Anterior
Posterior
wan-ju
PLAY
ju
PPwan
Likely area
of damage
w-
PRwan
-an
wa-
-an
First try for wan-ju ‘toy’
Anterior
We need to add
lemma/morpheme
nodes
Posterior
wan-ju
PLAY
ju
PPwan
Area of
damage?
w-
PRwan
-an
wa-
-an
Add lemma node for wan
with links
Lwan
PRwan
PPwan
w-
-an
wa-
-an
Add concept node for wan
PLAY
Lwan
PRwan
PPwan
w-
-an
wa-
-an
Add lemma node for wan-ju ‘toy’
Lwan-ju
Anterior Posterior
PLAY
Lju
Lwan
PRwan
PPwan
Presumed
area of
damage
w-
-an
wa-
-an
The beauty of this account
• Consistent with the lack of impairment of semantic connections
• The node for the compound is unimpaired
– Represents an object
– Therefore, likely to be in posterior cortex
• Consistent with patient’s ability to comprehend speech
• Consistent with diagnosis of Broca’s aphasia
• The trouble is just with production of the verbal component
(lemma) of the compound
Conclusions
• Nouns and verbs are discretely represented in the cortex
• Cardinal lemma and concept nodes for nouns are
represented in posterior regions (temporal and/or parietal)
• Cardinal lemma and concept nodes for verbs are
represented in anterior regions (frontal lobe)
• The differences between the representations of nouns and
verbs pertain to their lemma nodes as well as to their
respective semantic-conceptual representations
Major components of the linguistic system
Verbal
concepts
Syntax
Phonological
production
Nominal
concepts
Phonological
recognition
Major components of the linguistic system
Verbal
concepts
Syntax
Phonological
production
Nominal
concepts
Phonological
recognition
Topics
•
•
•
•
•
Introductory neuroanatomy
Functional webs
Phonology in the brain
Hierarchy and Cardinal Nodes
Nouns and verbs
Thank you for your attention!
References
Boroditsky, Lera, Schmidt, Phillips. 2003. Sex, syntax, and semantics.
Language in Mind (eds. Dedre Gentner & Susan Goldin-Meadow), MIT
Press.
Geschwind, Norman. 1964. The development of the brain and the
evolution of language. Georgetown Round Table on Languages and
Linguistics 17.155-169.
Lamb, Sydney, 1999. Pathways of the Brain: The Neurocognitive Basis of
Language. John Benjamins.
Lamb, sydney M. & Xiuhong Zhang. 2010. The mental representation of
Chinese compounds: evidence from aphasia. Journal of Chinese
Linguistics 38.26-44.
Mountcastle, Vernon, 1998. Perceptual Neuroscience:The Cerebral
Cortex. Harvard University Press.
Pulvermüller, Friedemann, 2002. The Neuroscience of Language.
Cambridge University Press
Whorf, Benjamin Lee. 1956. Language, Thought, and
Reality (ed. John B. Carroll). MIT Press.
For further information . .
www.rice.edu/langbrain
lamb@rice.edu