liina pylkkänen department of linguistics/ center for neuromagnetism new york university meg, the...

Liina PylkkänenLiina Pylkkänen

Department of Linguistics/ Center for NeuromagnetismDepartment of Linguistics/ Center for Neuromagnetism

New York UniversityNew York University

MEG, the Mental Lexicon and MEG, the Mental Lexicon and MorphologyMorphology

LP, Aug 03, Tateshina

Day 1Day 1 Lexical access 1: Lexical access 1:

The M350 as an MEG index of lexical activationThe M350 as an MEG index of lexical activation

Day 2Day 2 Lexical access 2: Lexical access 2:

The M350 and mechanisms of recognitionThe M350 and mechanisms of recognition

Day 3Day 3 Morphology 1: Morphology 1:

The M350 as a tool for investigating similarity and identityThe M350 as a tool for investigating similarity and identity

Day 4Day 4 Morphology 2: Morphology 2:

Electrophysiological and behavioral evidence for early Electrophysiological and behavioral evidence for early effects of morphologyeffects of morphology

MEG, the Mental Lexicon and MEG, the Mental Lexicon and MorphologyMorphology


AcknowledgementsAcknowledgements(the yellow people have kindly allowed me to use (the yellow people have kindly allowed me to use their slides in these presentations)their slides in these presentations)


• Alec Marantz (MIT)• Andrew Stringfellow (UCSD)• Laura Gonnerman (Lehigh University)• Martin Hackl (Pomona College)• David Embick (University of Pennsylvania)• Meltem Kelepir (Eastern Mediterranean University)• Jeanette Schaeffer (Ben Gurion University)• Elissa Flagg ( U Toronto)• Linnaea Stockall (MIT)• Sophie Feintuch (Portsmouth High School, NH)• Emily Hopkins (Portsmouth High School, NH)• Eytan Zweig (NYU)• Machteld van Rijsingen (NYU/ University of Amsterdam) • Tony Wilson (University of Minnesota)• Colin Phillips (University of Maryland, College Park)• Robert Fiorentino (University of Maryland, College Park)• David Poeppel (University of Maryland, College Park)

Day 1Day 1 Lexical access 1: Lexical access 1: The M350 as The M350 as an MEG index of lexical activationan MEG index of lexical activation


I.I. General remarks on methodology and methodological General remarks on methodology and methodological challenges in cognitive neuroscience.challenges in cognitive neuroscience.

II.II. Basic lexical access experiments (frequency, repetition Basic lexical access experiments (frequency, repetition priming): M350.priming): M350.

III.III. Modality question. Modality question.

IV.IV. More detail on the nature of frequency effects.More detail on the nature of frequency effects.

V.V. Pinpointing the cognitive level of the M350. Initial Pinpointing the cognitive level of the M350. Initial activation of the lexicon.activation of the lexicon.

VI.VI. Is this result compatible with evidence from other Is this result compatible with evidence from other techniques? Eye-tracking, masked priming. techniques? Eye-tracking, masked priming.

Linguistic theoryLinguistic theory

PsycholinguisticsPsycholinguistics

2. Use neural correlates of linguistic 2. Use neural correlates of linguistic processes as additional dependent processes as additional dependent variables in the study of languagevariables in the study of language

1. Use knowledge of language to isolate 1. Use knowledge of language to isolate neural correlates of linguistic processes neural correlates of linguistic processes


How to isolate neural correlates of How to isolate neural correlates of linguistic processeslinguistic processes?


Method 1• Conditions differ in

computational demands of linguistic function A.

Method 2• Conditions differ in presence

of linguistic function A.

Stim 1: Stim 2:

CAT CLAMFrequent Infrequent

Fast lexical access Slow lexical access

Stim 1: Stim 2:+lexical access - lexical access

Intuitively:

CAT KPT

or, often:

Task 1: Task 2:Semantic decision Phonological

decision• Task is constant so

reaction times can serve as behavioral index of manipulation

• If the task changes there can be no behavioral index of the manipulation.

• Need model of cognitive functions involved.

How to isolate neural correlates of How to isolate neural correlates of linguistic processeslinguistic processes?


Method 1• Conditions differ in computational

demands of linguistic function A.

• Same neural sources but different timing and/or magnitude

Method 2• Conditions differ in presence of

linguistic function A.

• (possibly) different sources

• Part of virtually all linguistic processing.Part of virtually all linguistic processing.

• 11stst processing stage that is potentially modality processing stage that is potentially modality independent, and “linguistic”, in a narrow sense of the independent, and “linguistic”, in a narrow sense of the word.word.

• Different theories about linguistic processing and Different theories about linguistic processing and representation make contrasting predictions about representation make contrasting predictions about lexical access lexical access

Neural correlate of lexical access a valuable additional Neural correlate of lexical access a valuable additional dependent measure to behavioral processing measures.dependent measure to behavioral processing measures.

Why lexical access?Why lexical access?LP, Aug 03, Tateshina


Linguistic theoryLinguistic theoryPsycholinguisticsPsycholinguistics

What affects lexical access?What affects lexical access?

What brain activity is affected by those factors?What brain activity is affected by those factors?


CAT

0 200 400 600 800 1000

Time [msec]

Response

• Lexical decision times are affected by:Lexical decision times are affected by:• Lexical frequencyLexical frequency• Semantic, phonological, morphological relatednessSemantic, phonological, morphological relatedness• Etc.Etc.

• But trying to infer the cognitive level of these effects But trying to infer the cognitive level of these effects from reaction times alone is complicated.from reaction times alone is complicated.

• Electrophysiological data adds a dependent measure Electrophysiological data adds a dependent measure for every millisecond:for every millisecond:


CAT

0 200 400 600 800 1000

Time [msec]

Response

• But identifying the activity affected by any one But identifying the activity affected by any one stimulus property is not particularly informative in of stimulus property is not particularly informative in of itself. itself.

• Need to show that some natural class of stimulus Need to show that some natural class of stimulus variables all affect the same neural activity, where variables all affect the same neural activity, where “natural class” is defined by the predictions of a “natural class” is defined by the predictions of a cognitive model.cognitive model.

Representation:Representation:

• There is a modality There is a modality independent lexicon.independent lexicon.

• Lexical entries connect Lexical entries connect sound and meaning – single sound and meaning – single lexicon.lexicon.

• All word formation is All word formation is syntactic. syntactic.

Assumptions/hypotheses that drive, and Assumptions/hypotheses that drive, and are tested by, the present researchare tested by, the present research


Processing:Processing:

• Timing of lexical access Timing of lexical access depends on the activation level depends on the activation level of lexical entries at stimulus of lexical entries at stimulus presentation.presentation.

• The activation level of lexical The activation level of lexical entries depends onentries depends on

• FrequencyFrequency

• Preceding context (priming)Preceding context (priming)

• Phonological and semantic Phonological and semantic relatedness should affect the relatedness should affect the same neural activity.same neural activity.

NB: All of these assumptions are more or less controversial so we’ll continually keep evaluating how they succeed in explaining the data.

http://www.ctf.com/Pages/page33.html

Magnetoencephalography (MEG)Magnetoencephalography (MEG)

EEGEEG


http://www.ctf.com/Pages/page33.html

Magnetoencephalography (MEG)Magnetoencephalography (MEG)

EEGEEGMEGMEG


Source: http://www.allgpsy.unizh.ch/graduate/mat/180102/Lecture1.pdf


MEG vs. EEGMEG vs. EEG

Source: http://hyperphysics.phy-astr.gsu.edu/hbase/magnetic/magcur.html#c1


Right-hand ruleRight-hand rule

Magnetoencephalography (MEG)

Distribution of magnetic field at 93 ms (auditory M100)

Averaged epoch of activity in all sensors overlain on each other.

Outgoing

Ingoing


Magnetoencephalography (MEG)LP, Aug 03, Tateshina

An MEG Study of Word Frequency Effects in Lexical

Decision

M. Hackl, D. Embick, J. Schaeffer, M. Kelepir, A.

Marantz

Dept. of Linguistics and Philosophy, MITJST/MIT [Mind Articulation] Project

Dept. of Linguistics, Ben-Gurion University of the Negev

The frequency effect

• Lexical decisions to frequent words faster than decisions to infrequent words.

• Account in activation-based models: frequent words have a higher “resting” level.

Objective: Identification of an MEG component whose latency varies with the frequency of words, to be used as an index in further studies of lexical access and lexical organization.

Primary Result: A component in the response to words at 350ms, m350, varies in latency with the frequency of words.

Stimuli:• Six bins of open-class words, arranged

according to frequency; Cobuild corpus, 320 million words

Category n/Million Log Freq. Example64 700 2.8 number65 140 2.1 ask66 30 1.4 wheel67 6 .7 candle68 1 0 clam69 .2 -.7 snarl

• Two classes of non-words, pronounceable and non-pronounceable; ratio of words:non-words 1:1.

Task: Lexical Decision.

Subjects: n = 9; 5F, 4M; right-handed native speakers of English.

Analysis: Peaks identified based on RMS analysis.A subset of 17 left-hemisphere sensors were used for identification of peaks; this set was

held constant across subjects/conditions.

1 2 3 4 5 6

Frequency Category (Frequent -- Infrequent)

Behavioral Data: Reaction Time

Categories (n/Million):

1: 7002: 1403: 30 4: 6 5: 1 6: .2

Three primary components

Frequency Category 1: m350 = 328ms

Contour Map at 328ms

m250 m350m170

0 200 300 400 Time [msec]

CAT

170msec 250msec 350msec

RMS analysis

M170 M250 M350M170 M250 M350

1. 2. 3.


1 2 3 4 5 6


Latency of m350 Component


1: 7002: 1403: 30 4: 6 5: 1 6: .2

• Latency of m350 response varies by log frequency of words

(p < .0001)

• Latency of m250 response does not vary with log frequency

(p = .8)

Two Distinct Components

1 2 3 4 5 6

Frequency Category

350 Component

250 Component

M250 and M350 Components



m250 m350 Magnetic Field andContour Map:

High Frequency



m250 m350

Magnetic Field andContour Map:

Low Frequency

The M350

• Is the first MEG component serving as a predictor of the behavioral frequency effect.

• If the M350 indexes lexical access, it is also predicted to show priming effects.

A neural response sensitive to repetition

L. Pylkkänen1,2, E, Flagg1, A. Stringfellow2, A. Marantz1,2

Dept. of Linguistics and Philosophy, MITJST/MIT [Mind Articulation] Project

The repetition priming effect

• Words are responded to more quickly on their second presentation than on their first.

• After a word has been accessed, its activation slowly returns to resting level – if the word is presented again while there is still residual activation, access is facilitated.

Objective: Identification of an MEG component whose latency predicts the behavioral repetition priming effect.

Result: A component in the response to words and pronouceable nonwords at 350ms, M350, occurs earlier for repeated than for nonrepeated words.

Stimuli• 2 x 2 design with repetition and target lexicality as factors. • Timing:

+DOG

DOG

Prime, 500 ms

500 ms

Target, real word or not?

Analysis• Only correct trials were analyzed.

• RMS from a minimum of 17 left hemisphere sensors showing large responses between 150 and 450 ms.

• The latencies and amplitudes of major RMS peaks were recorded using latency and magnetic field distribution as criteria for determining whether a peak belonged to a certain category of responses.

Effect of repetition on the M350 and RT

100

200

300

400

500

600

M170 M250 M350 RT

Repeated Nonrepeated

n.s

n.s

*

*

M350 positive signal maximum for repeated and for nonrepeated words (single subject data)

0 200 300 400 Time [msec]

CAT

170 msec 250 msec 350 msec

Sagittal view

A P

auditory M100

M350


Modality independent lexical access: MEG evidence from an auditory lexical decision task

Linnaea Stockall, Dan Wehner & Alec Marantz Dept. of

Linguistics and Philosophy, MIT & KIT/MIT MEG Lab

M350 facilitated by high frequency stimuli in visual lexical decision experiment

1 2 3 4 5 6


Latency of m350 Component


1: 700

2: 140

3: 30

4: 6

5: 1

6: .2

1 2 3 4 5 6


Behavioral Data: Reaction Time


1: 7002: 1403: 30 4: 6 5: 1 6: .2

Embick et al. (1999)

M350: index of initial lexical activationMEG activity elicited by visual words (lexical

decision task):

M350•The M350 is sensitive to Lexical frequency Repetition Phonological similarity Semantic similarity Sublexical frequency Morphological Family Size

•The M350 is NOT sensitive to interlexical competition

Question: Do visual word recognition and auditory word recognition involve accessing the same mental lexicon?:

Stimuli:• 48 High Frequency words• 48 Low Frequency words• 96 Non Word Fillers

• Matched for length, number of syllables and density

• Speech recorded in Soundedit and normalized for intensity

Materials & Method

Subjects:

• 10 right handed native English speakers with normal vision gave informed consent to participate in this experiment. RT and MEG data was collected from 6 subjects, RT data only from 4 subjects.

Materials & Method

Tone Test:

• After the frequency experiment, subjects listened to 50 300ms long 1KHz tones.

Materials & Method

Materials & Method

MEG Data collection:• Neuromagnetic fields were recorded using

an axial gradiometer whole-head system (Kanazawa Institute of Technology, Kanazawa, Japan). One subject was recorded with a 93 channel system, 3 with a 160 channel system Data were acquired in a band between DC and 200Hz, at a 1000Hz sampling frequency.

Materials & Method

MEG Data analysis:• Equivalent current dipole (ECD) analysis was used to

estimate the time course of activation in the cortical areas generating the M100/M350 response.

• Dipoles were localized for each subject for the M100 response to the tonetest using the subset of left hemisphere sensors covering the characteristic M100 field pattern

• The latency and intensity of the time point corresponding to the best GOF fit for the M100 dipole in the 0-500ms time window and the latency and GOF of the time point corresponding to the highest intensity for the M100 dipole in the 0-500ms time window were computed for each condition for each subject

Materials & Method

Helenius, Salmelin, Service, Connolly, Leinonen & Lyytinen (2002):

• Cortical Activation during Spoken-Word Segmentation

• Stimuli: 4 sentence types

Materials & Method

Left Hemisphere response locations1) Same source for 100 and N400m activation2) N400m in response to auditory lexical processing

Materials & Method

M100 Field Pattern (single subject)

Location of M100 Dipole (single subject)

3.5

7.4

0

1

2

3

4

5

6

7

8

9

10

High Frequency Low Frequency

Behavior (n=10)

1037.16

1097.23

950

1000

1050

1100

1150


Error Rate: Reaction Time:

Results

* **

* = p<0.005

** = p<0.0005

M350 Magnetic Evoked Component

MEG Data (single subject)

M350 Field Pattern

Results

Goodness of Fit of M100 dipole in 0-500ms time window

MEG Data (single subject)

0

10

20

30

40

50

60

70

80

90

1 101 201 301 401 501

GO

F (

%)


Results

Greatest GOF

355

421.5

200

300

400

500

Lat

ency

(m

s)


Latency of Best Fit of M100 dipole in 0-500ms time window

MEG Data (n=4)

Results

*

*= p<0.1

Intensity of Best Fit of M100 dipole in 0-500ms time window

MEG data (n=4)

18.1623.25

0.00

5.00

10.00

15.00

20.00

25.00

30.00

35.00

40.00

Inte

ns

ity

(n

Am

)


Results

n.s

Discussion:

• Auditory lexical decision evokes the same repsonse component evoked by visual lexical decision.

• component occurs at same latency• has same distribution and source localization• is sensitive to same stimulus manipulation

(facilitation for high frequency words)• Support for single lexicon model

M350 = lexical access?M350 = lexical access?

• Not necessarily – effect could be Not necessarily – effect could be secondary.secondary.

• For example, we might be measuring the For example, we might be measuring the timing of the word/nonword decisions, timing of the word/nonword decisions, which would be faster whenever lexical which would be faster whenever lexical access is faster.access is faster.

i.e. component could be task-related.i.e. component could be task-related.


M350 = lexical access?M350 = lexical access?

• Or: our assumptions about the cognitive Or: our assumptions about the cognitive level or frequency and repetition effects level or frequency and repetition effects might be wrong. might be wrong.


What processing stage(s) are affected by What processing stage(s) are affected by lexical frequency?lexical frequency?


• Most models: Most models:

Activation – high frequency representations have Activation – high frequency representations have a higher resting level. a higher resting level.

• Balota & Chumbley (1984, 1985, 1990, etc.):Balota & Chumbley (1984, 1985, 1990, etc.):

Post-access decision.Post-access decision.

Evidence that frequency effects can be “late”Evidence that frequency effects can be “late”

Connine et al. 1993:Connine et al. 1993:

Lexical frequency affects consonant identification:Lexical frequency affects consonant identification:

voicedvoiced ambiguousambiguous voiceless voiceless competitorcompetitor stimulusstimulus competitorcompetitor

BESTBEST ?EST?EST PESTPEST

BARKBARK ?ARK?ARK PARKPARK


BP

Would ?ARK behave like ?EST if embedded in a list of Would ?ARK behave like ?EST if embedded in a list of unambiguous low frequency stimuli? YES.unambiguous low frequency stimuli? YES.

Cynthia M. Connine, Debra Titone and Jian Wang. Auditory Word Recognition: Extrinsic and Intrinsic Cynthia M. Connine, Debra Titone and Jian Wang. Auditory Word Recognition: Extrinsic and Intrinsic Effects of Word Frequency, Effects of Word Frequency, Journal of Experimental Psychology: Learning, Memory, and CognitionJournal of Experimental Psychology: Learning, Memory, and Cognition , , Volume 19, Issue 1, January 1993, Pages 81-94. Volume 19, Issue 1, January 1993, Pages 81-94.


• Frequency may (and is likely) to affect multiple Frequency may (and is likely) to affect multiple levels of processing.levels of processing.

Cognitive processes involved in Cognitive processes involved in lexical accesslexical access

time

leve

l of

activ

atio

n

resting level

Stimulus: TURN

TURN

TURNIP

TURFTURTLE

ActivationActivation SelectionSelectionCompetitionCompetition


time

leve

l of

activ

atio

n

resting level

Stimulus: TURN

TURN

TURNIP

TURFTURTLE


Manipulate stimuli in such a way that Manipulate stimuli in such a way that Activation is Activation is facilitatedfacilitated

Selection is Selection is slowed downslowed down

To investigate the cognitive level of the M350: To investigate the cognitive level of the M350:

Which way would Which way would the M350 move?the M350 move?

How to simultaneously facilitate activation How to simultaneously facilitate activation and inhibit selection?and inhibit selection?

Linguistic theoryLinguistic theoryPsycholinguisticsPsycholinguistics


Phonotactic probability: Phonotactic probability: early facilitationearly facilitation

RT

• Same/different task (“low-level”) RTs to nonwords with a high phonotactic probability are speeded up.

High probability: MIDE

RT YUSHLow probability:

Sublexicalfrequency effect

(Vitevich and Luce 1998, 1999)


Phonotactic probability: Phonotactic probability: later inhibitionlater inhibition

RT

• Lexical decision (“high-level”) RTs to nonwords with a high phonotactic probability are slowed down.

High probability: MIDE

YUSH RT Low probability:

mile mild might migrate mike mime

mine mire mind mite migraine micro

neighborhood activated

yuppie yucca

yuck yum

neighborhood activated

Competition effect

(Vitevich and Luce 1998, 1999)


time

leve

l of

activ

atio

n

resting level

Stimulus: TURN

TURN

TURNIP

TURFTURTLE


Facilitates Facilitates activationactivation

slows down slows down selectionselection

induces intense induces intense competitioncompetition

High phonotactic probability/densityHigh phonotactic probability/densityLP, Aug 03, Tateshina

time

leve

l of

activ

atio

n

resting level

Stimulus: TURN

TURN

TURNIP

TURFTURTLE


Then high probability/ Then high probability/ density should delay density should delay M350 latenciesM350 latencies

If M350 = SelectionIf M350 = SelectionLP, Aug 03, Tateshina

time

leve

l of

activ

atio

n

resting level

Stimulus: TURN

TURN

TURNIP

TURFTURTLE


If M350 = ActivationIf M350 = ActivationThen high probability/ Then high probability/ density should speed up density should speed up M350 latenciesM350 latencies


High probability Low probability

Word BELL, LINE PAGE, DISH

Nonword MIDE, PAKE JIZE, YUSH

• Four categories of 70 stimuli:

• Lexical decision.

(Pylkkänen, Stringfellow, Marantz, Brain and Language, 2002)

Materials (visual)Materials (visual)LP, Aug 03, Tateshina

-400

-300

-200

-100

0

100

200

300

400

ms 98 198 298 398 498 598

[ms]

[fT

]

-400

-300

-200

-100

0

100

200

300

400

ms 98 198 298 398 498 598

[ms]

[fT

]

High probability word

Effect of probability/density Effect of probability/density (single subject)(single subject)

RT 640.36 M170 M250 M350 “M350-2”

-400

-300

-200

-100

0

100

200

300

400

ms 98 198 298 398 498 598

[ms]

[fT

]

-400

-300

-200

-100

0

100

200

300

400

ms 98 198 298 398 498 598

[ms]

[fT

]

Low probability wordHigh probability word

Effect of probability/density Effect of probability/density (single subject)(single subject)

-400

-300

-200

-100

0

100

200

300

400

ms 98 198 298 398 498 598

[ms]

[fT

]

M170 M250 M350 “M350-2”

RT 620.03 RT 640.36

(Pylkkänen, Stringfellow, Marantz, Brain and Language, 2002)

Effect of probability/density Effect of probability/density (n=10)(n=10)

100

200

300

400

500

600

700

800

M170 M250 M350 RT

High probability word Low probability word

n.s.

n.s.

*

*

Words

100

200

300

400

500

600

700

800

M170 M250 M350 RT

High probability nonword Low probability nonword

n.s.

n.s.

*

*

Nonwords

M350: (i) 1st component sensitive to lexical factors (ii) not affected by competition

time

leve

l of

activ

atio

n

resting level

Stimulus: TURN

TURN

TURNIP

TURFTURTLE


M350: (i) 1st component sensitive to lexical factors (ii) not affected by competition

• MEG evidence that lexical frequency affects activation.


350ms – are you KIDDING me??? That’s too LATE!!!!!!!!

EyetrackingEyetrackingLP, Aug 03, Tateshina

• Pace of fluent reading:Pace of fluent reading: In text, mean reading time for words is 239ms (Carpenter and Just, 1983).

• But:But:

• Reading in context should be faster.

• 239ms is averaging over all words, function and content. We have made no claims about the processing of function words.

The gaze durations of a typical reader The gaze durations of a typical reader (from Carpenter and Just, 1983)(from Carpenter and Just, 1983)


Another answer to the ever-intriguing question of pyramid construction has been suggested.

The Egyptian Engineer of 5,000 years ago may have used a simpled wooden device called a

weightarm for handling the 2 ½ to 7 ton pyramid blocks. The weightarm is like a lever or beam

pivoting on a fulcrum. Hundreds of weightarms may have been needed for each pyramid.

Weightarms may have been used to lift the blocks off the barges which came from the upriver

quarries. Also, they would be needed to transfer the blocks to skid roads leading to the base

and for lifting the blocks onto sledges. The sledges were hauled up greased tracks to the

working levels. Again, weightarms were used to pick up the blocks from the sledges and put

them on skidways where workers pulled them to their placements.

384 267 884 300 333 333 517

267 283 200 350 283 283 733 333 266 183 467 200

1201 333 367 1151 583 568 417 267 183 217

600 167 200 617 383 300 550 234 217 200 650 117

267 367 250 283 234 384 216 350 267 250 433

899 300 400 217 217 633 83 383 634 350 333

333 267 267 550 317 350 100 350 317

367 333 267 766 350 350 217 333 300 333 333

350 400 316 437 2150

(Carpenter, P. and M. A. Just, 1983, What your eyes do while your mind is reading. In Rayner, K. (ed.) Eye Movements in Reading: Perceptual and Language Processes, Academic Press, p. 275-305)

The gaze durations of a typical reader The gaze durations of a typical reader (from Carpenter and Just, 1983)(from Carpenter and Just, 1983)


• In this text there are: In this text there are:

• 67 content words

• 70 function words

• For the sake of argument, let’s assume that: For the sake of argument, let’s assume that:

• Processing content words in context takes 350ms.

• Processing function words, which are extremely frequent and often entirely predictable from the preceding syntactic context, takes 150ms, in context.

• Syntactic and lexical processing occur largely in parallel.

The mathThe math


• Time needed to process the content words:Time needed to process the content words:

• 67 x 350ms = 23 450ms

• Time needed to process the function words:Time needed to process the function words:

• 70 x 150ms = 10 500ms

• Total predicted word processing time:Total predicted word processing time:

• 23 450ms + 10 500ms = 33 950ms

• Total actual reading time of this text:Total actual reading time of this text:

• 23 450ms + 10 500ms = 34 591ms

The mathThe math


• The pace of normal fluent reading is The pace of normal fluent reading is perfectly compatible with the claim that perfectly compatible with the claim that lexical activation by isolated words lexical activation by isolated words takes 300-350ms. takes 300-350ms.


• Lexical effects can be seen in eyetracking way Lexical effects can be seen in eyetracking way before 350ms:before 350ms:

• Dahan, Magnuson & Tanenhaus (2001):

Lexical frequency affects eye movements at 250ms. If saccadic programming time is taken into account, this actually means that lexical frequency affects processing already at 100ms!

(Dahan, D., Magnuson, J.S., & Tanenhaus, M.K. (2001). Time course of frequency effects in spoken-word recognition: Evidence from eye movements. Cognitive Psychology, 42, 317-367.)


• Dahan, Magnuson & Tanenhaus paradigm (my reconstruction):Dahan, Magnuson & Tanenhaus paradigm (my reconstruction):


1. 500 ms of seeing the pictures

2. “Pick up the 2. “Pick up the bench”bench”

3. “and put it below 3. “and put it below the circle”.the circle”.

Target

High frequency competitor

Low frequency competitor




Result:

More fixations to high frequency competitor at 250-450ms after target onset.

Target

High frequency competitor

Low frequency competitor




Result:

More fixations to high frequency competitor at 250-450ms after target onset.

EyetrackingEyetracking




2. “Pick up the 2. “Pick up the benchbench””


Dahan, Magnuson & Tanenhaus: Dahan, Magnuson & Tanenhaus:

““With the current procedure, the delay between the presentation of the pictures and the spoken instruction was only 500 ms, making it less likely that participants would have time to implicitly name the pictures””








1. What’s relevant is the delay between the presentation of the pictures and target onset, not the delay between the presentation of the pictures and the spoken instruction.

Participants, in fact, have well over a second to activate the names of the objects before target onset.








1. It’s not a matter of “implicit naming of the pictures”. Pictures activate their names completely automatically, even if the pictures aren’t consciously perceived (e.g. Dell'Acqua & Grainger, Cognition,

1999).



• In this type of eye-tracking paradigm all the object In this type of eye-tracking paradigm all the object names are likely to be already accessed at the onset names are likely to be already accessed at the onset of the target word. of the target word.

• Further, it’s not even the usual type of priming Further, it’s not even the usual type of priming paradigm as the prime (i.e. the picture) continues to paradigm as the prime (i.e. the picture) continues to

be in the visual field during target processing. be in the visual field during target processing.

Data from this type of a paradigm do not challenge the Data from this type of a paradigm do not challenge the claim that lexical activation by isolated words takes claim that lexical activation by isolated words takes 300-350ms. 300-350ms.


Final note on masked primingFinal note on masked priming

• Interval between prime and target does not need to be Interval between prime and target does not need to be 350ms in order to obtain priming effects. 350ms in order to obtain priming effects.

• Semantic priming has been reported for SOA’s as Semantic priming has been reported for SOA’s as short as 50ms.short as 50ms.

• Can SOA manipulations, or masked priming, give us Can SOA manipulations, or masked priming, give us precise information about the timing of lexical precise information about the timing of lexical access?access?


Can we infer the timing of lexical access by measuring reaction times (RT) only?

NURSERT (yes or no)

DOCTOR

NURSERT

DRIVER

Example: Semantic priming.

Time

Time

Real word or not?

LP, Nov 00, Tokyo

Can we infer the timing of lexical access by measuring reaction times (RT) only?

NURSERT

DOCTOR

NURSERT

DRIVER

Is the effect lexical or post-lexical?I.e. automatic or conscious?

Time

Time

LP, Nov 00, Tokyo

If lexical (= automatic)

NURSERT

DOCTOR

NURSERT

DRIVER

DOCTOR activatesNURSE

Time

Time

LP, Nov 00, Tokyo

If lexical (= automatic)

NURSERT

DOCTOR

NURSERT

DRIVER

Time

Time

NURSE is accessed fasterdue to residual activation

LP, Nov 00, Tokyo

If post-lexical (= conscious)

NURSERT

DOCTOR

NURSERT

DRIVER

Time

Time

NURSE is responded to faster since it fits the preceding context(e.g. Neely 1991)

LP, Nov 00, Tokyo

If post-lexical, effect should dissappear if we make the “preceding context” invisible to

conscious recognition

NURSE#######

NURSE

Time

Time

Masking:

DOCTOR#######

#######DRIVER#######

LP, Nov 00, Tokyo

If post-lexical, effect should dissappear if we make the “preceding context” invisible to

conscious recognition

NURSERT

#######

NURSERT

Time

Time

Effect remains, i.e. is automatic

(e.g. Deacon et al 2000).

DOCTOR#######

#######DRIVER#######

LP, Nov 00, Tokyo

NURSE is accessed faster because DOCTOR already activated it

NURSERT

DOCTOR

NURSERT

DRIVER

Time

Time

nurse nurse

activation activation

nurse

activation

LP, Nov 00, Tokyo

NURSE is accessed faster because DOCTOR already activated it

NURSERT

DOCTOR

NURSERT

DRIVER

When does lexical access occur?

Time

Time

nurse nurse


nurse

activation

LP, Nov 00, Tokyo

When does the activation of NURSE occur?

NURSEDOCTOR

NURSERT

DRIVER

How much can we shorten the interval between the 1st and the 2nd word until the effect dissappears?

Time

Time

nurse nurse


nurse

activation

RT

LP, Nov 00, Tokyo


RT DOCTOR

NURSE RTDRIVER

Time

Time

nurse nurse


nurse

activation

NURSE


LP, Nov 00, Tokyo


RT DOCTOR

NURSERT

DRIVER

Time

Time

nurse nurse


nurse

activation

NURSE


LP, Nov 00, Tokyo


RT DOCTOR

NURSERT

DRIVER

Time

Time

nurse

activation

nurse

activation

NURSE

200ms


LP, Nov 00, Tokyo

Conclusions: (i) the effect on RTs is lexical.(ii) it takes at least 200 ms for

DOCTOR to activate NURSE (by semantic association).

RT DOCTOR

NURSERT

DRIVER

Time

Time

nurse

activation

nurse

activation

NURSE

200ms

LP, Nov 00, Tokyo

What we can’t conclude:• that the activation of the semantic associate happens in

some specific time window (the activation of NURSE by semantic

association could happen after the onset of the target).• anything about the activation time of the stimulus that the

subject is performing the task on (except that it’s faster or slower

than in some other condition).

• With MEG we can do both, and more...

NURSERT

DOCTOR

Time

nurse nurse


LP, Nov 00, Tokyo

Summary of Day 1Summary of Day 1

• M350:M350:• Sensitive to stimulus factors that we’d expect to Sensitive to stimulus factors that we’d expect to

affect lexical access.affect lexical access.

• Not task-related as is not sensitive to competition.Not task-related as is not sensitive to competition.

Index of early automatic lexical activation.Index of early automatic lexical activation.

An early dependent measure for testing An early dependent measure for testing hypotheses about language processing and hypotheses about language processing and represenations.represenations.

liina pylkkänen department of linguistics/ center for neuromagnetism new york university meg, the...

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