By combining and establishing advanced brain imaging techniques (fMRI and PET), the project aimed to understand how the brain manages its high energy demands during cognitive and memory processing and identify the metabolic processes involved in brain connectivity and brain work.
The first subproject (Ref 1 below) explored how the brain’s energy is distributed in its functional connectome. By using multimodal brain imaging, we found that evolutionarily expanded brain regions, particularly those involved in cognitive functions like reading and memory processing, have up to 67% higher energetic costs than sensory-motor regions. Additionally, we found evidence that increased brain size alone does not account for the human brain's heightened energy requirements; rather, the nature of signaling mechanisms in specific regions is key.
In a related subproject (Ref 2), we introduced the concept of "time-averaged control energy" (TCE) to quantify the energy costs of controlling brain dynamics at rest. Using functional and diffusion MRI, TCE was found to correlate spatially with oxygen metabolism, providing a bioenergetic perspective on how the brain manages energy consumption during resting states.
In a third subproject (Ref 3), we examined the relationship between fMRI signals and the brain's oxygen metabolism, challenging the traditional interpretation of BOLD signals in terms of neural activity. We found that changes in oxygen extraction fraction (OEF), rather than cerebral blood flow (CBF), were the primary drivers of oxygen supply in a large portion of voxels, especially during task states. This finding suggests that the interpretation of BOLD signals requires a more nuanced understanding of neurovascular coupling and that quantitative fMRI or additional CBF measurements are necessary for a valid assessment of regional brain activity.
In a fourth subproject (Ref 4), we explored how the brain balances its energy demands during visual perception under varying levels of predictability and subjective uncertainty. The findings revealed that predictable visual input led to reduced oxygen metabolism, particularly when participants were confident in their predictions. This resulted in cortical energy savings of up to 12%, suggesting that predictive processing enhances both behavioral performance and energy efficiency. This has significant implications for understanding how the brain optimizes energy use during cognitive tasks, such as memory consolidation.
In a final subproject (Ref 5), we examined the brain's response to insulin-induced hypoglycemia, focusing on the impact on cerebral oxygen metabolism (CMRO2) and memory consolidation. We found that despite a drop in blood glucose levels, CMRO2 remained stable, indicating that the brain efficiently shifts to alternative energy pathways, such as astrocytic glycogen, during hypoglycemia. However, we also found that hypoglycemia had long-lasting effects on memory consolidation, even after glucose levels were restored. This study underscores the brain's metabolic flexibility but also highlights the vulnerability of memory processes to metabolic disturbances.
Ref 1: An Energy Costly Architecture of Neuromodulators for Human Brain Evolution and Cognition.
Castrillon G, Epp S, Bose A, Fraticelli L, Hechler A, Belenya R, Ranft A, Yakushev I, Utz L, Sundar L, Rauschecker JP, Preibisch C, Kurcyus K, Riedl V.
Science Advances. 2023 Dec 13;9(50): eadi7632. DOI: 10.1126/sciadv.adi7632
Ref 2: The control costs of human brain dynamics.
Ceballos EG, Luppi AI, Castrillon G, Saggar M, Misic B, Riedl V.
Network Neuroscience. 2024 1-23; DOI: 10.1162/netn_a_00425
Ref 3: Two distinct modes of hemodynamic responses in the human brain
Epp SM, Castrillón G, Yuan B, Andrews-Hanna J, Preibisch C, Riedl V
bioRxiv 2023.12.08.570806; DOI: 10.1101/2023.12.08.570806
Ref 4: The energy metabolic footprint of predictive processing in the human brain
Hechler A, de Lange FP, Riedl V
bioRxiv 2023.12.08.570804; DOI: 10.1101/2023.12.08.570804
Ref 5: The selfish yet forgetful brain: Stable cerebral oxygen metabolism during hypoglycemia but impaired memory consolidation.
Bose A, Haschka SJ, Koehler J, Hesse F, Martin S, Steinberg L, Iakoubov R, Riedl V
bioRxiv 2024.12.12.628178; DOI: 10.1101/2024.12.12.628178
