Abstract
Functional MRI at 3T has become a workhorse for the neurosciences, e.g., neurology, psychology, and psychiatry, enabling non-invasive investigation of brain function and connectivity. However, BOLD-based fMRI is a rather indirect measure of brain function, confounded by physiology related signals, e.g., head or brain motion, brain pulsation, blood flow, intermixed with susceptibility differences close or distant to the region of neuronal activity. Even though a plethora of preprocessing strategies have been published to address these confounds, their efficiency is still under discussion. In particular, physiological signal fluctuations closely related to brain supply may mask BOLD signal changes related to “true” neuronal activation. Here we explore recent technical and methodological advancements aimed at disentangling the various components, employing fast multiband vs. standard EPI, in combination with fast temporal ICA. Our preliminary results indicate that fast (TR <0.5 s) scanning may help to identify and eliminate physiologic components, increasing tSNR and functional contrast. In addition, biological variability can be studied and task performance better correlated to other measures. This should increase specificity and reliability in fMRI studies. Furthermore, physiological signal changes during scanning may then be recognized as a source of information rather than a nuisance. As we are currently still undersampling the complexity of the brain, even at a rather coarse macroscopic level, we should be very cautious in the interpretation of neuroscientific findings, in particular when comparing different groups (e.g., age, sex, medication, pathology, etc.). From a technical point of view our goal should be to sample brain activity at layer specific resolution with low TR, covering as much of the brain as possible without violating SAR limits. We hope to stimulate discussion toward a better understanding and a more quantitative use of fMRI.
Highlights
Hampered by the inherently low sensitivity, caused by low energy difference in magnetic resonance imaging (MRI) spin transitions, and the low speed of data collection in 2D/3D MRI, increasing sensitivity was the prime focus for decades
Two major aspects presented here are the improved functional MRI (fMRI) data quality achieved with multi-band as compared to standard echo-planar imaging (EPI) sequences, as well as the identification of physiological components, with the potential to selectively remove them from the data
We would like to reemphasize that at a certain point, when TR is lower than T1 regional cerebral blood flow contributes stronger to EPImeasurements, which was separated from T2∗ (BOLD) contributions by the presented tICA analysis
Summary
Hampered by the inherently low sensitivity, caused by low energy difference in MRI spin transitions (ca.10−6eV), and the low speed of data collection in 2D/3D MRI, increasing sensitivity was the prime focus for decades. Substantially increasing image SNR via stronger static magnetic fields, and the sensitivity of multi-element phased-array coils and corresponding accelerated imaging acquisition techniques, did not yet increase time series SNR [3] nor, subsequently, contrast in functional MRI (fMRI). This is mainly due to non-white physiological noise, varying in different brain regions, and interacting with signal reduction due to susceptibility differences between brain tissue, cerebro-spinal fluid (CSF), air and bone as well as gross head motion. Will demonstrate below, that time has come to trade sensitivity for specificity in functional MRI of the human brain
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
