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14 - Branching and Working Memory

A Cross-Linguistic Approach

from Part III - Linguistic Theories and Frameworks

Published online by Cambridge University Press:  08 July 2022

By
Federica Amici ,
Alejandro Sanchez-Amaro  and
Trix Cacchione
Edited by
John W. Schwieter  and
Zhisheng (Edward) Wen
John W. Schwieter
Affiliation:
Wilfrid Laurier University
Zhisheng (Edward) Wen
Affiliation:
Hong Kong Shue Yan University
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Summary

According to some researchers, different languages foster specific habits of processing information, which may be retained beyond the linguistic domain. In left-branching languages, for instance, the head is usually preceded by its dependents, and real-time sentence comprehension may require a different allocation of attention as compared to right-branching languages. Such sensitivity to the branching of languages may be so pervasive to also affect how humans process stimuli other than words in a sentence. In this chapter, we will review previous studies on the link between word order, statistical learning habits, and attention allocation, and specifically discuss the effects that branching habits may have on working memory processes, well beyond the linguistic domain. We will conclude by fostering a stronger cross-linguistic approach to the study of branching and working memory, and suggesting possible lines for future research.

Keywords

psycholinguisticsGreenbergian correlationsword orderattentionrecency effects
Type
Chapter
Information
The Cambridge Handbook of Working Memory and Language , pp. 304 - 321
Publisher: Cambridge University Press
Print publication year: 2022

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References

Amici, F., Sanchez-Amaro, A., Sebastian-Enesco, C., Allritz, M., Salazar, J., Cacchione, T., & Rossano, F. (2019). The word order of languages predicts native speakers’ working memory. Scientific Reports, 9, 1124.Google Scholar
Baddeley, A. (2003). Working memory: Looking back and looking forward. Nature Reviews Neuroscience, 4, 829–839.Google Scholar
Baddeley, A. D. (1986). Working memory. Oxford University Press.Google ScholarPubMed
Barrouillet, P., & Camos, V. (2007). The time-based resource-sharing model of working memory. In Osaka, N., Logie, R. H., & D’Esposito, M. (Eds.), The cognitive neuroscience of working memory. Oxford Scholarship Online.Google Scholar
Boroditsky, L. (2001). Does language shape thought? English and Mandarin speakers’ conceptions of time. Cognitive Psychology, 43, 1–22.Google Scholar
Brent, M. R., & Cartwright, T. A. (1996). Distributional regularity and phonotactic constraints are useful for segmentation. Cognition, 61, 93–125.Google Scholar
Caplan, D., & Waters, G. S. (1999). Verbal working memory and sentence comprehension. Behavioral and Brain Sciences, 22, 77–94.Google Scholar
Caplan, D., & Waters, G. S. (2013). Memory mechanisms supporting syntactic comprehension. Psychonomic Bulletin & Review, 20, 243–268.Google Scholar
Carpenter, P. A., & Just, M. A. (1988). The role of working memory in language comprehension. In Klahr, D. & Kotovsky, K. (Eds.), Complex information processing: The impact of Herbert A. Simon (pp. 31–68). Erlbaum.Google Scholar
Casasanto, D. (2005). Crying “Whorf.” Science, 307, 1721–1722.CrossRefGoogle ScholarPubMed
Casasanto, D., Boroditsky, L., Phillips, W., Greene, J., Goswami, S., Bocanegra-Thiel, S., Santiago-Diaz, I., Fotokopoulu, O., Pita, R., & Gil, D. (2004). How deep are effects of language on thought? Time estimation in speakers of English, Indonesian, Greek, and Spanish. Proceedings of the Annual Meeting of the Cognitive Science Society, 26, 186–191.Google Scholar
Chen, E., Gibson, E., & Wolf, F. (2005). Online syntactic storage costs in sentence comprehension. Journal of Memory and Language, 52, 144–169.CrossRefGoogle Scholar
Christiansen, M. H., & Chater, N. (2016). The now-or-never bottleneck: A fundamental constraint on language. Behavioral and Brain Sciences, 39, e62Google Scholar
Christiansen, M. H., & MacDonald, M. C. (2009). A usage-based approach to recursion in sentence processing. Language Learning, 59, 126–161.Google Scholar
Conway, A. R., Kane, M., Bunting, M., Hambrick, D., Wilhelm, O., & Engle, R. (2005). Working memory span tasks: A methodological review and user’s guide. Psychonomic Bulletin & Review, 12, 769–786.CrossRefGoogle ScholarPubMed
Cowan, N. (1995). Attention and memory: An integrated framework. Oxford University Press.Google Scholar
Cowan, N. (1999). An embedded-processes model of working memory. In Miyake, A. & Shah, P. (Eds.), Models of working memory: Mechanisms of active maintenance and executive control (pp. 62–101). Cambridge University Press.Google Scholar
Cowan, N. (2001). The magical number 4 in short-term memory: A reconsideration of mental storage capacity. Behavioral and Brain Sciences, 24, 87–185.Google Scholar
Cowan, N. (2014). Working memory underpins cognitive development, learning, and education. Educational Psychology Review, 26, 197–223.CrossRefGoogle ScholarPubMed
Cowan, N., Elliott, E. M., Scott, S. J., Morey, C. C., Mattox, S., Hismjatullina, A., & Conway, A. R. (2005). On the capacity of attention: Its estimation and its role in working memory and cognitive aptitudes. Cognitive Psychology, 51, 42–100.Google Scholar
de Villiers, J. G. (2007). The interface of language and theory of mind. Lingua, 117, 1858–1878.Google Scholar
Draganski, B., Gaser, C., Kempermann, G., Kuhn, H. G., Winkler, J., Büchel, C., & May, A. (2006). Temporal and spatial dynamics of brain structure changes during extensive learning. Journal of Neuroscience, 26, 6314–6317.Google Scholar
Dryer, M. S. (1992). The Greenbergian word order correlations. Language, 68, 81–138.Google Scholar
Dryer, M. S. (2002). Case distinctions, rich verb agreement, and word order type. Theoretical Linguistics, 28, 151–157.CrossRefGoogle Scholar
Dryer, M. S. (2009). The branching direction theory revisited. In Scalise, S., Magni, E., & Bisetto, A. (Eds.), Universals of language today (pp. 185–207). Springer.CrossRefGoogle Scholar
Dryer, M. S., & Haspelmath, M. (Eds.). (2013). The world atlas of language structures online. Max Planck Institute for Evolutionary Anthropology. http://wals.infoGoogle Scholar
Engle, R. W. (2002). Working memory capacity as executive attention. Current Directions in Psychological Science, 11, 19–23.Google Scholar
Engle, R. W., & Oransky, N. (1999). The evolution from short-term to working memory: Multi-store to dynamic models of temporary storage. In Sternberg, R. (Ed.), The nature of cognition (pp. 514–555). MIT Press.Google Scholar
Engle, R., Kane, M., & Tuholski, S. (1999). Individual differences in working memory capacity and what they tell us about controlled attention, general fluid intelligence, and functions of the prefrontal cortex. In Miyake, A. & Shah, P. (Eds.), Models of working memory: Mechanisms of active maintenance and executive control (pp. 102–134). Cambridge University Press.CrossRefGoogle Scholar
Evans, N., & Levinson, S. 2009. The myth of language universals: Language diversity and its importance for cognitive science. Behavioral and Brain Sciences, 32, 429–448.Google Scholar
Fausey, C. M., & Boroditsky, L. (2010). Subtle linguistic cues influence perceived blame and financial liability. Psychonomic Bulletin & Review, 17, 644–650.Google Scholar
Fausey, C. M., & Boroditsky, L. (2011). Who dunnit? Cross-linguistic differences in eye-witness memory. Psychonomic Bulletin & Review, 18, 150–157.CrossRefGoogle ScholarPubMed
Finn, A. S., Minas, J. E., Leonard, J. A., Mackey, A. P., Salvatore, J., Goetz, C., West, M. R., Gabrieli, C. F. O., & Gabrieli, J. D. E. (2017). Functional brain organization of working memory in adolescents varies in relation to family income and academic achievement. Developmental Science, 20, e12450CrossRefGoogle ScholarPubMed
Frank, S. L., Trompenaars, T., & Vasishth, S. (2016). Cross-linguistic differences in processing double-embedded relative clauses: Working-memory constraints or language statistics? Cognitive Science, 40, 554–578.Google Scholar
Frazier, L. (1985). Syntactic complexity. In Dowty, D. R., Karttunnen, L., & Zwicky, A. M. (Eds.), Natural language parsing: Psychological, computational, and theoretical perspectives (pp. 129–189). Cambridge University PressGoogle Scholar
Frazier, L., & Fodor, J. A. (1978). The sausage machine: A new two-stage parsing model. Cognition, 6, 291–325.Google Scholar
Garrod, S., & Pickering, M. J. (2004). Why is conversation so easy? Trends in Cognitive Sciences, 8, 8–11.Google Scholar
Gaser, C., & Schlaug, G. (2003). Brain structures differ between musicians and non-musicians. The Journal of Neuroscience, 23, 9240–9245.CrossRefGoogle ScholarPubMed
Gibson, E. A. (1998). Linguistic complexity: Locality of syntactic dependencies. Cognition, 68, 1–76.CrossRefGoogle ScholarPubMed
Gibson, E., & Pearlmutter, N. J. (1998). Constraints on sentence comprehension. Trends in Cognitive Sciences, 2, 262–268.Google Scholar
Gibson, E., & Thomas, J. (1999). Memory limitations and structural forgetting: The perception of complex ungrammatical sentences as grammatical. Language and Cognitive Processes, 14, 225–248.Google Scholar
Gilbert, A., Regier, T., Kay, P., & Ivry, R. (2006). Whorf hypothesis is supported in the right visual field but not the left. Proceedings of the National Academy of Sciences, 103, 489–494.Google Scholar
Gimenes, M., Rigalleau, F., & Gaonac’h, D. (2009). When a missing verb makes a French sentence more acceptable. Language and Cognitive Processes, 24, 440–449.Google Scholar
Gomez, R. L., & Gerken, L. A. (2000). Infant artificial language learning and language acquisition. Trends in Cognitive Sciences, 4, 178–186.CrossRefGoogle ScholarPubMed
Greenberg, J. H. (Ed.). (1963). Universals of language. MIT Press.Google Scholar
Hale, J. (2001). A probabilistic Earley parser as a psycholinguistic model. Proceedings of NAACL, 2, 159–166.Google Scholar
Hale, K. (1983). Warlpiri and the grammar of non-configurational languages. Natural Language & Linguistic Theory, 1, 5-47.CrossRefGoogle Scholar
Haun, D. B. M., Rapold, C., Call, J., Janzen, G., & Levinson, S. C. (2006). Cognitive cladistics and cultural override in Hominid spatial cognition. Proceedings of the National Academy of Sciences, 103, 17568–17573.Google Scholar
Hawkins, J. A. (1994). A performance theory of order and constituency. Cambridge University Press.Google Scholar
Hawkins, J. A. (2004). Efficiency and complexity in grammars. Oxford University Press.Google Scholar
Hawkins, J. A. (2014). Cross-linguistic variation and efficiency. Oxford University Press.CrossRefGoogle Scholar
Hunt, E., & Agnoli, F. (1991). The Whorfian hypothesis: A cognitive psychology perspective. Psychological Review, 98, 377–389.Google Scholar
Jaeger, L. A. (2015). Working memory and prediction in human sentence parsing (Doctoral dissertation, University of Potsdam). https://publishup.uni-potsdam.de/opus4-ubp/frontdoor/deliver/index/docId/8251/file/jaeger_diss.pdfGoogle Scholar
Just, M. A., & Carpenter, P. A. (1992), A capacity theory of comprehension: Individual differences in working memory. Psychological Review, 99, 122–149.Google Scholar
Kamide, Y., Altmann, G. T. M., & Haywood, S. L. (2003). The time-course of prediction in incremental sentence processing: Evidence from anticipatory eye movements. Journal of Memory and Language, 49, 133–156.Google Scholar
Kane, M. J., Conway, A. R. A., Hambrick, D. Z., & Engle, R. W. (2007). Variation in working memory capacity as variation in executive attention and control. In Conway, A. R. A., Jarrold, C., Kane, M. J., Miyake, A., & Towse, J. N. (Eds.), Variation in working memory (pp. 21–48). Oxford University Press.Google Scholar
Kane, M. J., & Engle, R. W. (2003). Working-memory capacity and the control of attention: The contributions of goal neglect, response competition, and task set to Stroop interference. Journal of Experimental Psychology: General, 132, 47–70.Google Scholar
Konieczny, L. (1996). Human sentence processing: A semantics-oriented parsing approach (Doctoral dissertation, Universität Freiburg). https://www.researchgate.net/publication/36150321_Human_sentence_processing_a_semantics-oriented_parsing_approachGoogle Scholar
Konieczny, L. (2000). Locality and parsing complexity. Journal of Psychological Research, 29, 627–645.Google Scholar
Levinson, S. C., & Wilkins, D. P. (Eds.). (2006). Grammars of space: Explorations in cognitive diversity. Cambridge University Press.Google Scholar
Levy, R. (2008). Expectation-based syntactic comprehension. Cognition, 106, 1126–1177.CrossRefGoogle ScholarPubMed
Lewis, R. L., Vasishth, S., & Van Dyke, J. A. (2006). Computational principles of working memory in sentence comprehension. Trends in Cognitive Sciences, 10, 44–54.Google Scholar
Li, P., & Gleitman, L. R. (2002). Turning the tables: Language and spatial reasoning. Cognition, 83, 265–294.CrossRefGoogle ScholarPubMed
Maguire, E., Gadian, D., Johnsrude, I, Good, D., Ashburner, J., Frackowiak, R., & Frith, C. (2000) Navigation-related structural changes in the hippocampi of taxi drivers. Proceedings of the National Academy of Sciences, 97, 4398–4403.Google Scholar
Mazuka, R. (1998). The development of language processing strategies: A cross-linguistic study between Japanese and English. Psychology Press.Google Scholar
Mazuka, R., & Lust, B. (1988). Why is Japanese not difficult to process? A proposal to integrate parameter setting in Universal Grammar and parsing. NELS, 18, 333–356.Google Scholar
Melby-Lervåg, M., & Hulme, C. (2013). Is working memory training effective? A meta-analytic review. Developmental Psychology, 49, 270–291.Google Scholar
Miller, G. (1956). The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psychological Review, 63, 81–97.Google Scholar
Morrison, A. B., Conway, A. R., & Chein, J. M. (2014). Primacy and recency effects as indices of the focus of attention. Frontiers in Human Neuroscience, 8, 6.Google Scholar
Nakatani, K., & Gibson, E. (2010). An on-line study of Japanese nesting complexity. Cognitive Science, 34, 94–112.Google Scholar
Núñez, R. E., & Sweetser, E. (2006). With the future behind them: Convergent evidence from Aymara language and gesture in the crosslinguistic comparison of spatial construals of time. Cognitive Science, 30, 401–450.Google Scholar
Onnis, L., & Thiessen, E. (2013). Language experience changes subsequent learning. Cognition, 126, 268–284.Google Scholar
Pearlmutter, N. J., & MacDonald, M. C. (1995). Individual differences and probabilistic constraints in syntactic ambiguity resolution. Journal of Memory and Language, 34, 521–542.Google Scholar
Pica, P., Lemer, C., Izard, V., & Dehaene, S. (2004). Exact and approximate arithmetic in an Amazonian indigene group. Science, 306, 499–503.Google Scholar
Pickering, M. J., & Garrod, S. (2007). Do people use language production to make predictions during comprehension? Trends in Cognitive Sciences, 11, 105–110.Google Scholar
Pienemann, M. (Ed.). (2005). Cross-linguistic aspects of processability theory. John Benjamins Publishing.Google Scholar
Pyers, J. E., & Senghas, A. (2009). Language promotes false-belief understanding evidence from learners of a new sign language. Psychological Science, 20, 805–812.Google Scholar
Regier, T., & Kay, P. (2009). Language, thought, and color: Whorf was half right. Trends in Cognitive Sciences, 13, 439–446.Google Scholar
Saffran, J. R. (2003). Statistical language learning: Mechanisms and constraints. Current Directions in Psychological Science, 12, 110–114.CrossRefGoogle Scholar
Saffran, J. R., Aslin, R. N., & Newport, E. L. (1996). Statistical learning by 8-month-old infants. Science, 274, 1926–1928.Google Scholar
Seidenberg, M. S. (1997). Language acquisition and use: Learning and applying probabilistic constraints. Science, 275, 1599–1603.Google Scholar
Slobin, D. I. (1996). From “thought and language” to “thinking for speaking.” In Gumperz, J. J. & Levinson, S. C. (Eds.), Studies in the social and cultural foundations of language: Rethinking linguistic relativity (pp. 70–96). Cambridge University Press.Google Scholar
Spelke, E. S., & Tsivkin, S. (2001). Language and number: A bilingual training study. Cognition, 78, 45–88.Google Scholar
Stivers, T., Enfield, N. J., Brown, P., Englert, C., Hayashi, M., Heinemann, T., Hoymann, G., Rossano, F., de Ruiter, J., Yoon, K. E., & Levinson, S. C. (2009). Universals and cultural variation in turn-taking in conversation. Proceedings of the National Academy of Sciences, 106, 10587–10592.Google Scholar
Thiessen, E. D., Onnis, L., Hong, S. J., & Lee, K. S. (2019). Early developing syntactic knowledge influences sequential statistical learning in infancy. Journal of Experimental Child Psychology, 177, 211–221.Google Scholar
Unsworth, N., Fukuda, K., Awh, E. & Vogel, E. K. (2014). Working memory and fluid intelligence: Capacity, attention control, and secondary memory retrieval. Cognitive Psychology, 71, 1–26.Google Scholar
Unsworth, N., Heitz, R. P., Schrock, J. C., & Engle, R. W. (2005). An automated version of the operation span task. Behavior Research Methods, 37, 498–505.Google Scholar
Vasishth, S. (2003). Working memory in sentence comprehension: Processing Hindi center embeddings. Garland Press.Google Scholar
Vasishth, S., & Lewis, R. L. (2006). Argument-head distance and processing complexity: Explaining both locality and anti-locality effects. Language, 82, 767–794.CrossRefGoogle Scholar
Vasishth, S., Suckow, K., Lewis, R. L., & Kern, S. (2010). Short-term forgetting in sentence comprehension: Cross-linguistic evidence from verb-final structures. Language and Cognitive Processes, 25, 533–567.CrossRefGoogle Scholar
Winawer, J., Witthoft, N., Frank, M. C., Wu, L., Wade, A. R., & Boroditsky, L. (2007). Russian blues reveal effects of language on color discrimination. Proceedings of the National Academy of Sciences, 104, 7780–7785.CrossRefGoogle ScholarPubMed
Woollett, K., & Maguire, E. A. (2011). Acquiring “the knowledge” of London’s layout drives structural brain changes. Current Biology, 21, 2109–2114.Google Scholar

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