AMRI's current research is centered around the following three aims:

Aim 1: Development of high field MRI technology.

For almost 2 decades, AMRI has been at the forefront of developing technology and applications for higher field strength MRI, including 3 T and 7 T. High field development has enabled increased sensitivity, resolution, and novel tissue contrast and led to 7 T MRI now being adopted as a clinical platform. AMRI is continuing this development towards 11.7 T, in parallel with two other research sites in France and Korea.

The development of high field MRI is motivated by both basic scientific and clinical interest. A great deal about MRI contrast at 3 T has been learned from studies at 7 T, including the effects of cellular- and molecular-scale tissue structure on susceptibility-weighted MRI and the origin of magnetization transfer and relaxation, two basic contrast mechanisms in MRI [1,2]. Much interesting functional and anatomical detail occurs at millimeter and sub-millimeter scale, the size of cortical columns and layers. Such resolutions are currently at the limit of what is practical at 7 T. Therefore, modest resolution improvements are expected to reveal a wealth of new information expected to not only expanding basic (neuroscientific) knowledge, but also potentially clinically interesting for characterization of focal pathology, such as MR lesions, cortical dysplasia, and microbleeds secondary to brain trauma. For example, experimental MRI studies with extensive (8- hour long) signal averaging at 7 T have reached 0.2-0.4 mm resolutions for the study of brain morphology and demonstrated the importance of resolution improvement for accurate cortical delineation and thickness assessment [3,4,5]. While such scans are prohibitively long for clinical studies, this may be overcome at 11.7 T where the increased sensitivity may allow a four or more- fold scan time reduction.

One of the critical technologies at high field is transmission of the required radio-frequency (RF) electro-magnetic fields. Because of the exacerbated wavelength effects at high field, both the magnetic component of the electromagnetic RF field (needed for signal generation) as well as its electric component (leading to undesirable tissue heating) become more difficult to control. To address this, we plan together with scientists of the MRI Engineering Core, LFMI (EC) to further develop our on-coil amplifier technology (recently demonstrated at 7 T) for operation at 11.7 T. Also with EC, we plan to develop high density receive arrays to explore the limits of sensitivity and resolution.

Aim 2: Development of high resolution iron and myelin-weighted MRI

The MRI signal is typically a complex amalgam of a number of sources, whose relative contribution is strongly dependent on experimental details. Manipulating the relative contribution of these contrast sources to extract reproducible information about tissue composition can be done by dedicated acquisition techniques (or "pulse sequences"). Over the last decade, AMRI has spent much effort towards understanding how magnetic susceptibility contrast, a contrast that is particularly strong at high field, can be used to learn about tissue composition. We, and other researchers, found that main contrast contributors are iron, myelin and deoxyhemoglobin, and further demonstrated how tissue cellular and molecular structure affect contrast [6,7]. Because of its sensitivity to iron, susceptibility-weighted MRI may be uniquely capable of detecting iron accumulation in MS lesions [8,9], and may allow discerning between an active myelination process or demyelinated dead tissue [10].

One remaining difficulty with robust interpretation of SW contrast is distinguishing between the contributions of iron and myelin. As we proposed in 2017 [1], and as was very recently demonstrated [11], one may be able to distinguish between iron and myelin by comparing quantitative susceptibility maps (QSM [12]) and transverse relaxation (R2*) maps derived from the SW data. This is because both myelin and iron increase R2*, while their magnetic susceptibilities are of opposing polarity and thus counteract each other in QSM. However, this has limited accuracy due to a confounding dependency on white matter fiber orientation [13]. In this regard, independent measures of myelin content and fiber orientation may help disambiguation. We therefore plan to investigate how this may be done by the use of T1- and magnetization transfer (MT)-weighted methods, and fiber orientation information derived from diffusion tensor imaging, with specific focus on application at high field.

Aim 3: fMRI of brain physiology and function across arousal states

High field fMRI has the potential to map the units of functional specialization of the brain at the millimeter-level resolution of cortical columns and layers and as such allows a major step towards narrowing the gap with information from cellular circuit-level recordings. Dedicated studies with behavioral tasks at 7 T have shown early demonstrations of this ability in visual [14,15] and motor [16] systems and further improvements are expected with improved detectors [17] and with the transition to 11.7 T.

Nevertheless, several hurdles remain for fMRI to live up to this potential, including vascular blurring of the task-evoked neuronal activity [18], as well as unexplained neuronal and vascular variability that may be task evoked or occur spontaneously. For example, changes in heart rate, respiration, and blood pressure have all been tied to fMRI signal fluctuations [19,20,21], and these may occur spontaneously or be evoked by tasks. Similarly, variations in alertness and attention may affect the fMRI signal through a combination of neuronal and autonomic changes. Both brain- wide ("global"), and highly structured patterns in spontaneous fMRI activity have been widely reported [22], but as of yet remain only partly understood. To address this, AMRI over the years has performed and analyzed a range of experiments collecting combined electrophysiology and fMRI over a range of arousal states. This has recently developed into full blown overnight sleep studies using a variety of accessory measurements, including peripheral vascular tone, indicators of respiratory and cardiac cycles, and video monitoring of body movement. We plan to continue this work to ultimately be able to distinguish between autonomic and vascular sources to the fMRI signal on one hand, and the various possible neurogenic sources on the other.


  1. JH Duyn, J Schenck
    Contributions to magnetic susceptibility of brain tissue.
    NMR Biomed 2017 30:
  2. P van Gelderen, X Jiang, JH Duyn
    Effects of magnetization transfer on T1 contrast in human brain white matter.
    Neuroimage 2016 128:85-95
  3. F Lüsebrink, A Wollrab, O Speck
    Cortical thickness determination of the human brain using high resolution 3T and 7T MRI data.
    Neuroimage 2013 70:122-31
  4. D Stucht, KA Danishad, P Schulze, F Godenschweger, M Zaitsev, O Speck
    Highest Resolution In Vivo Human Brain MRI Using Prospective Motion Correction.
    PLoS One 2015 10:e0133921
  5. F Lüsebrink, A Sciarra, H Mattern, R Yakupov, O Speck
    Erratum: T<sub>1</sub>-weighted in vivo human whole brain MRI dataset with an ultrahigh isotropic resolution of 250??m.
    Sci Data 2017 4:170062
  6. J Lee, K Shmueli, M Fukunaga, P van Gelderen, H Merkle, AC Silva, JH Duyn
    Sensitivity of MRI resonance frequency to the orientation of brain tissue microstructure.
    Proc Natl Acad Sci U S A 2010 107:5130-5
  7. P Sati, P van Gelderen, AC Silva, DS Reich, H Merkle, JA de Zwart, JH Duyn
    Micro-compartment specific T2* relaxation in the brain.
    Neuroimage 2013 77:268-78
  8. F Bagnato, S Hametner, B Yao, P van Gelderen, H Merkle, FK Cantor, H Lassmann, JH Duyn
    Tracking iron in multiple sclerosis: a combined imaging and histopathological study at 7 Tesla.
    Brain 2011 134:3602-15
  9. B Yao, S Hametner, P van Gelderen, H Merkle, C Chen, H Lassmann, JH Duyn, F Bagnato
    7 Tesla magnetic resonance imaging to detect cortical pathology in multiple sclerosis.
    PLoS One 2014 9:e108863
  10. NJ Lee, SK Ha, P Sati, M Absinta, G Nair, NJ Luciano, EC Leibovitch, CC Yen, TA Rouault, AC Silva, S Jacobson, DS Reich
    Potential role of iron in repair of inflammatory demyelinating lesions.
    J Clin Invest 2019 129:4365-4376
  11. HG Shin, J Lee, YH Yun, SH Yoo, J Jang, SH Oh, Y Nam, S Jung, S Kim, M Fukunaga, W Kim, HJ Choi, J Lee
    ?-separation: Magnetic susceptibility source separation toward iron and myelin mapping in the brain.
    Neuroimage 2021 240:118371
  12. K Shmueli, JA de Zwart, P van Gelderen, TQ Li, SJ Dodd, JH Duyn
    Magnetic susceptibility mapping of brain tissue in vivo using MRI phase data.
    Magn Reson Med 2009 62:1510-22
  13. S Wharton, R Bowtell
    Effects of white matter microstructure on phase and susceptibility maps.
    Magn Reson Med 2015 73:1258-69
  14. RS Menon, S Ogawa, JP Strupp, K U?urbil
    Ocular dominance in human V1 demonstrated by functional magnetic resonance imaging.
    J Neurophysiol 1997 77:2780-7
  15. E Yacoub, A Shmuel, N Logothetis, K U?urbil
    Robust detection of ocular dominance columns in humans using Hahn Spin Echo BOLD functional MRI at 7 Tesla.
    Neuroimage 2007 37:1161-77
  16. L Huber, DA Handwerker, DC Jangraw, G Chen, A Hall, C Stüber, J Gonzalez-Castillo, D Ivanov, S Marrett, M Guidi, J Goense, BA Poser, PA Bandettini
    High-Resolution CBV-fMRI Allows Mapping of Laminar Activity and Connectivity of Cortical Input and Output in Human M1.
    Neuron 2017 96:1253-1263.e7
  17. B Guérin, JF Villena, AG Polimeridis, E Adalsteinsson, L Daniel, JK White, LL Wald
    The ultimate signal-to-noise ratio in realistic body models.
    Magn Reson Med 2017 78:1969-1980
  18. R Turner
    How much cortex can a vein drain? Downstream dilution of activation-related cerebral blood oxygenation changes.
    Neuroimage 2002 16:1062-7
  19. K Shmueli, P van Gelderen, JA de Zwart, SG Horovitz, M Fukunaga, JM Jansma, JH Duyn
    Low-frequency fluctuations in the cardiac rate as a source of variance in the resting-state fMRI BOLD signal.
    Neuroimage 2007 38:306-20
  20. RM Birn, MA Smith, TB Jones, PA Bandettini
    The respiration response function: the temporal dynamics of fMRI signal fluctuations related to changes in respiration.
    Neuroimage 2008 40:644-654
  21. R Wang, T Foniok, JI Wamsteeker, M Qiao, B Tomanek, RA Vivanco, UI Tuor
    Transient blood pressure changes affect the functional magnetic resonance imaging detection of cerebral activation.
    Neuroimage 2006 31:1-11
  22. RM Hutchison, T Womelsdorf, EA Allen, PA Bandettini, VD Calhoun, M Corbetta, S Della Penna, JH Duyn, GH Glover, J Gonzalez-Castillo, DA Handwerker, S Keilholz, V Kiviniemi, DA Leopold, F de Pasquale, O Sporns, M Walter, C Chang
    Dynamic functional connectivity: promise, issues, and interpretations.
    Neuroimage 2013 80:360-78

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