Synopsis
Whole-brain fMRI data
can now be acquired at high temporal resolution – on timescales of hundreds of
milliseconds. These ‘fast fMRI’ approaches have the potential to reveal new
information about brain function. Both acquisition and analysis techniques need
to be adapted for fast fMRI in order to exploit its full potential for
neuroscience. This lecture will provide an overview of techniques for fast fMRI,
how to design fast fMRI studies, and how to model and analyze fast fMRI data.
Finally, we will discuss the advantages and limitations of fast fMRI, and
highlight potential confounds in interpreting fast fMRI data.
Target Audience
Researchers
interested in using new techniques for accelerated fMRI to study brain
function, and MR physicists and engineers interested in the applications and
limitations of fast imaging techniques for neuroscience. Introduction
Whole-brain
fMRI data can now be acquired at high temporal resolution – on timescales of
hundreds of milliseconds. These approaches have the potential to reveal new
information about brain function. Both the acquisition and analysis of fMRI
data need to be adapted for fast fMRI in order to exploit its full potential
for neuroscience. In this lecture, we will provide an overview of techniques for
fast fMRI. We will discuss how to model and analyze fast fMRI data, and how the
properties of both hemodynamic and neural signals contribute to the data
acquired in fast fMRI studies. We will include a focus on how different signal
and noise sources contribute to fast fMRI data and approaches for
distinguishing these signals in the analysis. Finally, we will discuss the
limitations and advantages of fast fMRI. We will discuss which types of neural
signals can and cannot be detected with fast fMRI, and highlight potential
confounds in interpreting fast fMRI data.Outline
This
lecture will discuss:
·
An
overview of multiband acquisition, as well brief discussion of other techniques
for fast acquisition (e.g. MR encephalography; limited slice prescriptions)
·
The
temporal properties of the hemodynamic response, and its consequences for
signal properties of fast fMRI data: how fast are the underlying signals we
measure?
·
The
contributions of neural, physiological and thermal noise signals to fast fMRI
data
·
Other
signals detected in fast fMRI: inflow, eye movements, pulsations, multiband-related
artifacts
·
Spatial
variability of the temporal properties of the fMRI response: across brain
regions and across voxels with varying vascular anatomy
·
Analysis
considerations for fast fMRI data: how physiological noise correction and
autocorrelation affect statistical inferences
·
Applications
of fast fMRI for resting state studies: how to design the acquisition and
analysis
·
Applications
of fast fMRI for task-based fMRI studies: how to design the experimental
paradigm and analysis
·
The
advantages and limitations of fast fMRI: what new information can we extract
about neural activity, and what confounds to be cautious of in interpreting
these data
·
The
future possibilities for fast fMRI: what are the ultimate temporal limits of
fast fMRI at higher field strengths and higher spatial resolutions
Outcomes
Attendees will learn techniques
for acquiring and analyzing accelerated fMRI data, and their potential
applications in imaging the brain. They will be able to identify how analysis
techniques should be updated for fast fMRI studies, and to design studies that
take advantage of these methods, both in resting-state and task paradigms. They
will become familiar with both the limitations and advantages of fast fMRI, and
become equipped to use these approaches and evaluate their use in other
studies.Discussion
The fast
timescale of fMRI could potentially be very useful for advancing human
neuroscience, as it provides the only noninvasive technique to track
whole-brain dynamics over timescales of hundreds of milliseconds. However,
these signals are small, noisy, and complicated by the presence of
physiological and other noise sources. This lecture aims to provide attendees
with the essential information for designing, analyzing, and interpreting fast
fMRI studies.
Acknowledgements
No acknowledgement found.References
No reference found.