1. Lexical Access: Generation & Selection

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

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

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

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

6. 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?

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

8. 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

9. 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

10. 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?

11. Classic Experimental Paradigms

12. Reaction Time Paradigms
Lexical Decision
Priming

13. 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

14. Looking for Words +

15. Looking for Words
DASH

16. Looking for Words
RASK

17. Looking for Words
CURLY

18. Looking for Words
PURCE

19. Looking for Words
WINDOW

20. Looking for Words
DULIP

21. Looking for Words
LURID

22. (Embick et al., 2001)

23. Looking for Words
Semantically Related Word Pairs doctor nurse hand finger speak talk sound volume book volume

24. 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

25. Outline Speed & Robustness of Lexical Access Active Search
Evidence for Stages of Lexical Access
Autonomy & Interaction

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

27. 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

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

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

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

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

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

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

34. Cohort
SPIN
spin
spinach
spinster
spinaker
spindle

35. Cohort
SPINA
spinach

36. Cohort
SPINA
spinach
word uniqueness point

37. Cohort
SPINA
spinach
spinet
spineret

38. Cross-Modal Priming

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

41. 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?

42. Gating Measures Presentation of successive parts of words
SPI
SPIN
SPINA…
Average recognition times
Out of context: ms
In context: 200ms
(Grosjean 1980, etc.)

43. 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)

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

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

46. 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

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

48. 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)

49. 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

50. 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…

51. Cohort
SPINA
spinach

52. Cohort
SPIN
spin
spinach
spinster
spinaker
spindle

53. 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.]

54. Refining the Story Frequency in context
eye-tracking in reading
eye-tracking and object recognition
Electrophysiological measures of multiple access
When can context affect generation?
strongly supporting contexts
ERP evidence

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

56. 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?

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

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

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

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

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

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

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

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

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

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

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

68. Overview Reasons to be ‘active’
Speed
Using highly reliable information (e.g., eleph…; NP-nom…)
Using partially reliable information (e.g., ele…; NP V…; wh NP V…)
Robustness
Minimize storage
Reasons to be ‘informationally encapsulated’ (‘modular’)
Architectural constraints
Information availability
Capturing effects of context
Bottom-up word information proposes candidates for evaluation against context
Bottom-up word information yields activation based on frequency, phonotactic probability, etc. (assuming multiple access)
Contextual information may prime certain lexical/semantic features, leading to earlier activation/selection of some words; context can also prime morpho-syntactic features, leading to exclusion of some word candidates

69. 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.

70. Outline Speed & Robustness of Lexical Access Active Search
Evidence for Stages of Lexical Access
Autonomy & Interaction

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

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

73. M350 RESPONSE TO A VISUAL WORD 0 200 300 400 Time [msec] Sagittal view

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

75. (Embick et al., 2001)

76. 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 …

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

78. Stimuli High probability Low probability Word BELL, LINE PAGE, DISH
Materials of Vitevich and Luce 1999 converted into orthographic stimuli.
Four categories of 70 stimuli:
High probability
Low probability
Word
BELL, LINE
PAGE, DISH
Nonword
MIDE, PAKE
JIZE, YUSH
High and low density words frequency matched.
(Pylkkänen, Stringfellow, Marantz, Brain and Language, 2003)

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

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

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

82. Outline Speed & Robustness of Lexical Access Active Search
Evidence for Stages of Lexical Access
Autonomy & Interaction

83. Autonomy
“…a system [is] autonomous by being encapsulated, by not having access to facts that other systems know about” (Fodor 1983)
“Autonomy would imply that processing operations at a given level proceed in the same way irrespective of whatever counsel might be deducible from the higher-level considerations” (Boland & Cutler)

84. Model Implied So Far
Stage 1: activation based upon cohorts no effect of context at this stage
Stage 2: selection affected by context

85. Boland & Cutler
The debate over interaction/autonomy in lexical access focuses on the generation (activation) stage
There is broad agreement that context affects lexical choices once multiple candidates have been generated

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

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

88. Cross-Modal Priming
How could context prevent a contextually unsupported meaning from being accessed?

89. Cross-Modal Priming
Conflicting results over effect of context on multiple access
Tabossi (1998)
The violent hurricane did not damage the ships which were in the port, one of the best equipped along the coast.
Contexts are highly constraining, prime a specific feature of the target meaning.

90. Active Comprehension
Distinction between activation and selection applies equally to syntactic comprehension
Is active comprehension a fully general property of language understanding?

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

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

93. Input to left hem. visual system must have privileged access to information about predictions.

94. Implications
If Kutas & Federmeier’s results are robust, this implies that
lexical priming can cause apparent early context effects
this implies ‘very active search’
hemispheres are not alike in this regard

98. +

99. walk

100. +

101. walk

103. Overview Reasons to be ‘active’
Speed
Using highly reliable information (e.g., eleph…; NP-nom…)
Using partially reliable information (e.g., ele…; NP V…; wh NP V…)
Robustness
Minimize storage
Reasons to be ‘informationally encapsulated’ (‘modular’)
Architectural constraints
Information availability
Capturing effects of context
Bottom-up word information proposes candidates for evaluation against context
Bottom-up word information yields activation based on frequency, phonotactic probability, etc. (assuming multiple access)
Contextual information may prime certain lexical/semantic features, leading to earlier activation/selection of some words; context can also prime morpho-syntactic features, leading to exclusion of some word candidates
Hemispheric contrasts - does differential processing reflect deep differences?