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Connectionist approaches to understanding aphasic perseveration.

Stephen J Gotts1, David C Plaut

  • 1Department of Psychology, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA. gotts@nih.gov

Seminars in Speech and Language
|December 16, 2004
PubMed
Summary

Connectionist models offer insights into aphasic perseveration, a speech error common in patients with brain damage. Refining these models by including neuromodulatory system interactions may better explain perseverative errors in aphasia.

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Area of Science:

  • Neuroscience
  • Computational Linguistics
  • Psycholinguistics

Background:

  • Aphasic patients exhibit diverse speech errors, including perseverations, during language tasks.
  • Understanding these errors provides crucial insights into both damaged and intact language systems in the brain.

Purpose of the Study:

  • To explore the mechanisms underlying aphasic perseveration using connectionist models.
  • To evaluate the efficacy of existing models and propose improvements based on recent data.

Main Methods:

  • Reviewing the Plaut and Shallice connectionist model for optic aphasic errors in object naming.
  • Analyzing the limitations of current models in explaining recent aphasic perseveration data.

Main Results:

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  • The Plaut and Shallice model, based on short-term learning, partially explains aphasic perseverations.
  • Existing models face limitations in fully accounting for complex aphasic perseveration patterns.

Conclusions:

  • Connectionist models provide a valuable framework for understanding aphasic perseveration.
  • Integrating neuromodulatory system interactions with learning mechanisms can enhance models of aphasia and perseveration.