Literaturnachweis - Detailanzeige
| Autor/in | Willis, Athena S. |
|---|---|
| Titel | The Role of the Mirror Mechanism in Perception of Signing Avatars |
| Quelle | (2023), (188 Seiten)
PDF als Volltext Ph.D. Dissertation, Gallaudet University |
| Sprache | englisch |
| Dokumenttyp | gedruckt; online; Monographie |
| ISBN | 979-8-3794-2829-7 |
| Schlagwörter | Hochschulschrift; Dissertation; Deafness; Sign Language; Young Children; Cognitive Processes; Motion; Computer Simulation; Brain; Familiarity; Prediction; Intention; Visual Stimuli; Visual Perception; Artificial Intelligence |
| Abstract | Recent research shows that deaf signers show increased behavioral and neural sensitivity to certain types of movement, such as biological motion, human actions, and signing avatars. However, other work suggests that in deaf signers exposed to signed language before age five, the mirror mechanism has minimal involvement during the perception of signed languages. The mirror mechanism is an essential brain function that allows us to draw on our prior embodied experiences to generate predictive simulation of people's movements. This embodied simulation allows us to draw on familiarity and predictive processing to perceive, understand, and learn people's movement, intentions, and meaning. The disparity in the function of the deaf signers' mirror mechanism during signed language perception is a crucial question because of the emergence of signing avatars designed to engage learners' embodied simulation for learning. To understand the role of the mirror mechanism in the perception of signing avatars' movements, we created stimuli that vary in two ways. Four Signer Types differ in their movements (Motion Capture or Computer Synthesized signing movements) and form (Human or Avatar). By comparing these 4 stimuli during signed language perception, I am able to draw conclusions about the effect of familiarity of human movement on the mirror mechanism. We collected EEG oscillations from deaf signers (N = 21) as they watched the movements of individual signed words from four different Signer Types. We conducted ANOVA planned contrasts and time-frequency analysis between each Signer Types. After the EEG experiment, we found a significant increase in self-reported behavioral rating of familiarity with the Mocap Avatar. While participants were observing a non-moving Mocap Avatar, we found a significant synchronization in mu frequency, the EEG indices of the mirror mechanism, compared to the other three Signer Types. This suggests that when deaf signers observe the identity of the Signer Type, their predictive processing rapidly changes their expected movement before the stimuli start moving. During the perception of Signer Types' dynamic movement, deaf signers showed a cubic pattern of power changes in mu frequency across Signer Types. The cubic model of mirror mechanism suggests that familiarity effect on their perception is modulated by prediction error, predictive processing, and neural efficiency. My pre-registered EEG study suggests that during the perception of signed words, deaf signers engage their mirror mechanism for predictive processing and embodied simulation of human movements in signed words. I showed that the differing views on the role of dynamic movements in signed language perception have led to designs of movements in signing avatars and A.I. for signed language technology that may not account for deaf signers' mirror mechanism. This requires a reappraisal of which aspects of signing movements are important in animation of signing avatars' movement. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.] (As Provided). |
| Anmerkungen | ProQuest LLC. 789 East Eisenhower Parkway, P.O. Box 1346, Ann Arbor, MI 48106. Tel: 800-521-0600; Web site: http://www.proquest.com/en-US/products/dissertations/individuals.shtml |
| Erfasst von | ERIC (Education Resources Information Center), Washington, DC |
| Update | 2024/1/01 |
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