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129 Research products

  • Neuroinformatics
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Senden, Mario; Reuter, Niels; van den Heuvel, Martijn P.; Goebel, Rainer; +2 Authors

    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 between 68 cortical regions from functional magnetic resonance imaging activity for four different tasks (reflecting different cognitive domains) and resting state. We analyze the state-dependent input and output effective connectivity (EC) of the structural rich club and relate these to whole-cortex dynamics and network reconfigurations. We find that the cortical rich club exhibits an increase in outgoing EC during task performance as compared with rest while incoming connectivity remains constant. Increased outgoing connectivity targets a sparse set of peripheral regions with specific regions strongly overlapping between tasks. At the same time, community detection analyses reveal massive reorganizations of interactions among peripheral regions, including those serving as target of increased rich club output. This suggests that while peripheral regions may play a role in several tasks, their concrete interplay might nonetheless be task-specific. Furthermore, we observe that whole-cortex dynamics are faster during task as compared with rest. The decoupling effects usually accompanying faster dynamics appear to be counteracted by the increased rich club outgoing EC. Together our findings speak to a gating mechanism of the rich club that supports fast-paced information exchange among relevant peripheral regions in a task-specific and goal-directed fashion, while constantly listening to the whole network.,DATA_TASK_3DMOV_HP_CSF_WDBriefly, data comes from five functional runs consisting of a resting-state measurement (eyes closed), four individual task measurements including a visual n-back (n=2) task (Kirchner, 1958), the Eriksen flanker task (Eriksen & Eriksen, 1974), a mental rotation task (Shepard & Metzler, 1971), and a verbal odd-man-out task (Flowers & Robertson, 1985). All runs comprise 192 data points with tasks being continuously performed during this period. For the n-back and flanker task, stimuli were presented at a rate of 0.5 Hz; for the mental rotation and odd-man out tasks they were presented at a rate of 0.25 Hz. Task sequence was counterbalanced across participants with the exception that the resting state functional run was always acquired first to prevent carry-over effects (Grigg & Grady, 2010). The data were acquired using a 3 Tesla Siemens Prisma Fit (upgraded Tim Trio) scanner and a 64-channel head coil. Initial preprocessing was performed using BrainVoyager QX (v2.6; Brain Innovation, Maastricht, the Netherlands). This includes slice scan time correction, 3D-motion correction, high-pass filtering with a frequency cutoff of .01 Hz, and registration of functional and anatomical images. Subsequently, using MATLAB (2013a, The MathWorks,Natick, MA), signals were cleaned by performing wavelet despiking (Patel & Bullmore, 2015) and regressing out a global noise signal given by the first principal component of signals observed within the cerebrospinal fluid of the ventricles. Next, voxels were uniquely assigned to one of the 68 cortical ROIs specified by the DK atlas and an average BOLD time-series was computed for each region as the mean time-series over all voxels of that region., CC0 1.0

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ DANS-EASYarrow_drop_down
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    DANS-EASY
    Dataset . 2017
    Data sources: B2FIND
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    DRYAD; NARCIS
    Dataset . 2018
    License: CC 0
    Data sources: Datacite; NARCIS
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    ZENODO
    Dataset . 2018
    License: CC 0
    Data sources: ZENODO
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ DANS-EASYarrow_drop_down
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      DANS-EASY
      Dataset . 2017
      Data sources: B2FIND
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      DRYAD; NARCIS
      Dataset . 2018
      License: CC 0
      Data sources: Datacite; NARCIS
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZENODO
      Dataset . 2018
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    Authors: Schmidt, Ruben; LaFleur, Karl; Reus, Marcel De; Berg, Leonard Van Den; +1 Authors

    Figure S8. Global synchrony progression in the macaque. The order parameters r and r link for the macaque model network progressed in a manner similar to the human network (Figure 2), displaying a modular and a whole brain synchrony state separated by a critical regime.

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    Image . 2015
    License: CC BY
    Data sources: Datacite
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    Image . 2015
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      Image . 2015
      License: CC BY
      Data sources: Datacite
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      Image . 2015
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    Authors: D’Amato, Alfonsina; Mannelli, Lorenzo Di Cesare; Lucarini, Elena; Man, Angela L.; +15 Authors

    Additional file 11. Metabolome-proteome correlation (Pearson) .

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    Dataset . 2020
    License: CC BY
    Data sources: Datacite
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    Dataset . 2020
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    Data sources: Datacite
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ figsharearrow_drop_down
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      Dataset . 2020
      License: CC BY
      Data sources: Datacite
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      Dataset . 2020
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: van der Burgh, Hannelore;

    Objective: To understand the progressive nature of amyotrophic lateral sclerosis (ALS) by investigating differential brain patterns of gray and white matter involvement in clinically or genetically defined subgroups of patients using cross-sectional, longitudinal and multimodal MRI. Methods: We assessed cortical thickness, subcortical volumes and white matter connectivity from T1-weighted and diffusion-weighted MRI in 292 ALS patients (follow-up: n=150) and 156 controls (follow-up: n=72). Linear mixed-effects models were used to assess changes in structural brain measurements over time in patients compared to controls. Results: Patients with a C9orf72 mutation (n=24) showed widespread gray and white matter involvement at baseline, and extensive loss of white matter integrity in the connectome over time. In C9orf72-negative patients, we detected cortical thinning of motor and frontotemporal regions, and loss of white matter integrity of connections linked to the motor cortex. Spinal-onset patients displayed widespread white matter involvement at baseline and gray matter atrophy over time, whereas bulbar-onset patients started out with prominent gray matter involvement. Patients with unaffected cognition or behavior displayed predominantly motor system involvement, while widespread cerebral changes, including frontotemporal regions with progressive white matter involvement over time, were associated with impaired behavior or cognition. Progressive loss of gray and white matter integrity typically occurred in patients with shorter disease durations (<13 months), independent of progression rate. Conclusions: Heterogeneity of phenotype and C9orf72 genotype relates to distinct patterns of cerebral degeneration. We demonstrate that imaging studies have the potential to monitor disease progression and early intervention may be required to limit cerebral degeneration. Supplemental Data corresponding to research paper 'A multimodal longitudinal study of structural brain involvement in ALS' It contains appendices, supplemental figures and supplemental tables for this paper.

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    ZENODO
    Dataset . 2020
    License: CC 0
    Data sources: ZENODO
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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      ZENODO
      Dataset . 2020
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      Data sources: ZENODO
      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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    Authors: D’Amato, Alfonsina; Mannelli, Lorenzo Di Cesare; Lucarini, Elena; Man, Angela L.; +15 Authors

    Additional file 14. GFAP western blotting. Polyacrylamide (10%) gel stained with blue Coomassie with a representative image of molecular weight marker with relevant kDa (a). GAPDH visualized bands and merged with nitrocellulose membrane (b). GFAP visualized bands and merged with nitrocellulose membrane (c). In (d) a representative histogram shows levels of analysed protein both in FMT-Y and FMT-A treated and control animals. Lane 1 (positive control, DITNC1 astrocyte-derived cell line); lane 2 (negative control, BV-2 microglial cell line); lane 3 (aged mouse hippocampal proteins); lane 4 (adult mouse hippocampal protein); lane 5 (MT-aged hippocampal proteins); lane 6 (MT-adult hippocampal proteins). GFAP protein was detected approximately at 55 kDa (right blots). GAPDH (37 kDa) was used as housekeeping (left panel). Molecular weight (mw) used was SHARPMASS VII.

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    Image . 2020
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    Authors: Seguella, Luisa; Pesce, Mirella; Capuano, Riccardo; Casano, Fabrizio; +9 Authors

    Additional file 5 Representative images of hippocampal dentate gyrus and cultured neurons before starting the diet protocol. (A) Triple-label immunofluorescence for GFAP (green), TLR4 (red), and Dapi (blue) with relative fluorescence intensity quantification shown in Fig. 4. (B) BDNF protein expression (green) and immunoquantification in the dentate gyrus of the hippocampus. (C and D) Representative pictures show the neuronal spines (PSD 95 immunoreactivity, red) measured along hippocampal neurons’ dendrites (MAP-2 immunoreactivity, green) isolated before starting the diet protocol. Data were analyzed by 2-way ANOVA or 1-way ANOVA and Dunnettpost-hoc. Results are expressed as average relative fluorescence units (RFU) ± SEM per area unit or the average number of dendritic spines/10 μm of n assessments. Scale bars = 10 and 20 μm.

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    Authors: Zellner, Andreas; M��ller, Stephan A.; Lindner, Barbara; Beaufort, Nathalie; +7 Authors

    Additional file 1. Levels of the amyloid species A��1-40 and A��1-42 in the microvessel extracts determined by ELISA.

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    Authors: Schmidt, Ruben; LaFleur, Karl; Reus, Marcel De; Berg, Leonard Van Den; +1 Authors

    Figure S4. Hub versus random connectivity suppression. When edges were removed from the adjacency matrix, attaining whole brain synchrony required a higher cortical coupling factor. Removing both random and edges between hub nodes produces this result.

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    Authors: Schmidt, Ruben; LaFleur, Karl; Reus, Marcel De; Berg, Leonard Van Den; +1 Authors

    Figure S6. Modular frequency tracking during perturbation. Next to the Default Mode module (Figure 5), the effects of perturbation were examined for the remaining 10 functional modules as well. In each instance, the non-perturbed modules synchronized before the perturbed module joined in whole brain synchrony, consistent with the Default Mode perturbation and distinctly different from the hub node perturbation shown in figure 5.

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    Authors: Engels, Marjolein; Stam, Cornelis; Flier, Wiesje Van Der; Scheltens, Philip; +2 Authors

    The influence of the number of epochs. The number of epochs used for analyses influences the PLI outcomes. This supplement, including 1 figureand 1 table show that the PLI values become stable after 4 epochs of 8.192 seconds (4096 samples). (ZIP 66Â kb)

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129 Research products
  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Senden, Mario; Reuter, Niels; van den Heuvel, Martijn P.; Goebel, Rainer; +2 Authors

    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 between 68 cortical regions from functional magnetic resonance imaging activity for four different tasks (reflecting different cognitive domains) and resting state. We analyze the state-dependent input and output effective connectivity (EC) of the structural rich club and relate these to whole-cortex dynamics and network reconfigurations. We find that the cortical rich club exhibits an increase in outgoing EC during task performance as compared with rest while incoming connectivity remains constant. Increased outgoing connectivity targets a sparse set of peripheral regions with specific regions strongly overlapping between tasks. At the same time, community detection analyses reveal massive reorganizations of interactions among peripheral regions, including those serving as target of increased rich club output. This suggests that while peripheral regions may play a role in several tasks, their concrete interplay might nonetheless be task-specific. Furthermore, we observe that whole-cortex dynamics are faster during task as compared with rest. The decoupling effects usually accompanying faster dynamics appear to be counteracted by the increased rich club outgoing EC. Together our findings speak to a gating mechanism of the rich club that supports fast-paced information exchange among relevant peripheral regions in a task-specific and goal-directed fashion, while constantly listening to the whole network.,DATA_TASK_3DMOV_HP_CSF_WDBriefly, data comes from five functional runs consisting of a resting-state measurement (eyes closed), four individual task measurements including a visual n-back (n=2) task (Kirchner, 1958), the Eriksen flanker task (Eriksen & Eriksen, 1974), a mental rotation task (Shepard & Metzler, 1971), and a verbal odd-man-out task (Flowers & Robertson, 1985). All runs comprise 192 data points with tasks being continuously performed during this period. For the n-back and flanker task, stimuli were presented at a rate of 0.5 Hz; for the mental rotation and odd-man out tasks they were presented at a rate of 0.25 Hz. Task sequence was counterbalanced across participants with the exception that the resting state functional run was always acquired first to prevent carry-over effects (Grigg & Grady, 2010). The data were acquired using a 3 Tesla Siemens Prisma Fit (upgraded Tim Trio) scanner and a 64-channel head coil. Initial preprocessing was performed using BrainVoyager QX (v2.6; Brain Innovation, Maastricht, the Netherlands). This includes slice scan time correction, 3D-motion correction, high-pass filtering with a frequency cutoff of .01 Hz, and registration of functional and anatomical images. Subsequently, using MATLAB (2013a, The MathWorks,Natick, MA), signals were cleaned by performing wavelet despiking (Patel & Bullmore, 2015) and regressing out a global noise signal given by the first principal component of signals observed within the cerebrospinal fluid of the ventricles. Next, voxels were uniquely assigned to one of the 68 cortical ROIs specified by the DK atlas and an average BOLD time-series was computed for each region as the mean time-series over all voxels of that region., CC0 1.0

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    DANS-EASY
    Dataset . 2017
    Data sources: B2FIND
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    DRYAD; NARCIS
    Dataset . 2018
    License: CC 0
    Data sources: Datacite; NARCIS
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    ZENODO
    Dataset . 2018
    License: CC 0
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      Dataset . 2017
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      Dataset . 2018
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      ZENODO
      Dataset . 2018
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    Authors: Schmidt, Ruben; LaFleur, Karl; Reus, Marcel De; Berg, Leonard Van Den; +1 Authors

    Figure S8. Global synchrony progression in the macaque. The order parameters r and r link for the macaque model network progressed in a manner similar to the human network (Figure 2), displaying a modular and a whole brain synchrony state separated by a critical regime.

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    Authors: D’Amato, Alfonsina; Mannelli, Lorenzo Di Cesare; Lucarini, Elena; Man, Angela L.; +15 Authors

    Additional file 11. Metabolome-proteome correlation (Pearson) .

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    Dataset . 2020
    License: CC BY
    Data sources: Datacite
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    Dataset . 2020
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    Data sources: Datacite
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      Dataset . 2020
      License: CC BY
      Data sources: Datacite
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      Dataset . 2020
      License: CC BY
      Data sources: Datacite
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    Authors: van der Burgh, Hannelore;

    Objective: To understand the progressive nature of amyotrophic lateral sclerosis (ALS) by investigating differential brain patterns of gray and white matter involvement in clinically or genetically defined subgroups of patients using cross-sectional, longitudinal and multimodal MRI. Methods: We assessed cortical thickness, subcortical volumes and white matter connectivity from T1-weighted and diffusion-weighted MRI in 292 ALS patients (follow-up: n=150) and 156 controls (follow-up: n=72). Linear mixed-effects models were used to assess changes in structural brain measurements over time in patients compared to controls. Results: Patients with a C9orf72 mutation (n=24) showed widespread gray and white matter involvement at baseline, and extensive loss of white matter integrity in the connectome over time. In C9orf72-negative patients, we detected cortical thinning of motor and frontotemporal regions, and loss of white matter integrity of connections linked to the motor cortex. Spinal-onset patients displayed widespread white matter involvement at baseline and gray matter atrophy over time, whereas bulbar-onset patients started out with prominent gray matter involvement. Patients with unaffected cognition or behavior displayed predominantly motor system involvement, while widespread cerebral changes, including frontotemporal regions with progressive white matter involvement over time, were associated with impaired behavior or cognition. Progressive loss of gray and white matter integrity typically occurred in patients with shorter disease durations (<13 months), independent of progression rate. Conclusions: Heterogeneity of phenotype and C9orf72 genotype relates to distinct patterns of cerebral degeneration. We demonstrate that imaging studies have the potential to monitor disease progression and early intervention may be required to limit cerebral degeneration. Supplemental Data corresponding to research paper 'A multimodal longitudinal study of structural brain involvement in ALS' It contains appendices, supplemental figures and supplemental tables for this paper.

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    ZENODO
    Dataset . 2020
    License: CC 0
    Data sources: ZENODO
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