Categories in the Brain

1. Ling 411 – 14 Categories in the Brain

2. Variability in functional webs • Variable ignition • Variable web structure

3. Variability I – Variable Ignition • When ignition of a web occurs, it does not have to include the entire functional web • Examples: • It isn’t necessary to speak about everything one sees • Visualization is optional • At least to some extent • Application of attention can provide richer detail of ignition • More extensive activation of subwebs • For example, visualization

4. Ignition of a word web from visual input T C P Art PA V M

5. Ignition of a word web from visual input T C P Art PA V M

6. Ignition of a word web from visual input T C P Art PA V M

7. Ignition of a word web from visual input T C P Art PA V M

8. Ignition of a word web from visual input T C P Art PA V M

9. Ignition of a word web from visual input T C P Art PA V M

10. Ignition of a word web from visual input T C P Art PA V M

11. Ignition of a word web from visual input T C P Art PA V M

12. Ignition of a word web from visual input T C P Art PA V M

13. Ignition of a word web from visual input T C P Art PA V M

14. Ignition of a word web from visual input T C P Art PA V M

15. Ignition of a word web from visual input T C P Art PA V M Mention is optional

16. Ignition of a word web from visual input T C P Art PA V M

17. Speaking as a response to ignition of a web T C P Art PA V M

18. Speaking as a response to ignition of a web T C P Art PA V M

19. Speaking as a response to ignition of a web T C P Art PA V M The part of the motor structure that controls the articulation of [dog]

20. Speaking as a response to ignition of a web T C P Art PA V M From here to the muscles that control the organs of articulation

21. Ignition of a web from speech input Properties: C – Conceptual M – Memories PR – Phonolog. Rec. T – Tactile V - Visual T C PR PA V M

22. Ignition of a web from speech input Properties: C – Conceptual M – Memories PR – Phonolog. Rec. T – Tactile V - Visual T C PR PA V M

23. Ignition of a web from speech input Properties: C – Conceptual M – Memories P – Phonolog. Rec. T – Tactile V - Visual T C PR PA V M

24. Ignition of a web from speech input Properties: C – Conceptual M – Memories PR – Phonol. Rec. T – Tactile V - Visual T C PR PA V M

25. Ignition of a web from speech input T C PR PA V M Upon hearing “cat” we can also visualize a cat Probably a largely optional process

26. Visualization from speech input T C PR PA V M Upon hearing “cat” we can also visualize a cat

27. Visualization from speech input T C PR PA V M

28. Visualization from speech input T C PR PA V M

29. Visualization from speech input T C PR PA V M

30. Cortex-internal ignition • “… ignition of the web after sufficiently strong stimulation by … cortical neurons outside the functional web. This … cortex-internal activation of a web can be considered the organic basis of being reminded of an object even though it is absent in the environment.” (Pulvermüller 2002: 30)

31. Variability II – Variable web structure • Observation: every cat perceived or spoken about is different from others encountered previously • For example, different color • Each web is built based on experience • Consequence: the precise web structure for an individual is likely to differ in details for different instances of the same category • Inertia: some of the differences in a new exemplar are likely to be overlooked

32. Some Key Concepts • Functional Web • (Functional) Subweb • Cardinal node • Ignition • Reverberation

33. Understanding semantics • Semantic structure is largely a matter of conceptual categories • Understanding how categories work is the key to unlock the mysteries of semantics • To understand how categories work we need to understand how the brain manages categorial information

34. Types of Conceptual Categories • Discrete • Even integers • Counties in Texas • Radial • Birds • Vehicles • Family resemblance • Games • Furniture • Ill-defined • Thought • Mind

35. Phenomena associated with categories • No small set of defining features (with rare exceptions) • Fuzzy boundaries • Prototypical members and peripheral members • Subcategories, and sub-subcategories, in hierarchical chains • Categories are in the mind, not in the real world • Categories and their memberships vary from one language/culture system to another • Categories influence thinking, in both appropriate and inappropriate ways

36. Phenomena associated with categories: 1 • No small set of defining features (with rare exceptions) • The feature-attribute model fails • Works for some mathematical objects, but doesn’t apply to the way people’s cognitive systems apprehend most things • Example: CUP

37. Phenomena associated with categories: 2 • No small set of defining features (with rare exceptions) • Fuzzy boundaries • Example: VEHICLE • Car, truck, bus • Airplane? • Boat? • Toy car, model airplane? • Raft? • Roller skate? • Snowboard?

38. Fuzzy Categories No fixed boundaries Membership comes in degrees Prototypical Less prototypical Peripheral Metaphorical The property of fuzziness relates closely to the phenomenon of prototypicality

39. Phenomena associated with categories: 3 • No small set of defining features (with rare exceptions) • Fuzzy boundaries • Prototypical members and peripheral members • Prototypical • CAR, TRUCK, BUS • Peripheral: • AIRPLANE, TOY CAR, RAFT, ROLLER SKATE, etc. • Varying degrees of peripherality

40. Prototypicality phenomena The category BIRD Some members are prototypical ROBIN, SPARROW Others are peripheral EMU, PENGUIN The categoryVEHICLE Prototypical: CAR, TRUCK, BUS Peripheral: ROLLER SKATE, HANG GLIDER

41. Phenomena associated with categories: 4 • No small set of defining features (with rare exceptions) • Fuzzy boundaries • Prototypical members and peripheral members • Subcategories, and sub-subcategories, in hierarchical chains • ANIMAL – MAMMAL – CARNIVORE – CANINE – DOG –TERRIER – JACK RUSSELL TERRIER – EDDIE • Each subcategory has the properties of the category plus additional properties • Smallest subcategory has the most properties

42. Phenomena associated with categories: 5 • No small set of defining features (with rare exceptions) • Fuzzy boundaries • Prototypical members and peripheral members • Subcategories, and sub-subcategories, in hierarchical chains • Categories are in the mind, not in the real world • In the world, everything • is unique • lacks clear boundaries • changes from day to day (even moment to moment) • Whorf: “kaleidoscopic flux”

43. Phenomena associated with categories: 6 • No small set of defining features (with rare exceptions) • Fuzzy boundaries • Prototypical members and peripheral members • Subcategories, and sub-subcategories, in hierarchical chains • Categories are in the mind, not in the real world • Categories and their memberships vary from one language/culture system to another English: French: bell cloche (of a church) clochette (on a cow) sonnette (of a door) grelot (of a sleigh) timbre (on a desk) glas (to announce a death)

44. Phenomena associated with categories - 7 • No small set of defining features (with rare exceptions) • Fuzzy boundaries • Prototypical members and peripheral members • Subcategories, and sub-subcategories, in hierarchical chains • Categories are in the mind, not in the real world • Categories and their memberships vary from one language/culture system to another • Categories influence thinking, in both appropriate and inappropriate ways • B.L. Whorf • Example: Racial profiling

45. Beyond description to explanation • How can we explain these phenomena? • To answer this question we have to examine how our information about categories is represented in the brain • The brain is where our linguistic and cultural knowledge is represented

46. Facts and hypotheses that we can build on • The brain is a network • Composed, ultimately, of neurons • Cortical neurons are clustered in columns • Columns come in different sizes • Each minicolumn acts as a unit • Therefore a person’s linguistic and conceptual system is a network • Every word and every concept is represented as a sub-network • Term: functional web(Pulvermüller 2002)

47. Concepts and percepts: Cortical representation • Percept: one sensory modality • Locations are known • Auditory: temporal lobe • Visual: occipital lobe • Somatosensory: parietal lobe • Concept: more than one sensory modality • Higher level (more abstract) • Locations, for nominal concepts: • Angular gyrus • (?)MTG • (?)SMG

48. Hypotheses concerning functional webs • Hypothesis I: Functional Webs • A concept is represented as a functional web • Hypothesis II: Columnar Nodes • Nodes are implemented as cortical columns • Hypothesis III: Nodal Specificity • Every node in a functional web has a specific function • Hypothesis III(a): Adjacency • Nodes of related function are in adjacent locations • More closely related function, more closely adjacent

49. 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

50. Hypotheses concerning functional webs • Hypothesis IV: Extrapolation to Humans • The findings about cortical structure and function from experiments on cats, monkeys, and rats can be extrapolated to humans • Hypothesis IV(a): The extrapolation can be extended to linguistic and conceptual structures and functions • Hypothesis V:Hierarchy • A functionalweb is hierarchically organized • Hypothesis VI: Cardinal nodes • Every functional web has a cardinal node • Hypotheses VI(a): • Each subweb likewise has a cardinal node