Mario Senden

Mario Senden
Maastricht University | UM · Department of Cognitive Neuroscience

PhD

About

34
Publications
5,772
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546
Citations
Additional affiliations
June 2016 - May 2018
Maastricht University
Position
  • PostDoc Position

Publications

Publications (34)
Article
Full-text available
There is an ongoing need for novel biomarkers in clinical neuroscience, as diagnosis of neurological and psychiatric disorders is hampered by the pronounced overlap of behavioral symptoms and other pathophysiological characteristics. The question that this Focus Feature puts center stage is whether network-based biomarkers may provide a viable tool...
Preprint
A bstract The distribution of retinal ganglion cells in primate visual systems portrays a densely distributed central region, with an incrementally decreasing cell density as the angle of visual eccentricity increases. This results in a non-uniform sampling of the retinal image that resembles a wheelbarrow distortion. We propose that this sampling...
Article
Population receptive field (pRF) mapping is a popular tool in computational neuroimaging that allows for the investigation of receptive field properties, their topography and interrelations in health and disease. Furthermore, the possibility to invert population receptive fields provides a decoding model for constructing stimuli from observed corti...
Article
Full-text available
Stimulus-induced oscillations and synchrony among neuronal populations in visual cortex are well-established phenomena. Their functional role in cognition are, however, not well-understood. Recent studies have suggested that neural synchrony may underlie perceptual grouping as stimulus-frequency relationships and stimulus-dependent lateral connecti...
Preprint
Full-text available
Lateral connections play an important role for sensory processing in visual cortex by supporting discriminable neuronal responses even to highly similar features. In the present work, we show that establishing a biologically inspired Mexican hat lateral connectivity profile along the filter domain can significantly improve the classification accura...
Preprint
Full-text available
Population receptive field (pRF) mapping is a popular tool in computational neuroimaging that allows for the investigation of receptive field properties, their topography and interrelations in health and disease. Furthermore, the possibility to invert population receptive fields provides a decoding model for constructing stimuli from observed corti...
Article
Full-text available
In functional MRI (fMRI), population receptive field (pRF) models allow a quantitative description of the response as a function of the features of the stimuli that are relevant for each voxel. The most popular pRF model used in fMRI assumes a Gaussian shape in the features space (e.g., the visual field) reducing the description of the voxel’s pRF...
Article
Full-text available
Predicting salient regions in natural images requires the detection of objects that are present in a scene. To develop robust representations for this challenging task, high-level visual features at multiple spatial scales must be extracted and augmented with contextual information. However, existing models aimed at explaining human fixation maps d...
Article
Full-text available
Neuroimaging techniques are now widely used to study human cognition. The functional associations between brain areas have become a standard proxy to describe how cognitive processes are distributed across the brain network. Among the many analysis tools available, dynamic models of brain activity have been developed to overcome the limitations of...
Preprint
Full-text available
Previous research has shown that performance of a novice skill can be easily interfered with by subsequent training of another skill. We address the open questions whether extensively trained skills show the same vulnerability to interference as novice skills and which memory mechanism regulates interference between expert skills. We developed a re...
Article
Full-text available
Previous research has shown that performance of a novice skill can be easily interfered with by subsequent training of another skill. We address the open questions whether extensively trained skills show the same vulnerability to interference as novice skills and which memory mechanism regulates interference between expert skills. We developed a re...
Article
Full-text available
Models of learning typically focus on synaptic plasticity. However, learning is the result of both synaptic and myelin plasticity. Specifically, synaptic changes often co-occur and interact with myelin changes, leading to complex dynamic interactions between these processes. Here, we investigate the implications of these interactions for the coupli...
Article
Full-text available
Clinical network neuroscience, the study of brain network topology in neurological and psychiatric diseases, has become a mainstay field within clinical neuroscience. Being a multidisciplinary group of clinical network neuroscience experts based in The Netherlands, we often discuss the current state of the art and possible avenues for future invest...
Article
Full-text available
Visual mental imagery is the quasi-perceptual experience of “seeing in the mind’s eye”. While a tight correspondence between imagery and perception in terms of subjective experience is well established, their correspondence in terms of neural representations remains insufficiently understood. In the present study, we exploit the high spatial resolu...
Preprint
Full-text available
Predicting salient regions in natural images requires the detection of objects that are present in a scene. To develop robust representations for this challenging task, high-level visual features at multiple spatial scales must be extracted and augmented with contextual information. However, existing models aimed at explaining human fixation maps d...
Preprint
Full-text available
Models of learning typically focus on synaptic plasticity. However, learning is the result of both synaptic and myelin plasticity. Specifically, synaptic changes often co-occur and interact with myelin changes, leading to complex dynamic interactions between these processes. Here, we investigate the implications of these interactions for the coupli...
Preprint
Full-text available
Neuroimaging techniques are increasingly used to study brain cognition in humans. Beyond their individual activation, the functional associations between brain areas have become a standard proxy to describe how information is distributed across the brain network. Among the many analysis tools available, dynamic models of brain activity have been de...
Preprint
Full-text available
The concept of brain states, functionally relevant large-scale patterns, has become popular in neuroimaging. Not all components of such patterns are equally characteristic for each brain state, but machine learning provides a possibility of extracting the structure of brain states from functional data. However, the characterization in terms of func...
Preprint
Full-text available
The global geometrical arrangement of face parts (eyes over nose over mouth), commonly referred to as first order configural (FOC) properties, is believed to constitute a fundamental aspect of face detection. Indeed, several brain regions in the face processing network have been shown to display increased activity in response to abstract stimuli fo...
Preprint
Full-text available
Visual mental imagery is the quasi-perceptual experience of “seeing in the mind’s eye”. While a tight correspondence between imagery and perception in terms of subjective experience is well established, their correspondence in terms of neural representations remains insufficiently understood. In the present study, we exploit the high spatial resolu...
Article
Full-text available
Higher cognition may require the globally coordinated integration of specialized brain regions into functional networks. A collection of structural cortical hubs—referred to as the rich club—has been hypothesized to support task-specific functional integration. In the present paper, we use a whole-cortex model to estimate directed interactions betw...
Preprint
Full-text available
Higher cognition may require the globally coordinated integration of specialized brain regions into functional networks. A collection of structural cortical hubs - referred to as the rich club - has been hypothesized to support task-specific functional integration. In the present paper, we use a whole-cortex model to estimate directed interactions...
Article
Full-text available
A real-time population receptive field mapping procedure based on gradient descent is proposed. 10 Model-free receptive fields produced by the algorithm are evaluated in context of simulated data exhibiting 11 different levels of temporally autocorrelated noise and spatial point spread. As with any model-free approach, 12 the exact shape of recepti...
Poster
Full-text available
In the study of higher level vision it is most common to use experimental designs in which the stimuli are described with qualitative categories instead of formalized features. This limits the capability to describe the processes underlying specific high level visual tasks. How the face processing network works is still object of extensive research...
Poster
Full-text available
Our proof-of-concept study shows the feasibility of reconstructing imagined letters from high resolution fMRI data of the visual cortex.
Article
Full-text available
Within vision research retinotopic mapping and the more general receptive field estimation approach constitute not only an active field of research in itself but also underlie a plethora of interesting applications. This necessitates not only good estimation of population receptive fields (pRFs) but also that these receptive fields are consistent a...
Article
Full-text available
Resting state networks (RSNs) show a surprisingly coherent and robust spatiotemporal organization. Previous theoretical studies demonstrated that these patterns can be understood as emergent on the basis of the underlying neuroanatomical connectivity skeleton. Integrating the biologically realistic DTI/DSI-(Diffusion Tensor Imaging/Diffusion Spectr...