Towards a neural network based therapy for hallucinatory disorders.
J R Peláez
Neural Networks 2000 DOI: 10.1016/s0893-6080(00)00069-1 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Theoretical or philosophical paper Peer reviewed |
|---|---|
| Key points | Argues that diverse hallucinations—visual (Charles Bonnet syndrome, psychedelics), somatic (phantom limbs), and cognitive (schizophrenia, multiple personality disorders)—share a common mechanism of pattern completion in thalamic deafferented areas, modeled via a thalamic neural network and synaptic plasticity. Proposes that treatments combining peripheral stimulation with central inhibition alleviate these disorders by depressing the implicated neural circuits. |
Abstract
Pattern completion in a neural network model of the thalamus and a biologically plausible model of synaptic plasticity are the key concepts used in this paper for analyzing some cognitive disorders that involve hallucinations of several kinds: visual hallucinations in the Charles Bonnet syndrome and psychedelic drugs consumption, somatic hallucination in phantom limbs, cognitive hallucinations in schizophrenia and even in multiple personality disorders. All these types of hallucinations are proposed to be the result of a pattern completion dynamics performed in thalamic deafferented areas. Effective treatments of some of these disorders involve peripheral stimulation jointly with a central inhibition so that the neural circuits generating the disorders are depressed according to the proposed model of synaptic plasticity.