On the Neurocognitive Basis of Language Sydney Lamb l amb@rice

1. Wenzao Ursuline College of Languages Kaohsiung, Taiwan On the Neurocognitive Basis of LanguageSydney Lamblamb@rice.edu 2010 November 12

2. 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

3. Topics A little neuroanatomy Functional webs Nodes and links: Cortical columns Basic operations in the cortex More operations: Learning

4. Topics A little neuroanatomy Functional webs Nodes and links: Cortical columns Basic operations in the cortex Syntax More operations: Learning

5. 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

6. Two hemispheres Right Left Interhemispheric fissure (a.k.a. longitudinal fissure)

7. Corpus Callosum Connects Hemispheres Corpus Callosum

8. Major Left Hemisphere landmarks CentralSulcus Sylvian fissure

9. Major landmarks and the four lobes CentralSulcus Parietal Lobe Frontal Lobe Occipital Lobe Temporal Lobe Sylvian fissure

10. Some brain facts – now well established Locations of various kinds of “information” Visual, auditory, tactile, motor, … 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

11. Deductions from known facts Everything represented 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 lexical entry and every concept is a sub-network Term: functional web(Pulvermüller 2002)

12. Primary Areas Primary Somato- sensory Area CentralSulcus Primary Motor Area Primary Auditory Area Primary Visual Area Sylvian fissure

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

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

15. Hierarchy in cortical development

16. Topics A little neuroanatomy Functional webs Nodes and links: Cortical columns Basic operations in the cortex Syntax More operations: Learning

17. Hypothesis I: Functional Webs A word is represented as a functional web Spread over a wide area of cortex Meaning 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

18. 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

19. Building a model of a functional web:first steps Each node in this diagram represents the cardinal node* of a subweb of properties For example C T M Let’s zoom in on this one V *to be defined in a moment!

20. Zooming in on the “V” Node.. A network of visual features Cardinal V-node Etc. etc. (many layers)

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

44. Topics A little neuroanatomy Functional webs Nodes and links: Cortical columns Basic operations in the cortex More operations: Learning

45. Hypothesis 2: Nodes as Cortical Columns Nodes are implemented as cortical columns The interconnections are represented by inter-columnar neural connections and synapses Axonal fibers – neural output Dendritic fibers – neural input

46. 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

47. Quote from Mountcastle “[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

48. Three views of the gray matter Different stains show different features

49. Layers of the Cortex From top to bottom, about 3 mm

50. The Cerebral Cortex • Grey matter • Columns of neurons • White matter • Inter-column connections