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Cognitive Maps: How the Brain Organizes Knowledge

Ling 411 – 18. Cognitive Maps: How the Brain Organizes Knowledge. The Cognitive Map Hypothesis. Hypothesis: Knowledge is organized in the cortex as maps Established (hence not hypothetical): The cognitive map of the body Primary motor and somatosensory areas The map of pitch frequency

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Cognitive Maps: How the Brain Organizes Knowledge

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  1. Ling 411 – 18 Cognitive Maps:How the Brain Organizes Knowledge

  2. The Cognitive Map Hypothesis • Hypothesis: Knowledge is organized in the cortex as maps • Established (hence not hypothetical): • The cognitive map of the body • Primary motor and somatosensory areas • The map of pitch frequency • In primary auditory area • Hypothesized: • Conceptual • Phonological

  3. Properties of cognitive maps • Established for somatic and frequency maps • Local specificity • Every cortical location has a specific function • Adjacency • Adjacent locations for adjacent functions • Nearby locations for related functions • Comes in degrees • Hypothesis: these properties apply to • all homotypical cortical areas • all types of knowledge represented in the cortex

  4. First step in exploring the hypothesis:Categories • Understanding phonology • Phonological structure is organized around phonological categories • E.g., vowels and consonants, voiceless stops • 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

  5. What is a concept?Concepts vs. percepts • 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

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

  7. Phenomena associated with conceptual categories • No small set of defining features (with rare exceptions) • Fuzzy boundaries • Prototypical members and peripheral members • 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 • Subcategories, and sub-subcategories, in hierarchical chains

  8. 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

  9. 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?

  10. 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

  11. 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

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

  13. Phenomena associated with categories: 4 • No small set of defining features (with rare exceptions) • Fuzzy boundaries • Prototypical members and peripheral members • 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”

  14. Phenomena associated with categories: 5 • No small set of defining features (with rare exceptions) • Fuzzy boundaries • Prototypical members and peripheral members • 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)

  15. Phenomena associated with categories - 6 • No small set of defining features (with rare exceptions) • Fuzzy boundaries • Prototypical members and peripheral members • 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

  16. Phenomena associated with categories - 7 • No small set of defining features (with rare exceptions) • Fuzzy boundaries • Prototypical members and peripheral members • 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 • 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

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

  18. Facts and a hypothesis that we can build on • Fact: 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 • Hypothesis: Every word and every concept is represented as a sub-network • Term: functional web(Pulvermüller 2002)

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

  20. Property 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

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

  22. (Part of) the functional web for CAT The cardinal node for the entire functional web T C P A V M Cardinal nodes of the subwebs

  23. REVIEW 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

  24. REVIEW How to explain? • Description is fine, but its only a start • Next step: Explanation • How to explain? • By answering the question of how categories are represented in the brain

  25. Phenomena associated with categories: 1-3 • No small set of defining features (with rare exceptions) • Example: CUP • More realistic alternative: radial categories • Fuzzy boundaries • Example: VEHICLE • Prototypical members and peripheral members • VEHICLE • Prototypical: • CAR, TRUCK, BUS • Peripheral: • AIRPLANE, TOY CAR, RAFT, ROLLER SKATE, etc. • Varying degrees of peripherality • These three phenomena are interdependent

  26. How do radial categories work? • Different connections have different strengths (weights) • More important properties have greater strengths • For CUP, • Important (but not necessary!) properties: • Short (as compared with a glass) • Ceramic • Having a handle • Cups with these properties are more prototypical

  27. The properties of a category have different weights The cardinal node The threshold CUP T MADEOF GLASS SHORT CERAMIC HASHANDLE The properties are represented by nodes which are connected to lower-level nodes More important properties have greater weights, represented by greater thicknesses of lines

  28. Activation of a category node • The node will be activated by any of many different combinations of properties • The key word is enough – it takes enough activation from enough properties to satisfy the threshold • The node will be activated to different degrees by different combinations of properties • When strongly activated, it transmits stronger activation to its downstream nodes.

  29. Prototypical exemplars provide stronger and more rapid activation Activation threshold (can be satisfied to varying degrees) Inhibitory connection CUP T MADE OF GLASS SHORT CERAMIC HAS HANDLE Stronger connections carry more activation

  30. Explaining Prototypicality • Cardinal category nodes get more activation from the prototypical exemplars • More heavily weighted property nodes • E.g., FLYING is strongly connected to BIRD • Property nodes more strongly activated • Peripheral items (e.g. EMU) provide only weak activation, weakly satisfying the threshold (emus can’t fly) • Borderline items may or may not produce enough activation to satisfy threshold

  31. Activation of different sets of properties produces greater or lesser satisfaction of the activation threshold of the cardinal node CUP MADE OF GLASS SHORT CERAMIC HAS HANDLE

  32. Explaining prototypicality: Summary Variation in strength of connections Many connecting properties of varying strength Varying degrees of activation Prototypical members receive stronger activation from more associated properties BIRD is strongly connected to the property FLYING Emus and ostriches don’t fly But they have some properties connected with BIRD Sparrows and robins do fly And as commonly occurring birds they have been experienced often, leading to entrenchment – stronger connections

  33. Phenomena associated with categories: 4 • No small set of defining features (with rare exceptions) • Fuzzy boundaries • Prototypical members and peripheral members • 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”

  34. REVIEW Phenomena associated with categories: 5 • No small set of defining features (with rare exceptions) • Fuzzy boundaries • Prototypical members and peripheral members • 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)

  35. Phenomena associated with categories - 6 • No small set of defining features (with rare exceptions) • Fuzzy boundaries • Prototypical members and peripheral members • 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

  36. These phenomena (4-6) are interrelated • 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

  37. Bidirectional processing and inference These connections are bidirectional CUP T MADE OF GLASS SHORT CERAMIC Separate fibers for the two directions; shown as one line in the notation HANDLE

  38. Bidirectional processing and inference Thought process: 1. The cardinal concept node is activated by a subset of its property nodes 2. Feed-backward processing activates other property nodes Consequence: We “apprehend” properties that are not actually perceived CUP T SHORT HANDLE

  39. Another hypothesis of Whorf • Grammatical categories of a language influence the thinking of people who speak the language • Can we explain this too in terms of brain structure?

  40. Example: Grammatical gender • Does talking about inanimate objects as if they were masculine or feminine actually lead people to think of inanimate objects as having a gender? • Could the grammatical genders assigned to objects by a language influence people’s mental representation of objects? Boroditsky (2003)

  41. Experiment: Gender and Associations(Boroditsky et al. 2002) • Subjects: speakers of Spanish or German • All were fluent also in English • English used as language of experiment • Task: Write down the 1st 3 adjectives that come to mind to describe each object • All the (24) objects have opposite gender in German and Spanish • Raters of adjectives: Native English speakers

  42. Examples: • Key (masc in German, fem in Spanish) • Adjectives used by German speakers: • Hard, heavy, jagged, metal, serrated, useful • Adjectives used by Spanish speakers: • Golden, intricate, little, lovely, shiny, tiny • Bridge (fem in German, masc in spanish) • Adjectives used by German speakers: • Beautiful, elegant, fragile, peaceful, pretty • Adjectives used by Spanish speakers: • Big, dangerous, long, strong, sturdy, towering

  43. Results of the Experiment(Boroditsky et al. 2002) • Raters of adjectives were native English speakers • Result: Adjectives were rated as masculine or feminine in agreement with the gender in subject’s native language

  44. Categories and the brain All of these phenomena associated with categories can be explained as inevitable consequences of the structure and function of the human brain

  45. Phenomena associated with categories: 7 • 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

  46. How to explain? Perceptual Neuroscience • Hypothesis I: Extrapolation • The findings described by Mountcastle can be extrapolated to humans • Hypothesis I(a): Extrapolation can be extended to linguistic and conceptual structures • Why? Cortical structure, viewed locally, is • Uniform across mammalian species • Uniform across different cortical regions • Cortical structure and function, locally, are essentially the same in humans as in cats and monkeys and rats • Moreover, in humans, the regions that support language have the same structure locally as other cortical regions

  47. REVIEW Support for the extrapolation hypothesis • Conceptual systems in humans evidently use the same structures as perceptual systems • Therefore it is not too great a stretch to suppose that experimental findings on the structure of perceptual systems in monkeys can be applied to an understanding of the structure of conceptual systems of human beings • In particular to the structures of conceptual categories

  48. Columns of different sizes • Minicolumn • Basic anatomically described unit • 70-110 neurons (avg 75-80) • Diameter barely more than that of pyramidal cell body (30-50 μ) • Maxicolumn (term used by Mountcastle) • Diameter 300-500 μ • Bundle of about 100 continuous minicolumns • Hypercolumn – up to 1 mm diameter • Can be long and narrow rather than cylindrical • Functional column • Intermediate between minicolumn and maxicolumn • A contiguous group of minicolumns

  49. Functional Columns • Intermediate in size between minicolumn and maxicolumn • Hypothesized functional unit whose size is determined by experience/learning • A maxicolumn consists of multiple functional columns • A functional column consists of multiple minicolumns • Functional column may be further subdivided with learning of finer distinctions

  50. Columns of different sizes In order according to size Minicolumn The smallest unit 70-110 neurons Functional column Variable size – depends on experience Intermediate between minicolumn and maxicolumn Maxicolumn (a.k.a. column) 100 to a few hundred minicolumns Hypercolumn Several contiguous maxicolumns

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