Olaf Hauk

Olaf Hauk
Medical Research Council (UKRI) | mrc · MRC Cognition and Brain Sciences Unit

PhD

About

138
Publications
48,847
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11,308
Citations
Additional affiliations
January 2001 - December 2013
MRC Cognition and Brain Sciences Unit

Publications

Publications (138)
Article
Full-text available
Fast periodic visual stimulation (FPVS) allows the objective measurement of brain responses of human word discrimination (i.e., reproducible word-category-selective responses) with a high signal-to-noise ratio. This approach has been successfully employed over the last decade in a number of scalp electroencephalography (EEG) studies. Three importan...
Preprint
Full-text available
Fast periodic visual stimulation (FPVS) allows the recording of objective brain responses of human word discrimination (i.e., reproducible word-category-selective responses) with a high signal-to-noise ratio. This approach has been successfully employed over the last decade in a number of scalp electroencephalography (EEG) studies. Three important...
Article
Full-text available
Studies using frequency-tagging in electroencephalography (EEG) have dramatically increased in the past 10 years, in a variety of domains and populations. Here we used Fast Periodic Visual Stimulation (FPVS) combined with an oddball design to explore visual word recognition. Given the paradigm’s high sensitivity, it is crucial for future basic rese...
Preprint
Full-text available
Multidimensional connectivity methods are critical to reveal the full pattern of complex interactions between brain regions over time. However, to date only bivariate multidimensional methods are available for time-resolved EEG/MEG data, which may overestimate connectivity due to the confounding effects of spurious and indirect dependencies. Here,...
Article
We used eye-tracking during natural reading to study how semantic control and representation mechanisms interact for the successful comprehension of sentences, by manipulating sentence context and single-word meaning. Specifically, we examined whether a word’s semantic characteristic (concreteness) affects first fixation and gaze durations (FFDs an...
Preprint
Full-text available
The temporal dynamics within the semantic brain network and its dependence on stimulus and task parameters are still not well understood. Here, we addressed this by decoding task as well as stimulus information from source-estimated EEG/MEG data. We presented the same visual word stimuli in a lexical decision (LD) and three semantic decision (SD) t...
Preprint
Full-text available
In recent years, a fast periodic oddball-like paradigm has proved to be highly sensitive to measure category-selective visual word representation and characterize its development and neural basis. In this approach, deviant words are inserted in rapid streams of base stimuli every n th occurrence (e.g., Lochy et al., 2015). To understand the nature...
Article
Functional and effective connectivity methods are essential to study the complex information flow in brain networks underlying human cognition. Only recently have connectivity methods begun to emerge that make use of the full multidimensional information contained in patterns of brain activation, rather than unidimensional summary measures of these...
Preprint
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Investigating task- and stimulus-dependent connectivity is key to understanding how brain regions interact to perform complex cognitive processes. Most existing connectivity analysis methods reduce activity within brain regions to unidimensional measures, resulting in a loss of information. While recent studies have introduced new functional connec...
Article
Full-text available
Understanding language semantically related to actions activates the motor cortex. This activation is sensitive to semantic information such as the body part used to perform the action (e.g. arm-/leg-related action words). Additionally, motor movements of the hands/feet can have a causal effect on memory maintenance of action words, suggesting that...
Preprint
We used natural reading of sentences to study how semantic control and representation mechanisms interact for the successful comprehension of sentences, by manipulating sentence context and single-word meaning. Specifically, we examined whether a word’s semantic characteristic (concreteness) affects first fixation and gaze durations (FFDs and GDs),...
Preprint
Full-text available
Functional and effective connectivity methods are essential to study the complex information flow in brain networks underlying human cognition. Only recently have connectivity methods begun to emerge that make use of the full multidimensional information contained in patterns of brain activation, rather than univariate summary measures of these pat...
Article
The spatial resolution of EEG/MEG source estimates, often described in terms of source leakage in the context of the inverse problem, poses constraints on the inferences that can be drawn from EEG/MEG source estimation results. Software packages for EEG/MEG data analysis offer a large choice of source estimation methods but few tools to experimenta...
Article
Full-text available
Human brain activity is based on electrochemical processes, which can only be measured invasively. Thus, quantities such as magnetic flux density (MEG) or electric potential differences (EEG) are measured non-invasively in medicine and research. The reconstruction of the neuronal current from the measurements is a severely ill-posed problem though...
Article
Full-text available
Semantic knowledge is supported by numerous brain regions, but the spatiotemporal configuration of the network that links these areas remains an open question. The hub-and-spokes model posits that a central semantic hub coordinates this network. In this study, we explored distinct aspects that define a semantic hub, as reflected in the spatiotempor...
Preprint
Full-text available
Human brain activity is based on electrochemical processes, which can only be measured invasively. Therefore, quantities such as magnetic flux density (MEG) or electric potential differences (EEG) are measured non-invasively in medicine and research. The reconstruction of the neuronal current from the measurements is a severely ill-posed problem th...
Article
Full-text available
How does brain activity in distributed semantic brain networks evolve over time, and how do these regions interact to retrieve the meaning of words? We compared spatiotemporal brain dynamics between visual lexical and semantic decision tasks (LD and SD), analysing whole-cortex evoked responses and spectral functional connectivity (coherence) in sou...
Article
Full-text available
Fast periodic visual stimulation (FPVS) allows the recording of objective brain responses of human face categorization (i.e., generalizable face-selective responses) with high signal-to-noise ratio. This approach has been successfully employed in a number of scalp electroencephalography (EEG) studies but has not been used with magnetoencephalograph...
Preprint
Full-text available
Linking brain and behavior is one of the great challenges in cognitive neuroscience. Ultimately, we want to understand how the brain processes information to guide every-day behavior. However, most neuroscientific studies employ very simplistic experimental paradigms whose ecological validity is doubtful. Reading is a case in point, since most neur...
Preprint
Full-text available
How does brain activity in distributed semantic brain networks evolve over time, and how do these regions interact to retrieve the meaning of words? We compared spatiotemporal brain dynamics between visual lexical and semantic decision tasks (LD and SD), analysing whole-cortex evoked responses and spectral functional connectivity (coherence) in sou...
Article
Full-text available
Cognitive neuroscience increasingly relies on complex data analysis methods. Researchers in this field come from highly diverse scientific backgrounds, such as psychology, engineering, and medicine. This poses challenges with respect to acquisition of appropriate scientific computing and data analysis skills, as well as communication among research...
Article
Full-text available
Purpose This study aimed to provide novel insights into the neural correlates of language improvement following intensive language-action therapy (ILAT; also known as constraint-induced aphasia therapy). Method Sixteen people with chronic aphasia underwent clinical aphasia assessment (Aachen Aphasia Test [AAT]), as well as functional magnetic reso...
Article
Full-text available
The estimation of functional connectivity between regions of the brain, for example based on statistical dependencies between the time series of activity in each region, has become increasingly important in neuroimaging. Typically, multiple time series (e.g. from each voxel in fMRI data) are first reduced to a single time series that summarises the...
Preprint
The estimation of functional connectivity between regions of the brain, for example based on statistical dependencies between the time series of activity in each region, has become increasingly important in neuroimaging. Typically, multiple time series (e.g. from each voxel in fMRI data) are first reduced to a single time series that summarises the...
Preprint
Full-text available
The estimation of functional connectivity between regions of the brain, for example based on dependencies between the time series of activity in each region, has become increasingly important in functional neuroimaging. Typically, multiple time series in each region (e.g, each voxel in fMRI data) are first reduced to one time series that summarises...
Article
Full-text available
Semantically ambiguous words challenge speech comprehension, particularly when listeners must select a less frequent (subordinate) meaning at disambiguation. Using combined magnetoencephalography (MEG) and EEG, we measured neural responses associated with distinct cognitive operations during semantic ambiguity resolution in spoken sentences: (i) in...
Article
Full-text available
Most connectivity metrics in neuroimaging research reduce multivariate activity patterns in regions-of-interests (ROIs) to one dimension, which leads to a loss of information. Importantly, it prevents us from investigating the transformations between patterns in different ROIs. Here, we applied linear estimation theory in order to robustly estimate...
Article
Full-text available
Significance Understanding the computational principles that underlie human vision is a key challenge for neuroscience and could help improve machine vision. Feedforward neural network models process their input through a deep cascade of computations. These models can recognize objects in images and explain aspects of human rapid recognition. Howev...
Preprint
Full-text available
The question "What is the spatial resolution of EEG/MEG?" can only be answered with many ifs and buts, as the answer depends on a large number of parameters. Here, we describe a framework for resolution analysis of EEG/MEG source estimation, focusing on linear methods. The spatial resolution of linear methods can be evaluated using the resolution m...
Chapter
The choice and application of EEG/MEG source estimation methods require an understanding of their underlying modeling assumptions as well as tools to evaluate their spatial resolution and localization performance. Linear methods are the most popular for EEG/MEG source estimation, because most of them are computationally efficient and easy to apply...
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...
Preprint
Full-text available
It is now well recognised that human semantic knowledge is supported by a large neural network distributed over multiple brain regions, but the dynamic organisation of this network remains unknown. Some studies have proposed that a central semantic hub coordinates this network. We explored the possibility of different types of semantic hubs; namely...
Preprint
Full-text available
Most connectivity metrics in neuroimaging research reduce multivariate activity patterns in regions-of-interests (ROIs) to one dimension, which leads to a loss of information. Importantly, it prevents us from investigating the transformations between patterns in different ROIs. Here, we applied linear estimation theory in order to robustly estimate...
Preprint
Full-text available
When understanding language semantically related to actions, the motor cortex is active and may be sensitive to semantic information, for example about the body-part-relationship of displayed action-related words. Conversely, movements of the hands or feet can impair memory performance for arm- and leg-related action words respectively, suggesting...
Preprint
Full-text available
Cognitive neuroscience increasingly relies on complex data analysis methods. Researchers in this field come from highly diverse scientific backgrounds, such as psychology, engineering and medicine. This poses challenges with respect to acquisition of appropriate scientific computing and data analysis skills, as well as communication among researche...
Preprint
Full-text available
There is growing interest in the rich temporal and spectral properties of the brain's functional connectome that are provided by Electro- and Magnetoencephalography (EEG/MEG). However, the problem of leakage between brain sources that arises when reconstructing brain activity from EEG/MEG recordings outside the head makes it difficult to distinguis...
Article
Full-text available
There is growing interest in the rich temporal and spectral properties of the brain's functional connectome that are provided by Electro- and Magnetoencephalography (EEG/MEG). However, the problem of leakage between brain sources that arises when reconstructing brain activity from EEG/MEG recordings outside the head makes it difficult to distinguis...
Chapter
The idea that concepts are represented as mental images that revoke sensory experiences is intuitive and has a long history in philosophy. The empirical question regarding the degree to which these processes are embodied or grounded in sensory-motor brain systems still remains controversial after several decades of neuroscientific research. This co...
Poster
Introduction: The organization of semantic networks in the brain has been a controversial topic in cognitive science for decades. With theories ranging from fully symbolic and amodal to entirely embodied semantic cognition, brain imaging in recent years has provided evidence mostly for theories that take an intermediate position. But it remains to...
Article
Full-text available
problem-solving relies on a sequence of cognitive steps involving phases of task encoding, the structuring of solution steps, and their execution. On the neural level, metabolic neuroimaging studies have associated a frontal-parietal network with various aspects of executive control during numerical and nonnumerical problem-solving. We used EEG–MEG...
Poster
Electro- and Magnetoencephalography (EMEG) studies normally use anatomical parcellations to define regions of interest (ROIs) in the brain. This is not ideal with EMEG source estimation because 1) signals from deeper brain areas are less likely to be localised with high accuracy, and 2) the size of the ROIs might be too large or small with respect...
Article
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Theoretical developments about the nature of semantic representations and processes should be accompanied by a discussion of how these theories can be validated on the basis of empirical data. Here, I elaborate on the link between theory and empirical research, highlighting the need for temporal information in order to distinguish fundamental aspec...
Article
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Arithmetic problem-solving can be conceptualized as a multistage process ranging from task encoding over rule and strategy selection to step-wise task execution. Previous fMRI research suggested a frontal–parietal network involved in the execution of complex numerical and nonnumerical tasks, but evidence is lacking on the particular contributions o...
Article
approaches? For this special issue “Prediction in language comprehension and production” in Language, Cognition and Neuroscience we invited opinion papers, theory-guided reviews and empirical studies that offer new insights into the phenomenon of prediction. They do so by defining or differentiating the concept of prediction itself, by providing be...
Article
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Activation in sensorimotor areas of the brain following perception of linguistic stimuli referring to objects and actions has been interpreted as evidence for strong interpretations of embodied semantics. Although a large number of studies have demonstrated this “language-to-action” link, important questions about how activation in the sensorimotor...
Article
Full-text available
Mental arithmetic is a powerful paradigm to study problem solving using neuroimaging methods. However, the evaluation of task complexity varies significantly across neuroimaging studies. Most studies have parameterized task complexity by objective features such as the number size. Only a few studies used subjective rating procedures. In fMRI, we pr...
Article
In the attentional blink, a target event (T1) strongly interferes with perception of a second target (T2) presented within a few hundred milliseconds. Concurrently, the brain's electromagnetic response to the second target is suppressed, especially a late negative-positive EEG complex including the traditional P3 wave. An influential theory propose...
Article
Full-text available
In the attentional blink, a target event (T1) strongly interferes with perception of a second target (T2) presented within a few hundred milliseconds. Concurrently, the brain's electromagnetic response to the second target is suppressed, especially a late negative-positive EEG complex including the traditional P3 wave. An influential theory propose...
Article
Full-text available
Visual word recognition is often described as automatic, but the functional locus of top–down effects is still a matter of debate. Do task demands modulate how information is retrieved, or only how it is used? We used EEG/MEG recordings to assess whether, when, and how task contexts modify early retrieval of specific psycholinguistic information in...
Article
Full-text available
The time course of brain activation during word production has become an area of increasingly intense investigation in cognitive neuroscience. The predominant view has been that semantic and phonological processes are activated sequentially, at about 150 and 200-400 ms after picture onset. Although evidence from prior studies has been interpreted a...
Article
Brain activation estimated from EEG and MEG data is the basis for a number of time-series analyses. In these applications, it is essential to minimize "leakage" or "cross-talk" of the estimates among brain areas. Here, we present a novel framework that allows the design of flexible cross-talk functions (DeFleCT), combining three types of constraint...
Article
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A number of previous studies have interpreted differences in brain activation between arithmetic operation types (e.g. addition and multiplication) as evidence in favor of distinct cortical representations, processes or neural systems. It is still not clear how differences in general task complexity contribute to these neural differences. Here, we...
Article
Full-text available
Action-perception circuits containing neurons in the motor system have been proposed as the building blocks of higher cognition; accordingly, motor dysfunction should entail cognitive deficits. Autism spectrum conditions (ASC) are marked by motor impairments but the implications of such motor dysfunction for higher cognition remain unclear. We here...
Article
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Do task demands change the way we extract information from a stimulus, or only how we use this information for decision making? In order to answer this question for visual word recognition, we used EEG/MEG as well as fMRI to determine the latency ranges and spatial areas in which brain activation to words is modulated by task demands. We presented...
Article
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The conductivity profile of the head has a major effect on EEG signals, but unfortunately the conductivity for the most important compartment, skull, is only poorly known. In dipole modeling studies, errors in modeled skull conductivity have been considered to have a detrimental effect on EEG source estimation. However, as dipole models are very re...
Article
Full-text available
Semantic knowledge is based on the way we perceive and interact with the world. However, the jury is still out on the question: To what degree are neuronal systems that subserve acquisition of semantic knowledge, such as sensory-motor networks, involved in its representation and processing? We will begin with a critical evaluation of the main behav...
Article
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The basic inverse problems for the functional imaging techniques of electroencephalography (EEG) and magnetoencephalography (MEG) consist in estimating the neuronal current in the brain from the measurement of the electric potential on the scalp and of the magnetic field outside the head. Here we present a rigorous derivation of the relevant formul...
Article
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We usually feel that we understand a familiar word "immediately". However, even basic aspects of the time-line of word recognition are still controversial. Different domains of research have still not converged on a coherent account. An integration of multiple sources of information would lead to more strongly constrained theoretical models, and he...
Article
A recent breakthrough in understanding brain-language mechanisms is the discovery of local motor cortex activations that index specific meaning features of words, phrases and sentences. The words "talk" and "walk" activate different parts of the motor cortex, reflecting the body part relationship of actions the linguistic items are typically used t...