Year: 2026
Type: preprint
Study design: Observational Study
Abstract: Despite decades of extensive research, the complex architecture underlying human brain signaling remains incompletely understood. Previous work investigating the relationship between brain glucose metabolism and functional connectivity (FC) employed whole-brain analysis, without accounting for network interactions, dependencies or hierarchies. Here, we assess network-specific differences in the relationship between FC and metabolic demand, using [18F]FDG PET/MR data from three independent datasets. The metabolic cost of FC, i.e., the change in glucose demand associated with corresponding changes in FC, was modeled at rest, during cognitive task performance and in Alzheimer′s disease (AD). Our findings reveal network-specific differences in metabolic cost, with the default mode (DM), somatomotor (SM) and fronto-temporal networks accounting for highest, intermediate and lowest metabolic demands, respectively. Similarly, time-resolved variability of FC demonstrated highest costs for states with DM network involvement and lowest for SM network participation. This relationship was reversed in participants with AD, who exhibited decreased demands in the DM network and increased costs in the SM network. Cognitive performance consistently revealed cost reductions in the DM and SM networks, as well as increases in task relevant networks. Together, these results highlight the flexibility of functional network architecture associated with cognitive demands and neuropathology, and shed light on the complex interplay between glucose metabolism and network interactions.
Authors: Sarah Maria Tüchler, Pia Falb, Christian Milz, Matej Murgaš, Murray B Reed, Samantha Graf, Gabriel Schlosser, Clemens Schmidt, Alexandra Mayerweg, Sebastian Klug, Ivan Pörnbacher, Lukas Artmeier, Adam Harouak, Aurelia Sahl, Maximilian Grohmann, Lukas Nics, Godber M Godbersen, Sazan Rasul, Dan Rujescu, Marcus Hacker, Rupert Lanzenberger, Andreas Hahn, For the Alzheimer's Disease Neuroimaging Initiative
Institution: Medical University of Vienna
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: green
Funders: Foundation for the National Institutes of Health, Alzheimer's Association, Bristol-Myers Squibb, Eli Lilly and Company, Pfizer, Biogen, F. Hoffmann-La Roche, Meso Scale Diagnostics, Alzheimer's Disease Neuroimaging Initiative, BioClinica, Novartis Pharmaceuticals Corporation, Northern California Institute for Research and Education, Österreichischen Akademie der Wissenschaften, Austrian Science Fund, Universität Wien, Eisai, Medizinische Universität Wien, Servier, H. Lundbeck A/S, IXICO, National Institutes of Health, Genentech, Canadian Institutes of Health Research, National Institute on Aging
Awards: Impact of stress on brain energy metabolism, G1880935189, G29951154, G3553156159, G3752451908, G3870774570, G3966393351, G4079001475, G4501223628, G5209990037, G5235017436, G5654639750, G5740349702, G6203725628, G6371410416, G6899163935, G7414321945, G781725486, G839208290, G8590477180, G866201112, Alzheimer's Disease Neuroimaging Initiative (ADNI4)
OpenAlex ID: W7212233822