Utrecht Brain Center Rudolf Magnus

Utrecht, Netherlands

Utrecht Brain Center Rudolf Magnus

Utrecht, Netherlands

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Schilbach L.,Max Planck Institute of Psychiatry | Schilbach L.,University of Cologne | Hoffstaedter F.,Jülich Research Center | Hoffstaedter F.,Heinrich Heine University Düsseldorf | And 15 more authors.
NeuroImage: Clinical | Year: 2016

Schizophrenia and depression are prevalent psychiatric disorders, but their underlying neural bases remains poorly understood. Neuroimaging evidence has pointed towards the relevance of functional connectivity aberrations in default mode network (DMN) hubs, dorso-medial prefrontal cortex and precuneus, in both disorders, but commonalities and differences in resting state functional connectivity of those two regions across disorders has not been formally assessed. Here, we took a transdiagnostic approach to investigate resting state functional connectivity of those two regions in 75 patients with schizophrenia and 82 controls from 4 scanning sites and 102 patients with depression and 106 controls from 3 sites. Our results demonstrate common dysconnectivity patterns as indexed by a significant reduction of functional connectivity between precuneus and bilateral superior parietal lobe in schizophrenia and depression. Furthermore, our findings highlight diagnosis-specific connectivity reductions of the parietal operculum in schizophrenia relative to depression. In light of evidence that points towards the importance of the DMN for social cognitive abilities and well documented impairments of social interaction in both patient groups, it is conceivable that the observed transdiagnostic connectivity alterations may contribute to interpersonal difficulties, but this could not be assessed directly in our study as measures of social behavior were not available. Given the operculum's role in somatosensory integration, diagnosis-specific connectivity reductions may indicate a pathophysiological mechanism for basic self-disturbances that is characteristic of schizophrenia, but not depression. © 2016 The Authors. Published by Elsevier Inc.


PubMed | University of Tübingen, Max Planck Institute of Psychiatry, Utrecht Brain Center Rudolf Magnus, Heinrich Heine University Düsseldorf and 3 more.
Type: | Journal: NeuroImage. Clinical | Year: 2016

Schizophrenia and depression are prevalent psychiatric disorders, but their underlying neural bases remains poorly understood. Neuroimaging evidence has pointed towards the relevance of functional connectivity aberrations in default mode network (DMN) hubs, dorso-medial prefrontal cortex and precuneus, in both disorders, but commonalities and differences in resting state functional connectivity of those two regions across disorders has not been formally assessed. Here, we took a transdiagnostic approach to investigate resting state functional connectivity of those two regions in 75 patients with schizophrenia and 82 controls from 4 scanning sites and 102 patients with depression and 106 controls from 3 sites. Our results demonstrate common dysconnectivity patterns as indexed by a significant reduction of functional connectivity between precuneus and bilateral superior parietal lobe in schizophrenia and depression. Furthermore, our findings highlight diagnosis-specific connectivity reductions of the parietal operculum in schizophrenia relative to depression. In light of evidence that points towards the importance of the DMN for social cognitive abilities and well documented impairments of social interaction in both patient groups, it is conceivable that the observed transdiagnostic connectivity alterations may contribute to interpersonal difficulties, but this could not be assessed directly in our study as measures of social behavior were not available. Given the operculums role in somatosensory integration, diagnosis-specific connectivity reductions may indicate a pathophysiological mechanism for basic self-disturbances that is characteristic of schizophrenia, but not depression.


Bleichner M.G.,Utrecht Brain Center Rudolf Magnus | Freudenburg Z.V.,Utrecht Brain Center Rudolf Magnus | Jansma J.M.,Utrecht Brain Center Rudolf Magnus | Aarnoutse E.J.,Utrecht Brain Center Rudolf Magnus | And 3 more authors.
Brain Structure and Function | Year: 2016

The increasing understanding of human brain functions makes it possible to directly interact with the brain for therapeutic purposes. Implantable brain computer interfaces promise to replace or restore motor functions in patients with partial or complete paralysis. We postulate that neuronal states associated with gestures, as they are used in the finger spelling alphabet of sign languages, provide an excellent signal for implantable brain computer interfaces to restore communication. To test this, we evaluated decodability of four gestures using high-density electrocorticography in two participants. The electrode grids were located subdurally on the hand knob area of the sensorimotor cortex covering a surface of 2.5–5.2 cm2. Using a pattern-matching classification approach four types of hand gestures were classified based on their pattern of neuronal activity. In the two participants the gestures were classified with 97 and 74 % accuracy. The high frequencies (>65 Hz) allowed for the best classification results. This proof-of-principle study indicates that the four gestures are associated with a reliable and discriminable spatial representation on a confined area of the sensorimotor cortex. This robust representation on a small area makes hand gestures an interesting control feature for an implantable BCI to restore communication for severely paralyzed people. © 2014, The Author(s).


Bleichner M.G.,Utrecht Brain Center Rudolf Magnus | Bleichner M.G.,University of Oldenburg | Jansma J.M.,Utrecht Brain Center Rudolf Magnus | Salari E.,Utrecht Brain Center Rudolf Magnus | And 3 more authors.
Journal of Neural Engineering | Year: 2015

Objective. A brain-computer interface (BCI) is an interface that uses signals from the brain to control a computer. BCIs will likely become important tools for severely paralyzed patients to restore interaction with the environment. The sensorimotor cortex is a promising target brain region for a BCI due to the detailed topography and minimal functional interference with other important brain processes. Previous studies have shown that attempted movements in paralyzed people generate neural activity that strongly resembles actual movements. Hence decodability for BCI applications can be studied in able-bodied volunteers with actual movements. Approach. In this study we tested whether mouth movements provide adequate signals in the sensorimotor cortex for a BCI. The study was executed using fMRI at 7 T to ensure relevance for BCI with cortical electrodes, as 7 T measurements have been shown to correlate well with electrocortical measurements. Twelve healthy volunteers executed four mouth movements (lip protrusion, tongue movement, teeth clenching, and the production of a larynx activating sound) while in the scanner. Subjects performed a training and a test run. Single trials were classified based on the Pearson correlation values between the activation patterns per trial type in the training run and single trials in the test run in a 'winner-takes-all' design. Main results. Single trial mouth movements could be classified with 90% accuracy. The classification was based on an area with a volume of about 0.5 cc, located on the sensorimotor cortex. If voxels were limited to the surface, which is accessible for electrode grids, classification accuracy was still very high (82%). Voxels located on the precentral cortex performed better (87%) than the postcentral cortex (72%). Significance. The high reliability of decoding mouth movements suggests that attempted mouth movements are a promising candidate for BCI in paralyzed people. © 2015 IOP Publishing Ltd.


Harschnitz O.,Utrecht Brain Center Rudolf Magnus | Jongbloed B.A.,Utrecht Brain Center Rudolf Magnus | Jongbloed B.A.,St Elisabeth Hospital | Franssen H.,Utrecht Brain Center Rudolf Magnus | And 3 more authors.
Journal of Clinical Immunology | Year: 2014

Multifocal motor neuropathy (MMN) is a rare inflammatory neuropathy characterized by progressive, asymmetric distal limb weakness and conduction block (CB). Clinically MMN is a pure motor neuropathy, which as such can mimic motor neuron disease. GM1-specific IgM antibodies are present in the serum of approximately half of all MMN patients, and are thought to play a key role in the immune pathophysiology. Intravenous immunoglobulin (IVIg) treatment has been shown to be effective in MMN in five randomized placebo-controlled trials. Despite long-term treatment with intravenous immunoglobulin (IVIg), which is efficient in the majority of patients, slowly progressive axonal degeneration and subsequent muscle weakness cannot be fully prevented. In this review, we will discuss the current understanding of the immune pathogenesis underlying MMN and how this may cause CB, available treatment strategies and future therapeutic targets. © The Author(s) 2014.


Van den Heuvel D.M.A.,Utrecht Brain Center Rudolf Magnus | Harschnitz O.,Utrecht Brain Center Rudolf Magnus | van den Berg L.H.,Utrecht Brain Center Rudolf Magnus | Pasterkamp R.J.,Utrecht Brain Center Rudolf Magnus
Trends in Molecular Medicine | Year: 2014

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease caused by the loss of lower and upper motor neurons leading to progressive muscle weakness and respiratory insufficiency. No treatment is currently available to cure ALS. Recent progress has led to the identification of several novel genetic determinants of this disease, including repeat expansions in the ataxin-2 (ATXN2) gene. Ataxin-2 is mislocalized in ALS patients and represents a relatively common susceptibility gene in ALS, making it a promising therapeutic target. In this review, we summarize genetic and pathological data implicating ataxin-2 in ALS, discuss potential disease mechanisms linked to altered ataxin-2 localization or function, and propose potential strategies for therapeutic intervention in ALS based on ataxin-2. © 2013 Elsevier Ltd.


PubMed | Utrecht Brain Center Rudolf Magnus
Type: Journal Article | Journal: Brain structure & function | Year: 2016

The increasing understanding of human brain functions makes it possible to directly interact with the brain for therapeutic purposes. Implantable brain computer interfaces promise to replace or restore motor functions in patients with partial or complete paralysis. We postulate that neuronal states associated with gestures, as they are used in the finger spelling alphabet of sign languages, provide an excellent signal for implantable brain computer interfaces to restore communication. To test this, we evaluated decodability of four gestures using high-density electrocorticography in two participants. The electrode grids were located subdurally on the hand knob area of the sensorimotor cortex covering a surface of 2.5-5.2 cm(2). Using a pattern-matching classification approach four types of hand gestures were classified based on their pattern of neuronal activity. In the two participants the gestures were classified with 97 and 74% accuracy. The high frequencies (>65 Hz) allowed for the best classification results. This proof-of-principle study indicates that the four gestures are associated with a reliable and discriminable spatial representation on a confined area of the sensorimotor cortex. This robust representation on a small area makes hand gestures an interesting control feature for an implantable BCI to restore communication for severely paralyzed people.

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