Graduate School of Informatics /Cognitive Sciences

In partial fulfillment of the requirements for the degree of Master of Science Çağatay Taşcı will defend his thesis.

Title: AN INVESTIGATION OF BRAIN-TO-BRAIN CONNECTIVITY PATTERNS DURING A COOPERATIVE FLUID INTELLIGENCE TASK

Date: 31st August 2018

Time: 11:30 AM

Place: A-108

Thesis Abstract : Several studies have shown that executing the same task simultaneously can create synchronization among participants’ brain hemodynamics (Funane et al. 2011; Osaka et al. 2015). In this thesis we aim to examine multiple participants’ brain hemodynamics while they engage with a cooperative Raven’s matrices task which requires them to combine and coordinate the information they individually posses to correctly solve the given puzzle. We will use NIRS (Near-infrared spectroscopy) hyperscanning to observe the brain hemodynamics of two participants simultaneously while they are engaged with a fluid intelligence task organized in a jigsaw format. Machine learning techniques will be employed to extract patterns from raw neuroimaging data in terms of brain-to-brain connectivity patterns in the prefrontal cortex to predict the level of success. We expect to observe increased coherence in the partners’ prefrontal cortices during successful trials. Through this study we aim to contribute to the literature with new findings on brain-to-brain correlates of social interaction.