Jozef (Jeff) H. Duyn

Senior Investigator, Advanced MRI Section, Laboratory of Functional and Molecular Imaging

Division

Division of Intramural Research

Areas of Interest

Neuroimaging and Neuroscience

Contact

jeff.duyn@nih.gov

301-594-7305

Dr. Duyn received his M.Sc. and Ph.D. degrees in physics at the University of Delft, Holland where he was involved with the development of X-ray diffraction techniques, as well as the early development of magnetic resonance imaging (MRI). During his postdoctoral assignments at the University of California, San Francisco, and at NIH, his research focused on the study of human brain physiology, as measured by spectroscopic and functional MRI techniques. Dr. Duyn moved to NINDS in 2000.

Research Interests

In addition to providing structural information, MRI has the potential to non-invasively map physiologic parameters and function. Our research focuses on optimally exploiting this potential by investigating the mechanisms behind MRI contrast, exploring avenues to manipulate the contrast, and optimizing MRI data acquisition and analysis to achieve optimum sensitivity, resolution, reliability, and accuracy. Specific aims are the development of MRI techniques for the measurements of structural anatomy, tissue metabolism, tissue perfusion, and the spatial distribution of brain activity. Recent work has focused on high field MRI technology, the magnetic properties of brain tissue, and the study of spontaneous brain activity.

Advanced Magnetic Resonance Imaging (AMRI) Section

Part of the Laboratory of Functional and Molecular Imaging, Advanced MRI (AMRI) is a research laboratory at the Bethesda campus of the National Institutes of Health, as part of the NIH Intramural Research Program. Research in LFMI concerns the development of novel applications for the study of neurological disease through improvement of Magnetic Resonance Imaging (MRI) technology. Recent work has been in the fields of array detectors, high field technology, and functional imaging.

Mission

The mission of AMRI is to improve neuroimaging through basic technological development. The strategy is to develop new techniques for the acquisition and analysis of MRI images that provide various types anatomical and functional contrast. This involves the development of novel detectors for MR signal reception, the manipulation of image contrast through acquisition, image reconstruction, and image analysis techniques, and the combination of MRI with the acquisition of physiogical signals such as EEG.

History

The AMRI section, together with its host laboratory, the Laboratory of Functional and Molecular Imaging (LFMI), was formed in 2000 with the recruitment of Jeff Duyn into NINDS. Its research initially centered around development of novel MRI detector and receiver hardware and imaging techniques for anatomical and functional MRI of human brain at high field. This was first done on the early 3 T and 4 T scanners, and then on an early 7 T system. Currently, technology is being developed for a range of field strengths including 0.55 T, 1.5 T, 3 T, 7 T, and for one of the first human 11.7 T systems that is currently being (re-)installed at NIH. Since its early days, AMRI has collaborated with various clinical groups to evaluate novel technology, including the use of contrast agents to detect perfusion abnormalities in stroke (using so-called bolus arrival time maps), the use of magnetic susceptibility contrast to detect focal iron accumulation, vascular changes, and myelin loss in MS and ALS. Together with continuing technical development, a major current interest of AMRI is the application of novel techniques to study of joint variations in brain activity and autonomic activity associated with arousal changes during both wake and sleep.

AMRI Research Aims

Objectives

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.

References

JH Duyn, J Schenck
Contributions to magnetic susceptibility of brain tissue.
NMR Biomed 2017 30:
P van Gelderen, X Jiang, JH Duyn
Effects of magnetization transfer on T1 contrast in human brain white matter.
Neuroimage 2016 128:85-95
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
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
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
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
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
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
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
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
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
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
S Wharton, R Bowtell
Effects of white matter microstructure on phase and susceptibility maps.
Magn Reson Med 2015 73:1258-69
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
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
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
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
R Turner
How much cortex can a vein drain? Downstream dilution of activation-related cerebral blood oxygenation changes.
Neuroimage 2002 16:1062-7
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
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
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
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

Lab Techniques

Artifact removal from EEG-fMRI data
Software for the removal of MRI-induced artifacts from EEG data. Contact Jacco de Zwart to request a copy of this software.

^{Liu Z, de Zwart JA, van Gelderen P, Kuo LW, Duyn JH (2012)}
^{Statistical feature extraction for artifact removal from concurrent fMRI-EEG recordings.}
^{Neuroimage, 59:2073-87. PubMed ID:}^22036675

Three-component fitting of MGRE & multi-layer myelin exchange modeling
A software for three-component fitting of MGRE and multi-layer myelin exchange modeling. Contact Jacco de Zwart for more infomration..

^{P van Gelderen, JH Duyn}
^{White matter inter-compartmental water exchange rates determined from detailed modeling of the myelin sheath}
^{Magn Reson Med [under review]}

Facilities Available To AMRI

0.55 T human scanner (Siemens)
1.5 T human scanner (Siemens)
3 T human scanners (GE 750 and Siemens Prisma)
7 T human scanners (Siemens Terra and pre-Terra systems)
11.7 T head-only human scanner (Siemens)
Up to 128-channel MRI-compatible EEG (Brain Products)
275-channel MEG (CTF)

Studies, Active IRB Protocols and Resources

Human Studies
Several of the projects in AMRI make use of human subjects, primarily normal volunteers. This work is done in a manner that is consistent with all the rules and regulations of the NINDS Institutional Review Board (IRB) and NIH Clinical Center guidelines for use of human subjects. Subjects are used in support of MRI studies aimed at developing new anatomical, functional, and molecular MRI techniques. Volunteers are given a stipend for their participation.

Active IRB Protocols
00-N-0082 - Characterization of Brain Morphology and Activity Using Functional and Anatomical Contrast.
05-N-0179 - MRI Measurement of Brain Metabolism Across the Sleep-Wake Cycle.

Animal Studies
There are currently no active animal protocols in AMRI.

Other Imaging Resources

Lab Members

Name	Title
Peter van Gelderen, Ph.D.	Staff Scientist
Susan Guttman, B.S., R.T.	MR Technologist
Hadar Halivni	Postbac IRTA
Niki Lam	Postbac IRTA
Hendrik Mandelkow, Ph.D.	Special Volunteer
Pinar Ozbay, Ph.D.	Special Volunteer
Steve Newman	Volunteer Recruitment Coordinator
Dante Picchioni, Ph.D.	Contract Scientist
Yicun Wang, Ph.D.	Research Fellow
Nils Yang, Ph.D.	Research Fellow
Jacco de Zwart, Ph.D.	Staff Scientist

Lab Alumni

Name	Timeframe	Position After Departure from AMRI
Natalia Gudino	Feb 2013 - Dec 2018	Staff Scientist, LFMI, NINDS, NIH
Catie Chang	Sep 2011 - Aug 2018	Assistant Professor of Computer Science, Electrical Engineering, Computer Engineering & Biomedical Engineering Vanderbilt, Nashville, TN, USA
Erika Raven	Aug 2013 - Aug 2017	Postdoctoral Fellow, Cardiff University, UK
Yulin Chang	Jan 2016 - Mar 2017	Senior Scientist, Siemens Medical Solutions, USA
Xiao Liu	Sep 2011 - Aug 2016	Assistant Professor of Biomedical Engineering Pennsylvania State University, State College, PA
Xiaozhen Li	May 2013 - Nov 2014	Attending Physician, Dongzhimen Hospital, Beijing, China
Zhongming Liu	May 2009 - Aug 2013	Assistant Professor of Biomedical Engineering and Electrical & Computer Engineering, Purdue University
Brian (Bing) Yao	Aug 2006 - Dec 2012	Manager of Neuroimaging Center, Kessler Foundation
Karin Shmueli	Dec 2005 - Dec 2011	Lecturer in Magnetic Resonance Imaging, University College London, UK
Marta Bianciardi	Feb 2007 - Sep 2011	Assistant in Neuroscience / Instructor in Radiology, MGH / Harvard
Li-Wei Kuo	Apr 2010 - Aug 2011	Assistant Investigator, National Health Research Institutes, Taiwan
Molly Bright	Oct 2006 - Mar 2011	Postdoctoral Fellow, Cardiff University, UK
Jongho Lee	Oct 2007 - Oct 2010	Assistant Professor, Department of Radiology, University of Pennsylvania
Masaki Fukunaga	Apr 2003 - Mar 2010	Assistant Professor, Osaka University, Japan
Lei Qin	Jul 2006 - Feb 2009	Research Fellow, Brigham and Women's Hospital, Harvard
Silvina Horovitz	Feb 2004 - Jan 2008	Staff Scientist, Human Motor Control section, NINDS, NIH, MD, USA
Sebastien Roujol	Mar 2007 - Aug 2007	PhD Candidate, IMF, Univerisite Victor Segalen, Bordeaux, France
Martijn Jansma	Jun 2002 - Jun 2007	Research Fellow, Mood and Anxiety Branch, NIMH, NIH, MD, USA
Vicky Ikonomidou	Jun 2003 - May 2006	Research Fellow, Neuroimmunology Branch, NINDS, NIH, MD, USA
Renxin Chu	Dec 2001 - Jan 2005	U. Colorado, CO, USA
Roel Deckers	Apr 2004 - Aug 2004	PhD Candidate, IMF, Universite Victor Segalen, Bordeaux, France
Yuxi Pang	Nov 2001 - Jun 2002	Research Investigator, U. Michigan Ann Arbor, MI, USA
Martin Yongbi	Sep 1998 - Mar 2001	US Dept. of the Interior

Publications

Explore AMRI publications and presentations organized by year.

2023

Yang FN, Picchioni D, Duyn JH (2023)
The effect of sleep-corrected social jetlag on crystalized intelligence, school performance, and functional connectome in early adolescence.
medRxiv, PubMed ID: 37502864

Bilgic B, Costagli M, Chan KS, Duyn J, Langkammer C, Lee J, Li X, Liu C, Marques JP, Milovic C, Robinson SD, Schweser F, Shmueli K, Spincemaille P, Straub S, van Zijl P, Wang Y, Group IETPS (2023)
Recommended Implementation of Quantitative Susceptibility Mapping for Clinical Research in The Brain: A Consensus of the ISMRM Electro-Magnetic Tissue Properties Study Group.
ArXiv, PubMed ID: 37461418

Van Gelderen P, Li X, de Zwart JA, Beck ES, Okar SV, Huang Y, Lai K, Sulam J, van Zijl PCM, Reich DS, Duyn JH, Liu J (2023)
Effect of motion, cortical orientation and spatial resolution on quantitative imaging of cortical R2* and magnetic susceptibility at 0.3 mm in-plane resolution at 7 T.
Neuroimage, 270:119992. PubMed ID: 36858332

2022

Gu Y, Han F, Sainburg LE, Schade MM, Buxton OM, Duyn JH, Liu X (2022)
An orderly sequence of autonomic and neural events at transient arousal changes.
Neuroimage, 264:119720. PubMed ID: 36332366

Wang Y, van Gelderen P, de Zwart JA, Özbay PS, Mandelkow H, Picchioni D, Duyn JH (2022)
Cerebrovascular activity is a major factor in the cerebrospinal fluid flow dynamics.
Neuroimage, 258:119362. PubMed ID: 35688316

La Rosa F, Beck ES, Maranzano J, Todea RA, van Gelderen P, de Zwart JA, Luciano NJ, Duyn JH, Thiran JP, Granziera C, Reich DS, Sati P, Bach Cuadra M (2022)
Multiple sclerosis cortical lesion detection with deep learning at ultra-high-field MRI.
NMR Biomed, 35:e4730. PubMed ID: 35297114

Beck ES, Maranzano J, Luciano NJ, Parvathaneni P, Filippini S, Morrison M, Suto DJ, Wu T, van Gelderen P, de Zwart JA, Antel S, Fetco D, Ohayon J, Andrada F, Mina Y, Thomas C, Jacobson S, Duyn J, Cortese I, Narayanan S, Nair G, Sati P, Reich DS (2022)
Cortical lesion hotspots and association of subpial lesions with disability in multiple sclerosis.
Mult Scler, 28:1351-1363. PubMed ID: 35142571

Picchioni D, Özbay PS, Mandelkow H, de Zwart JA, Wang Y, van Gelderen P, Duyn JH (2022)
Autonomic arousals contribute to brain fluid pulsations during sleep.
Neuroimage, 249:118888. PubMed ID: 35017126

Ma Z, Reich DS, Dembling S, Duyn JH, Koretsky AP (2022)
Outlier detection in multimodal MRI identifies rare individual phenotypes among more than 15,000 brains.
Hum Brain Mapp, 43:1766-1782. PubMed ID: 34957633

2021

Liu J, Beck ES, Filippini S, van Gelderen P, de Zwart JA, Norato G, Sati P, Al-Louzi O, Kolb H, Donadieu M, Morrison M, Duyn JH, Reich DS (2021)
Navigator-Guided Motion and B0 Correction of T2*-Weighted Magnetic Resonance Imaging Improves Multiple Sclerosis Cortical Lesion Detection.
Invest Radiol, 56:409-416. PubMed ID: 34086012

de Zwart JA, van Gelderen P, Duyn JH (2021)
Sensitivity limitations of high-resolution perfusion-based human fMRI at 7 Tesla.
Magn Reson Imaging, 84:135-144. PubMed ID: 34624401

Wang Y, van Gelderen P, de Zwart JA, Campbell-Washburn AE, Duyn JH (2021)
FMRI based on transition-band balanced SSFP in comparison with EPI on a high-performance 0.55 T scanner.
Magn Reson Med, 85:3196-3210. PubMed ID: 33480108

Goodale SE, Ahmed N, Zhao C, de Zwart JA, Özbay PS, Picchioni D, Duyn J, Englot DJ, Morgan VL, Chang C (2021)
fMRI-based detection of alertness predicts behavioral response variability.
Elife, 10 PubMed ID: 33960930

2020

Liu J, van Gelderen P, de Zwart JA, Duyn JH (2020)
Reducing motion sensitivity in 3D high-resolution T2*-weighted MRI by navigator-based motion and nonlinear magnetic field correction.
Neuroimage, 206:116332. PubMed ID: 31689535

Duyn JH, Ozbay PS, Chang C, Picchioni D (2020)
Physiological changes in sleep that affect fMRI inference.
Curr Opin Behav Sci, 33:42-50. PubMed ID: 32613032

Van Gelderen P, Duyn JH (2020)
Background suppressed magnetization transfer MRI.
Magn Reson Med, 83:883-891. PubMed ID: 31502706

Wang Y, van Gelderen P, de Zwart JA, Duyn JH (2020)
B0-field dependence of MRI T1 relaxation in human brain.
Neuroimage, 213:116700. PubMed ID: 32145438

Presentations

2022

Joint Annual Meeting ISMRM-ESMRMB & ISMRT 31st Annual Meeting London, England, UK (07-12 May 2022)

2021

ISMRM & SMRT Annual Meeting & Exhibition (15-20 May 2021)
OHBM Annual Meeting (21-25 June 2021)

2020

ISMRM & SMRT Virtual Conference & Exhibition (08-14 August 2020)

Volunteer for Studies

Patients and normal volunteers studied in AMRI are enrolled in research protocols taking place at the clinical center of the NIH in Bethesda, Maryland. All human subject studies are conducted in conformance with the relevant IRB guidelines and NMR Facility safety regulations. If you are interested in volunteering for a study please consult the NIH Clinical Center's Volunteer Program and see our Research page.

Directions

If you are enrolled in a study and need directions to NIH NMR center research center, where the studies are performed, you may use the directions below.

Address
10 Center Dr.
Bldg. 10, Room B1D-728
Bethesda, MD 20892

Directions to the AMRI Office
Once inside building 10, AMRI is located in the B1 Level (Wing D) of the Clinical Center (Building 10). Take the Clinical Center main elevators to the B1 level and follow signs to the 'NMR Research Center'. After you enter NMR Research Center, walk straight ahead until you see a courtyard on your left. Immediately after this, turn left. Go through the oor at the end of the hallway and follow the hallway as it bends to the left. The LFMI office is on your right in room B1D-728.

How to Travel to National Institutes of Health
Refer to the NIH visitor information page. This page also contains a map of NIH campus.

Active IRB Protocols

00-N-0082 - Characterization of Brain Morphology and Activity Using Functional and Anatomical Contrast.

05-N-0179 - MRI Measurement of Brain Metabolism Across the Sleep-Wake Cycle.

If you would like to sign up as a volunteer for one of these protocols, please contact Susan Guttman or Steve Newman.

Jozef (Jeff) H. Duyn, Ph.D.

Research Interests

Advanced Magnetic Resonance Imaging (AMRI) Section

Mission

History

AMRI Research Aims

Objectives

Aim 1: Development of high field MRI technology

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

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

References

Lab Techniques

Facilities Available To AMRI

Studies, Active IRB Protocols and Resources

Lab Members

Lab Alumni

Publications

2023

2022

2021

2020

Archive

2019

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2016

2015

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Presentations

2022

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2020

Archive

2019

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Volunteer for Studies

Directions

Active IRB Protocols