Nikos Gekas PhD

Nikos Gekas

Research Interests

My primary research interest is to identify neural processes that accurately represent uncertainty in the cortex. Using psychophysical experimental procedures, I aim to investigate the properties of induced expectations, in particular the limits of forming priors in complex visual tasks of statistical learning, which involve feature-dependent as well as time-dependent paradigms. Using computational models, I aim to evaluate possible neural mechanisms of learning, and propose a unified framework that incorporates both uncertainty and learning.


Neural representations of uncertainty for perception and learning (PhD)