Predicting functional vision via multi-sensory interactions

I joined Unit for Visually Impaired People at Istituto Italiano di Tecnologia, Genova Italy in August 2022.I am carrying out the project under the supervision of Dr. Monica Gori and Prof. Dr. Silvio P. Sabatini.

Personal Background and Interests: 

• Bachelor's degree in Foreign Languages Education at Yıldız Technical University
• Teaching experience as a lecturer at Kapadokya University's Aviation Department.
• Master's degree in Cognitive Science at Yeditepe University. During my studies, I focused on cognitive vision and subsequently applied for my current position.
• Ph.D. student in the Bioengineering and Robotics department at Università degli Studi di Genova. My research primarily involves developing applications and devices for detecting visual scotoma.

Outside of my academic pursuits, I:

• create digital content by/with photo and video editing, programming, Unity.
• practice Japanese calligraphy and follow the principles of Ni-Ten Ichi Ryu.
• enjoy charcoal drawing and playing instruments. 

Aim of the project:

The objectives of this project are to 1) determine whether individuals with a scotoma experience audio-spatial compression in their blind zone and whether this can be used to establish the presence of scotoma and predict functional vision and 2) use a recently developed audio device and VR to quantify the auditory space compression with psychophysics, eye-tracking and EEG.

Current activities:

To date, I have developed various preliminary tools to quantify the modulation of audio space in scotoma patients. The technical availability at this stage is optimal for central scotoma measurements. I am currently conducting an experiment to determine whether individuals with a central scotoma have audio-spatial compression in their blind zone. Since the experiment aims to measure the very basic foundational principles of the project, the results from the first data collection period are expected to enhance the later stages of the project.

Future directions:

As a follow-up, the tool will be tested in peripheral scotoma patients. The collected data will be used to train machine learning algorithms. Ultimately, I hope to implement the tool in VR or mobile technologies.