Researchers at the University of Texas at Austin recently used a virtual computer model, also known as a neural network, to test what happens when the your brain releases excess dopamine. In doing so they found that the network acted schizophrenic, in other words, they gave a computer Schizophrenia.
The researchers, in an effort to study disorganized speech and delusions in schizophrenia, simulated eight different corresponding illness mechanisms in DISCERN, an artificial neural network model for narrative understanding and recall. Some of these illness mechanisms involved malfunctions in “working memory, semantics, prediction error, and dopamine neuromodulation.”
In addition to using DISCERN to simulate illness mechanisms, the researchers also studied living persons with schizophrenia or schizoaffective disorders. By studying the live subjects the researchers were able to determine which mechanisms were related to certain illnesses or narrative breakdown profiles. Then comparing that data to what DISCERN was simulating they were able to verify that they had made the correct matching between illness mechanisms and narrative breakdown profiles.
In the end they found that their network worked for matching for healthy control subjects. But when they tested certain mechanisms like spisodic memories they found that the simulations yielded massive delusion. Also, while simulating excessive dopamin release, researchers found that the neural network produced memories very much like those of person suffering from Schizophrenia. After a while, the neural network started putting itself in the center of stories–some which were very absurd. At one point the computer system claimed responsibility for a terrorist bombing.
The researchers concluded that persons with schizophrenia have a problem where narrative memories in long term storage (long-term memory?) are corrupted and exaggeratedcausing the schizophrenic to produce wild and delusional stories. To get the full details check out the article published in Biological Psychiatry.
[PubMed and University of Texas at Austin via Gizmodo / Photo: skpy on Flickr (CC BY-SA 2.0)]
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