Cortical instability and the mechanism of mania: a neural network simulation and perceptual test

Abstract

Background: A previous neural network simulation suggested that manic states arise from excessive levels of noise that destabilize neural representations. The Necker cube stick figure provides a simple perceptual task that assesses stability of gestalt-type representations. Methods: A neural network was developed that included a simulation of the Necker cube task. Noise was added to induce maniclike jumps from one representation to another. A parallel study of Necker cube perception was conducted with 16 patients diagnosed with manic-spectrum disorder, 18 patients with schizophrenia, and 19 normal control subjects. Cognitive speed and rate of indiscriminate responses were assessed using an auditory continuous performance task. Results: During processing of the “Necker cube” stimulus, the reversal rate of the noise-destabilized “manic” network was increased by 30%. In the human subject study, the median score of Necker cube reversal rates for manic-spectrum patients was roughly twice that of normal control subjects and patients with schizophrenia. Accelerated reversal rates in the manic-spectrum group were not attributable to excessive cognitive speed or higher rates of indiscriminate responses. Conclusions: The two studies, considered together, support the hypothesis that excessive cortical noise destabilizes neural representations in manic-spectrum patients.