Using a Speech Perception Neural Network Computer Simulation to Contrast Neuroanatomic versus Neuromodulatory Models of Auditory Hallucinations

R. E. Hoffman; T. H. McGlashan

doi:10.1055/s-2006-931496

Pharmacopsychiatry, Inhaltsverzeichnis

Pharmacopsychiatry 2006; 39: 54-64
DOI: 10.1055/s-2006-931496

Original Paper

Using a Speech Perception Neural Network Computer Simulation to Contrast Neuroanatomic versus Neuromodulatory Models of Auditory Hallucinations

R. E. Hoffman¹ , T. H. McGlashan¹

¹Department of Psychiatry, Yale University School of Medicine, Yale-New Haven Psychiatric Hospital, New Haven, USA

Support for research described in this article has been provided by NIMH grants RO1-MH50557 (REH), a Dana Foundation grant (REH) a NARSAD Independent Investigator Award, Peterson 50th Anniversary Research Partner (REH), NMH grants R21MH63326 and R01MH067073 (REH) and KO5-MH01654 (THM). Some portions of this article will appear shortly in a book chapter entitled, ”Using a speech perception neural network simulation to study normal neurodevelopment and auditory hallucinations in schizophrenia,” in Advances in Clinical Cognitive Science: Formal Modeling and Assessment of Processes and Symptoms. (Neufeld, R.W.J., ed), American Psychological Association Publications, Washington, D.C., in press.

Abstract

A number of studies suggest that schizophrenia may arise from overzealous pruning of synapses that are an extension of normal developmental pruning during adolescence. Moreover, there has been a long history of studies suggesting that this disorder arises from alterations in the dopaminergic neuromodulatory systems. In order to further assess and compare these two hypotheses, a computer simulation of some aspects of speech perception was developed utilizing a recurrent, backpropagation model of working memory previously reported by Elman [13]. This system was found to produce spontaneous percepts simulating hallucinated speech when the working memory component either was excessively pruned or when neuronal responses were modulated to simulatea hyperdopaminergic system. These hallucinogenic systems also demonstrated disruptions in processing input information when ”phonetic information” was degraded. The perceptual performance of these systems were compared to that of actual hallucinating patients and normal controls while tracking (repeating while simultaneously listening to) speech that was phonetically degraded. We found that the neural network simulation producing the best match to speech tracking performance of human hallucinators was an overpruned system with compensatory hypodopaminergic adjustments. These data suggest that the primary pathophysiology of schizophrenia arises from curtailed connectivity in working memory systems and that dopaminergic alterations reflect secondary compensatory adjustments.

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