I am an associate professor at the Donders Institute and the department of Artificial Intelligence (AI) of the Radboud University. My research interests are centered around understanding the large-scale dynamics of brain function, both over time and across the lifespan. I also teach Brain for AI students and am involved in the AI honours program at Radboud University. Before moving to the Donders, I did a postdoc with Rik Henson at the MRC-Cognition and Brain Sciences Unit in Cambridge and a PhD with Monicque Lorist and Natasha Maurits at the University of Groningen. In my free time I enjoy walking and cycling in the beautiful nature around Nijmegen.
I am a postdoctoral researcher in cognitive neuroscience at the Donders Institute. My current project is about brain function in people who are highly sensitive to external stimuli, and how that relates to their physical and mental health outcomes in different environments. I completed an MSc in biomedical neuroscience at the Icahn School of Medicine at Mount Sinai in New York City, and a PhD in cognitive neuroscience at the Donders Institute in Nijmegen. As a fan of public outreach and science communication, I also spend time as a blogger and editor for Donders Wonders. In my spare moments, I love to get lost in her sketch book, a museum, or my thoughts.
As a postdoctoral fellow I use neuroimaging analyses techniques to investigate associations between task-related functional connectivity, ageing, and memory performance. In my current study, I apply the mixture model to analyse behavioural responses on a delayed recall task and use whole-brain correlational psychophysiological interactions (cPPI) to study task-modulated functional connectivity in relation to age. Functional connectivity between attentional control and sensory regions is likely critical to working memory performance and examining age differences therein will inform our understanding of why working memory declines with age. This work complements the research I conducted during my PhD in which I investigated how memory subsystems relate at a behavioural and neural level in healthy aging and stroke patients.
Age-related changes in brain and cognitive functioning are highly heterogeneous across individuals. My research focuses on 1) understanding individual differences in healthy aging and 2) how we could use those differences to optimize cognitive training efficacy. Ultimately, I hope that my research contributes to improving cognitive aging. When I am not conducting science, I like to work on my tiny house and to explore forests.
As a PhD candidate in the Dynamic Naturalistic Cognitive Neuroscience lab I study how the brain responds to dynamic realistic stimuli, under the supervision of Linda Geerligs and Umut Güçlü. I am interested in how the brain processes the complex information that we receive in our daily lives by means of segmenting this information into meaningful chunks, which we call event segmentation. My research focuses on neural states, which are stable patterns of brain activity within a certain brain area, as these neural states may form the neural mechanism that underlies event segmentation.
Dora Gözükara (on the right)
As a part of the DyNaC-Lab, I'm studying the relationship between the temporal and spatial dynamics of neural representations in the context of event segmentation and metastable neural activity. To that end, I'm currently working on building model brains with artificial neural networks which are in no way as comprehensive as they sound. I'm also a part of the Neural Coding Lab run by Umut Güçlü. Apart from my work, I go wherever my curiosity leads me.
Understanding how brain connectivity develops as we age, and how connectivity influences cognition, is of great importance. Under the supervision of Max Hinne and Linda Geerligs, I aim to predict dynamic brain connectivity using Bayesian nonparametric models. More specifically, I am working on an approach called Bayesian network regression. Finally, I plan to use this method to study different domains of network neuroscience, such as connectivity changes induced by healthy ageing and in patients diagnosed with Alzheimer’s disease.
How does our “internal models” of the world change throughout our lives and how does this change shape our perception of the world? These are the questions I’m interested to answer in my research as a PhD candidate under the supervision of Linda Geerligs and Umut Güçlü. I will address these questions in the context of language processing by studying predictive signals in the human brain when listening to natural stimuli such as naratives.
As an early-stage researcher in the European training network for the Empirical study of literature (ELIT), I am studying the neurocognitive aspects of written naturalistic narrative comprehension: Literary reading. More specifically, I investigate the affective, immersive and communicative potential of literary texts for different types of readers. To that end, I use quantitative text analyses, classic questionnaires, behavioural data, and eye-tracking. For my project at the DyNaC-lab, I am gathering evidence from haemodynamic neuroimaging (fMRI).
I am a Cognitive Neuroscience and Artificial Intelligence master student. My goal is to combine these fields to reverse-engineer the human brain in order to increase our understanding of it. I work as Research Assistant at the DyNaC-Lab under supervision of Djamari Oetringer and provide support with the implementation and analysis of her study about neural states in event segmentation, and with the collection of fMRI data for this. Furthermore, I am an activist who stimulates gender diversity in STEM at VHTO and combats anti-Asian racism at Asian Raisins.