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A computerized technique to assess language use patterns in patients with frontotemporal dementia
Serguei Vs Pakhomov1, Glenn E Smith, Susan Marino
1Center for Clinical and Cognitive Neuropharmacology, University of Minnesota, Twin Cities, Minnesota.
Journal of Neurolinguistics
|March 2, 2011
Summary
Frontotemporal lobar degeneration (FTLD) language impairments were assessed using information theory. Novel measures, perplexity and OOV rate, distinguished FTLD subtypes, aiding clinical diagnosis.
Area of Science:
- Neuroscience
- Linguistics
- Computational Linguistics
Background:
- Frontotemporal lobar degeneration (FTLD) is a group of neurodegenerative disorders primarily affecting language and behavior.
- Language deficits are a hallmark of several FTLD subtypes, necessitating accurate diagnostic tools.
Purpose of the Study:
- To evaluate a novel computerized information-theoretic technique for characterizing language impairments in FTLD.
- To assess the sensitivity of perplexity and out-of-vocabulary (OOV) rates in distinguishing FTLD variants.
Main Methods:
- Analysis of audio-recorded speech samples from 48 FTLD patients using the Cookie Theft picture stimulus.
- Calculation of perplexity index and OOV rate to quantify deviations in word patterns and vocabulary usage.
- Comparison of patient measures against a normative dataset of healthy adult speech patterns.
Main Results:
- The perplexity index and OOV rate effectively captured spontaneous language alterations in FTLD patients.
- These measures demonstrated sensitivity in differentiating semantic dementia from progressive logopenic aphasia.
- The technique showed potential for objective language assessment in clinical trials.
Conclusions:
- Information-theoretic measures provide a novel, objective method for characterizing FTLD-related language deficits.
- Perplexity and OOV rates can aid in the differential diagnosis of FTLD subtypes, particularly semantic dementia.
- This approach supports the validation of semantic dementia as a distinct clinical syndrome.
