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Contrasting gaze-based interaction vs. spontaneous gaze behavior: EEG, MEG and fMRI studies.
- Source :
- Journal of Eye Movement Research; 2019, Vol. 12 Issue 7, p155-155, 1p
- Publication Year :
- 2019
-
Abstract
- Unlike most human behaviors, eye movements with similar overt characteristics can be either automatic or intentional and consciously controlled. Contrasting these two types of eye movements may help to study mechanisms of intention and to search for the "markers" of intention in brain signals accompanying gaze- based interaction with a computer. We review our studies that employed this approach. Samples of gaze-based interaction and spontaneous gaze behavior were collected in participants who played "gaze-controlled" games. The data included EEG recorded under interaction using dwells (Shishkin et al., 2016) and smooth pursuit (Zhao et al., submitted), as well as MEG+EEG and (separately) fMRI recorded under interaction using dwells. Gaze dwells/pursuits were selected for analysis using a set of criteria maximizing contrast on the "intentionality" scale and minimizing influence of irrelevant factors. The EEG related to gaze interaction but not to spontaneous gaze behavior exhibited a component likely related to the feedback expectation, in line with Protzak et al. (2013). The MEG and the fMRI showed signs of brain activity that were unrelated to the feedback expectation and presumably more intention-specific. We are currently using contrasting interaction-related vs. spontaneous gaze behavior to develop an interface that on-the-fly classifies gaze events based on the neural markers, which we call the eye-brain-computer interface (EBCI). Such an interface may enable particularly fluent human-machine interaction. [ABSTRACT FROM AUTHOR]
- Subjects :
- GAZE
HUMAN behavior
ELECTROENCEPHALOGRAPHY
EYE movements
Subjects
Details
- Language :
- English
- ISSN :
- 19958692
- Volume :
- 12
- Issue :
- 7
- Database :
- Complementary Index
- Journal :
- Journal of Eye Movement Research
- Publication Type :
- Academic Journal
- Accession number :
- 142777736