Lexical Access:
Generation & Selection
Main Topic
• Listeners as active participants in
comprehension process
• Model system: word recognition
Outline
1.
2.
3.
4.
Speed & Robustness of Lexical Access
Active Search
Evidence for Stages of Lexical Access
Autonomy & Interaction
Outline
1.
2.
3.
4.
Speed & Robustness of Lexical Access
Active Search
Evidence for Stages of Lexical Access
Autonomy & Interaction
The mental lexicon
sing
turk
water
sport
door
figure
carry
turf turtle gold
turkey
turn
turbo
turquoise
turnip turmoil
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?
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)
Marslen-Wilson 1975
Speech shadowing involves on-line repetition of a speaker…
Speech shadowing involves on-line repetition of a speaker…
250-1000ms
Shadowing latency
The new peace terms have been announced…
surrender of …
They call for the unconditional universe of …
already of …
normal
semantic
syntactic
Marslen-Wilson 1975
“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)
“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).
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
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
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?
Classic Experimental Paradigms
Reaction Time Paradigms
• Lexical Decision
• Priming
Looking for Words
• List 1
sickle
cathartic
torrid
gregarious
oxymoron
atrophy
• List 2
parabola
periodontist
preternatural
pariah
persimmon
porous
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
Looking for Words
+
Looking for Words
DASH
Looking for Words
+
Looking for Words
RASK
Looking for Words
+
Looking for Words
CURLY
Looking for Words
+
Looking for Words
PURCE
Looking for Words
+
Looking for Words
WINDOW
Looking for Words
+
Looking for Words
DULIP
Looking for Words
+
Looking for Words
LURID
(Embick et al., 2001)
Looking for Words
• Semantically Related Word Pairs
doctor
nurse
hand
finger
speak
talk
sound
volume
book
volume
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
Outline
1.
2.
3.
4.
Speed & Robustness of Lexical Access
Active Search
Evidence for Stages of Lexical Access
Autonomy & Interaction
Active Recognition
• System actively seeks matches to input does not wait for complete match
This allows for speed, but …
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
The mental lexicon
sing
turk
water
sport
door
figure
carry
turf turtle gold
turkey
turn
turbo
turquoise
turnip turmoil
The mental lexicon
sing
turk
water
TURN
sport
door
figure
carry
turf turtle gold
turkey
turn
turbo
turquoise
turnip turmoil
Automatic activation
sing
sport
door
water
TURN
figure
carry
turf turtle gold
turk
turkey
turn
turbo turquoise
turnip turmoil
Lateral inhibition
sing
sport
door
turk
gold
turn
water
TURN
figure
carry
turf turtle
turkey
turbo
turquoise
turnip
turmoil
What is lexical access?
Activation
Competition
Selection/Recognition
level of activation
1.2
1
0.8
0.6
0.4
0.2
resting level0
time
Stimulus: TURN
(e.g. Luce et al. 1990, Norris 1994)
Cohort
S
song
story
sparrow
saunter
slow
secret
sentry
etc.
Cohort
SP
spice
spoke
spare
spin
splendid
spelling
spread
etc.
Cohort
SPI
spit
spigot
spill
spiffy
spinaker
spirit
spin
etc.
Cohort
SPIN
spin
spinach
spinster
spinaker
spindle
Cohort
SPINA
spinach
Cohort
SPINA
word uniqueness point
spinach
Cohort
SPINA
spinach
spinet
spineret
Cross-Modal Priming
Evidence for Cohort Activation
KAPITEIN
KAPITAAL
(Marslen-Wilson, Zwitserlood)
Evidence for Cohort Activation
KAPITEIN
KAPITAAL
KAPIT…
(Marslen-Wilson, Zwitserlood)
Evidence for Cohort Activation
KAPITEIN
KAPITAAL
BOOT
KAPIT…
GELD
(Marslen-Wilson, Zwitserlood)
Evidence for Cohort Activation
KAPITEIN
KAPITAAL
BOOT
KAPIT…
GELD
(Marslen-Wilson, Zwitserlood)
Evidence for Cohort Activation
KAPITEIN
BOOT
KAPIT…
GELD
KAPITAAL
BOOT
KAPITEIN
GELD
(Marslen-Wilson, Zwitserlood)
Evidence for Cohort Activation
CAPTAIN
SHIP
CAPT…
GUARD
CAPTIVE
SHIP
CAPTAIN
GUARD
(Marslen-Wilson, Zwitserlood)
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?
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.)
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)
Cross-Modal Priming
The guests drank vodka, sherry and port at the reception
(Swinney 1979, Seidenberg et al. 1979)
Cross-Modal Priming
The guests drank vodka, sherry and port at the reception
WINE
SHIP
(Swinney 1979, Seidenberg et al. 1979)
Cross-Modal Priming
The guests drank vodka, sherry and port at the reception
WINE
SHIP
(Swinney 1979, Seidenberg et al. 1979)
Cross-Modal Priming
The guests drank vodka, sherry and port at the reception
WINE
SHIP
(Swinney 1979, Seidenberg et al. 1979)
Cross-Modal Priming
The guests drank vodka, sherry and port at the reception
WINE
SHIP
(Swinney 1979, Seidenberg et al. 1979)
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
Cross-modal Priming
• Early: multiple access
• Late: single access
…i.e., delayed effect of context
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)
• 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.
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?
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.]
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
Tanenhaus & Lucas 1987
Cross-Modal Lexical Access
• Seidenberg, Tanenhaus, Leiman, & Bienkowski (1982)
– Cross-modal naming
– They all rose vs. They bought a rose
Probes: 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
Experiment 1
Experiment 1
Experiment 2
cost
no cost
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
Electrophysiology of Sentence Comprehension
N400
• Semantic anomaly
I drink my coffee with cream and sugar
I drink my coffee with cream and socks
N400
Kutas & Hillyard (1980)
Electrophysiology of Sentence Comprehension
Left Anterior Negativity
(LAN)
P600
he mows
he *mow
N400
 Negative polarity
 peaking at around 400 ms
 central scalp distribution
and priming
Kutas & Federmeier, 2000, TICS
The day was breezy so the boy went out to fly …
deLong, Urbach, & Kutas, 2005, Nature Neurosci.
(Kutas & Federmeier 2000)
‘baseball’ is not at all plausible
here, yet it elicits a smaller N400
- why?
(Kutas & Federmaier 2000)
Ultra-fast Syntactic Analysis
•
Ultra-Fast Analysis
Electrophys. studies show responses to some
syntactic errors within 150-250ms after word onset Early Left Anterior Negativity, ELAN
1500ms
Early negativity
– John criticized Max’s proof of the theory.
– John criticized Max’s of proof the theory.
(Hahne et al., 2002)
(Neville et al., 1991)
• 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
(Friederici et al., 2000)
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
criticized
Max’s
Test case: same error, varying prediction
Although John criticized Bill’s data,
he didn’t criticize Max’s.
NP
N
of
With prediction
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.
FT7
1000ms
Without prediction
(Lau, Stroud, Plesch, & Phillips, 2006)
Eye-tracking
Frequency in Object Recognition
X
“Pick up the be..”
(Dahan, Magnuson, & Tanenhaus, 2001)
Frequency in Object Recognition
lobster
bench
X
bell
bed
“Pick up the be..”
(Dahan, Magnuson, & Tanenhaus, 2001)
Frequency in Object Recognition
• Timing estimates
– Saccadic eye-movements take 150-180ms to program
– Word recognition times estimated as eye-movement times minus
~200ms
Frequency in Object Recognition
(Dahan, Magnuson, & Tanenhaus, 2001)
Frequency in Object Recognition
(Dahan, Magnuson, & Tanenhaus, 2001)
Frequency in Object Recognition
(Dahan, Magnuson, & Tanenhaus, 2001)
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…
Cohort
SPINA
spinach
Cohort
SPIN
spin
spinach
spinster
spinaker
spindle
Evidence for Cohort Activation
CAPTAIN
SHIP
CAPT…
GUARD
CAPTIVE
SHIP
CAPTAIN
GUARD
(Marslen-Wilson, Zwitserlood)
Matches to other parts of words
• Word-ending matches don’t prime
– honing
woning
foning
[honey]
[apartment]
[--]
bij
[bee]
Disagreements
– Continuous activation, not limited to cohort, as
in TRACE model (McClelland & Elman, 1986)
– Predicts activation of non-cohort members, e.g.
shigarette, bleasant
BIG
B
I
BAT
G
DOG
A
T
Words
R
Phonemes
Feedback vs. Decision Bias
Non-Cohort Competitors
“Pick up the…”
beaker
beetle (onset)
speaker (non-onset)
carriage (distractor)
(Allopenna, Magnuson, & Tanenhaus, 1998)
Non-Cohort Competitors
“Pick up the…”
beaker
beetle (onset)
speaker (non-onset)
carriage (distractor)
(Allopenna, Magnuson, & Tanenhaus, 1998)
Non-Cohort Competitors
“Pick up the…”
beaker
beetle (onset)
speaker (non-onset)
carriage (distractor)
(Allopenna, Magnuson, & Tanenhaus, 1998)
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
Outline
1.
2.
3.
4.
Speed & Robustness of Lexical Access
Active Search
Evidence for Stages of Lexical Access
Autonomy & Interaction
M350
(based on research by Alec Marantz,
Liina Pylkkänen, Martin Hackl & others)
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
RESPONSE TO A
VISUAL WORD
M350
Sagittal view
A
P
00E-13
00E-13
00E-13
M350
00E-13
00E-13
00E+0 0
00E-13
00E-13
00E-13
00E-13
0
200
300
400
Time [msec]
MEG response components elicited by visually
presented words in the lexical decision task
RMS analysis of
component field patterns.
(Embick et al., 2001)
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 …
Behavioral evidence for dual effects
• Same/different task (“low-level”)
RTs to nonwords with a high phonotactic probability are speeded up.
High probability:
MIDE
Low probability:
YUSH
Sublexical
frequency
effect
RT
RT
• Lexical decision task (“high-level”)
RTs to nonwords with a high phonotactic probability are slowed down!
High probability:
MIDE
Low probability:
YUSH
RT
Competition
effect
RT
(Vitevich and Luce 1997,1999)
Stimuli
•
•
•
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)
Effect of probability/density (words)
HighProbWord
LowProbWord
700
*
600
500
**
400
300
200
n.s.
n.s.
100
M170
M250
M350
RT
(Pylkkänen, Stringfellow, Marantz, Brain and Language, 2003)
Effect of probability/density (nonwords)
HighProbNonword LowProbNonword
**
800
700
600
500
*
400
n.s.
300
200
n.s.
100
0
M170
M250
M350
RT
(Pylkkänen, Stringfellow, Marantz, Brain and Language, 2003)
M350 = 1st component sensitive to lexical
factors but not affected by competition
M350
Activation Competition Selection/Recognition
level of activation
1.2
1
0.8
0.6
0.4
0.2
resting level0
time
Stimulus: TURN
Automatic vs. Controlled Processes
DOCTOR
NURSE
DINRUP
NURSE
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
(Automatic) Spreading Activation
fMRI studies of semantic priming
Lau, Phillips, & Poeppel, in press, Nature Rev. Neurosci.
fMRI studies of semantic priming
Lau, Phillips, & Poeppel, in press, Nature Rev. Neurosci.
fMRI studies of semantic priming
Lau, Phillips, & Poeppel, in press, Nature Rev. Neurosci.
Lau, Phillips, & Poeppel, in press, Nature Rev. Neurosci.
Rodd, Davis, & Johnsrude, 2005, Cereb. Cortex
High ambig: The shell was fired towards the tank.
Low ambig: Her secrets were written in her diary.
Masked Priming
#######
brother
BROTH