Resting state network modularity along the prodromal late onset Alzheimer's disease continuum

Joey A. Contreras, Andrea Avena-Koenigsberger, Shannon L. Risacher, John D. West, Eileen Tallman, Brenna C. McDonald, Martin R. Farlow, Liana G. Apostolova, Joaquín Goñi, Mario Dzemidzic, Yu Chien Wu, Daniel Kessler, Lucas Jeub, Santo Fortunato, Andrew J. Saykin, Olaf Sporns

Research output: Contribution to journalArticle

6 Scopus citations

Abstract

Alzheimer's disease is considered a disconnection syndrome, motivating the use of brain network measures to detect changes in whole-brain resting state functional connectivity (FC). We investigated changes in FC within and among resting state networks (RSN) across four different stages in the Alzheimer's disease continuum. FC changes were examined in two independent cohorts of individuals (84 and 58 individuals, respectively) each comprising control, subjective cognitive decline, mild cognitive impairment and Alzheimer's dementia groups. For each participant, FC was computed as a matrix of Pearson correlations between pairs of time series from 278 gray matter brain regions. We determined significant differences in FC modular organization with two distinct approaches, network contingency analysis and multiresolution consensus clustering. Network contingency analysis identified RSN sub-blocks that differed significantly across clinical groups. Multiresolution consensus clustering identified differences in the stability of modules across multiple spatial scales. Significant modules were further tested for statistical association with memory and executive function cognitive domain scores. Across both analytic approaches and in both participant cohorts, the findings converged on a pattern of FC that varied systematically with diagnosis within the frontoparietal network (FP) and between the FP network and default mode network (DMN). Disturbances of modular organization were manifest as greater internal coherence of the FP network and stronger coupling between FP and DMN, resulting in less segregation of these two networks. Our findings suggest that the pattern of interactions within and between specific RSNs offers new insight into the functional disruption that occurs across the Alzheimer's disease spectrum.

Original languageEnglish (US)
Article number101687
JournalNeuroImage: Clinical
Volume22
DOIs
StatePublished - Jan 1 2019

Keywords

  • Alzheimer's disease
  • Brain networks
  • Connectomics
  • Functional connectivity
  • Resting state

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging
  • Neurology
  • Clinical Neurology
  • Cognitive Neuroscience

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    Contreras, J. A., Avena-Koenigsberger, A., Risacher, S. L., West, J. D., Tallman, E., McDonald, B. C., Farlow, M. R., Apostolova, L. G., Goñi, J., Dzemidzic, M., Wu, Y. C., Kessler, D., Jeub, L., Fortunato, S., Saykin, A. J., & Sporns, O. (2019). Resting state network modularity along the prodromal late onset Alzheimer's disease continuum. NeuroImage: Clinical, 22, [101687]. https://doi.org/10.1016/j.nicl.2019.101687