Models of Auditory Hallucination

Overview

The purpose of this study is to address the shortcoming in clinical hallucination research by causally manipulating the neural loci of conditioned hallucination task behavior in-person in patients with psychosis using transcranial magnetic stimulation (TMS), tracking the impact of this manipulation on the number of times participants with hallucinations report hearing tones that were not presented. With such a causal intervention, the veracity of this explanation of hallucinations will be either validated or disconfirmed. If validated, the task can be further developed as a biomarker for predicting the hallucination onset, guiding, developing or tracking the effects of treatments for hallucinations.

Hallucinations are percepts without stimulus. 70% of patients with schizophrenia suffer distressing auditory hallucinations. Their mere presence increases the risk of suicide. Most reach remission with D2 dopamine receptor blocking drugs after 1 year of adherence. However, 30% of patients have intractable hallucinations, and 50% are non-adherent to their medications, commonly because of unfavorable side-effects - those intractable and non-adherent patients continue to suffer. There is a clear need for a mechanistic understanding of hallucinations as a prelude to rational treatment design. This study provides the initial steps towards the development of an interventional biomarker for clinical hallucinations, grounded in computational neuroscience. Computational psychiatry involves harnessing the power of computational neuroscience to address the clinical needs of those suffering from serious mental illnesses. There has been much discussion of the promise of the approach. There have been few studies thus far and they have largely involved correlative methods like functional neuroimaging. This study will address this shortcoming by causally manipulating the neural loci of computational model parameters in-person in patients with psychosis using transcranial magnetic stimulation (TMS), tracking the impact of this manipulation on behavioral task performance . With such a causal intervention, the veracity of the model's explanation of hallucinations will be either validated or disconfirmed. If validated, the model can be further developed as a biomarker for predicting the hallucination onset, guiding, developing or tracking the effects of treatments for hallucinations. If disconfirmed, the model ought to be discarded and other alternatives should be pursued.