Author
Listed:
- Stefan Albert
- Katharina Schmack
- Philipp Sterzer
- Gaby Schneider
Abstract
Viewing of ambiguous stimuli can lead to bistable perception alternating between the possible percepts. During continuous presentation of ambiguous stimuli, percept changes occur as single events, whereas during intermittent presentation of ambiguous stimuli, percept changes occur at more or less regular intervals either as single events or bursts. Response patterns can be highly variable and have been reported to show systematic differences between patients with schizophrenia and healthy controls. Existing models of bistable perception often use detailed assumptions and large parameter sets which make parameter estimation challenging. Here we propose a parsimonious stochastic model that provides a link between empirical data analysis of the observed response patterns and detailed models of underlying neuronal processes. Firstly, we use a Hidden Markov Model (HMM) for the times between percept changes, which assumes one single state in continuous presentation and a stable and an unstable state in intermittent presentation. The HMM captures the observed differences between patients with schizophrenia and healthy controls, but remains descriptive. Therefore, we secondly propose a hierarchical Brownian model (HBM), which produces similar response patterns but also provides a relation to potential underlying mechanisms. The main idea is that neuronal activity is described as an activity difference between two competing neuronal populations reflected in Brownian motions with drift. This differential activity generates switching between the two conflicting percepts and between stable and unstable states with similar mechanisms on different neuronal levels. With only a small number of parameters, the HBM can be fitted closely to a high variety of response patterns and captures group differences between healthy controls and patients with schizophrenia. At the same time, it provides a link to mechanistic models of bistable perception, linking the group differences to potential underlying mechanisms.Author summary: Patients suffering from schizophrenia show specific cognitive deficits. One way to study these cognitive phenomena works with the presentation of ambiguous stimuli. During viewing of an ambiguous stimulus, perception alters spontaneously between different percepts. Percept changes occur as single events during continuous presentation, whereas during intermittent presentation, percept changes occur at regular intervals either as single events or bursts. Here we investigate perceptual responses to continuous and intermittent stimulation in healthy control subjects and patients with schizophrenia. Interestingly, the response patterns can be highly variable but show systematic group differences. We propose a model that connects these perceptual responses to underlying neuronal processes. The model mainly describes the activity difference between competing neuronal populations on different neuronal levels. In a hierarchical manner, the differential activity generates switching between the conflicting percepts as well as between states of higher and lower perceptual stability. By fitting the model directly to empirical responses, a high variety of patterns can be reproduced, and group differences between healthy controls and patients with schizophrenia can be captured. This helps to link the observed group differences to potential neuronal mechanisms, suggesting that patients with schizophrenia tend to spend more time in neuronal states of lower perceptual stability.
Suggested Citation
Stefan Albert & Katharina Schmack & Philipp Sterzer & Gaby Schneider, 2017.
"A hierarchical stochastic model for bistable perception,"
PLOS Computational Biology, Public Library of Science, vol. 13(11), pages 1-38, November.
Handle:
RePEc:plo:pcbi00:1005856
DOI: 10.1371/journal.pcbi.1005856
Download full text from publisher
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pcbi00:1005856. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ploscompbiol (email available below). General contact details of provider: https://journals.plos.org/ploscompbiol/ .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.