Logo image
We make predictions about eye of origin of visual input: Visual mismatch negativity from binocular rivalry
Journal article   Open access   Peer reviewed

We make predictions about eye of origin of visual input: Visual mismatch negativity from binocular rivalry

B.N. Jack, U. Roeber and R.P. O'Shea
Journal of Vision, Vol.15(13), pp.1-19
2015
pdf
negativity from binocular rivalry.pdfDownloadView
Published (Version of Record)CC BY V4.0 Open Access
url
Free to Read *No subscription requiredView

Abstract

The visual mismatch negativity (vMMN) is a negative component of event-related potentials (ERPs). It occurs when an infrequent visual stimulus, a deviant, is randomly and unpredictably presented in a sequence of frequent visual stimuli, the standards, and is thought to reflect prediction and prediction error of visual input. We investigated the sensitivity of vMMN to eye of origin (utrocular) information as well as to orientation information. We presented 80% of binocular rivalry standards (one grating to one eye and an identical, orthogonally oriented grating to the other eye), and 20% of deviants, either by swapping the gratings between the eyes to change the eye of origin of the gratings (an eye-swap deviant) or by rotating the gratings by 45° to change the orientation of the gratings (an orientation deviant). We found an orientation vMMN that was maximal at about 250 ms and an eye-swap vMMN that was maximal at about 380 ms. We also found deviance-related activity to both sorts of stimuli earlier than is traditionally defined as a vMMN. We used standardized low-resolution brain electromagnetic tomography (sLORETA) to localize each vMMN component and found similar sources for both vMMNs in occipital and frontal areas of the brain but differences in parietal and temporal areas. We conclude that eye of origin information can be used to elicit vMMN, that eye-swap vMMN is different to orientation vMMN, and that vMMN can be generated from information of which observers are unaware.

Details

UN Sustainable Development Goals (SDGs)

This output has contributed to the advancement of the following goals:

#3 Good Health and Well-Being

Source: InCites

Metrics

116 File views/ downloads
33 Record Views

InCites Highlights

These are selected metrics from InCites Benchmarking & Analytics tool, related to this output

Collaboration types
Domestic collaboration
International collaboration
Citation topics
1 Clinical & Life Sciences
1.7 Neuroscanning
1.7.968 Mismatch Negativity
Web Of Science research areas
Ophthalmology
ESI research areas
Clinical Medicine
Logo image