Promotor: J.N. Kok, Co-promotor: H.J. Hoogeboom

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In this thesis, time-lapse fluorescent microscopy plays a pivotal role in investigating functional materials within living cells as well as the migratory behaviour of neural progenitor cells.

How do genetic and environmental factors make us vulnerable to depression?

Brain activity changes as people age, which can lead to cognitive decline. By measuring and comparing brain data from mice and humans, the researcher will investigate how the brain’s noise levels change with age and affect choice behavior.

Promotor: S.M. Verduyn Lunel, Co-Promotor: O.W. van Gaans

A P300-based Brain Computer Interface character speller, also known as P300 speller, has been an important communication pathway, under extensive research, for people who lose motor ability, such as patients with Amyotrophic Lateral Sclerosis or spinal-cord injury because a P300 speller allows human-beings…

A key challenge in neuroscience is understanding how neurons in hundreds of interconnected brain regions integrate sensory inputs with previous expectations to initiate movements and make decisions.

Human language is constantly evolving with its linguistic structure being shaped by language users at both individual and population levels. Focusing on the interplay between processes of language acquisition and communicative need in shaping human languages, this thesis introduces a novel computational…

What are the social and neural mechanisms that contribute to fluctuations in self-esteem in healthy adolescents and adolescents with depression?

How do dissociative states affect the ability to suppress emotional distraction (in the context of a working memory task) in patients with Borderline Personality Disorder?

Vocal learning is a trait shared by songbirds and humans. It is also a trait that is restricted by the brain rather than by a species' vocal apparatus. In this dissertation, functional MRI is employed in both species in order to explore potential common neural mechanisms underlying the ability to develop…

To argue that people can control the relative contributions of goal-driven and stimulus-driven processes to decision-making and action selection.

On the 17th of December, Jin Wang successfully defended a doctoral thesis. Leiden University Centre for Linguistics congratulates Jin on this achievement!

There is concern about the threat that nanoplastics (NPs) may pose to both wildlife and humans. This thesis explores the mechanisms of toxicity of polystyrene nanoparticles (PS-NPs) in chicken embryo.

In this thesis, deep learning is studied from a statistical perspective. Convergence rates for the worst case risk bounds of neural network estimators are obtained in the classification, density estimation and linear regression model.

A convolutional neural network (CNN) is a biologically inspired algorithm, highly capable at processing images and videos.

An accurate description of reactive scattering of molecules on metal surfaces often requires the modeling of energy transfer between the molecule and the surface phonons. Although ab initio molecular dynamics (AIMD) can describe this energy transfer, AIMD is at present untractable for reactions with…

This thesis mainly focuses on cross-modal retrieval and single-modal image retrieval via deep learning methods, i.e. by using deep convolutional neural networks.

Tomography is a powerful technique to non-destructively determine the interior structure of an object.Usually, a series of projection images (e.g.\ X-ray images) is acquired from a range of different positions.

How did Google's computer programme AlphaGo become so powerful? On June 29, developer Aja Huang elaborated on this during a lecture in the Gorlaeus building.

In this thesis we explore machine and deep learning approaches that address keychallenges in high dimensional problem areas and also in improving accuracy in wellknown problems. In high dimensional contexts, we have focused on computational fluid dynamics (CFD) simulations.

Sewer pipes are an essential infrastructure in modern society and their proper operation is important for public health. To keep sewer pipes operational as much as possible, periodical inspections for defects are performed.

In this work, I explore the creation of new methods that optimize simulations of the gravitational N-body problem. Specifically, I take advantage of the recent popularity of Machine Learning methods to find tools that can suit this problem.

The invention of neural networks marks a critical milestone in the pursuit of true artificial intelligence. Despite their impressive performance on various tasks, these networks face limitations in learning efficiently as they are often trained from scratch.

Promotor: J.N. Kok, Co-promotor: M.S. Lew

This thesis investigates the application of deep learning techniques in image analysis across various domains, focusing on four main themes: feature extraction, classification, segmentation, and integration, demonstrating the transformative potential of these technologies.

Promotor: S.M. Verduyn Lunel, Co-promotor: O. van Gaans

Smartphone behaviors are so common but how does the brain generate this behavior? The Cognition in the digital environment laboratory (CODELAB) investigated the brain activity surrounding smartphone interactions with the help of Artificial Intelligence. According to their research, the brain fluidly…

Neural networks have a wide range of applications. In Leiden, psychologists use them to build robot brains, whereas archaeologists use them to hunt for prehistoric graves.

Fundamental understanding of molecular reactions on metal surfaces is important for improving heterogeneous catalysis.

Deep learning has revolutionized image processing, enabling remarkable advances in fields from autonomous driving to medical diagnostics.

The section Developmental and Educational Psychology consists of more than 45 people, who are mainly involved in education and research.

In this thesis, topics relating to the optimization of high-throughput pipelines used for imaging are discussed. In particular, different levels of implementation, i.e., conceptual, software, and hardware, are discussed and the thesis outlines how advances on each level need to be made to make gains…

Training a robot in a real-life environment is more or less impossible. Computer scientist and psychologist Roy de Kleijn switched to training in a simulated, virtual one instead. ‘You do have a reality gap, but the more precisely you train the robot, the better it is in practice.’ His inspiration:…

The Co-Align Conference 2023 will be held on 16 May 2023 at Leiden University.

Is it possible to pharmacologically condition oxytocin responses in healthy individuals and identify the neural circuitry underlying such conditioning?

Brain development in children with an extra X chromosome as compared to children with autism: evidence from MRI

A neurobiological perspective on individual differences in social competence

Mapping the neural mechanisms underlying social motivations of adolescents and adults

Advancing AutoML systems targeting machine learning tasks based on Earth Observation (EO) Datasets.

Up to 50% of all children and adolescents growing up worldwide are exposed to at least one form of childhood adversity (CA), which is one of the strongest predictors for later-life psychopathology.

A neural network mimics how our brain works. Evolutionary algorithms use the principle of natural selection to solve complex problems. This kind of 'natural computing' is being used to improve the diagnosis of Parkinson's disease or the production of steel.

In deep reinforcement learning, searching and learning techniques are two important components. They can be used independently and in combination to deal with different problems in AI, and have achieved impressive results in game playing and robotics. These results have inspired research into artificial…