Cortical Thickness and Resting State Cardiac Function Across the Lifespan: A Cross-Sectional Pooled Mega Analysis

Contributors:
  1. Birgit Abler
  2. Ingrid Agartz
  3. Torbjörn Åkerstedt
  4. Ole A. Andreassen
  5. Mia Anthony
  6. Katja Bertsch
  7. Rebecca C. Brown
  8. Romuald Brunner
  9. Kathryn R. Cullen
  10. Eco J.C. de Geus
  11. Isabel Dziobek
  12. Herta Flor
  13. Peter J. Gianaros
  14. Simon Guendelman
  15. Sabine C. Herpertz
  16. Mandy X. Hu
  17. Michael Kaess
  18. Tobias Kaufmann
  19. Marlene Krauch
  20. Femke Lamers
  21. Mats Lekander
  22. Feng Lin
  23. Elena Makovac
  24. Matteo Mancini
  25. Falk Mancke
  26. Stephen B. Manuck
  27. Bryon Mueller
  28. Vera Muench
  29. Frauke Nees
  30. Daniela Ordonez Acuna
  31. Brenda W.J.H. Penninx
  32. Allison Ponzio
  33. Govinda R. Poudel
  34. Janis Reinelt
  35. Ping Ren
  36. Lin Sørensen
  37. Karsten Specht
  38. Joana Straub
  39. Julian F. Thayer
  40. Benjamin Ubani
  41. Laura S. van Velzen
  42. Carlos Ventura-Bort
  43. David R. Watson
  44. Luqing Wei
  45. Julia Wendt
  46. Melinda Westlund Schreiner

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Description: Resting state autonomic nervous system activity [ANS] indexed by measures of heart rate [HR] and its variability [HRV], is associated with brain morphology, in particular cortical thickness [CT]. However, findings have been mixed regarding the regions of interest [ROI] associated with HR/HRV and the direction of the association. Sex and age differences in HR/HRV and CT may explain some of the existing inconsistencies. Understanding the association between ANS function and brain morphology across aging, may provide important insights into neurovisceral mechanisms underlying health and disease. Previous studies have been limited by small sample sizes, prohibiting the assessment of sex differences, and effects of aging, in the association between ANS function and CT. In an effort to overcome these limitations, data from researchers worldwide, applying similar protocols in the assessment of CT and recording of HR/HRV, will be pooled for a mega-analysis. This preprint details the hypotheses, strategies for pooling of data and planned analyses of this project.

License: CC0 1.0 Universal

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If you are interested to contribute data to this project, please contact J. Koenig up until May 1st 2018.

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