Mechanistic model for human brain metabolism and its connection to the neurovascular coupling

PLoS Comput Biol. 2022 Dec 22;18(12):e1010798. doi: 10.1371/journal.pcbi.1010798. eCollection 2022 Dec.

Abstract

The neurovascular and neurometabolic couplings (NVC and NMC) connect cerebral activity, blood flow, and metabolism. This interconnection is used in for instance functional imaging, which analyses the blood-oxygen-dependent (BOLD) signal. The mechanisms underlying the NVC are complex, which warrants a model-based analysis of data. We have previously developed a mechanistically detailed model for the NVC, and others have proposed detailed models for cerebral metabolism. However, existing metabolic models are still not fully utilizing available magnetic resonance spectroscopy (MRS) data and are not connected to detailed models for NVC. Therefore, we herein present a new model that integrates mechanistic modelling of both MRS and BOLD data. The metabolic model covers central metabolism, using a minimal set of interactions, and can describe time-series data for glucose, lactate, aspartate, and glutamate, measured after visual stimuli. Statistical tests confirm that the model can describe both estimation data and predict independent validation data, not used for model training. The interconnected NVC model can simultaneously describe BOLD data and can be used to predict expected metabolic responses in experiments where metabolism has not been measured. This model is a step towards a useful and mechanistically detailed model for cerebral blood flow and metabolism, with potential applications in both basic research and clinical applications.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Brain / physiology
  • Cerebrovascular Circulation / physiology
  • Hemodynamics / physiology
  • Humans
  • Magnetic Resonance Imaging / methods
  • Neurovascular Coupling* / physiology

Grants and funding

This work was supported by the Swedish Research Council (2018-05418 and 2018-03319, GC; 2018-03391, ME). Additional support came from CENIIT (15.09, GC), from the Swedish foundation for strategic research (ITM17-0245, GC), from SciLifeLab and KAW (2020.0182, GC), from the H2020 project PRECISE4Q (777107, GC), from the Swedish Fund for Research without Animal Experiments (F2019-0010, GC), from the Swedish Brain Foundation (ME), from ELLIIT (GC), from VisualSweden (GC), and from VINNOVA (2020-04711, GC). The funders have had no role in the study design, data collection and analysis, decision to publish, or preparing the manuscript.