Mathematical modelling of the human physiology
| dc.contributor.author | Magnusson, Gustav | |
| dc.contributor.department | Chalmers tekniska högskola / Institutionen för fysik | sv |
| dc.contributor.examiner | Apell, Peter | |
| dc.contributor.supervisor | Cedersund, Gunnar | |
| dc.date.accessioned | 2020-12-07T15:04:21Z | |
| dc.date.available | 2020-12-07T15:04:21Z | |
| dc.date.issued | 2020 | sv |
| dc.date.submitted | 2020 | |
| dc.description.abstract | This master’s thesis is carried out within the field of systems biology and aims to contribute to the advancement of mathematical modelling for human physiology. This is important for many reasons, e.g. the potential reduction of animal testing. The work consists of two related parts: firstly, the development of a new framework for creating mathematical models to fulfill requirements of the Digital twin project, an undertaking currently being performed by Gunnar Cedersund’s group at Linköping University. The Digital twin project aims to produce a detailed computer model of an individual person which can be tuned to their unique physiology, i.e. a digital twin. This digital twin could then be used to improve patient compliance and/or understanding by simulating the likely effects of a medical treatment, or to make risk predictions for various diseases. The second part of the thesis revolves around the development of a neurovascular coupling model. This model is used to test the hypothesis that the post-stimulus response seen in a typical blood oxygen level dependent signal, measured by a magnetic resonance imaging camera, is due to a change in relative excitatory and inhibitory neural activity. This neurovascular coupling model also serves as a test for the new modelling framework described above. A first version of a digital twin software, where the new modelling framework plays a central role, was successfully completed and provides a solid foundation for further development in the digital twin project. The neurovascular coupling model was successful in showing the capabilities of this new modelling framework, however due to concerns regarding its validity it cannot definitively support the neural hypothesis. Instead, the model demonstrates the importance of thoroughly understanding the underlying physiology in order to assess the legitimacy of a neurovascular coupling model. This thesis has provided that understanding, and therefore can be viewed as a good starting point for future efforts to model the neurovascular coupling phenomenon. | sv |
| dc.identifier.coursecode | TIFX05 | sv |
| dc.identifier.uri | https://hdl.handle.net/20.500.12380/302106 | |
| dc.language.iso | eng | sv |
| dc.setspec.uppsok | PhysicsChemistryMaths | |
| dc.subject | mathematical modelling | sv |
| dc.subject | systems biology | sv |
| dc.subject | object-oriented modelling | sv |
| dc.subject | neurovascular coupling | sv |
| dc.subject | fMRI | sv |
| dc.subject | BOLD | sv |
| dc.title | Mathematical modelling of the human physiology | sv |
| dc.type.degree | Examensarbete för masterexamen | sv |
| dc.type.uppsok | H |