Liina Pylkkänen (NYU) and Alec Marantz (MIT)

1. Morphological families and phonological neighborhoods – who competes when? MEG evidence. Liina Pylkkänen (NYU) and Alec Marantz (MIT)

2. Same number of derivates High frequency derivatives Low frequency derivatives - ist –ize -ism - ic –ize –ism terror magnet Matched for surface frequency Effect of lexical frequency • High frequency words are processed faster than low frequency words. • Prediction of decompositional theories of morphology: cumulative root frequency effects.

3. Should be faster due to high cumulative root frequency Effect of lexical frequency • High frequency words are processed faster than low frequency words. • Prediction of decompositional theories of morphology: cumulative root frequency effects. Same number of derivates High frequency derivatives Low frequency derivatives - ist –ize -ism - ic –ize –ism terror magnet Matched for surface frequency

4. Cumulative root frequency effects for inflection • Response times to a noun depend on the cumulative frequency of the singular and plural (Schreuder & Baayen, JML, 1997) CAT CATS

5. Family size LOW HIGH - ic –ity –ify –head –test –washed - ist acid diary But NO cumulative root frequency effects for derivation Schreuder & Baayen (1997): • Family frequency HIGH LOW Family frequency does not affect lexical decision times. - ist –ize -ism - ic –ize –ism S&B: Therefore, no decomposition in derivation. terror magnet High family size speeds up lexical decision times. S&B: this is a late post-lexical effect.

6. Alternative explanation for lack of cumulative root frequency effects in derivation • High morphological family frequency speeds up root activation BUT this facilitation is cancelled out by subsequent competition between the highly frequent morphological family members. • Hypothesized affix-competition in priming (Marslen-Wilson, et al. 1994): In crossmodal priming, NO PRIMING FOR government – governor ALTHOUGH ROBUST PRIMING FOR government – govern (Marslen-Wilson, W. D., Tyler, L., Waksler, R., & Older, L. (1994). Morphology and meaning in the English mental lexicon. Psychological Review 101, 3-33.)

7. Alternative explanation for lack of cumulative root frequency effects in derivation • High morphological family frequency speeds up root activation BUT this facilitation is cancelled out by subsequent competition between the highly frequent morphological family members. • How to measure timing of root activation, prior to any effect of competition? • M350, an magnetoencephalographic (MEG) response component elicited by word stimuli, peaking at ~350ms post word-onset

8. Magnetoencephalography (MEG) • Measures magnetic fields generated by large populations of neurons firing in synchrony. • Millisecond temporal resolution. • Millimeter spatial resolution (at least for cortical sources).

9. Magnetoencephalography (MEG)

10. What happens in the brain when we read words? 150-200ms (M170) 200-300ms (M250) 300-400ms (M350) 400-500ms 200 [fT] 0 200 -100 0 100 200 300 400 500 600 700 [msec] Pylkkänen and Marantz, Trends in Cognitive Sciences, in press. Letter string processing (Tarkiainen et al. 1999) Lexical activation (Pylkkänenet al. 2002)

11. What happens in the brain when we read words? Lexical activation (Pylkkänenet al. 2002) The M350 is sensitive to • Lexical frequency (a) • Repetition (b) • Phonological similarity (c) • Semantic similarity (d) • Sublexical frequency (e, f) The M350 is NOT sensitive to • Interlexical competition (e) 300-400ms (M350) • Embick, D., Hackl, M., Schaeffer, J., Kelepir, M. & Marantz, A. (2001). A magnetoencephalographic component whose latency reflects lexical frequency. Cognitive Brain Research 10:3, 345-348. • Pylkkänen, L., Stringfellow, A., Flagg, E., Marantz, A. (2001). A Neural Response Sensitive to Repetition and Phonotactic Probability: MEG Investigations of Lexical Access. Proceedings of Biomag 2000. 12th International Conference on Biomagnetism. Helsinki University of Technology, Espoo, Finland. 363-367. (c) Pylkkänen, L., Stringfellow, A. Marantz, A. 2002. Inhibition and Competition in Word Recognition: MEG Evidence. Submitted. (d) Pylkkänen, L. Stringfellow, A., Gonnerman, L., Marantz, A. 2002. Magnetoencephalographic indices of identity and similarity in lexical access. In preparation. • Pylkkänen, L., Stringfellow, A. Marantz, A. 2002. Neuromagnetic evidence for the timing of lexical activation: an MEG component sensitive to phonotactic probability but not to neighborhood density. Brain and Language 81, 666-678. (f) Stockall, L. Stringfellow, A. Marantz, A. 2003. The precise time course of lexical activation: MEG measurements of the effects of frequency, probability and density in lexical decision, Submitted. Pylkkänen and Marantz, Trends in Cognitive Sciences, in press.

12. What happens in the brain when we read words? Lexical activation (Pylkkänenet al. 2002) The M350 is sensitive to • Lexical frequency (a) • Repetition (b) • Phonological similarity (c) • Semantic similarity (d) • Sublexical frequency (e, f) The M350 is NOT sensitive to • Interlexical competition (e) 300-400ms (M350) • Embick, D., Hackl, M., Schaeffer, J., Kelepir, M. & Marantz, A. (2001). A magnetoencephalographic component whose latency reflects lexical frequency. Cognitive Brain Research 10:3, 345-348. • Pylkkänen, L., Stringfellow, A., Flagg, E., Marantz, A. (2001). A Neural Response Sensitive to Repetition and Phonotactic Probability: MEG Investigations of Lexical Access. Proceedings of Biomag 2000. 12th International Conference on Biomagnetism. Helsinki University of Technology, Espoo, Finland. 363-367. (c) Pylkkänen, L., Stringfellow, A. Marantz, A. 2002. Inhibition and Competition in Word Recognition: MEG Evidence. Submitted. (d) Pylkkänen, L. Stringfellow, A., Gonnerman, L., Marantz, A. 2002. Magnetoencephalographic indices of identity and similarity in lexical access. In preparation. • Pylkkänen, L., Stringfellow, A. Marantz, A. 2002. Neuromagnetic evidence for the timing of lexical activation: an MEG component sensitive to phonotactic probability but not to neighborhood density. Brain and Language 81, 666-678. (f) Stockall, L. Stringfellow, A. Marantz, A. 2003. The precise time course of lexical activation: MEG measurements of the effects of frequency, probability and density in lexical decision, Submitted. Pylkkänen and Marantz, Trends in Cognitive Sciences, in press.

13. High probability: MIDE Low probability: YUSH Phonotactic probability/density: early facilitation • Same/different task (“low-level”) • RTs to nonwords with a high phonotactic probability are speeded up. RT Sublexical frequency effect RT (Vitevich and Luce 1998, 1999)

14. mile mild might migrate mike mime mine mire mind mite migraine micro neighborhood activated yuppie yucca yuck yum neighborhood activated Phonotactic probability/density: later inhibition • Lexical decision (“high-level”) • RTs to nonwords with a high phonotactic probability are slowed down. Competition effect RT High probability: MIDE RT Low probability: YUSH (Vitevich and Luce 1998, 1999)

15. High phonotactic probability/density slows down selection Facilitates activation Activation Competition Selection TURN TURNIP level of activation TURF TURTLE resting level time Stimulus: TURN induces intense competition

16. If M350 = Selection Then high probability/ density should delay M350 latencies Activation Competition Selection TURN TURNIP level of activation TURF TURTLE resting level time Stimulus: TURN

17. If M350 = Activation Then high probability/ density should speed up M350 latencies Activation Competition Selection TURN TURNIP level of activation TURF TURTLE resting level time Stimulus: TURN

18. Materials (visual) • Four categories of 70 stimuli: • Lexical decision. (Pylkkänen, Stringfellow, Marantz, Brain and Language, 2002)

19. Effect of probability/density (single subject) High probability word M250 M350 “M350-2” M170 RT 640.36

20. Effect of probability/density (single subject) Low probability word High probability word M250 M350 “M350-2” M170 RT 640.36 RT 620.03

21. Effect of probability/density (n=10) * * * * n.s. n.s. n.s. n.s. (Pylkkänen, Stringfellow, Marantz, Brain and Language, 2002)

22. Activation Competition Selection TURN TURNIP level of activation TURF TURTLE resting level time Stimulus: TURN M350 (i) 1st component sensitive to lexical factors (such as lexical frequency) (ii) not affected by competition

23. Earlier effect of probability/density on M250 amplitude (n=10) * (Pylkkänen, Stringfellow, Marantz, Brain and Language, 2002)

24. Effect of high morphological family frequency? M350 RT - slow-down due to competition from highly frequent family members - speed-up due to cumulative root frequency Hypothesis • Effect of high phonotactic probability/ high neighborhood density: M350 RT - slow-down due to competition - speed-up due to sublexical frequency

25. Materials (from Baayen, R. H., Lieber, R., & Schreuder, R. (1997). Linguistics 35, 861-877) • Four categories of visual words, all nouns • Contrast 1: Family frequency HIGH • Matched for: • Length • Freq. of the sg, • Cumulative freq. of the sg. & pl. forms • Family size • Mean bigram frequency LOW - ist –ize -ism - ic –ize –ism terror (n=18) magnet (n=18) • Contrast 2: Family size LOW • Matched for: • Length • Freq. of the sg, • Cumulative freq. of the sg. & pl. forms • Family frequency (not perfectly) • Mean bigram frequency HIGH - ic –ity –ify –head –test –washed - ist acid (n=21) diary (n=21)

26. n.s. * n.s. * Behavior (Pylkkänen, Feintuch, Hopkins & Marantz, Cognition, to appear)

27. MEG data, single subject (Pylkkänen, Feintuch, Hopkins & Marantz, Cognition, to appear)

28. AXIAL VIEW L R SAGITTAL VIEW A P CORONAL VIEW L R = M250 = M350 MEG data, n = 10 LATENCY INTENSITY n.s. n.s. n.s. n.s. M250 P=0.006 n.s. ** P=0.03 n.s. * M350 (Pylkkänen, Feintuch, Hopkins & Marantz, Cognition, to appear)

29. AXIAL VIEW L R SAGITTAL VIEW A P CORONAL VIEW L R = M250 = M350 MEG data, n = 10 • High family size speeds up the M350, just like it does RT •  Family size affects processing early. • Contrary to the hypothesis from decomposition, high family frequency has an inhibitory effect on M350 amplitudes P=0.006 n.s. ** P=0.03 n.s. * M350 (Pylkkänen, Feintuch, Hopkins & Marantz, Cognition, to appear)

30. M250 M170 M350 RT (lexical decision) 1. Difference in the time course of competition. 2. High family size has an early facilitory effect. Why?

31. fine lie - ist –ize -ism loin pine TERROR LINE lane like light lime nine fine lie loin pine LINE lane like light lime nine 1. Difference in the time course of competition High frequency morphological family High density phonological neighborhood (frequency-weighted) • Relationship between target and competitors qualitatively different: difference is due to morphology. DECOMPOSITION • Difference is due to the different phonological and/or semantic properties of the competitors. terrorism TERROR NO DECOMPOSITION terrorist terrorize

32. fine lie loin pine LINE lane like light lime nine 1. Difference in the time course of competition • Non-decompositional account also predicts interference effects in priming for pairs such as TERRORISM – TERROR. • BUT this is completely unsupported by data – effect is robustly facilitory (e.g. a-d). • Difference is due to the different phonological and/or semantic properties of the competitors. terrorism TERROR NO DECOMPOSITION terrorist terrorize • (a) Marslen-Wilson, W. D., Tyler, L., Waksler, R., & Older, L. (1994). Morphology and meaning in the English mental lexicon. Psychological Review 101, 3-33. • (b) Pylkkänen, L. Stringfellow, A., Gonnerman, L., Marantz, A. 2002. Magnetoencephalographic indices of identity and similarity in lexical access. In preparation. • Gonnerman, L. 1999, Morphology and the lexicon: exploring the semantics-phonology interface, PhD thesis, University of Southern California. • Rastle, K., Davis, M., Marslen-Wilson, W., & Tyler, L.K. (2000). Morphological and semantic effects in visual word recognition: A time course study. Language and Cognitive Processes, 15, 507-538.

33. fine lie - ist –ize -ism loin pine TERROR LINE lane like light lime nine 1. Difference in the time course of competition High frequency morphological family High density phonological neighborhood (frequency-weighted) DECOMPOSITION • Competition between morphological family members appears to precede competition between phonological neighbors. • There are currently no models capturing this effect but what does seem clear is that an account of the phenomenon needs to make a distinction between morphological and phonological competitors.

34. 2. High family size has an early facilitory effect • One possibility: • Effect is semantic in nature and is related to effects of polysemy. • Heavily polysemous words (such as belt) are processed faster than words that only have few “senses” (such as ant). • (Rodd, Gaskell & Marslen-Wilson (2002) Making Sense of Semantic Ambiguity: Semantic Competition in Lexical Access. Journal of Memory and Language 46, 245–266) • Different morphological environments induce different senses of the root and therefore nouns with large morphological families have more senses than nouns with small morphological families. • Prediction: semantically opaque morphological family members should contribute to the family size effect the most, as those would involve the most “sense-switching”. • BUT: there is at least some evidence that the family size effect is in fact mostly carried by the semantically transparent members of the family. • (De Jong NH, Feldman LB, Schreuder R, Pastizzo M, Baayen RH (2002) The processing and representation of Dutch and English compounds: peripheral morphological and central orthographic effects. Brain Lang 2002 Apr-Jun;81(1- 3):555-67.)

35. -ic -ity -ify -head -test -washed -Ø -st -ø acid diary Keeping family frequency constant but lowering family size creates more potent competitors. 2. High family size has an early facilitory effect Alternatively: The family size effect is not a facilitory effect of high family size, but an inhibitory effect stemming from more potent competitors in the low family size condition. (See Perea and Rosa (2000) for a review of studies indicating that the important neighborhood variable in visual word recognition is not the number of neighbors per se, but the frequency of a word's neighbors relative to its own frequency. Perea M. and E. Rosa (2000) Psicologica, 21, 327-340)

36. Conclusion • Evidence for decomposition (although somewhat indirect). • Evidence for the existence of morphological competition (cf. Marslen-Wilson 1994). • Identification of a neural correlate of the morphological family size effect. Thanks to: Sophie Feintuch & Emily Hopkins (Portsmouth High School, NH)