1. WORD RECOGNTION (Sereno, 2/06) I.Introduction to psycholinguistics II.Basic units of language III.Word recognition IV.Word frequency & lexical ambiguity

2. III. Word Recognition How long does it take to recognise a visual word? –What is meant by “recognition” or “lexical access”? –Can lexical access be accurately measured? –What factors affect lexical access and when? The “magic moment” (Balota, 1990) of lexical access: “At this moment, presumably there is recognition that the stimulus is a word, and access of other information (such as the meaning of the word, its syntactic class, its sound, and its spelling) would be rapid if not immediate.” (Pollatsek & Rayner, 1990)

3. III. Word Recognition Measures Components Models Eye movements (EMs) Event-related potentials (ERPs)

4. Measures Standard behavioral techniques Eye movements (EMs) Neuroimaging –“Electrical”: EEG, MEG, (TMS) –“Blood flow”: PET, fMRI

5. Measures Standard behavioural techniques –lexical decision, naming, categorisation; also RSVP, self-paced reading –priming, masking, lateralised presentation –Donders (1868): subtractive method assumes strictly serial stages of processing additive vs. interactive effects –automaticvs. strategic (Posner & Snyder, 1975) unconscious exogenous bottom-up benefit controlled endogenous top-down cost & benefit

6. RT Stimulus Quality Context Frequency Stim Qual X Freq Context X Stim Qual Context X Freq

7. Relatedcatdog 500 500 Unrelatedbeddog 550 600 Neutralxxxdog 550 550 PRIMETARGET prime target SOA 250 RT SOA = Stimulus Onset Asynchrony ISI = InterStimulus Interval time

8. Measures Standard behavioral techniques Eye movements (EMs) Neuroimaging –“Electrical”: EEG, MEG, (TMS) –“Blood flow”: PET, fMRI

9. MEASURE Normal reading TASK fixation duration (as well as location and sequence of EMs) TIME RES. GOOD POOR “blood flow” imaging: fMRI, PET “electrical” imaging: EEG, MEG various word tasks ms-by-ms seconds various word tasks naming categorisation lexical decision Standard word recognition paradigms (± priming, ± masking): RT ~500 ms ~600 ms ~800 ms ~250 ms

10. Components Orthography of language –English vs. Hebrew or Japanese Language skill –beginning (novice) vs. skilled (expert) reader –easy vs. difficult text

11. Components Intraword variables –word-initial bi/tri-gramsclown vs. dwarf –spelling-to-sound regularityhint vs. pint –neighborhood consistencymade vs. gave –morphemes prefix vs. pseudoprefixremind vs. relish compound vs. pseudocompoundcowboy vs. carpet

12. Components Word variables –word lengthduke vs. fisherman –word frequencystudent vs. steward –AoAdinosaur vs. university –ambiguitybank vs. edge, brim –syntactic classopen vs. closed; A,N,V –concretenesstree vs. idea –affective tonelove vs. farm vs. fire –etc.

13. Components Extraword variables –contextual predictability The person saw the... moustache. The barber trimmed the... –syntactic complexity Mary took the book.*Mary took the book was good. Mary knew the book. Mary knew the book was good. *Mary hoped the book. Mary hoped the book was good. –discourse factors (anaphora, elaborative inferences) He assaulted her with his weapon.......knife... stabbed

14. Models Dual-route account (Coltheart, 1978) Direct route (addressed) phonologysemanticsorthography Indirect route (assembled)

15. Models Dual-route account (Coltheart, 1978) Direct route (addressed) phonologysemanticsorthography Indirect route (assembled) Deep dyslexia - visual/semantic errors (sympathy -> orchestra) - can’t read nonwords

16. Models Dual-route account (Coltheart, 1978) Direct route (addressed) phonologysemanticsorthography Indirect route (assembled) Surface dyslexia - regularization errors (broad -> brode) - Reg wds,NWs are OK (GPC rules intact)

17. Models Interactive (Morton, 1969; Seidenberg & McClelland, 1989) /m A k/ phonology meaningorthography M A K E context

18. Models Modular (Forster, 1979; Fodor, 1983) decision output Lexical processor Syntactic processor Message processor General Problem Solver input features

19. Models Hybrid –2-stage: generate candidate set  selection –(Becker & Killion; Norris; Potter)

20. III. Word Recognition Measures Components Models Eye movements (EMs) Event-related potentials (ERPs)

21. MEASURE Normal reading TASK fixation duration (as well as location and sequence of EMs) TIME RES. GOOD POOR “blood flow” imaging: fMRI, PET “electrical” imaging: EEG, MEG various word tasks ms-by-ms seconds various word tasks naming categorisation lexical decision Standard word recognition paradigms (± priming, ± masking): RT ~500 ms ~600 ms ~800 ms ~250 ms

22. Tools of choice: Recording eye movements in reading Recording ERPs in language tasks

23. Eye Movements (EMs) Best on-line measure of visual word recognition in the context of normal reading: Fast (avg fixation time ≈ 250 ms) Ecologically valid task Eye-mind span is tight

25. ERPs Best real-time measure of brain activity associated with the perceptual and cognitive processing of words: Continuous ms-by-ms record of events Early, exogenous components (before 200 ms) should reflect lexical processing

26. P1 N1 P300 N400 Number of trials 1 2 4 8 16 EEG ERP

27. (Sereno & Rayner, Trends in Cognitive Sciences, 2003)

28. DIVERSION High-density ERP Analysis: A case of “too many notes”?

29. High-density ERP Analysis: Typical approaches for space & time Pick ‘n choose favourite electrode and ERP component

31. High-density ERP Analysis: Typical approaches for space & time Pick ‘n choose favourite electrode and ERP component Hunt down where/when the effect is strongest and gather data from those electrodes/time window

33. High-density ERP Analysis: Typical approaches for space & time Pick ‘n choose favourite electrode and ERP component Hunt down where/when the effect is strongest and gather data from those electrodes/time window Procrustean regions analysis (turtle shell) or series of pre-set time windows (eg, 50, 100, 200 ms)

36. High-density ERP Analysis: Typical approaches for space & time Pick ‘n choose favourite electrode and ERP component Hunt down where/when the effect is strongest and gather data from those electrodes/time window Procrustean regions analysis (turtle shell) or series of pre-set time windows (eg, 50, 100, 200 ms) Spatial and/or temporal principal component analysis (PCA)

37. Scalp topography of the N1 @ 132-192 ms SF1 loadingsVoltages (Sereno, Brewer, & O’Donnell, Psychological Science, 2003)

38. Scalp topography of the N1 @ 132-192 ms SF1 loadingsVoltages ± 0.7 factor loading contours

39. WORD RECOGNTION (Sereno, 1/05) I.Introduction to psycholinguistics II.Basic units of language III.Word recognition IV.Word frequency & lexical ambiguity

40. Frequency: “When is access?” A word frequency effect [ HF < LF ] is used as a marker (index) of successful word recognition (lexical access). The sore on Tam-Tam’s was swollen. (HF) back (LF) rump Word frequency effect = differential response to commonly used high-frequency (HF) words vs. low-frequency (LF) words that occur much less often: If you can track frequency, you can track lexical access...

41. 553 ms 490 ms 259 ms 275 ms 280 ms 293 ms (Sereno & Rayner, Trends in Cognitive Sciences, 2003)