Exposure to Co-occurrence Regularities in Language Drives Semantic Integration of New Words

Overview

Journal J Exp Psychol Learn Mem Cogn

Publisher American Psychological Association

Specialty Psychology

Date 2022 Apr 7

PMID 35389699

Authors

Olivera Savic

Layla Unger

Vladimir M Sloutsky

Affiliations

Soon will be listed here.

Abstract

Human word learning is remarkable: We not only learn thousands of words but also form organized semantic networks in which words are interconnected according to meaningful links, such as those between and . These links play key roles in our abilities to use language. How do words become integrated into our semantic networks? Here, we investigated whether humans integrate new words by harnessing simple statistical regularities of word use in language, including: (a) Direct co-occurrence (e.g., ) and (b) Shared co-occurrence (e.g., and both co-occur with ). In four reported experiments ( = 139), semantic priming (Experiments 1-3) and eye-tracking (Experiment 4) paradigms revealed that new words became linked to familiar words following exposure to sentences in which they either directly co-occurred, or shared co-occurrence. This finding highlights a potentially key role for co-occurrence in building organized word knowledge that is fundamental to our unique fluency with language. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

References

Huettig F, Rommers J, Meyer A . Using the visual world paradigm to study language processing: a review and critical evaluation. Acta Psychol (Amst). 2011; 137(2):151-71. DOI: 10.1016/j.actpsy.2010.11.003. View

Tse D, Langston R, Kakeyama M, Bethus I, Spooner P, Wood E . Schemas and memory consolidation. Science. 2007; 316(5821):76-82. DOI: 10.1126/science.1135935. View

Roelke A, Franke N, Biemann C, Radach R, Jacobs A, Hofmann M . A novel co-occurrence-based approach to predict pure associative and semantic priming. Psychon Bull Rev. 2018; 25(4):1488-1493. DOI: 10.3758/s13423-018-1453-6. View

Saffran J, Aslin R, Newport E . Statistical learning by 8-month-old infants. Science. 1996; 274(5294):1926-8. DOI: 10.1126/science.274.5294.1926. View

Schapiro A, Turk-Browne N, Botvinick M, Norman K . Complementary learning systems within the hippocampus: a neural network modelling approach to reconciling episodic memory with statistical learning. Philos Trans R Soc Lond B Biol Sci. 2016; 372(1711). PMC: 5124075. DOI: 10.1098/rstb.2016.0049. View

Mirman D, Dixon J, Magnuson J . Statistical and computational models of the visual world paradigm: Growth curves and individual differences. J Mem Lang. 2008; 59(4):475-494. PMC: 2593828. DOI: 10.1016/j.jml.2007.11.006. View

Frermann L, Lapata M . Incremental Bayesian Category Learning From Natural Language. Cogn Sci. 2015; 40(6):1333-81. DOI: 10.1111/cogs.12304. View

Willits J, Amato M, MacDonald M . Language knowledge and event knowledge in language use. Cogn Psychol. 2015; 78:1-27. PMC: 5951625. DOI: 10.1016/j.cogpsych.2015.02.002. View

Ouyang L, Boroditsky L, Frank M . Semantic Coherence Facilitates Distributional Learning. Cogn Sci. 2016; 41 Suppl 4:855-884. DOI: 10.1111/cogs.12360. View

10.

McClelland J, McNaughton B, OReilly R . Why there are complementary learning systems in the hippocampus and neocortex: insights from the successes and failures of connectionist models of learning and memory. Psychol Rev. 1995; 102(3):419-457. DOI: 10.1037/0033-295X.102.3.419. View

11.

Kirkham N, Slemmer J, Johnson S . Visual statistical learning in infancy: evidence for a domain general learning mechanism. Cognition. 2002; 83(2):B35-42. DOI: 10.1016/s0010-0277(02)00004-5. View

12.

Mestres-Misse A, Rodriguez-Fornells A, Munte T . Watching the brain during meaning acquisition. Cereb Cortex. 2006; 17(8):1858-66. DOI: 10.1093/cercor/bhl094. View

13.

Trueswell J, Medina T, Hafri A, Gleitman L . Propose but verify: fast mapping meets cross-situational word learning. Cogn Psychol. 2012; 66(1):126-56. PMC: 3529979. DOI: 10.1016/j.cogpsych.2012.10.001. View

14.

Dagenbach D, Horst S, Carr T . Adding new information to semantic memory: how much learning is enough to produce automatic priming?. J Exp Psychol Learn Mem Cogn. 1990; 16(4):581-91. DOI: 10.1037//0278-7393.16.4.581. View

15.

van Kesteren M, Beul S, Takashima A, Henson R, Ruiter D, Fernandez G . Differential roles for medial prefrontal and medial temporal cortices in schema-dependent encoding: from congruent to incongruent. Neuropsychologia. 2013; 51(12):2352-9. DOI: 10.1016/j.neuropsychologia.2013.05.027. View

16.

Pelucchi B, Hay J, Saffran J . Statistical learning in a natural language by 8-month-old infants. Child Dev. 2009; 80(3):674-85. PMC: 3883431. DOI: 10.1111/j.1467-8624.2009.01290.x. View

17.

Johns B, Mewhort D, Jones M . The Role of Negative Information in Distributional Semantic Learning. Cogn Sci. 2019; 43(5):e12730. DOI: 10.1111/cogs.12730. View

18.

Nation K, Snowling M . Developmental differences in sensitivity to semantic relations among good and poor comprehenders: evidence from semantic priming. Cognition. 1999; 70(1):B1-13. DOI: 10.1016/s0010-0277(99)00004-9. View

19.

Romberg A, Saffran J . Statistical learning and language acquisition. Wiley Interdiscip Rev Cogn Sci. 2011; 1(6):906-914. PMC: 3112001. DOI: 10.1002/wcs.78. View

20.

Tanenhaus M, Eberhard K, Sedivy J . Integration of visual and linguistic information in spoken language comprehension. Science. 1995; 268(5217):1632-4. DOI: 10.1126/science.7777863. View