Computational brain modelling

The Computational Brain Modelling group develop mathematical and computational models of cerebral physiology, with a particular focus on oxygen metabolism and blood flow. These models are able to integrate and simulate measurements from near-infrared spectroscopy (NIRS) and magnetic resonance spectroscopy (MRS), and assist with data interpretation in both experimental and clinical contexts.

We are using the models to investigate the effect of physiological insults such as anoxia, hypoxia and ischaemia. By comparing model predictions with measured data, we can obtain a better understanding of the metabolic changes that occur in the brain during and in the aftermath of these insults.

Models

A number of related but distinct models have been developed to address different situations of physiological and clinical interest.

BrainCirc

A model of oxygenation, circulation and metabolism in the adult human brain. First published in 2005, this is the most complex and detailed of our models.

BrainSignals

A simplified version of BrainCirc, adapted to model changes in the oxidation state of cytochrome-c-oxidase (CCO), a metabolic marker measurable via NIRS.

BrainPiglet

A further extension of the BrainSignals model, incorporating MRS-measured variables such as ATP, PCr, Pi and lactate. The model is tailored to the study of hypoxia-ischaemia in piglets, an important model organism for human neonates in clinical experiments.

Software

The custom modelling programs used to implement our models are fully open source. More information and download links can be found on our Software page.

Publications

Caldwell, M., Hapuarachchi, T., Highton, D., Elwell, C., Smith, M., Tachtsidis, I. (2015). BrainSignals Revisited: Simplifying a Computational Model of Cerebral Physiology. PLoS ONE, 10(5), e0126695.

Moroz, T., Hapuarachchi, T., Bainbridge, A., Price, D., Cady, E. B., Baer, E., et al. (2013). Modelling Blood Flow and Metabolism in the Piglet Brain During Hypoxia-Ischaemia: Simulating Brain Energetics. Advances in Experimental Medicine and Biology, 789, 339–344.

Hapuarachchi, T., Moroz, T., Bainbridge, A., Price, D., Cady, E. B., Baer, E., et al. (2013). Modelling Blood Flow and Metabolism in the Piglet Brain During Hypoxia-Ischaemia: Simulating pH Changes. Advances in Experimental Medicine and Biology, 789, 331–337.

Moroz, T., Banaji, M., Tisdall, M. M., Cooper, C. E., Elwell, C. E., & Tachtsidis, I. (2012). Development of a model to aid NIRS data interpretation: results from a hypercapnia study in healthy adults. Advances in Experimental Medicine and Biology, 737, 293–300.

Jelfs, B., Banaji, M., Tachtsidis, I., Cooper, C. E., & Elwell, C. E. (2012). Modelling Noninvasively Measured Cerebral Signals during a Hypoxemia Challenge: Steps towards Individualised Modelling. PLoS ONE, 7(6), e38297.

Moroz, T., Banaji, M., Robertson, N. J., Cooper, C. E., & Tachtsidis, I. (2012). Computational modelling of the piglet brain to simulate near-infrared spectroscopy and magnetic resonance spectroscopy data collected during oxygen deprivation. Journal of the Royal Society Interface, 9(72), 1499–1509.

Banaji, M., Mallet, A., Elwell, C. E., Nicholls, P., & Cooper, C. E. (2008). A Model of Brain Circulation and Metabolism: NIRS Signal Changes during Physiological Challenges. PLoS Computational Biology, 4(11), e1000212.

Banaji, M., Tachtsidis, I., Delpy, D., & Baigent, S. (2005). A physiological model of cerebral blood flow control. Mathematical Biosciences, 194(2), 125–173. doi:10.1016/j.mbs.2004.10.005