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Language Electrified pp 447–503Cite as

Neural Correlates of Morphology Computation and Representation

Part of the Neuromethods book series (NM,volume 202)

Abstract

In this chapter, we critically review experiments on morphological processing focusing on compounds, derived and inflected words. Two main types of experiments are presented, those with single word or priming paradigms and those involving sentence processing, while focusing on morphological properties of words. We present as much cross-linguistic data as possible, in order to extract commonalities in morphological processing found across languages. Furthermore, studies on second-language learners, and occasionally early bilinguals, as well as child language development are presented, as they provide interesting data on differences and changes in brain behavior relating to morphological processing. Following this, we discuss domains of further research while highlighting issues in data interpretation for present and future studies, in the hopes that readers will be encouraged to develop innovative research paradigms for the study of morphological processing.

Key words

  • Lexical access
  • Morphology
  • Compounding
  • Derivation
  • Inflection
  • Sentence processing
  • Child language
  • Second-language learning
  • Bilingualism

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Notes

  1. 1.

    Headedness (e.g., right vs. left) differs across languages.

  2. 2.

    Reduplications, as its name implies, involves full—or partial—reduplication of a root or word stem. It is used for both derivation and inflection. For example, in Malagasy halo “mix” is reduplicated to create halohalo “mixed desert.”

  3. 3.

    Triple route models involving whole word, decomposition, and analogy are not addressed in neuropsychology [201, 202].

  4. 4.

    The point where the word has no other lexical competitors, here used for monomorphemes.

  5. 5.

    -reich can only combine with noun stems, e.g., farbereich “color + rich” = “colorful.”

  6. 6.

    With the exception of re- prefixed words which show the opposite pattern.

  7. 7.

    A locative case in Finnish.

  8. 8.

    The N250 is occasionally labeled the early N400. It can index formal processing [203, 204].

  9. 9.

    The past tense of “dive.”

  10. 10.

    Note that archer and arch are in fact morphologically related. The relation is semantically opaque in English. Stimuli lists were not provided.

  11. 11.

    Or uniqueness point in monomorphemic words.

  12. 12.

    A measure derived from the lexical frequencies of a given stem’s morphological family members [205].

  13. 13.

    Note however, that Schneebesen has a less frequent but transparent meaning “snow broom.”

  14. 14.

    All items – prime words and targets pictures– were named.

  15. 15.

    Within-sentence presentation was argued to be more ecological than single-word presentation, which is more likely to tap into post-lexical effects.

  16. 16.

    These results do not appear to be due to an interaction of the two frequency effects.

  17. 17.

    In exocentric compounds, the meaning of the whole is not related to either of the two stems. Verb + noun compounds are generally considered to be exocentric and do not have “heads.”

  18. 18.

    However, some analyses appear to show linear trends for semantic priming effects across conditions.

  19. 19.

    That is, regular but not default inflection [206,207,208].

  20. 20.

    See Subheading 3 for LAN effects and their functional interpretation.

  21. 21.

    Accusative is used for direct objects, dative for indirect ones.

  22. 22.

    Cross-modal priming (e.g., using auditory-visual prime–target pairs) attempts to avoid purely physical (visual or auditory) overlap effects between prime and target by “eliminat[ing] prelexical, modality-specific components of auditory [or visual] priming–including the priming of acoustic elements, phonemes, and syllables–and instead to limit the effects to the lexical entry” [206].

  23. 23.

    Some fMRI studies also point to differential regular and irregular priming effects (see [2] for a review) and involve additional languages such as Russian (e.g., [207,208,209,210]). Some argue that priming effects are linked to quantity of formal overlap rather than morphological priming [207]. Early studies using positron emission tomography (PET) found similar results, i.e., distinctions between regular and irregular verb processing [208, 210], but see [209] for contradictory evidence when a randomized design with oral sentence production was used instead of a blocked design with single-word production.

  24. 24.

    See also [211] for Mandarin Chinese compound processing using fMRI. Finnish and Japanese fMRI studies also suggest dedicated areas for inflection processing [212, 213].

  25. 25.

    Note that using mixed linear models can also cause interpretation issues, as using different intercepts can result in different results. See [183] for a discussion of priming data and models illustrating this problem.

  26. 26.

    In this study, separate experiments were run for regular and irregular verbs.

  27. 27.

    Post hoc analyses for these differences reported by the authors are not supported by the main effects or interactions.

  28. 28.

    Only small differences were found in Pz electrodes, 50–150 ms after word onset.

  29. 29.

    See also [214], directly contrasting P3b and P600 effects for syntactic structure errors.

  30. 30.

    We refer readers to the paper for discussion of differing effects across conditions.

  31. 31.

    Both the negativities and positivities were analyzed using the same time-windows. This is because effects overlapped to a large extent while showing different scalp distributions. Analyses thus focused on electrode sets that were selected a priori. See [130] for a method integrating all scalp electrodes and subsequently analyzing effects by region based on significant interactions.

  32. 32.

    Thus, when a participant saw a word like hasaxkaniot “the actresses,” they had a likely cue that the target verb would disagree with it in gender.

  33. 33.

    Note however that the LAN was not observed in an earlier similar experiment [218].

  34. 34.

    Note that this specific result depends on which baseline was used (−100 ms before the target or the N400 peak). We refer interested readers to the article.

  35. 35.

    But see [121] who observe positivities for overregularizations and irregularizations in list contexts even without sentences.

  36. 36.

    Children are known to default to the singular, and thus results might have varied based on this feature.

  37. 37.

    Contrary to most languages with inflection, the third person singular in English carries more morphological information than the plural.

  38. 38.

    “Long distance” is not really what is making these sentences more difficult to process, but rather their syntactic structure (accusativus cum infinitivo) linked to certain verbs and causative clauses that demand accusative objects which, in turn, subcategorize for uninflected infinitives (He makes him talk), not present tense forms as the authors claim. Furthermore, these sentences might induce attraction effects due to intervening noun phrases before the verb. See [219] for attraction effects in children and adults.

  39. 39.

    The authors also do not discuss -en irregularization patterns, which they also presented to participants.

  40. 40.

    Note that on average, only 22 items were analyzed by condition in child groups due to artifacts (adults retained 28–30/40 items per condition). Similar issues arise in another study [217].

  41. 41.

    Native Italians who reduced their exposure to Italian in adulthood having lived more than 10 years in an English L2 environment.

  42. 42.

    An fMRI study investigating highly proficient bilinguals suggests that language typology (i.e., richer vs. poorer morphology) might influence sensitivity to, or parsing strategies for, inflection morphology [218].

  43. 43.

    See also an fMRI study showing that morphological parsing strategies for derivation in two different languages may differ within the same Hebrew–English bilinguals [219].

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Authors and Affiliations

  1. Université de Montréal, CRBLM, BRAMS, Montreal, QC, Canada

    Phaedra Royle

  2. McGill University, CRBLM, Montreal, QC, Canada

    Karsten Steinhauer

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  1. Phaedra Royle
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  2. Karsten Steinhauer
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Correspondence to Phaedra Royle .

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  1. Centro di Ricerca Interdisciplinare sul Linguaggio (CRIL), University of Salento, Lecce, Italy

    Mirko Grimaldi

  2. Department of Clinical Medicine, Aarhus University, Aarhus, Denmark

    Elvira Brattico

  3. Center of Functionally Integrative Neuroscience (CFIN), Department of Clinical Medicine, Aarhus University, Aarhus, Denmark

    Yury Shtyrov

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Royle, P., Steinhauer, K. (2023). Neural Correlates of Morphology Computation and Representation. In: Grimaldi, M., Brattico, E., Shtyrov, Y. (eds) Language Electrified. Neuromethods, vol 202. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-3263-5_14

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