Photo of Henrik Podéus

Henrik Podéus

PhD student

I use mathematical models to understand the origins of brain activity. My main research focus is modeling of the electrical communication between neurons and the neurovascular coupling. 

Mathematical modeling of brain activity

Brain activity originates from the electrical communication between neurons and is typically recorded with two different types of measurement. The first, electrophysiological measurements, records the electrical activity generated from electrical signaling in various ways. Some measurements are Local Field Potential (LFP), Electroencephalogram (EEG), and cell spiking rate. The second type, neurovascular measurements, measure the downstream changes in the cerebral vasculature following electrical activity, like cerebral blood flow (CBF), hemoglobin levels, and the blood oxygen-level dependent (BOLD) signal. These downstream changes are connected to the electrical activity through the neurovascular coupling, which incorporates the pathways that link the electrical activity and the secretion of vasoactive substances. Many different types of pathways and neurons are involved in the neurovascular coupling and therefore it is very challenging to relate these measurements to one another.

In my research, I am identifying and evaluating the pathways included in the neurovascular coupling using mathematical modeling. I aim to create a framework that allows us to relate the electrophysiological and neurovascular measurements to each other.



Henrik Podéus, Christian Simonsson, Patrik Nasr, Mattias Ekstedt, Stergios Kechagias, Peter Lundberg, William Lövfors, Gunnar Cedersund (2024) A physiologically-based digital twin for alcohol consumption-predicting real-life drinking responses and long-term plasma PEth npj Digital Medicine, Vol. 7, Article 112 Continue to DOI


Sebastian Sten, Henrik Podéus, Nicolas Sundqvist, Fredrik Elinder, Maria Engström, Gunnar Cedersund (2023) A quantitative model for human neurovascular coupling with translated mechanisms from animals PloS Computational Biology, Vol. 19, Article e1010818 Continue to DOI