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Language electrified

Language electrified. Department of Psychology Maastricht University Bernadette Schmitt Blok 3.2 Neurocognition October 1999. Language. Speaking is one of the most complex cognitive skills in humans Automatic Fast 150 words per minute 6 syllables per second

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Language electrified

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  1. Language electrified Department of Psychology Maastricht University Bernadette Schmitt Blok 3.2 Neurocognition October 1999

  2. Language Speaking is one of the most complex cognitive skills in humans Automatic Fast 150 words per minute 6 syllables per second 1 out of 1000 words incorrect

  3. Language ERPs in Comprehension ERPs in Production Language theories

  4. Oh boy, gimme a big hug!!

  5. Oh boy, gimme a big hug!! Oh man, that’s what wea already doin’, but I won’t tellya.

  6. Speech Production (Levelt)

  7. Speech Comprehension (Cutler)

  8. Units of speech perception • Sound waves • Phonemes • Syllables • Words • Sentences

  9. Example of a syllable detection experiment • present words to participants • task: detect phonemes group /bal/ in • balcony • ballet • detection time shorter in balcony -> syllable • but where is the syllable in the signal? • and when is it processed?

  10. physical signal does not show these units segmentation problem variability problem Difficulties

  11. Variability • Real world speech • slow vs. fast • within/between speakers Segmentation • no start/end

  12. Alternative methods • high temporal resolution methods ERPs • phonological encoding • meaning encoding • syntactic encoding • discourse processing

  13. Phonological encoding and ERP • When is phonological information processed? • Subject hears pairs of words • phonologically related at the beginning “cap - cat” • phonologically related at the end “hat - cat” • unrelated control “sun - cat” • see where ERP signals are different • Praamstra, Meyer, and Levelt (1994)

  14. Phonological encoding estimated by ERPs

  15. negativity around 400 ms N400 reduced for related words 250 - 450 ms for onset related pairs 450 - 700 ms for rhyme related pairs time course of phonological encoding distribution of N400 similar to standard N400: Phonology = Semantics ??? Conclusion ERP on phonology

  16. Integration of meaning

  17. Integration of meaning • Present sentences to subjects word by word • one with normal meaning • one with weird meaning • Kutas and Hillyard (1980) • He was stung by a bee • He was stung by a mile

  18. Integration of meaning • Present sentences to subjects word by word • one with normal meaning • one with weird meaning • Kutas and Hillyard (1980) • He was stung by a bee • He was stung by a mile

  19. Review by Kutas and Van Petten, 1994 integration component because all words in a sentence generate N400 word frequency; larger for low frequency words concreteness; larger for abstract words repetition; reduced N400 if word is repeated semantic relation; reduced N400 if two words are related 19 years of N400 research

  20. integration of words into sentence N400 gets smaller the further into the sentence it occurs Control study: syntactic prose Colorless green ideas sleep furiously no N400 reduction across the sentence 19 years of N400 research

  21. N400 and discourse (Van Berkum et al., 1997)

  22. N400 and cognitive development

  23. negativity around 400 ms N400 reduced for expected words both in sentence and discourse sensitive to semantic relations integration of meaning takes place around 400 ms after word onset Conclusion ERP and Meaning

  24. Integration of syntax

  25. Integration of syntax • Present sentences word by word • one with normal syntax • one with incorrect syntax • My pet aardvark prefers to eat potatoes • My pet aardvark prefer to eat potatoes

  26. Integration of syntax • Present sentences word by word • one with normal syntax • one with incorrect syntax • My pet aardvark prefers to eat potatoes • My pet aardvark prefer to eat potatoes

  27. Integration of syntax • Present sentences word by word • one with normal syntax • one with incorrect syntax • My pet aardvark prefers to eat potatoes • My pet aardvark prefer to eat potatoes

  28. Integration of syntax Osterhout et al., 1992; Hagoort et al., 1993)

  29. Ambiguity detection (Hagoort and Brown, 1994)

  30. P600 in syntactic prose(Muente et al., 1997)

  31. Conclusion ERP and Syntax • P600/SPS • Syntactic anomalies • Ambiguities • in normal sentences and prose • not in pseudo-word sentences • P600/SPS related to syntax in the context of available mental representations

  32. Sentence processing and Memory

  33. Sentence processing and Memory • Let subjects read sentence • easy ones • difficult ones • King and Kutas, 1995; Mueller et al., 1997 • The aardvark that really scared the cop ran into the bushes. • The aardvark that the cop scared ran into the bushes.

  34. Sentence processing and Memory • Let subjects read sentence • easy ones • difficult ones • King and Kutas, 1995; Mueller et al., 1997 • The aardvark that really scared the cop ran into the bushes. • The aardvark that the cop scared ran into the bushes.

  35. Sentence processing and Memory • Let subjects read sentence • easy ones • difficult ones • King and Kutas, 1995; Mueller et al., 1997 • The aardvark that really scared the cop ran into the bushes. • The aardvark that the cop scared ran into the bushes.

  36. Language and Memory Left anterior negativity (LAN)

  37. Conclusions on relation of language and working memory • Left anterior negativity (LAN) • more negative if difficult process • sensitive to syntactic structures • sensitive to semantic integration • if something has to keep activated for a while

  38. Take home message “ERPs in comprehension” • Phonological component (N400 like) • Meaning integration component (N400) • Syntactic component (P600/SPS) • Memory component (LAN) • Open: Interaction of these processes

  39. BREAK

  40. ERPs in language production The theory Some examples of RT experiments ERP I: LRP ERP II: N200

  41. A psycho-linguistic view of language Intention to say or understand something Meaning Syntax Sound Articulation

  42. Speaking • a picture -> speech planning -> naming

  43. Speaking • a picture -> speech planning -> a response DOCTOR

  44. Speaking • a picture -> speech planning -> a response DOCTOR 800 ms

  45. Manipulate meaning access Picture-Word Interference Paradigm • naming Doctor, hearing Nurse 880 ms • naming Doctor, hearing Sun 830 ms -------- slow down 50 ms semantic interference effect

  46. Manipulate syntactic access Picture-Word Interference Paradigm • is Doctor a “de” or “het” word, seeing “het” 680 ms • is Doctor a “de” or “het” word, seeing “de” 620 ms -------- slow down 60 ms syntactic incongruency effect

  47. Manipulate phonological access Picture-Word Interference Paradigm • naming Doctor, hearing Doll 800 ms • naming Doctor, hearing Sun 830 ms -------- speed up 30 ms phonological facilitation effect

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