Outline of the module
Functional MRI is a widely employed neuroimaging technique to investigate neuronal activity by means of changes in blood oxygenation and blood volume. The module “Advanced Design & Analysis in fMRI I” covers the main principles of experimental design and the analysis steps required to perform an fMRI study, analyse and interpret the data.
The module will start from the design of an fMRI experiment, discussing the available strategies to maximise experimental design efficiency, given the constraints posed by the indirect nature of the fMRI signal and all possible sources of noise and artefacts. Several commonly employed experimental designs (such as block designs, “slow” and “fast” and event-related designs) will be discussed in detail. The module will then address the issue related to the pre-processing and filtering steps, which are required to reduce the noise and prepare the fMRI time series to the statistical analysis. The module will then cover the statistical analyses usually employed to extract useful information from BOLD signal, with emphasis on parametric models (i.e. General Linear Model) for single-subject and group studies and on strategies to account for the “multiple comparison” problem. Throughout the module and in parallel with the theoretical lectures, the participants will design, measure and analyse an own fMRI experiment, thus having the opportunity to apply all the principles and techniques learned during the module.
At the end of this module, students should be able to answer the following questions:
• Which experimental design is more suited for which scientific question?
• Which are the strengths and weaknesses of block designs, as compared to event-related designs?
• Which are the main pre-processing steps performed on fMRI data?
• Which statistical analyses can be performed to relate measured fMRI data to the research question?
• Which techniques can be employed to account for the problem of multiple comparisons?
• How can different subjects be combined and compared for group studies?
Learning objectives
At the end of this module, students will have knowledge of:
• Theoretical and practical aspects on fMRI experimental design
• fMRI data preprocessing principles and strategies
• Statistical approaches employed to infer neural processing from fMRI data
• Strategies for dealing with the “multiple comparison” issue in fMRI
• Theoretical and practical aspects related to group studies.
Content
Thanks to its high spatial resolution and its non-invasiveness, functional MRI is employed in a large amount of neuroscientific studies that investigate brain functions in healthy subjects as well as in patients. ,
The Blood Oxygen Level Dependent (BOLD) signal - which is typically measured with fMRI - has specific spatio-temporal properties that need to be accounted for, when designing and analysing an fMRI experiment. In this module, all the steps that are needed to perform an fMRI investigation will be discussed: which is the most efficient experimental design, given the properties of the BOLD signal? Which are the pre-processing steps that need to be performed to reduce optimally the effects of noise on BOLD signal? Which are the statistical methods that can be employed to relate fMRI signal to the research question? Which are the strategies to account for the large amount of statistical tests performed (multiple comparison problem)? Which are the statistical analyses that can be employed to perform a group study?
This module will answer these questions in form of lectures, and in practical sessions in which the students will design an own fMRI study and conduct all the analyses needed to answer the research question behind the experiment.
Overview of tasks and lectures
There will be 10 lectures of 2 hours distributed over 5 days.
• Module overview and fMRI experimental design I
• fMRI experimental design II
• fMRI data preprocessing
• Statistical analysis of fMRI data I
• Statistical analysis of fMRI data II
• Event-related designs and deconvolution
• Strategies for multiple comparison correction
• Strategies for normalisation and statistics in group studies I
• Strategies for normalisation and statistics in group studies II
• Module summary + questions/answers
Position within the programme
This is a unique module in this Master programme dealing with the design principles and analyses steps employed in fMRI studies. The knowledge of these principles and steps is highly relevant for a correct design of fMRI data and for a correct interpretation of the results. 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. In addition, the students will design an fMRI experiment, collect fMRI data, and analyse the data under the guidance of 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).