Golestani et al., Cerebral Cortex , 2006

1. Golestani et al., Cerebral Cortex, 2006

2. Psycholinguistics I LING 640

3. Today • Goals of the course • Integrative overview of psycholinguistics • Recurring themes • Practical skills • Practical information • Specialization & Abstraction • Introducing Lab #1

4. www.ling.umd.edu/~colin/readings OR www.ling.umd.edu/colin/readings Username: linguser Password: aspects

6. What is psycholinguistics about?

7. From Cellsto Syntax

8. Sensory Maps Internal representations of the outside world. Cellular neuroscience has discovered a great deal in this area.

9. The mind/brain’s view of the body body parts scaled to area in brain: somatosensory homunculus

10. Guiding Questions • What do speakers of a language mentally represent? • How did those representations get there? • How are those representations constructed? • How are those representations encoded?

11. Language is a Human Specialization • Species specificity • Within-species invariance • Spontanous development, insensitivity to input • Independence of general intelligence • Selective brain damage • The ‘Language Instinct’ [Pinker 1994]; see Gleitman & Newport chapter [readings] for nice summary • These arguments suggest that there’s a coherent object of study, but tell us very little about its form

12. We need explicit answers… • What do speakers of a language mentally represent? • How did those representations get there? • How are those representations constructed? • How are those representations encoded?

13. Explicit models quickly reveal surprising complexity

14. A Simple(-ish) Example • Distribution of pronouns/reflexives • John likes him/himself. • John thinks that Mary likes him/himself. • Infinitival clauses • John appeared to Bill to like himself. • John appeared to Bill to like him. • But… • John appealed to Bill to like himself. • John appealed to Bill to like him. • Abstract solution… • Johni appealed to Billj [PROj to like himselfj ]

15. Abstraction is a double-edged sword

16. Abstraction • Abstraction is valuable • Provides representational power • Provides representational freedom • Provides an efficient code • Abstraction is costly • Linguistic representations are more distant from experience • This places a burden on the learner - motivation for innate knowl. • This places a burden on comprehension/production systems • … and it makes it harder to know what to look for in the brain

17. Abstraction and Learning

18. Abstraction and Learning • Must ensure easy learning of any human language • Learner must project from finite input to a system with infinite expressive power

19. typology problem =learning problem N. Chomsky Principles & Parameters program (1980s)

20. Who do you think John likes __? Who do you think that John likes __? Who do you think __ likes John? Who do you think that __ likes John? that-trace effect English * French * Spanish ok Italian ok Levantine Ar. * Beni-Hassan Ar. ok Post-verbal subject position ‘Telephoned John.’ Who do you think that likes John __?

21. typology problem =learning problem Challenges… Link all hard-to-observe facts to easy-to-observe phenomena Find reliable parameters of variation in the face of microvariation Find a reliable learning procedure Show evidence of abstract inference in learning Principles & Parameters program (1980s)

22. statistical learning! Elissa Newport Challenges… Learning is closely tied to experience Robust learning procedures available, noise sensitive Evidence of learning available Almost nothing to say about hard-to-observe phenomena Little to say about typological consistency

23. Abstraction, Sounds, and Concepts

24. “It has sometimes been argued that linguistic theory must meet the empirical condition that it account for the ease and rapidity of parsing. But parsing does not, in fact, have these properties. […] In general, it is not the case that language is readily usable or ‘designed for use.’” (Chomsky & Lasnik, 1993, p. 18)

25. Translating Representations • We can show that comprehension and production are, in fact, rapid and accurate • Entails a need to quickly translate between codes • Sounds abstract stuff Concepts • Similar arguments apply as in learning: abstraction carries a cost

26. Abstraction and Encoding

27. From Cellsto Syntax

28. Linguistic Theories • Classify (im)possible expressions • Emphasize complex hierarchical structures • Representations are symbolic and abstract • Rich cross-language variation • Typically disavow claims about real-timeoperations

29. Human Brain • 100 billion neurons • Vast numbers of connections (synapses) • Rich cytoarchitectonicdiversity • Cortex and sub-corticalneuclei • Signaling: electrical and chemical; analogand digital

30. Sensory Maps Internal representations of the outside world. Cellular neuroscience has discovered a great deal in this area.

31. The mind/brain’s view of the body body parts scaled to area in brain: somatosensory homunculus

32. www.ling.umd.edu/~colin/readings

33. Acoustic Continua andPhonetic Categories

34. Frequency - Tones

35. Frequency - Tones

36. Frequency - Tones

37. Frequency - Tones

38. Frequency - Complex Sounds

39. Frequency - Complex Sounds

40. Frequency - Vowels • Vowels combine acoustic energy at a number of different frequencies • Different vowels ([a], [i], [u] etc.) contain acoustic energy at different frequencies • Listeners must perform a ‘frequency analysis’ of vowels in order to identify them(Fourier Analysis)

41. Frequency - Male Vowels

42. Frequency - Male Vowels

43. Frequency - Female Vowels

44. Frequency - Female Vowels

45. Synthesized Speech • Allows for precise control of sounds • Valuable tool for investigating perception

46. Timing - Voicing

47. Voice Onset Time (VOT) 60 msec

48. English VOT production • Not uniform • 2 categories

49. Perceiving VOT ‘Categorical Perception’

50. Discrimination Same/Different