Words in the Brain The Mental Lexicon Sydney Lamb Rice University 8 November 2010 National Taiwan University.

Words in the Brain The Mental Lexicon Sydney Lamb Rice University lamb@rice.edu 8 November 2010 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 Right Interhemispheric fissure (a.k.a. longitudinal fissure)

Corpus Callosum Connects Hemispheres Corpus Callosum

Major Left Hemisphere landmarks Central Sulcus Sylvian fissure

Major landmarks and the four lobes Central Sulcus Sylvian fissure Frontal Lobe Parietal Lobe Temporal Lobe Occipital Lobe

Primary Areas Primary Somato- sensory Area Primary Motor Area Primary Auditory Area Primary Visual Area Central Sulcus Sylvian fissure

Divisions of Primary Motor and Somatic Areas Primary Somato- sensory Area Primary Motor Area Primary Auditory Area Primary Visual Area Mouth Hand Fingers Arm Trunk Leg

Higher level motor areas Primary Somato- sensory Area Actions performed by hand Primary Auditory Area Primary Visual Area Mouth Hand Fingers Arm Trunk Leg Actions per- Formed by leg Actions performed by mouth

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)

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 V C Each node in this diagram represents the cardinal node* of a subweb of properties For example M T *to be defined in a moment!

Add phonological recognition V M C For example, FORK Labels for Properties: C – Conceptual M – Motor P – Phonological image T – Tactile V – Visual T P The phonological image of the spoken form [fork] (in Wernicke’s area) These are all cardinal nodes – each is supported by a subweb

Add node in primary auditory area V M C T P PA Primary Auditory: the cortical structures in the primary auditory cortex that are activated when the ears receive the vibrations of the spoken form [fork] For example, FORK Labels for Properties: C – Conceptual M – Motor P – Phonological image PA – Primary Auditory T – Tactile V – Visual

Add node for phonological production V M C T P PA PP For example, FORK Labels for Properties: C – Conceptual M – Motor P – Phonological image PA – Primary Auditory PP – Phonological Production T – Tactile V – Visual Arcuate fasciculus

Part of the functional web for DOG (showing cardinal nodes only) V M C T P PA PP Each node shown here is the cardinal node of a subweb For example, the cardinal node of the visual subweb

An activated functional web (with two subwebs partly shown) V PR PA M C PP T Visual features C – Cardinal concept node M – Memories PA – Primary auditory PP – Phonological production PR – Phonological recognition T – Tactile V – Visual

Ignition of a functional web from visual input V PR PA M C Art T

V PR PA M C Art T Ignition of a functional web from visual input

V PR PA M C Art T

Ignition of a functional web from visual input V PR PA M C Art T

Speaking as a response to ignition of a web V PR PA M C Art T

Speaking as a response to ignition of a web V PR PA M C Art T From here (via subcortical structures) to the muscles that control the organs of articulation

An MEG study from Max Planck Institute Levelt, Praamstra, Meyer, Helenius & Salmelin, J.Cog.Neuroscience 1998

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/mm 2 of cortical surface: 1460 Minicolumns/cm 2 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 Integration Broadcasting Wow, I got activated! Now I’ll tell my friends!

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 Somato- sensory Area Primary Motor Area Primary Auditory Area Primary Visual Area

Speech Recognition in the Left Hemisphere Primary Auditory Area Phonological Production Wernicke’s Area Phonological Recognition

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 Phonological Recognition Wernicke’s Area Broca’s Area Speech Production

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 V M C T P PA PP Cardinal node of the whole web Cardinal node of the visual subweb Each node shown here is the cardinal node of a subweb

(Part of) the functional web for CAT V P A M C The cardinal node for the entire functional web T 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 noun- verb 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) fei-ji ‘airplane’ fei ‘to fly’ ji ‘machine’ ji wan-ju ‘toy’ wan ‘play’ ju ‘instrument’ ju shui-yi ‘pajamas’ shui ‘to sleep’ yi ‘clothes’ yi wei-qi ‘go (game)’ wei ‘to surround’ qi ‘chess’ qi-lu (lu ‘strategy’) Target Components Response

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) fei-ji ‘airplane’ fei ‘to fly’ ji ‘machine’ ji wan-ju ‘toy’ wan ‘play’ ju ‘instrument’ ju shui-yi ‘pajamas’ shui ‘to sleep’ yi ‘clothes’ yi wei-qi ‘go (game)’ wei ‘to surround’ qi ‘chess’ qi-lu (lu ‘strategy’) Target Components Response

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 well- established 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 AnteriorPosterior fei-ji n. ‘airplane’ fei v. ‘fly’ ji n. ‘machine’ delay

Cortical representation of a compound AnteriorPosterior wan-ju n. ‘toy’ wan v. ‘play’ ju n. ‘thing’ delay

Nodes for phonological recognition (presumably in Wernicke’s area) wa- -an wan wan ‘to play’ demisyllables

Nodes for phonological production (presumably in Broca’s area) w- -an PP wan wan ‘to play’

Phonological nodes for wan ‘to play’ PP wan Internal feedback nodes from PP to PR not shown wa- -an PR wan w- -an

Add (cardinal) concept node for wan PLAY PP wan wa- -an PR wan w- -an

Add node for wan-ju ‘toy’ wan-ju ju Anterior Posterior PLAY PP wan wa- -an PR wan w- -an But this proposal looks too simple

Why wouldn’t it work instead like this? wan-ju ju Anterior Posterior PLAY PP wan wa- -an PR wan w- -an Likely area of damage

First try for wan-ju ‘toy’ wan-ju ju Area of damage? Anterior Posterior PLAY PP wan wa- -an PR wan w- -an We need to add lemma/morpheme nodes

Add lemma node for wan with links PP wan wa- -an PR wan w- -an L wan

Add concept node for wan PLAY PP wan wa- -an PR wan w- -an L wan

Add lemma node for wan-ju ‘toy’ L wan-ju L ju Presumed area of damage Anterior Posterior PLAY PP wan wa- -an PR wan w- -an L wan

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 Phonological recognition Phonological production Nominal concepts Verbal concepts Syntax

Major components of the linguistic system Phonological recognition Phonological production Syntax Verbal concepts Nominal concepts

T h a n k y o u f o r y o u r a t t e n t i o n !

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

Words in the Brain The Mental Lexicon Sydney Lamb Rice University 8 November 2010 National Taiwan University.

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