Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Learning and morphological change

M Hare1, J L Elman

  • 1Center for Research in Language, University of California, San Diego, La Jolla 92093-0526, USA.

Cognition
|July 1, 1995
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Racial disparities in the treatment of endometrial intraepithelial neoplasia in postmenopausal women.

Gynecologic oncology reports·2024
Same author

High-precision measurement of the <i>W</i> boson mass with the CDF II detector.

Science (New York, N.Y.)·2022
Same author

Search for the Exotic Meson X(5568) with the Collider Detector at Fermilab.

Physical review letters·2018
Same author

Combined Forward-Backward Asymmetry Measurements in Top-Antitop Quark Production at the Tevatron.

Physical review letters·2018
Same author

Tevatron Combination of Single-Top-Quark Cross Sections and Determination of the Magnitude of the Cabibbo-Kobayashi-Maskawa Matrix Element V_{tb}.

Physical review letters·2015
Same author

Search for Resonances Decaying to Top and Bottom Quarks with the CDF Experiment.

Physical review letters·2015
Same journal

Corrigendum to 'Consonant, vowel, and tone cues in early wordform recognition: Evidence from Cantonese-learning infants' [Cognition 275 (2026) 106624].

Cognition·2026
Same journal

Identifying distinct sources of whole number interference in children's decimal comparison: the role of numerical magnitude and inhibitory control.

Cognition·2026
Same journal

Evidence for abstract spatial concept learning in young animals.

Cognition·2026
Same journal

Blurred lines or clear boundaries? Synchrony and social dominance shape domain-specific self-other processing.

Cognition·2026
Same journal

Knowability predicts curiosity and learning.

Cognition·2026
Same journal

Throwing good effort after bad: Evidence for a sunk-cost effect in cognitive effort-based decision-making.

Cognition·2026
See all related articles

This study models English verb morphology changes using a connectionist approach. It shows how irregular verb forms become regularized over time due to learning patterns in networks.

Area of Science:

  • Computational linguistics
  • Historical linguistics
  • Cognitive science

Background:

  • English verb morphology has evolved significantly from Old English to Modern English.
  • Understanding the mechanisms of language change, particularly grammatical regularization, is crucial.

Purpose of the Study:

  • To model the historical changes in English verb inflection using a connectionist approach.
  • To investigate how morphological knowledge is acquired and applied in language change.

Main Methods:

  • Developed a technique for modeling historical change in connectionist networks.
  • Trained networks on Old English verb data, simulating learning processes.
  • Used error propagation between networks to mimic generational transmission of linguistic patterns.

Related Experiment Videos

Main Results:

  • Connectionist networks demonstrated a tendency to regularize irregular patterns over simulated time.
  • Learned patterns were influenced by frequency and phonological regularities, mirroring historical linguistic trends.
  • Simulated results closely matched observed historical developments in English verb inflection.

Conclusions:

  • Connectionist network dynamics provide a computational rationale for the observed regularization in English verb morphology.
  • The model successfully accounts for the gradual shift from complex Old English verb systems to the simpler Modern English system.
  • This approach offers insights into the cognitive underpinnings of language evolution.