I am a postdoctoral researcher in the DyNaC-Lab at the Donders Institute. My current research focuses on investigating how knowledge-based predictions shape information processing in older adults. In this research, I use naturalistic paradigms to simulate real-world contexts, and utilize neuroimaging techniques (e.g., fMRI) to assess neural activities in the brain. Before this position, I did an MSc at Beijing Normal University and a PhD at the Donders Institute, both in cognitive neuroscience with a specific topic on the neural mechanisms underlying emotional memory integration in humans. During my free time, I take pleasure in leisurely walks, exploring open markets in various cities, and watching TV dramas at home.

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.

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. 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 double master’s student in Artificial Intelligence and Cognitive Neuroscience. My interest in these fields is to use AI to obtain a better understanding of the brain by simulating brain processes and using it as a tool for analysis. Within the DyNaC-lab, I am working on my master thesis, which involves investigating how prediction error informs neural state boundaries by adapting GSBS to make it suitable for MEG data and by using large language models to measure surprisal. Additionally, I work as a student assistant for Sahel Azizpour by aiding her in developing naturalistic stimuli for her experiment. 

I am a master's student in Artificial Intelligence at the Radboud University, with a specialisation in Neurotechnology and Healthcare. Outside of these areas, I am also interested in language, which is why I have done a minor in Ancient Greek in Utrecht during my bachelor studies. In the DyNaC-Lab, I am working on my master thesis under the supervision of Sahel Azizpour. My thesis involves analyzing the brain signal before and after word onset  while listening to speech to analyze the predictive coding. I will do this using MEG data and GPT embeddings. Other than that, I will also help my supervisor with her data collection.

I was a Cognitive Neuroscience and Artificial Intelligence master student. My goal was to combine these fields to reverse-engineer the human brain in order to increase our understanding of it. I worked as Research Assistant at the DyNaC-Lab under supervision of Djamari Oetringer and provided 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. 

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. 

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. 

I am a PhD candidate in Cognitive Neuroscience visiting the DyNaC Lab from Brock University in Ontario, Canada. In my work, I investigate how age-related differences in executive processes, such as attentional control, influence memory performance across the lifespan. My current projects employ naturalistic stimuli to assess how the perception and processing of continuous real-world information may influence how older adults ultimately recall events. I am visiting the DyNaC lab to apply statistical models of event processing to EEG data to help us better understand the neural underpinnings of age-related differences in event processing and the role of event segmentation in memory performance in older adulthood.