A Subsymbolic Model of Language Pathology in Schizophrenia (2007)
This paper reports first results of a simulation of language pathology in schizophrenia. Using DISCERN, a subsymbolic model of story understanding and recall, the impact of different simulated lesions hypothesized to underlie schizophrenia is investigated. In response to excessive connection pruning, the model reproduces symptoms of delusions and disorganized language seen in schizophrenia, as well as the reduced output seen in compensated later states of the disorder. The effects of other lesions are less consistent with the symptoms of schizophrenia. The model therefore forms a promising basis for future computational investigations into the underlying causes of schizophrenia.
In Proceedings of the 29th Annual Conference of the Cognitive Science Society, pp. 311-316, Hillsdale, NJ 2007. Erlbaum.

Uli Grasemann Postdoctoral Alumni uli [at] cs utexas edu
Ralph E. Hoffman Formerly affiliated Collaborator ralph hoffman [at] yale edu
Risto Miikkulainen Faculty risto [at] cs utexas edu

This package contains the C-code and data for training and testing the DISLEX model of the lexicon, which is also par...


PROC The PROC package contains the C-code and data for training and testing the story processing modules of the DISCERN syste... 1994

DISCERN DISCERN is a large, modular neural network system for reading, paraphrasing and answering questions about stereotypical ... 1993