Resting State fMRI & Recent Advances
Marta Bianciardi1
1Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States

Synopsis

Keywords: Neuro: Brain connectivity

In this course, we first describe the major networks defined in humans based on resting state fMRI. We then present methods used for static and dynamic resting state fMRI connectivity analysis. Further, we provide an overview of resting state fMRI applications in neuroscience and in clinical studies, including recent advances in the field. Finally, we discuss current limitations of resting state fMRI methods and future directions. The target audience includes MRI scientists, neuroscientists, clinical researchers, neurologists and neurosurgeons interested in learning about methods, applications and recent advances of resting state fMRI in humans.

Target Audience

MRI scientists, neuroscientists, clinical researchers, neurologists and neurosurgeons interested in learning about methods, applications and recent advances of resting state fMRI in humans.

Objectives

Attendees will learn about:
- Major networks defined in humans based on resting state fMRI;
- Methods used for static and dynamic resting state fMRI connectivity analysis;
- Application of resting state fMRI in neuroscience and recent advances;
- Application of resting state fMRI in clinical studies and recent advances;
- Current limitations of resting state fMRI methods and recent advances.

Background

Despite the booming of resting state fMRI studies since seminal work in 1995, the ultimate method to compute resting state fMRI connectivity and to validate the identified networks has yet to be determined. Current limitations of resting state fMRI methods include the presence of physiological confounds, the polysynaptic nature of connectivity, the uncertainty in the definition of the ground truth, the within- and between-subject variability, and that these methods are computationally intense. Except for specific applications such as pre-surgical mapping, these limitations might have precluded a widespread use of resting state fMRI as a clinical diagnostic or prognostic tool. On the other hand, the ability to map functional networks in the human brain using an endogenous contrast mechanism with good spatial resolution has favored its extensive application in neuroscience and in clinical research studies.

Purpose

The purpose of this course is to present resting state fMRI analyses methods and their application to investigate functional connectivity in neuroscience and in clinical studies, including a discussion of opportunities, limitations, as well as recent advances in the field.

Outline

This course will cover:
- A brief historical perspective of the seminal study demonstrating the presence of resting state fMRI correlations [1];
- A review of major resting state networks and of the methods used for static and dynamic resting state fMRI connectivity analysis [2-5];
- Resting state fMRI in neuroscience: relationship to structural connectivity [5-9], genetics and neurotransmitter distribution [10-11], recent advances in subcortical resting state fMRI [7-8];
- Resting state fMRI in clinical studies: epilepsy [12-13], stroke [14], movement disorders [15], attention-deficit/hyperactivity disorder [16], coma [17-18];
- Current limitations of resting state fMRI methods [5, 19-21]: physiological confounds; indirect connectivity; definition of ground truth; reproducibility; methods standardization;
- Conclusions.

Acknowledgements

National Institute of Aging, National Institutes of Health R01 AG063982; Michael J Fox Foundation Award MJFF-022672.

References

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Proc. Intl. Soc. Mag. Reson. Med. 31 (2023)