Tim C. Kietzmann's research while affiliated with Radboud University and other places

Publications (73)

Article
Full-text available
Line drawings convey meaning with just a few strokes. Despite strong simplifications, humans can recognize objects depicted in such abstracted images without effort. To what degree do deep convolutional neural networks (CNNs) mirror this human ability to generalize to abstracted object images? While CNNs trained on natural images have been shown to...
Preprint
Full-text available
Recurrent neural networks (RNNs) have been shown to perform better than feedforward architectures in visual object categorization tasks, especially in challenging conditions such as cluttered images. However, little is known about the exact computational role of recurrent information flow in these conditions. Here we test RNNs trained for object ca...
Preprint
Full-text available
Deep neural networks (DNNs) are promising models of the cortical computations supporting human object recognition. However, despite their ability to explain a significant portion of variance in neural data, the agreement between models and brain representational dynamics is far from perfect. Here, we address this issue by asking which representatio...
Preprint
Full-text available
The thickness and surface area of cortex are genetically distinct aspects of brain structure, and may be affected differently by age. However, their potential to differentially predict age and cognitive abilities has been largely overlooked, likely because they are typically aggregated into the commonly used measure of volume . In a large sample of...
Article
Deep neural networks (DNNs) trained on object recognition provide the best current models of high-level visual cortex. What remains unclear is how strongly experimental choices, such as network architecture, training, and fitting to brain data, contribute to the observed similarities. Here, we compare a diverse set of nine DNN architectures on thei...
Preprint
Full-text available
Neural mechanisms of face perception are predominantly studied in well-controlled experimental settings that involve random stimulus sequences and fixed eye positions. While powerful, the employed paradigms are far from what constitutes natural vision. Here, we demonstrate the feasibility of ecologically more valid experimental paradigms using natu...
Article
Full-text available
Development and aging of the cerebral cortex show similar topographic organization and are governed by the same genes. It is unclear whether the same is true for subcortical regions, which follow fundamentally different ontogenetic and phylogenetic principles. We tested the hypothesis that genetically governed neurodevelopmental processes can be tr...
Preprint
Line drawings convey meaning with just a few strokes. Despite strong simplifications, humans can recognize objects depicted in such abstracted images without effort. To what degree do deep convolutional neural networks (CNNs) mirror this human ability to generalize to abstracted object images? While CNNs trained on natural images have been shown to...
Article
Full-text available
Deep neural networks provide the current best models of visual information processing in the primate brain. Drawing on work from computer vision, the most commonly used networks are pretrained on data from the ImageNet Large Scale Visual Recognition Challenge. This dataset comprises images from 1,000 categories, selected to provide a challenging te...
Preprint
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Predictive coding represents a promising framework for understanding brain function. It postulates that the brain continuously inhibits predictable sensory input, ensuring a preferential processing of surprising elements. A central aspect of this view is its hierarchical connectivity, involving recurrent message passing between excitatory bottom-up...
Article
Full-text available
We examined whether sleep quality and quantity are associated with cortical and memory changes in cognitively healthy participants across the adult lifespan. Associations between self-reported sleep parameters (Pittsburgh Sleep Quality Index, PSQI) and longitudinal cortical change were tested using five samples from the Lifebrain consortium (n = 22...
Article
Full-text available
Deep neural networks (DNNs) excel at visual recognition tasks and are increasingly used as a modeling framework for neural computations in the primate brain. Just like individual brains, each DNN has a unique connectivity and representational profile. Here, we investigate individual differences among DNN instances that arise from varying only the r...
Article
Full-text available
Deep feedforward neural network models of vision dominate in both computational neuroscience and engineering. The primate visual system, by contrast, contains abundant recurrent connections. Recurrent signal flow enables recycling of limited computational resources over time, and so might boost the performance of a physically finite brain or model....
Article
Advances in artificial intelligence and deep neural networks have led to a rise in synthetic media, i.e., automatically and artificially generated or manipulated photo, audio, and video content. Synthetic media today is highly believable and “true to life”; so much so that we will no longer be able to trust what we see or hear is unadulterated and...
Preprint
Full-text available
While development and aging of the cerebral cortex show a similar topographic organization and are mainly governed by the same genes, it is unclear whether the same is true for subcortical structures, which follow fundamentally different ontogenetic and phylogenetic principles than the cerebral cortex. To test the hypothesis that genetically govern...
Preprint
Full-text available
Deep neural networks (DNNs) trained on object recognition provide the best current models of high-level visual areas in the brain. What remains unclear is how strongly network design choices, such as architecture, task training, and subsequent fitting to brain data contribute to the observed similarities. Here we compare a diverse set of nine DNN a...
Preprint
Full-text available
Background Older persons with poor sleep are more likely to develop neurodegenerative disease, but the causality underlying this association is unclear. To move towards explanation, we examine whether sleep quality and quantity are similarly associated with brain changes across the adult lifespan. Methods Associations between self-reported sleep p...
Preprint
Full-text available
Deep neural networks (DNNs) excel at visual recognition tasks and are increasingly used as a modelling framework for neural computations in the primate brain. However, each DNN instance, just like each individual brain, has a unique connectivity and representational profile. Here, we investigate individual differences among DNN instances that arise...
Article
Full-text available
Although manipulations of visual and auditory media are as old as media themselves, the recent entrance of deepfakes has marked a turning point in the creation of fake content. Powered by the latest technological advances in artificial intelligence and machine learning, deepfakes offer automated procedures to create fake content that is harder and...
Article
Full-text available
Objectives Poor sleep is associated with multiple age-related neurodegenerative and neuropsychiatric conditions. The hippocampus plays a special role in sleep and sleep-dependent cognition, and accelerated hippocampal atrophy is typically seen with higher age. Hence, it is critical to establish how the relationship between sleep and hippocampal vol...
Article
Full-text available
The human visual system is an intricate network of brain regions that enables us to recognize the world around us. Despite its abundant lateral and feedback connections, object processing is commonly viewed and studied as a feedforward process. Here, we measure and model the rapid representational dynamics across multiple stages of the human ventra...
Preprint
Full-text available
Background Poor sleep is associated with multiple age-related neurodegenerative and neuropsychiatric conditions. The hippocampus plays a special role in sleep and sleep-dependent cognition, and accelerated hippocampal atrophy is typically seen with higher age. Hence, it is critical to establish how the relationship between sleep and hippocampal vol...
Preprint
Full-text available
Deep feedforward neural network models of vision dominate in both computational neuroscience and engineering. The primate visual system, by contrast, contains abundant recurrent connections. Recurrent signal flow enables recycling of limited computational resources over time, and so might boost the performance of a physically finite brain or model....
Preprint
Full-text available
Representational similarity analysis (RSA) has been shown to be an effective framework to characterize brain-activity profiles and deep neural network activations as representational geometry by computing the pairwise distances of the response patterns as a representational dissimilarity matrix (RDM). However, how to properly analyze and visualize...
Article
Full-text available
Purpose The purpose of this paper is to explain the technological phenomenon artificial intelligence (AI) and how it can contribute to knowledge-based marketing in B2B. Specifically, this paper describes the foundational building blocks of any artificial intelligence system and their interrelationships. This paper also discusses the implications o...
Preprint
Full-text available
Deep convolutional neural networks trained for image object categorization have shown remarkable similarities with representations found across the primate ventral visual stream. Yet, artificial and biological networks still exhibit important differences. Here we investigate one such property: increasing invariance to identity-preserving image tran...
Preprint
Full-text available
The visual system is an intricate network of brain regions that enables us to recognize the world around us. Despite its abundant lateral and feedback connections, human object processing is commonly viewed and studied as a feedforward process. Here, we measure and model the rapid representational dynamics across multiple stages of the human ventra...
Article
The goal of computational neuroscience is to find mechanistic explanations of how the nervous system processes information to give rise to cognitive function and behaviour. At the heart of the field are its models, i.e. mathematical and computational descriptions of the system being studied, which map sensory stimuli to neural responses and/or neur...
Preprint
Full-text available
The goal of computational neuroscience is to find mechanistic explanations of how the nervous system processes information to give rise to cognitive function and behaviour. At the heart of the field are its models, i.e. mathematical and computational descriptions of the system being studied, which map sensory stimuli to neural responses and/or neur...
Conference Paper
Full-text available
The analysis of multimodal data comprised of images, videos and additional recordings, such as gaze trajectories, EEG, emotional states, and heart rate is presently only feasible with custom applications. Even exploring such data requires compilation of specific applications that suit a specific dataset only. This need for specific applications ari...
Article
Full-text available
We present a dataset of free-viewing eye-movement recordings that contains more than 2.7 million fixation locations from 949 observers on more than 1000 images from different categories. This dataset aggregates and harmonizes data from 23 different studies conducted at the Institute of Cognitive Science at Osnabrück University and the University Me...
Article
Oculomotor selection exerts a fundamental impact on our experience of the environment. To better understand the underlying principles, researchers typically rely on behavioral data from humans, and electrophysiological recordings in macaque monkeys. This approach rests on the assumption that the same selection processes are at play in both species....
Article
Full-text available
Eye movement research is a highly active and productive research field. Here we focus on how the embodied nature of eye movements can act as a window to the brain and the mind. In particular, we discuss how conscious perception depends on the trajectory of fixated locations and consequently address how fixation locations are selected. Specifically,...
Article
Faces provide a wealth of information, including the identity of the seen person and social cues, such as the direction of gaze. Crucially, different aspects of face processing require distinct forms of information encoding. Another person's attentional focus can be derived based on a view-dependent code. In contrast, identification benefits from i...
Article
Significance statement: Faces are among the most salient objects we encounter during our everyday activities. Moreover, we are remarkably adept at identifying people at a glance, despite the diversity of viewpoints during our social encounters. Here, we investigate the cortical mechanisms underlying this ability by focusing on effects of viewpoint...
Article
Full-text available
Faces provide a large variety of information, including the identity of the seen person, their emotional state and social cues, such as the direction of gaze. Crucially, these different aspects of face processing require distinct forms/types of viewpoint encoding. Whereas another person's attentional focus is supported by a view-based code, identif...
Article
The sampling of our visual environment through saccadic eye movements is an essential function of the brain, allowing us to overcome the limits of peripheral vision. Understanding which parts of a scene attract overt visual attention is subject to intense research, and considerable progress has been made in unraveling the underlying cortical mechan...
Article
Humans are highly proficient at recognizing individual faces from a wide variety of viewpoints, but the neural substrates underlying this ability remain unclear. Recent work suggests that viewpoint-symmetric responses to rotated faces, found across a large network of visual areas, may constitute a key computational step in achieving full viewpoint...
Poster
The ability to recognize faces irrespective of viewpoint is crucial for our everyday behavior and social interaction. However, not all viewpoints allow for equally good recognition and generalization performance, an effect known as the ¾-view advantage [Krouse, 1981, Journal of Applied Psychology, 66, 651-654]. Here, we use fMRI BOLD to investigate...
Conference Paper
Background / Purpose: The categorization of visual input is one of the most essential challenges faced by our visual system.Despite its importance, however, the debate on the cortical origin and the timing of category-specific effects remains unsettled. In part this is due to low-level confounds in naturally occurring visual categories, which hav...
Article
Although the ability to recognize faces and objects from a variety of viewpoints is crucial to our everyday behavior, the underlying cortical mechanisms are not well understood. Recently, neurons in a face-selective region of the monkey temporal cortex were reported to be selective for mirror-symmetric viewing angles of faces as they were rotated i...
Conference Paper
Background / Purpose: Although we are able to recognize objects from a variety of different viewpoints, the vast majority of object-selective neurons in the inferotemporal cortex exhibit viewpoint-specific rather than viewpoint-invariant tuning.Recently, neurons in a face-selective region of the monkey temporal cortex were reported to be selectiv...
Article
Full-text available
Models of fixation selection are a central tool in the quest to understand how the human mind selects relevant information. Using this tool in the evaluation of competing claims often requires comparing different models' relative performance in predicting eye movements. However, studies use a wide variety of performance measures with markedly diffe...
Data
Experiment 2. Shown is an example stimulus together with the calculated centroids of the 80% congruency regions (circles), as marked by a set of independent subjects. The colored crosses correspond to the shifted fixation cross positions used in experiment 1, the black cross shows the centered fixation cross used in experiment 1. (TIF)
Data
The subject's pupil dilation was used as additional marker of the perceptual decision. To better estimate the time-point of the perceptual decision, we contrast pupil dilation changes preceding perceptual and motor-decisions. This revealed significant differences from 528 ms before to 3000 ms after the button press. (DOCX)
Article
Full-text available
Our everyday conscious experience of the visual world is fundamentally shaped by the interaction of overt visual attention and object awareness. Although the principal impact of both components is undisputed, it is still unclear how they interact. Here we recorded eye-movements preceding and following conscious object recognition, collected during...
Data
Stimuli. Shown are the ten ambiguous and disambiguated stimuli that were used for the analysis. The first column contains the ambiguous image, the second and third the respective disambiguated versions. (TIF)
Data
Pupil Size Analysis. The averaged pupil size z-scores from the (a) percept formation condition (data from experiment 1) and (b) the control experiment in which subjects pressed the same keyboard button whenever they wished to do so. The shaded area around the pupil diameter shows the SEM. Time periods with a significant positive slope are marked wi...
Article
To date, the relative contribution of the different levels of the visual hierarchy during perceptual decisions remains unclear. Typical models of visual processing, with the reverse hierarchy theory (RHT) as a prominent example, strongly emphasize the role of higher levels and interpret lower levels as sequence of simple feature detectors. Here, we...
Article
Full-text available
Different tasks can induce different viewing behavior, yet it is still an open question how or whether at all high-level task information interacts with the bottom-up processing of stimulus-related information. Two possible causal routes are considered in this paper. Firstly, the weak top-down hypothesis, according to which top-down effects are med...
Article
Philosophical accounts of causality and causal explanation can provide important guidelines for the experimental sciences and valid experimental setups. In addition to the obvious requirement of logic validity, however, the approaches must account for the generally accepted experimental practice to be truly useful. To investigate this important int...
Article
We propose a conceptual framework for artificial object recognition systems based on findings from neurophysiological and neuropsychological research on the visual system in primate cortex. We identify some essential questions, which have to be addressed in the course of designing object recognition systems. As answers, we review some major aspects...
Conference Paper
This paper describes a novel real-world reinforcement learning application: The Neuro Slot Car Racer. In addition to presenting the system and first results based on Neural Fitted Q-Iteration, a standard batch reinforcement learning technique, an extension is proposed that is capable of improving training times and results by allowing for a reducti...