Michal Gabay
Minducate Ph.D.
School of Neurobiology, Biochemistry and Biophysics, Faculty of Life Science, and Sagol School of Neuroscience.
PI: Prof. Tom Schonberg, School of Neurobiology, Biochemistry and Biophysics, Faculty of Life Science, and Sagol School of Neuroscience.
THE EFFECT OF EXPERIENCE MODALITY ON INDIVIDUAL LEARNING CHARACTERISTICS
Project description
The utilization of the immersive and gamified nature of virtual reality (VR) is spreading in research and real-world applications. Specifically, it seems to hold a promise for enhancement of learning processes in general and particularly in education systems. However, the impact of using VR on cognitive processes is yet to be determined. A crucial step to achieve meaningful utilization of VR is identifying the effect of using VR in experiences on cognitive and individual performance.
Here, we aim to address this basic gap by comparing learning properties and experience measures in three modality settings of spatial navigation. We translated a classic spatial learning task from animals to humans, where three spatial learning strategies were observed. In our experiment we will compare 3 conditions: In two of the settings participants will wear a VR headset with a built-in eye-tracker comparing walking physically vs. using a controller, and in the 3rd, the environment will be displayed on a 2D screen and navigated with a mouse and keyboard to control movement. Learning properties of navigational strategy used, and experience measures will be assessed using behavioral and eye-tracking (ET) data and presence questionnaires.
Our findings could shed light on the effect of using VR in different cognitive and learning processes and their related physiological signals of ET. These in turn may serve for optimization of VR utilization for development of learning tasks in education systems and professional training, and potentially provide with novel means to diagnose different psychiatric disorders.
About me
Michal Gabay, has a BSc and an MSc in biomedicalengineering from the Technion and Tel-Aviv University respectively, graduated with honors. During her studies she specialized in physiological mathematical models, and signal and image processing. Thereafter, Michal has joined a biomedical startup company as a machine learning (ML) and computer vision algorithms developer and team leader, with the objective of early breast cancer detection. After 6 years and motivated by a great interest in individual learning differences and their underlying neural mechanism, Michal has joined Tom Schonberg’s lab in Sagol School for Neuroscience as a data scientist. Following a year of specializing in multivariate pattern analysis of functional magnetic resonance imaging she started her PhD there in 2018. Michal aims to find the relation between individuals' learning differences and their physiological and neurological signals (as ET, and MRI), using a gamified VR environment, to enhance learning.
At the beginning of her PhD, Michal co-founded a professional and social platform for PhD students who identify as women in the field of Neuroscience on campus, named “Women who Brain” to provide with tools for the unique challenges women encounter during their PhD.