Modelling: from neurons to fMRI

Outline of the module
The fMRI signal is an indirect measure of neuronal activity reporting brain function via induced changes in blood oxygenation and blood volume. The module “Modelling: from neurons to fMRI” is an introduction in forward models of the physiological and physical steps leading to the fMRI signal. In addition, inversion schemes – inferring neuronal activity from experimental data – will be taught.

The module will discuss models how neuronal activity quantitavely causes changes in cerebral blood flow (termed neurovascular coupling) and is associated with oxidative metabolism (termed neurometabolic coupling). In addition, neuronal network models will be introduced to map specific brain functions on the native brain space. Furthermore, these physiological changes influence the level of blood oxygenation which in turn changes the micro- and mesoscopic magnetic field homogeneity. This endogenous susceptibility effect can then be detected by MRI using radiofrequency pulses and changing external magnetic fields. Thus, physical models of fMRI signal generation will be an essential part of this module. At the end of this module, students will have basic understanding of how to model the chain of physiological and physical events evoking the fMRI signal. Finally, mathematical algorithms to deduce neuronal activity from experimental data will be lectured and implemented in computer simulations.

The module covers the following topics:
• How is neuronal activity associated with metabolism (neurometabolic coupling)?
• How does neuronal activity evoke changes in cerebral blood flow?
• How to model vascular dynamics (balloon model)?
• How to model neuronal networks mimicking brain functions?
• How to model fMRI signal generation?
• How to infer neuronal activity from the fMRI signal?


Learning objectives
At the end of this module, students will have knowledge of:
• Implementation of physiological and physical models into computer simulations (i.e. in MATLAB)
• Cellular processes utilising oxygen and glucose for sustaining neuronal activity
• Neurochemical processes mediating the changes of neuronal activity with blood flow
• Understanding the link between computer simulations and brain function
• Interaction of magnetic fields (i.e. Radiofrequency pulses, gradients) with biological tissue
• MRI sequences to detect physiological changes
• Magnetic field strength and echo time dependency of fMRI signals
• Understanding of inversion algorithms (i.e. blind deconvolution, Kalman filtering, dynamic causal modelling), implementation them in computer simulations and applying them on experimental data


Content
Functional MRI is typically used to study human and animal brain function and is currently regarded as the most important non-invasive tool for cognitive neuroscience. However, fMRI does not report neuronal activity directly but via changes on the vascular level as neuronal activity changes the blood oxygenation and blood volume. These vascular changes affect the MRI signal as a) deoxygenated hemoglobin is paramagnetic and oxygenated hemoglobin diamagnetic and b) the intra- and extra-vascular proton density is determined by blood volume.

Thus, for the correct interpretation of fMRI signals, it is essential that the mediating steps from neuronal activity to vascular changes are revealed. In this module, all processes within the brain tissue affecting blood oxygenation and volume will be discussed: What is the relationship of neuronal activity and oxidative metabolism which decreases blood oxygenation? What are the mechanisms used by neurons to control cerebral blood flow and volume? Why are these physiological changes detectable by MRI? How is the content of neuronal processing modelled by neuronal networks in specific brain areas? How can these forward models be inverted to infer neuronal activity patterns from sparse experimental data?

This module will try to answer these questions in form of lectures, and in practical sessions in which they implement mathematical algorithms and apply them of acquired fMRI data.

Overview of tasks and lectures
There will be 10 lectures of 2 hours distributed over 5 days.
• Introduction into functional MRI
• Neuronal Basis of functional MRI
• Neuro-vascular and neuro-metabolic coupling
• Principles of functional MRI physics
• Neuronal network models I
• Neuronal network models II
• Inversion algorithms I
• Inversion algorithms II
• Dynamic causal modelling & Functional connectivity analysis
• Summary and Introduction of post-module assignments

Position within the programme
This is a unique module in this Master programme dealing with the chain of physiological and physical events giving rise to the fMRI signal. The knowledge of these processes is highly relevant for a correct interpretation of fMRI data. This module is complementary to the general modules dealing with MRI physics and data analysis basics and to the modules dealing with advanced analysis methods and applications. 


Teaching format

Structure
The module is a one week-long residential module consisting of 10 lectures of 2 hours. Each day, the students will in addition perform implementation of computer algorithms relevant to one the lecture topics guided by tutors. Furthermore, the residential part is combined with a preparatory reading phase and post-module marked assignments.

Grading
Passing the module requires an 85% attendance to the lectures and practical sessions, and a satisfactory completion of the practical sessions and the module assignments. The module assignments will be summarised by the students in a written form which will be evaluated by the module coordinator(s).


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