(Press-News.org) Researchers at the Technical University of Munich (TUM) and the Friedrich-Alexander-University Erlangen-Nuremberg (FAU) found that an increased fMRI signal is associated with reduced brain activity in around 40 percent of cases. At the same time, they observed decreased fMRI signals in regions with elevated activity. First author Dr. Samira Epp emphasizes: “This contradicts the long-standing assumption that increased brain activity is always accompanied by an increased blood flow to meet higher oxygen demand. Since tens of thousands of fMRI studies worldwide are based on this assumption, our results could lead to opposite interpretations in many of them.”
Test tasks reveal deviations from the standard interpretation
PD Dr. Valentin Riedl, now Professor at FAU, and his colleague Epp examined more than 40 healthy participants during their time at TUM. Each was given several experimental tasks – such as mental arithmetic or autobiographical memory recall – which are known to produce predictable fMRI signal changes in distributed brain regions. During these experiments, the researchers simultaneously measured the actual oxygen consumption using a novel quantitative MRI technique.
Depending on the task and the brain region, the physiological results varied. Increased oxygen consumption – for instance in areas involved in calculation – did not coincide with the expected rise in blood flow. Instead, the quantitative analyses showed that these regions met their additional energy demand by extracting more oxygen from the unchanged blood supply. Thus, they used the oxygen available in the blood more efficiently without requiring greater perfusion.
Implications for interpreting brain disorders
According to Riedl, these insights also affect the interpretation of research findings in brain disorders: “Many fMRI studies on psychiatric or neurological diseases – from depression to Alzheimer’s – interpret changes in blood flow as a reliable signal of neuronal under- or over-activation. Given the limited validity of such measurements, this must now be reassessed. Especially in patient groups with vascular changes – for instance due to aging or vascular disease – the measured values may primarily reflect vascular differences rather than neuronal deficits.” Previous animal studies already point in this direction.
The researchers therefore propose complementing the conventional MRI approach with quantitative measurements. In the long term, this combination could form the basis for energy-based brain models: rather than showing activation maps that depend on assumptions about blood flow, future analyses could display values indicating how much oxygen – and therefore energy – is actually consumed for information processing. This opens new perspectives for examining aging, psychiatric, or neurodegenerative diseases in terms of absolute changes in energy metabolism – and for understanding them more accurately.
Publication:
Samira M. Epp, Gabriel Castrillón, Beijia Yuan, Jessica Andrews-Hanna, Christine Preibisch, Valentin Riedl: BOLD signal changes can oppose oxygen metabolism across the human cortex, published in Nature Neuroscience, December 16, 2025, https://doi.org/10.1038/s41593-025-02132-9
Further information:
The research was conducted at the Neuro-Head Center of the Institute of Neuroradiology at the TUM University Hospital. It was funded by the European Research Council through an ERC Starting Grant.
Additional material for media outlets:
Photos for download: https://go.tum.de/410691
Subject matter expert:
Prof. Dr. Valentin Riedl
Research Fellow
Technical University of Munich
TUM University Hospital – Neuro-Head Center
valentin.riedl@tum.de
Contact at the TUM Corporate Communications Center:
Ulrich Meyer
Press Spokesman
ulrich.meyer@tum.de
www.tum.de
END
40 percent of MRI signals do not correspond to actual brain activity
Why blood flow is not a reliable indicator of the brain's energy requirements
2025-12-16
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[Press-News.org] 40 percent of MRI signals do not correspond to actual brain activityWhy blood flow is not a reliable indicator of the brain's energy requirements