Previous lab members

  1. Post-doctoral researchers
  2. PhD researchers
  3. Visiting researchers
  4. Internship students

Post-doctoral researchers

Cristian Buc Calderon

Cristian 'Cris' Buc Calderon

My research focuses on understanding how humans select one out of many competing actions. My past research tested specific predictions of the affordance competition hypothesis (Cisek & Kalaska, 2010, Ann. Rev. Neurosci.), both at the neural architecture and decision dynamics levels (Calderon et al., 2015, JEPG; Calderon et al., 2017, PNAS; Calderon et al., 2018, Front. Hum. Neurosci.; Calderon et al., 2018, Psychol. Rev.).

More recently, I have been awarded a FWO postdoctoral fellow where I will investigate how the brain learns the optimal timing of individual actions within a sequence of actions (in collaboration with Michael Frank @ Brown University and Tom Verguts @ Ghent University). To carry out this project, I use computational modeling, behavioral and neural methods.

Kobe Desender

Kobe Desender

In my research, I focus on the question how metacognition is used for further adaptation of behavior. Currently, I examine how subjective confidence in a decision is used to further optimize cognition. Theoretical models of confidence posit an important role for confidence in learning and adapting behavior, and these are the dynamics that I wish to unravel. I combine behavioral measures, computational modeling, and electrophysiological recordings to answer these questions. In previous work performed during my PhD at the VUB (Belgium), I used behavioral and EEG recordings to unravel the relation between metacognition and conflict processing. I am supported by an FWO {PEGASUS} Marie Skłodowska-Curie fellowship.

ORCID iD icon@KDesender
ORCID iD iconhttps://kobedesender.com

PhD researchers

Kate Ergo

Kate Ergo

My research focuses on how reward and reward prediction errors (i.e., mismatches between reward outcome and reward expectation) influence declarative memory (e.g., learning a foreign language). To this end, I use both behavioral and (electro)physiological (i.e., EEG, tACS and eye tracking) measures. My PhD is funded by the Flanders Fund for Scientific Research (FWO).

GitHub icon@KateErgo
ORCID iD icon@KateErgo
ORCID iD iconhttps://kateergo.github.io

Visiting researchers

Fabrice Luyckx

Fabrice Luyckx

I am currently in the final stages of my DPhil at Oxford University in the Summerfield lab. My work focuses on how information is structured and transformed in the brain during decision making, mainly using neurophysiological measures (EEG) and computational modelling. One line of research has looked at how structure (e.g. a line, circle, hierarchy, …) is represented in the brain. For example we studied whether decisions about different categories with a shared underlying structure rely on the same neural signals (Luyckx et al., eLife, 2019). A different line of research has focused on the neural mechanisms of value-based decision making, specifically how neural patterns can shed a light on why we make economically “irrational” choices (Luyckx et al., CerCor, 2020).

GitHub icon@FabriceLuyckx
ORCID iD icon@NeuroLuyckx

Internship students

Jacopo Bonazzi

Jacopo Bonazzi

I’m a master student from Milano Bicocca University doing the internship in Ghent thanks to the Erasmus+ program. In this project I’m trying to understand how uncertainty and variability can influence inferences. We live in a world that is intrinsically chaotic, and uncertainty is omnipresent in every aspect of our life. Learning, choosing and predicting in such an environment requires estimating and computing how variable is the world and how reliable is the mental model used to capture this variability. The current project aims to unravel how these two different sources of uncertainty, namely expected and unexpected, influence visual search performance. I plan to collect behavioral data and test the predictions of different computational models.

When I’m not troubled by uncertainties, I love to sail (quite uncertain conditions anyway) and hike in the mountains!