Semantic network abnormality predicts rate of cognitive decline in patients with probable Alzheimer's disease

Agnes S. Chan, Nelson Butters, Agnes S. Chan, Nelson Butters, Shannon A. Johnson, David P. Salmon

Research output: Contribution to journalArticlepeer-review

50 Citations (Scopus)

Abstract

The present study examined the relationship between rate of cognitive decline in patients with Alzheimer's disease (AD) and the integrity of the network of associations that comprise their semantic knowledge. The integrity of the semantic network of 12 AD patients was determined by comparing their networks to a standard normal control network derived with Pathfinder analysis, a multidimensional graphic analysis technique. A simple linear regression analysis, comparing the degree of semantic network deterioration with rate of cognitive decline as measured by the difference between the Dementia Rating Scale (DRS) scores obtained at the time of the testing of semantic knowledge (Year 1) and one year later (Year 2), was highly significant (r2 =. 84; p <. 001). These results suggest that a sensitive measure of the structural deterioration of semantic knowledge may be useful for predicting the rate of progression of cognitive changes in patients with AD. (JINS, 1995, 1, 297-303.).

Original languageEnglish
Pages (from-to)297-303
Number of pages7
JournalJournal of the International Neuropsychological Society
Volume1
Issue number3
DOIs
Publication statusPublished - May 1995
Externally publishedYes

Bibliographical note

Funding Information:
The authors thank Jody DeLaPena and Kirsten Taylor for help with scheduling and testing subjects. This study was supported in part by funds from the Medical Research Service of the Department of Veterans Affairs, by the Simeon Jacobs Memorial Fund, and by NIMH predoctoral fellowship MH-10609, NIA grant AG-05131, and NIMH grant MH-48819 to the University of California, San Diego.

ASJC Scopus Subject Areas

  • General Neuroscience
  • Clinical Psychology
  • Clinical Neurology
  • Psychiatry and Mental health

PubMed: MeSH publication types

  • Journal Article
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.
  • Research Support, U.S. Gov't, P.H.S.

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