Edinburgh Napier University

  Energetic considerations play a crucial role in brain function and disease. The study of brainenergy metabolism is, however, rendered difficult by a relative lack of experimental tools thatcan probe the contributions of different intricately connected cell types and processes. Inthis context, mathematical modelling has a role to play, but typically leads to models, whosecomplexity reflects that of the underlying biological system, and from which it is difficult toextract biologically actionable information.Here, an experimentally-calibrated multi-scale model of human brain energy metabolism [1] is analysed using the so-called Computational Singular Perturbation algorithm in order to identify key biological processes and periods, during and after a brain area has been activated. We identify a key role for both oxidative and glycolytic astrocytic metabolism in driving the behaviour of the brain's metabolic circuitry. Neuronal energy metabolism, by opposition, only plays a transient role for the first few seconds after the onset or offset of activation. We additionally identify a key role for the creatine phosphate shuttle in late stages of activation and post-activation. Our approach highlights the importance of glial cells in brain circuits, and introduces a systematic and unbiased methodology to study the dynamics of complex biochemical networks that can be readily scaled to metabolic networks of any size and complexity.