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Hyperlearning: A Connectionist Model of Psychosis in Schizophrenia (2009)
Uli Grasemann
,
Risto Miikkulainen
and
Ralph Hoffman
Abnormal brain processes that underlie schizophrenia are incompletely understood. Diagnosis of this disorder relies in large part on psychotic symptoms that are observed through conversational language. In this paper, two such symptoms, delusions (fixed false beliefs) and derailments (inability to follow a coherent discourse plan) are modeled using DISCERN, a connectionist model of human story processing. Simulations of alternative pathologies thought to underlie schizophrenia are applied to DISCERN, and the resulting language abnormalities are evaluated for symptoms of schizophrenia. "Hyperlearning", a simulation of excessive dopamine release, is shown to produce a compelling model for both delusional and derailed language. Applied to different locations in the model, hyperlearning led to different symptoms, suggesting how clinical subtypes of schizophrenia could arise from a common underlying process.
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PDF
Citation:
In
Proceedings of the 31st Annual Meeting of the Cognitive Science Society
, N. A. Taatgen and H. van Rijn (Eds.), Amsterdam, The Netherlands 2009.
Bibtex:
@InProceedings{grasemann:cogsci09, title={Hyperlearning: A Connectionist Model of Psychosis in Schizophrenia}, author={Uli Grasemann and Risto Miikkulainen and Ralph Hoffman}, booktitle={Proceedings of the 31st Annual Meeting of the Cognitive Science Society}, editor={N. A. Taatgen and H. van Rijn}, address={Amsterdam, The Netherlands}, url="http://www.cs.utexas.edu/users/ai-lab?grasemann:cogsci09", year={2009} }
People
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
Areas of Interest
Brain and Cognitive Disorders
Computational Neuroscience
Labs
Neural Networks