Functional Connectivity Analysis with fNIRS: Theory to Practice
Instructors: Rickson C. Mesquita, Androu Abdalmalak
About this course
The brain is a complex system with integrated functional capabilities that can be revealed by neuroimaging modalities. In particular, functional connectivity has been extensively employed in fNIRS studies to better understand the connection between different regions of the brain both at rest and during functional activation. Despite its simple experimental protocol, it is important to understand the intrinsic properties of the fNIRS time-series in order to correctly interpret functional connectivity in fNIRS. In this mini-course we will focus on the fundamental steps required to obtain reliable functional connectivity measures from fNIRS data. We will discuss key features of fNIRS signals, some of the common preprocessing steps and pitfalls when applying them. Participants will explore hands-on activities of open-source data, starting with basic approaches and progressing to seed-based correlation analysis. By the end of the course, participants will have a clear and practical understanding of how to compute and interpret basic connectivity measures in fNIRS.
What will you learn?
After participating in this course, participants will be able to:
- Understand the advantages and limitations of fNIRS functional connectivity protocols.
- Describe the intrinsic properties of the fNIRS signal and how they influence connectivity analysis
- Apply appropriate pre-processing for functional connectivity analysis in fNIRS data.
- Perform seed-based functional connectivity analysis in fNIRS data.
Course details
Course duration
3 hours
Prerequisites and/or other notes
This course is structured as a two-part series. This is part one, which aims to introduce the fundamentals of functional connectivity and preprocessing, including a hands-on walkthrough of a standard preprocessing pipeline. This session is designed to run approximately 3 hours.
Delivery plan
- The brain as a complex system: introduction to functional connectivity methods (30 min)
- Introduction to preprocessing pipelines for functional connectivity (60 min)
- Hands-on: preprocessing data for functional connectivity analysis (60 min)
- Hands-on: performing pairwise functional connectivity analysis (30 min)
Why should you enroll in this course?
Functional connectivity studies have gained interest by fNIRS users in the past few years. In the majority of cases, methods developed for fMRI data have been simply translated to fNIRS data without considering the intrinsic properties of the fNIRS time-series, which can lead to confusion and misinterpretation of functional connectivity maps acquired with fNIRS. The main goal of this mini-course is to provide users with a clear description of the advantages and pitfalls of fNIRS functional connectivity, and present solutions to overcome limitations of functional connectivity with fNIRS data with focused hands-on activities. The course is aimed at fNIRS users at all levels; basic MATLAB skills are needed to complete the hands-on exercises.