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Nicolas Sundqvist

I’m a PhD-student and my work centres around modelling of the brain and different brain functions. The primary focus of my PhD project is to gain a further understanding for the vital role that the neuronal metabolism plays in the regulation of the cerebral blood flow. I’m also trying to integrate the approaches of metabolic flux analysis (MFA) with our current model for the coupling between neuronal, vascular, and metabolic activity in the brain.

This coupling is commonly known as the neurovascular coupling (NVC). The NVC is a cornerstone of functional magnetic imaging (fMRI), which analysis the so-called blood-oxygen-dependent (BOLD) signal. The BOLD signal is governed by the regional balance between the vascular and metabolic activity. This balance between the BOLD-signal and neuronal activity is non-linear, time varying, and partially unknown, and current fMRI-analysis tools are statistical in nature, and do not account for these complex interactions. One approach to better deal with this complexity is to use mechanistic mathematical modelling. Current mathematical models for the NVC provide only a very simple description of the metabolism. While detailed neurometabolic models include the contribution of the NVC only as a quasi-phenomenological description.

Further, understanding the intracellular metabolic phenotype of the neuronal cells is vital to understand and properly characterize the different levels of activity in the brain. Arguably some of the most important parameters in the metabolism are the intracellular metabolic conversion rates, also called metabolic fluxes. These fluxes describe how metabolite conversions occur throughout the metabolic system. Describing and mapping how these fluxes interconnect, into larger metabolic networks, is one of the cornerstones of metabolic engineering.

However, metabolic fluxes are very difficult to measure in living tissue. Currently, the approach of 13C metabolic flux analysis (13C MFA) provides the best solution for quantitatively determining the metabolic fluxes. Metabolic flux analysis uses mathematical modelling to quantify the metabolic fluxes based on the metabolic distribution of isotopically labelled substrates. In the past the 13C MFA approach have mainly been used for mapping the metabolism of simpler organism such as E-coli and have only to a limited extent been used to evaluate more complex systems, such as the human cellular metabolism. While MFA can have been showed to accurately determine the flux configuration of complex systems, the modelling part of the methodology needs to be further developed. Thus, the aim of my project is to expand on the existing modelling framework in order to develop a robust, reliable and realistic methodology for modelling metabolic fluxes in human cerebral systems.

Additionally, I’m involved in a project that aims to develop a new structural model for explaining the kinetics of voltage gated Ion channels. In this project we aim to expand upon the understanding of the well-established Hodgkin-Huxley models for ion channel kinetics, to develop a model structure that is more general for different types of voltage gated ion channels and that more precisely represent the current physiological understanding of these ion channels.