Head of multiscale neuroimaging (FAU) and neuroenergetics (TUM) labs
The brain consumes 20% of the human body’s energy budget. Neuronal communication among highly connected brain regions is the main driver of the brain’s energy demands. While we know much about the macroscopic organization of the human brain in specialized regions and brain networks, the energy budget of human brain function is still unclear. Moreover, brain metabolism is heavily disturbed in several neuropsychiatric disorders but the relationship to brain network communication is also unknown. In my two research groups, we measure energy consumption of the human brain and relate these to common measures of brain organization. We simultaneously acquire energy metabolism and brain connectivity measures on an integrated PET/MR (Siemens Biograph mMR) scanner at TUM, and quantify metabolism with ultra-high field MRI (7T) at FAU. We measure inhibitory and excitatory neurotransmitter levels using 1H-Magnetic Resonance Spectroscopy (MRS) and modulate brain function using non-invasive, stereotactic transcranial magnetic stimulation (TMS).
Methods: hybrid PET/MRI (Positron Emission Tomography, Magnetic Resonance Imaging), Magnetic Resonance Spectroscopy (MRS), Transcranial Magnetic Stimulation (TMS)
FAU, Erlangen: ultra-high field MRI (7T) TUM, Munich: simultaneous PET/MRI
Keywords: neuroenergetics, brain metabolism, brain imaging, brain networks, neuromodulators, ultra-high field MRI (7T), hybrid PET/MRI, TMS, MRS
- Develop new imaging approaches to integrate brain profiles of energy metabolism and network connectivity.
- Study the energy metabolism of brain networks during memory consolidation and modulate this process with non-invasive brain stimulation.
- Link brain energetics with nutrition and body metabolism.
- Uncover deficient metabolic brain profiles in patients with neuropsychiatric disorders.
ERC starting grant 759659, Deutsche Forschungsgesellschaft (DFG) RI2519, Kommission für klinische Forschung (KKF) 8762754, Alzheimer Forschungsinitiative (AFI) 088660
Castrillon G, Sollmann N, Kurcyus K, Razi A, Krieg SM, Riedl V The physiological effects of noninvasive brain stimulation fundamentally differ across the human cortex. Science Advances. 2020 Jan 31. doi: 10.1126/sciadv.aay2739
Scherr M, Utz L, Tahmasian M, Pasquini L, Grothe MJ, Rauschecker JP, Grimmer T, Drzezga A, Sorg C, Riedl V. Effective connectivity in the default mode network is distinctively disrupted in Alzheimer’s disease – a simultaneous resting-state FDG-PET/fMRI study. Hum Brain Mapp 2019 Jan 30; doi: 10.1002/hbm.2451
Kurcyus K, Annac E, Hanning NM, Harris AD, Oeltzschner G, Edden R, Riedl V. Opposite dynamics of GABA and glutamate levels in the occipital cortex during visual processing. J Neurosci. 2018 Nov 14;38(46):9967-9976; doi: 10.1523/JNEUROSCI.1214-18.2018
Riedl V, Utz L, Castrillón G, Grimmer T, Rauschecker JP, Ploner M, Friston KJ, Drzezga A, Sorg C. Metabolic connectivity mapping reveals effective connectivity in the resting human brain. Proc Natl Acad Sci U S A. 2016 Jan 12;113(2):428-33. doi: 10.1073/pnas.1513752113
Riedl V, Bienkowska K, Strobel C, Tahmasian M, Grimmer T, Förster S, Friston KJ, Sorg C, Drzezga A. Local activity determines functional connectivity in the resting human brain: a simultaneous FDG-PET/fMRI study. J Neurosci. 2014 Apr 30;34(18):6260-6. doi: 10.1523/JNEUROSCI.0492-14.2014
Sorg C, Riedl V, Mühlau M, Calhoun VD, Eichele T, Läer L, Drzezga A, Förstl H, Kurz A, Zimmer C, Wohlschläger AM. Selective changes of resting-state networks in individuals at risk for Alzheimer's disease. Proc Natl Acad Sci U S A. 2007 Nov 20;104(47):18760-5. doi: 10.1073/pnas.0708803104