Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (2/2 displayed)

  • 2024Cerebral MRI in a prospective cohort study on depression and atherosclerosis: the BiDirect sample, processing pipelines, and analysis toolscitations
  • 2023Cognitive performance and brain structural connectome alterations in major depressive disorder8citations

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Chart of shared publication
Minnerup, Heike
1 / 1 shared
Wulms, Niklas
1 / 1 shared
Kugel, Harald
1 / 1 shared
Tenberge, Anja
1 / 1 shared
Cnyrim, Christian
1 / 1 shared
Sundermann, Benedikt
1 / 1 shared
Schwindt, Wolfram
1 / 1 shared
Berger, Klaus
1 / 2 shared
Chart of publication period
2024
2023

Co-Authors (by relevance)

  • Minnerup, Heike
  • Wulms, Niklas
  • Kugel, Harald
  • Tenberge, Anja
  • Cnyrim, Christian
  • Sundermann, Benedikt
  • Schwindt, Wolfram
  • Berger, Klaus
OrganizationsLocationPeople

article

Cognitive performance and brain structural connectome alterations in major depressive disorder

  • Borgers, Tiana
  • Gruber, Marius
  • Meinert, Susanne
  • Dannlowski, Udo
  • Lange, Siemon C. De
  • Stein, Frederike
  • Winter, Nils Ralf
  • Thiel, Katharina
  • Lemke, Hannah
  • Leehr, Elisabeth J.
  • Enneking, Verena
  • Redlich, Ronny
  • Breuer, Fabian
  • Heuvel, Martijn P. Van Den
  • Pfarr, Julia-Katharina
  • Nenadić, Igor
  • Brosch, Katharina
  • Mauritz, Marco
  • Bauer, Jochen
  • Grotegerd, Dominik
  • Grumbach, Pascal
  • Goltermann, Janik
  • Opel, Nils
  • Waltemate, Lena
  • Repple, Jonathan
  • Winter, Alexandra
  • Hahn, Tim
  • Kircher, Tilo
  • Meller, Tina
  • Klug, Melissa
  • Ringwald, Kai Gustav
Abstract

<jats:title>Abstract</jats:title><jats:sec id="S0033291722004007_sec_a1"><jats:title>Background</jats:title><jats:p>Cognitive dysfunction and brain structural connectivity alterations have been observed in major depressive disorder (MDD). However, little is known about their interrelation. The present study follows a network approach to evaluate alterations in cognition-related brain structural networks.</jats:p></jats:sec><jats:sec id="S0033291722004007_sec_a2" sec-type="methods"><jats:title>Methods</jats:title><jats:p>Cognitive performance of <jats:italic>n</jats:italic> = 805 healthy and <jats:italic>n</jats:italic> = 679 acutely depressed or remitted individuals was assessed using 14 cognitive tests aggregated into cognitive factors. The structural connectome was reconstructed from structural and diffusion-weighted magnetic resonance imaging. Associations between global connectivity strength and cognitive factors were established using linear regressions. Network-based statistics were applied to identify subnetworks of connections underlying these global-level associations. In exploratory analyses, effects of depression were assessed by evaluating remission status-related group differences in subnetwork-specific connectivity. Partial correlations were employed to directly test the complete triad of cognitive factors, depressive symptom severity, and subnetwork-specific connectivity strength.</jats:p></jats:sec><jats:sec id="S0033291722004007_sec_a3" sec-type="results"><jats:title>Results</jats:title><jats:p>All cognitive factors were associated with global connectivity strength. For each cognitive factor, network-based statistics identified a subnetwork of connections, revealing, for example, a subnetwork positively associated with processing speed. Within that subnetwork, acutely depressed patients showed significantly reduced connectivity strength compared to healthy controls. Moreover, connectivity strength in that subnetwork was associated to current depressive symptom severity independent of the previous disease course.</jats:p></jats:sec><jats:sec id="S0033291722004007_sec_a4" sec-type="conclusions"><jats:title>Conclusions</jats:title><jats:p>Our study is the first to identify cognition-related structural brain networks in MDD patients, thereby revealing associations between cognitive deficits, depressive symptoms, and reduced structural connectivity. This supports the hypothesis that structural connectome alterations may mediate the association of cognitive deficits and depression severity.</jats:p></jats:sec>

Topics
  • impedance spectroscopy
  • strength
  • size-exclusion chromatography