2. Lexical Access: Generation & Selection

3. Main Topic Listeners as active participants in comprehension process Model system: word recognition

4. Outline 1.Speed & Robustness of Lexical Access 2.Active Search 3.Evidence for Stages of Lexical Access 4.Autonomy & Interaction

5. Outline 1.Speed & Robustness of Lexical Access 2.Active Search 3.Evidence for Stages of Lexical Access 4.Autonomy & Interaction

6. The mental lexicon sport figure sing door carry turf turtle gold turk turkey turn water turbo turquoise turnip turmoil

7. How do we recognize words? The Simplest Theory –Take a string of letters/phonemes/syllables, match to word in the mental lexicon –(That’s roughly how word processors work) …is it plausible?

8. Word Recognition is Fast Intuitively immediate - words are recognized before end of word is reached Eye-tracking studies indicate effects of access within 200-300ms Speech shadowing at very brief time-lags, ~250ms (Marslen-Wilson 1973, 1975)

9. Marslen-Wilson 1975 Speech shadowing involves on-line repetition of a speaker… Shadowing latency 250-1000ms The new peace terms have been announced… They call for the unconditional surrender of … universe of … already of … normal semantic syntactic

10. Marslen-Wilson 1975

11. “If the interaction between higher and lower levels of of analysis takes place only after the initial phonetic and lexical identification of the word, then restoration of disrupted words should be equally frequent in all Context conditions. The shadower would have no basis, in his initial repetition, for rejecting contextually anomalous restorations. However, if immediate identification does interact on-line with the semantic and syntactic context, then it becomes possible for context variables to determine word restoration frequency.” (Marslen-Wilson, 1975, p. 226)

12. “The high incidence of WR errors in Normal2 illustrates the speed and the precision with which structural information can be utilized. If the first syllable indicates a word that matches the context, then the close shadower can immediately start to restore that word in his repetition. This implies, first, that the constraints derived from the preceding items of the string are available to guide the analysis of even the first syllable of the target word. Second, these constraints can specify the permissible form-class and meaning of the target word with sufficient precision to enable the shadower to assess the appropriateness of just its first syllable.” (Marslen-Wilson 1975, p. 227).

13. Lexical Access is Robust Succeeds in connected speech Succeeds in fast speech Survives masking effects of morphological affixation and phonological processes Deleted or substituted segments Speech embedded in noise

14. But… Speed and robustness depends on words in context sentence --> word context effects In isolation, word recognition is slower and a good deal more fragile, susceptible to error …but still does not require perfect matching

15. Questions How does lexical access proceed out of context? Why is lexical access fast and robust in context? When does context affect lexical access? –does it affect early generation (lookup) processes? –does it affect later selection processes?

16. Classic Experimental Paradigms

17. Reaction Time Paradigms Lexical Decision Priming

18. Looking for Words List 1 sickle cathartic torrid gregarious oxymoron atrophy List 2 parabola periodontist preternatural pariah persimmon porous

19. Looking for Words List 1 sickle cathartic torrid gregarious oxymoron atrophy List 2 parabola periodontist preternatural pariah persimmon porous Speed of look-up reflects organization of dictionary

20. Looking for Words +

21. DASH

22. Looking for Words +

23. RASK

24. Looking for Words +

25. CURLY

26. Looking for Words +

27. PURCE

28. Looking for Words +

29. WINDOW

30. Looking for Words +

31. DULIP

32. Looking for Words +

33. LURID

34. (Embick et al., 2001)

35. Looking for Words Semantically Related Word Pairs doctornurse handfinger speaktalk soundvolume bookvolume

36. Looking for Words In a lexical decision task, responses are faster when a word is preceded by a semantically related word DOCTOR primes NURSE Implies semantic organization of dictionary

37. Outline 1.Speed & Robustness of Lexical Access 2.Active Search 3.Evidence for Stages of Lexical Access 4.Autonomy & Interaction

38. Active Recognition System actively seeks matches to input - does not wait for complete match This allows for speed, but …

39. Cost of Active Search… Many inappropriate words activated Inappropriate choices must be rejected Two Stages of Lexical Access activation vs. competition recognition vs. selection proposal vs. disposal

40. The mental lexicon sport figure sing door carry turf turtle gold turk turkey turn water turbo turquoise turnip turmoil

41. The mental lexicon sport figure sing door carry turf turtle gold turk turkey turn water turbo turquoise turnip turmoil TURN

42. Automatic activation TURN sport figure sing door carry turf turtle gold turk turkey water turn turbo turquoise turnip turmoil

43. Lateral inhibition TURN sport figure sing door carry turf turtle gold turk turkey water turn turbo turquoise turnip turmoil

44. What is lexical access? time level of activation resting level TURN Stimulus: TURN TURNIP TURF TURTLE Activation Competition Selection/Recognition (e.g. Luce et al. 1990, Norris 1994)

45. Cohort S song story sparrow saunter slow secret sentry etc.

46. Cohort SP spice spoke spare spin splendid spelling spread etc.

47. Cohort SPI spit spigot spill spiffy spinaker spirit spin etc.

48. Cohort SPIN spin spinach spinster spinaker spindle

49. Cohort SPINA spinach

50. Cohort SPINA spinach word uniqueness point

51. Cohort SPINA spinach spinet spineret

52. Cross-Modal Priming

54. Evidence for Cohort Activation KAPITEIN KAPITAAL (Marslen-Wilson, Zwitserlood)

55. Evidence for Cohort Activation KAPITEIN KAPITAAL KAPIT… (Marslen-Wilson, Zwitserlood)

56. Evidence for Cohort Activation KAPITEIN KAPITAAL KAPIT… BOOT GELD (Marslen-Wilson, Zwitserlood)

57. Evidence for Cohort Activation KAPITEIN KAPITAAL KAPIT… BOOT GELD (Marslen-Wilson, Zwitserlood)

58. Evidence for Cohort Activation KAPITEIN KAPITAAL KAPIT… BOOT GELD KAPITEIN BOOT GELD (Marslen-Wilson, Zwitserlood)

59. Evidence for Cohort Activation CAPTAIN CAPTIVE CAPT… SHIP GUARD CAPTAIN SHIP GUARD (Marslen-Wilson, Zwitserlood)

60. Cohort Model Partial words display priming properties of multiple completions: motivates multiple, continuous access Marslen-Wilson’s claims –Activation of candidates is autonomous, based on cohort only –Selection is non-autonomous, can use contextual info. How, then, to capture facilitatory effect of context?

61. Gating Measures Presentation of successive parts of words –S –SP –SPI –SPIN –SPINA… Average recognition times –Out of context: 300-350ms –In context: 200ms (Grosjean 1980, etc.)

62. Word Monitoring Listening to sentences - monitoring for specific words –Mean RT ~240ms –Identification estimate ~200ms Listening to same words in isolation –Identification estimate ~300ms (Brown, Marslen-Wilson, & Tyler)

63. Cross-Modal Priming The guests drank vodka, sherry and port at the reception (Swinney 1979, Seidenberg et al. 1979)

64. Cross-Modal Priming The guests drank vodka, sherry and port at the reception WINE SHIP (Swinney 1979, Seidenberg et al. 1979)

65. Cross-Modal Priming The guests drank vodka, sherry and port at the reception WINE SHIP (Swinney 1979, Seidenberg et al. 1979)

66. Cross-Modal Priming The guests drank vodka, sherry and port at the reception WINE SHIP (Swinney 1979, Seidenberg et al. 1979)

67. Cross-Modal Priming The guests drank vodka, sherry and port at the reception WINE SHIP (Swinney 1979, Seidenberg et al. 1979)

68. Generation and Selection Investigating the dependence on ‘bottom-up’ information in language understanding ‘Active’ comprehension has benefits and costs –Speed –Errors –Overgeneration entails selection Sources of information for generating candidates –Bottom-up information (e.g., lexical cohorts) –‘Top-down’ information (e.g., sentential context) –Questions about whether context aids generation or selection

69. Cross-modal Priming Early: multiple access Late: single access …i.e., delayed effect of context

70. CMLP - Qualifications Multiple access observed –when both meanings have roughly even frequency –when context favors the lower frequency meaning Selective access observed –when strongly dominant meaning is favored by context (see Simspon 1994 for review)

71. Context vs. frequency –The guests drank wine, sherry, and port at the reception. –The violent hurricane did not damage the ships which were in the port, one of the best equipped along the coast.

72. Frequency in Reading Rayner & Frazier (1989): Eye-tracking in reading –measuring fixation durations in fluent reading –ambiguous words read more slowly than unambiguous, when frequencies are balanced, and context is unbiased –unbalanced words: reading profile like unambiguous words –when prior context biases one meaning dominant-biased: no slowdown due to ambiguity subordinate-biased: slowdown due to ambiguity contextual bias can offset the effect of frequency bias –how can context boost the accessibility of a subordinate meaning?

73. Speed of Integration If context can only be used to choose among candidates generated by cohort… –context can choose among candidates prior to uniqueness point –but selection must be really quick, in order to confer an advantage over bottom-up information –[… or recognition following uniqueness point must be slow in the absence of context.]

74. Why multiple/selective access? How could context prevent a non-supported meaning from being accessed at all? (Note: this is different from the question of how the unsupported meaning is suppressed once activated) Possible answer: selective access can only occur in situations where context is so strong that it pre-activates the target word/meaning

75. Tanenhaus & Lucas 1987

76. Cross-Modal Lexical Access Seidenberg, Tanenhaus, Leiman, & Bienkowski (1982) –Cross-modal naming –They all rose vs. They bought a roseProbes: FLOWER, STOOD –Immediate presentation: equal priming; 200ms delay: selective priming Prather & Swinney (1977): similar w/ cross-modal lexical decision Tanenhaus & Donnenworth-Nolan (1984): similar, w/ extra delay in presenting target word

78. Experiment 1

80. Experiment 2

81. costno cost

82. Summary so far Accounting for single vs. multiple access findings in context How to relate context to lexical retrieval processes (Non-)effects of syntactic category constraints

83. Electrophysiology of Sentence Comprehension Semantic anomaly N400 I drink my coffee with cream and sugar I drink my coffee with cream and socks Kutas & Hillyard (1980) N400

84. he mows he *mow P600 Left Anterior Negativity (LAN) Electrophysiology of Sentence Comprehension

85. N400  Negative polarity  peaking at around 400 ms  central scalp distribution

86. Kutas & Federmeier, 2000, TICS and priming

87. The day was breezy so the boy went out to fly … deLong, Urbach, & Kutas, 2005, Nature Neurosci.

88. (Kutas & Federmeier 2000)

89. (Kutas & Federmaier 2000) ‘baseball’ is not at all plausible here, yet it elicits a smaller N400 - why?

90. Ultra-fast Syntactic Analysis (Friederici et al., 2000) Puzzle… –As fast or faster than word recognition –Leaves almost zero time for syntactic analysis! –Elicited by a subclass of errors –Localizes to Ant. Tpl. Regions and Broca’s Area Early negativity (Hahne et al., 2002) 1500ms Ultra-Fast Analysis Electrophys. studies show responses to some syntactic errors within 150-250ms after word onset - Early Left Anterior Negativity, ELAN –John criticized Max’s proof of the theory. –John criticized Max’s of proof the theory. (Neville et al., 1991)

91. Ultra-fast Syntactic Analysis Suggestion: fastest analysis occurs when structure is built before word is seen in input Fastest responses reflect mismatch, when incoming word mismatches predicted category NP Max’sN criticized of FT7 1000ms With prediction Without prediction (Lau, Stroud, Plesch, & Phillips, 2006) Test case: same error, varying prediction Although John criticized Bill’s data, he didn’t criticize Max’s. a.Although John criticized Bill’s data… …he didn’t criticize Max’s of proof the theory. b.Although John criticized Bill… …he didn’t criticize Max’s of proof the theory.

92. Eye-tracking

93. Frequency in Object Recognition X “Pick up the be..” (Dahan, Magnuson, & Tanenhaus, 2001)

94. Frequency in Object Recognition X bench bed bell lobster “Pick up the be..” (Dahan, Magnuson, & Tanenhaus, 2001)

95. Frequency in Object Recognition Timing estimates –Saccadic eye-movements take 150-180ms to program –Word recognition times estimated as eye-movement times minus ~200ms

96. Frequency in Object Recognition (Dahan, Magnuson, & Tanenhaus, 2001)

97. Frequency in Object Recognition (Dahan, Magnuson, & Tanenhaus, 2001)

98. Frequency in Object Recognition (Dahan, Magnuson, & Tanenhaus, 2001)

99. Cohort Model Partial words display priming properties of multiple completions: motivates multiple, continuous access Marslen-Wilson’s claims –Activation of candidates is autonomous, based on cohort only –Selection is non-autonomous, can use contextual info. How, then, to capture facilitatory effect of context…

100. Cohort SPINA spinach

101. Cohort SPIN spin spinach spinster spinaker spindle

102. Evidence for Cohort Activation CAPTAIN CAPTIVE CAPT… SHIP GUARD CAPTAIN SHIP GUARD (Marslen-Wilson, Zwitserlood)

103. Matches to other parts of words Word-ending matches don’t prime –honing[honey]bij[bee] woning[apartment] foning[--]

104. Disagreements –Continuous activation, not limited to cohort, as in TRACE model (McClelland & Elman, 1986) –Predicts activation of non-cohort members, e.g. shigarette, bleasant

105. BIGATR BIGBATDOG Words Phonemes Feedback vs. Decision Bias

106. Non-Cohort Competitors (Allopenna, Magnuson, & Tanenhaus, 1998) “Pick up the…” beaker beetle (onset) speaker (non-onset) carriage (distractor)

107. Non-Cohort Competitors (Allopenna, Magnuson, & Tanenhaus, 1998) “Pick up the…” beaker beetle (onset) speaker (non-onset) carriage (distractor)

108. Non-Cohort Competitors (Allopenna, Magnuson, & Tanenhaus, 1998) “Pick up the…” beaker beetle (onset) speaker (non-onset) carriage (distractor)

109. I wanted to point out a minor difference in your interpretation of Allopenna, Magnuson, & Tanenhaus (1998) and mine. Allopenna et al. is cited on p. 75 as one of the "estimates in the literature [that] the earliest processes involved in lexical access often fall in the 200 ms range". But eye tracking data of the sort we presented actually gives a strikingly different estimate. What we find again and again in studies using the visual world paradigm is that there is an approximately 200-250 ms lag between events in the speech signal and changes in fixation proportions. However, this should not suggest that it takes 200 ms for processes of lexical access to kick in. Rather, given that it takes at least about 150 ms to plan and launch an eye movement to a point of light in a darkened room, this means we can roughly subtract 150 msecs of the lag and attribute it to saccade planning. This leaves us with only about 50 msecs to attribute to the very earliest processes of access that are indexed by the eye movements. (This seems too short by 1-2 dozen msecs, but note that only a very small proportion of trials include such early eye movements, and statistically reliable differences between related and unrelated items emerge another ~25-50 msecs later.) [Email message, 6/26/07] Jim Magnuson, UConn

110. Outline 1.Speed & Robustness of Lexical Access 2.Active Search 3.Evidence for Stages of Lexical Access 4.Autonomy & Interaction

111. M350 (based on research by Alec Marantz, Liina Pylkkänen, Martin Hackl & others)

112. Lexical access involves 1.Activation of lexical representations including activation of representations matching the input, and lateral inhibition between activated representations 2.Followed by selection or decision involving competition among activated representations that are similar in form

113. RESPONSE TO A VISUAL WORD Sagittal view AP M350 0200300400 Time [msec]

114. MEG response components elicited by visually presented words in the lexical decision task RMS analysis of component field patterns.

115. (Embick et al., 2001)

116. Neighbors & Competitors Phonotactic probability –sound combinations that are likely in English –e.g. ride vs. gush Neighborhood density –number of words with similar sounds –ride, bide, sighed, rile, raid, guide, died, tried, hide, bride, rise, read, road, rhyme, etc. –gush, lush, rush, gut, gull …

117. RT Behavioral evidence for dual effects Same/different task (“low-level”) RTs to nonwords with a high phonotactic probability are speeded up. Lexical decision task (“high-level”) RTs to nonwords with a high phonotactic probability are slowed down! High probability: MIDE YUSH RT MIDE YUSH RT Low probability: High probability: Low probability: Sublexical frequency effect (Vitevich and Luce 1997,1999) Competition effect

118. Stimuli High probabilityLow probability WordBELL, LINEPAGE, DISH NonwordMIDE, PAKEJIZE, YUSH Materials of Vitevich and Luce 1999 converted into orthographic stimuli. Four categories of 70 stimuli: High and low density words frequency matched. (Pylkkänen, Stringfellow, Marantz, Brain and Language, 2003)

119. Effect of probability/density (words) n.s. ** * (Pylkkänen, Stringfellow, Marantz, Brain and Language, 2003)

120. Effect of probability/density (nonwords) n.s. * ** (Pylkkänen, Stringfellow, Marantz, Brain and Language, 2003)

121. M350 = 1st component sensitive to lexical factors but not affected by competition time level of activation resting level TURN TURNIP TURF TURTLE Activation Competition Selection/Recognition M350 Stimulus: TURN

122. Automatic vs. Controlled Processes

123. NURSEDOCTOR DINRUP COUCH NURSE Semantic association  facilitation [consistent] No association  inhibition [sometimes] Controlled/strategic effects Long SOA (Stimulus Onset Asynchrony), e.g. > 500ms Explicit pairing of words High proportion of associated pairs

124. (Automatic) Spreading Activation

125. Lau, Phillips, & Poeppel, in press, Nature Rev. Neurosci. fMRI studies of semantic priming

126. Lau, Phillips, & Poeppel, in press, Nature Rev. Neurosci.

127. fMRI studies of semantic priming

128. Lau, Phillips, & Poeppel, in press, Nature Rev. Neurosci.

129. High ambig: The shell was fired towards the tank. Low ambig: Her secrets were written in her diary. Rodd, Davis, & Johnsrude, 2005, Cereb. Cortex

131. Masked Priming

133. #######

134. brother

135. BROTH