Jordy Thielen

Jordy Thielen
Radboud University | RU · Donders Institute for Brain, Cognition, and Behaviour

PhD

About

10
Publications
1,618
Reads
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140
Citations
Citations since 2017
8 Research Items
136 Citations
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Introduction
I am assistant professor at the Donders Institute for Brain, Cognition and Behaviour at Radboud University. I aim to unravel the neural mechanisms underlying human visual perception and develop sophisticated machine learning methods to model and decode signals from the human brain. Combining these two efforts (i.e., artificial intelligence and cognitive neuroscience), I work towards assistive devices by advancing neurotechnological systems including (non-invasive) brain-computer interfacing.

Publications

Publications (10)
Article
Objective. Code-modulated visual evoked potentials (c-VEP) have been consolidated in recent years as robust control signals capable of providing non-invasive brain–computer interfaces (BCIs) for reliable, high-speed communication. Their usefulness for communication and control purposes has been reflected in an exponential increase of related articl...
Article
Objective Brain-Computer Interface (BCI) spellers that make use of code-modulated Visual Evoked Potentials (cVEP) may provide a fast and more accurate alternative to existing visual BCI spellers for patients with Amyotrophic Lateral Sclerosis (ALS). However, so far the cVEP speller has only been tested on healthy participants. Methods We assess th...
Article
Objective: Typically, a brain computer interface (BCI) is calibrated using user- and session-specific data because of the individual idiosyncrasies and the non-stationary signal properties of the electroencephalogram (EEG). Therefore, it is normal that BCIs undergo a time-consuming passive training stage that prevents users from directly operating...
Article
Full-text available
Eye movements can have serious confounding effects in cognitive neuroscience experiments. Therefore, participants are commonly asked to fixate. Regardless, participants will make so-called fixational eye movements under attempted fixation, which are thought to be necessary to prevent perceptual fading. Neural changes related to these eye movements...
Preprint
Full-text available
Population receptive field (pRF) mapping is an important asset for cognitive neuroscience. The pRF model is used for estimating retinotopy, defining functional localizers and to study a vast amount of cognitive tasks. In a classic pRF, the cartesian location and receptive field size are modeled as a 2D Gaussian kernel in visual space and are estima...
Article
Full-text available
Amodal completion is the phenomenon of perceiving completed objects even though physically they are partially occluded. In this review, we provide an extensive overview of the results obtained from a variety of neuroimaging studies on the neural correlates of amodal completion. We discuss whether low-level and high-level cortical areas are implicat...
Article
Full-text available
Decoding has become a standard analysis technique for contemporary cognitive neuroscience. Already more than a decade ago, it was shown that orientation information could be decoded from functional magnetic resonance imaging voxel time series. However, the underlying neural mechanism driving the decodable information is still under debate. Here, we...
Chapter
Full-text available
Broad-band evoked potentials (BBEPs) are responses to non-periodic stimuli, evoked in reponse to carefully chosen pseudo-random noise-sequences (PRNS). In this chapter, a generative method called reconvolution is discussed. Reconvolution is a method that decomposes BBEPs in response to PRNS into transient responses to the individual events. With re...
Conference Paper
Full-text available
We developed task-optimized deep neural networks (DNNs) that achieved state-of-the-art performance in different evaluation scenarios for automatic music tagging. These DNNs were subsequently used to probe the neural representations of music. Representational similarity analysis revealed the existence of a representational gradient across the superi...
Article
Full-text available
Brain-Computer Interfaces (BCIs) allow users to control devices and communicate by using brain activity only. BCIs based on broad-band visual stimulation can outperform BCIs using other stimulation paradigms. Visual stimulation with pseudo-random bit-sequences evokes specific Broad-Band Visually Evoked Potentials (BBVEPs) that can be reliably used...

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