Working memory capacity and the functional connectome - insights from resting-state fMRI and voxelwise centrality mapping

被引:0
|
作者
Sebastian Markett
Martin Reuter
Behrend Heeren
Bernd Lachmann
Bernd Weber
Christian Montag
机构
[1] University of Bonn,Department of Psychology
[2] University of Bonn,Center for Economics and Neuroscience
[3] University of Bonn,Institute for Numerical Simulation
[4] University of Bonn,Department of Epileptology
[5] University of Bonn,Department of NeuroCognition, Life & Brain Center
[6] Ulm University,Institute of Psychology and Education
[7] University of Electronic Science and Technology of China,Key Laboratory for NeuroInformation
来源
关键词
Working memory; Resting-state fMRI; Connectome; Intraparietal sulcus; Working; memory capacity, cognitive ability;
D O I
暂无
中图分类号
学科分类号
摘要
The functional connectome represents a comprehensive network map of functional connectivity throughout the human brain. To date, the relationship between the organization of functional connectivity and cognitive performance measures is still poorly understood. In the present study we use resting-state functional magnetic resonance imaging (fMRI) data to explore the link between the functional connectome and working memory capacity in an individual differences design. Working memory capacity, which refers to the maximum amount of context information that an individual can retain in the absence of external stimulation, was assessed outside the MRI scanner and estimated based on behavioral data from a change detection task. Resting-state time series were analyzed by means of voxelwise degree and eigenvector centrality mapping, which are data-driven network analytic approaches for the characterization of functional connectivity. We found working memory capacity to be inversely correlated with both centrality in the right intraparietal sulcus. Exploratory analyses revealed that this relationship was putatively driven by an increase in negative connectivity strength of the structure. This resting-state connectivity finding fits previous task based activation studies that have shown that this area responds to manipulations of working memory load.
引用
收藏
页码:238 / 246
页数:8
相关论文
共 50 条
  • [1] Working memory capacity and the functional connectome - insights from resting-state fMRI and voxelwise centrality mapping
    Markett, Sebastian
    Reuter, Martin
    Heeren, Behrend
    Lachmann, Bernd
    Weber, Bernd
    Montag, Christian
    BRAIN IMAGING AND BEHAVIOR, 2018, 12 (01) : 238 - 246
  • [2] Resting-state fMRI in the Human Connectome Project
    Smith, Stephen M.
    Beckmann, Christian F.
    Andersson, Jesper
    Auerbach, Edward J.
    Bijsterbosch, Janine
    Douaud, Gwenaelle
    Duff, Eugene
    Feinberg, David A.
    Griffanti, Ludovica
    Harms, Michael P.
    Kelly, Michael
    Laumann, Timothy
    Miller, Karla L.
    Moeller, Steen
    Petersen, Steve
    Power, Jonathan
    Salimi-Khorshidi, Gholamreza
    Snyder, Abraham Z.
    Vu, An T.
    Woolrich, Mark W.
    Xu, Junqian
    Yacoub, Essa
    Ugurbil, Kamil
    Van Essen, David C.
    Glasser, Matthew F.
    NEUROIMAGE, 2013, 80 : 144 - 168
  • [3] Damage to the structural connectome reflected in resting-state fMRI functional connectivity
    Wodeyar, Anirudh
    Cassidy, Jessica M.
    Cramer, Steven C.
    Srinivasan, Ramesh
    NETWORK NEUROSCIENCE, 2020, 4 (04) : 1197 - 1218
  • [4] Functional network centrality in obesity: A resting-state and task fMRI study
    Garcia-Garcia, Isabel
    Angeles Jurado, Maria
    Garolera, Maite
    Marques-Iturria, Idoia
    Horstmann, Annette
    Segura, Barbara
    Pueyo, Roser
    Jose Sender-Palacios, Maria
    Vemet-Vemet, Maria
    Villringer, Arno
    Junque, Carme
    Margulies, Daniel S.
    Neumann, Jane
    PSYCHIATRY RESEARCH-NEUROIMAGING, 2015, 233 (03) : 331 - 338
  • [5] Benchmarking functional connectome-based predictive models for resting-state fMRI
    Dadi, Kamalaker
    Rahim, Mehdi
    Abraham, Alexandre
    Chyzhyk, Darya
    Milham, Michael
    Thirion, Bertrand
    Varoquaux, Gael
    NEUROIMAGE, 2019, 192 : 115 - 134
  • [6] Functional connectomics from resting-state fMRI
    Smith, Stephen M.
    Vidaurre, Diego
    Beckmann, Christian F.
    Glasser, Matthew F.
    Jenkinson, Mark
    Miller, Karla L.
    Nichols, Thomas E.
    Robinson, Emma C.
    Salimi-Khorshidi, Gholamreza
    Woolrich, Mark W.
    Barch, Deanna M.
    Ugurbil, Kamil
    Van Essen, David C.
    TRENDS IN COGNITIVE SCIENCES, 2013, 17 (12) : 666 - 682
  • [7] Functional correlates of cognitive performance and working memory in temporal lobe epilepsy: Insights from task-based and resting-state fMRI
    Fajardo-Valdez, Alfonso
    Camacho-Tellez, Vicente
    Rodriguez-Cruces, Raul
    Garcia-Gomar, Maria Luisa
    Pasaye, Erick Humberto
    Concha, Luis
    PLOS ONE, 2024, 19 (03):
  • [8] Transdiagnostic connectome signatures from resting-state fMRI predict individual-level intellectual capacity
    Tong, Xiaoyu
    Xie, Hua
    Carlisle, Nancy
    Fonzo, Gregory A.
    Oathes, Desmond J.
    Jiang, Jing
    Zhang, Yu
    TRANSLATIONAL PSYCHIATRY, 2022, 12 (01)
  • [9] Transdiagnostic connectome signatures from resting-state fMRI predict individual-level intellectual capacity
    Xiaoyu Tong
    Hua Xie
    Nancy Carlisle
    Gregory A. Fonzo
    Desmond J. Oathes
    Jing Jiang
    Yu Zhang
    Translational Psychiatry, 12
  • [10] Connectopic mapping with resting-state fMRI
    Haak, Koen V.
    Marquand, Andre E.
    Beckmann, Christian F.
    NEUROIMAGE, 2018, 170 : 83 - 94