A computational language approach to modeling prose recall in schizophrenia.

ABSTRACT: Many cortical disorders are associated with memory problems. In schizophrenia, verbal memory deficits are a hallmark feature. However, the exact nature of this deficit remains elusive. Modeling aspects of language features used in memory recall have the potential to provide means for measuring these verbal processes. We employ computational language approaches to assess time-varying semantic and sequential properties of prose recall at various retrieval intervals (immediate, 30 min and 24 h later) in patients with schizophrenia, unaffected siblings and healthy unrelated control participants. First, we model the recall data to quantify the degradation of performance with increasing retrieval interval and the effect of diagnosis (i.e., group membership) on performance. Next we model the huma

SUBMITTER: Rosenstein M 

PROVIDER: S-EPMC4039570 | biostudies-literature | 2014 Jun

REPOSITORIES: biostudies-literature