A computerized technique to assess language use patterns in patients with frontotemporal dementia

Serguei V.S. Pakhomov, Glenn E. Smith, Susan Marino, Angela Birnbaum, Neill Graff-Radford, Richard Caselli, Bradley Boeve, David S. Knopman

Research output: Contribution to journalArticlepeer-review

19 Scopus citations


Frontotemporal lobar degeneration (FTLD) is a neurodegenerative disorder that affects language. We applied a computerized information-theoretic technique to assess the type and severity of language-related FTLD symptoms. Audio-recorded samples of 48 FTLD patients from three participating medical centers were elicited using the Cookie-Theft picture stimulus. The audio was transcribed and analyzed by calculating two measures: a perplexity index and an out-of-vocabulary (OOV) rate. The perplexity index represents the degree of deviation in word patterns used by FTLD patients compared to patterns of healthy adults. The OOV rate represents the proportion of words used by FTLD patients that were not used by the healthy speakers to describe the stimulus. In this clinically well-characterized cohort, the perplexity index and the OOV rate were sensitive to spontaneous language manifestations of semantic dementia and the distinction between semantic dementia and progressive logopenic aphasia variants of FTLD. Our study not only supports a novel technique for the characterization of language-related symptoms of FTLD in clinical trial settings, it also validates the basis for the clinical diagnosis of semantic dementia as a distinct syndrome.

Original languageEnglish (US)
Pages (from-to)127-144
Number of pages18
JournalJournal of Neurolinguistics
Issue number2
StatePublished - Mar 2010

Bibliographical note

Funding Information:
The work presented in this paper was supported by the United States National Institute of Aging grants: R01-AG023195 , P50-AG 16574 (Mayo Alzheimer's Disease Research Center), P30-AG19610 (Arizona ADC) and a Grant in Aid of Research from the University of Minnesota. We would also like to thank Dustin Chacon for helping with transcription of speech samples.


  • Entropy
  • Frontotemporal lobar degeneration
  • Perplexity
  • Semantic dementia
  • Statistical language modeling


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