Nikos Efthimiou is a non-clinical researcher at the Athinoula A. Martinos Center for Biomedical Research with more than ten years of experience in Medical Imaging, focused on Positron Emission Tomography. Nikos’ expertise spans detector technologies such as Silicon Photomultipliers, front-end electronics, system and detector modeling, statistical image reconstruction, absolute quantification, motion, and scatter correction.
Thanks to his interdisciplinary background, he has a successful record of accomplishments in academia. In his current position, Nikos investigates synergistic motion and attenuation correction in PET/MR scanners. Also, has developed energy-based scatter correction algorithms for Long Axial FOV PET scanners. Also, he has explored other emerging technological challenges, such as BGO-Cherenkov detectors for PET scanners. Nikos has lived in three countries and speaks English and Greek. His colleagues describe him as analytical, thorough, committed, and hard-working.

Education

PhD in Medical Physics, University of Patras

Select Publications

1. N. Efthimiou, J.S. Karp, S. Surti, “Data-driven, Energy-based method for estimation of Scattered events in Positron Emission Tomography”, Phys. Med. Biol 67 095010.
2. D.P. Watts, J. Bordes, J.R. Brown, A. Cherlin, R. Newton, J. Allison, M. Bashkanov, N. Efthimiou, N.A. Zachariou, “Photon quantum entanglement in the MeV regime and its application in PET imaging”, Nat Commun 12, 2646 (2021).
3. N. Efthimiou, N. Kratochwil, S. Gundacker, A. Polesel, M. Salomoni, E. Auffray, and M. Pizzichemi, “TOF-PET image reconstruction with multiple timing kernels applied on Cherenkov radiation in BGO”, IEEE TRPMS vol. 5, no. 5, pp. 703-711.

Highlights

* 2019 EMIM Poster Award “Monte Carlo simulation of a Total Body PET scanner based on the PENN PET”, Novel Nuclear Medicine technologies session
* 2017 The Allam Lecture First place: Oral presentation Award for “Benefits on Positron Emission Tomography from Ultra-Fast Time-of-Flight detectors.”
* 2008 State Scholarships Foundation’s (ΙΚΥ) scholarship for postgraduate studies on Telecommunication applications applied to Medicine.
* Member of the IEEE Nuclear and Plasma Sciences Society
* Developer at SIRF, the Collaborative Computational Platform for Synergistic Reconstruction for PET/MR
* Developed and maintainer of STIR: PET image reconstruction toolkit

Associated Labs

The Caravan Lab,
Catana Group

Dr. Maria Hakonen is an Instructor (Research Faculty) at Massachusetts General Hospital (MGH) and Harvard Medical School. She has extensive experience studying human brain function using 3T/7T fMRI, MEG, and EEG. She is specifically interested in individual differences in brain functional networks and how these differences relate to individual characteristics in both health and disease.

Her recent work has centered on mapping the functional connectivity of the auditory cortex. In her K99/R00 project, she investigates whether tinnitus can be classified into subtypes based on brain network patterns. In addition, she is working on a project exploring the relationship between age-related hearing loss and Alzheimer’s disease using advanced functional network analyses.

Education

PhD in Biomedical Engineering, Aalto University, Finland

Select Publications

Hakonen, M., Dahmani, L., Blazejewska, A., Cui, W., Kotlarz, P., Lankinen, K., Li, M., Polimeni, J., Ren, J., Turpin, T., Wang, D., Liu, H., Ahveninen J. (2025). Individual connectivity-based parcellations reflect functional properties of human auditory cortex. Imaging Neuroscience.

Hakonen, M., May, P. J., Jääskeläinen, I. P., Jokinen, E., Sams, M. & Tiitinen, H. (2017). Predictive processing increases intelligibility of acoustically distorted speech: Behavioral and neural correlates. Brain and Behavior. 7.9.

Hakonen, M., Nurmi, T., Vallinoja, J., Jaatela, J., & Piitulainen, H. (2022). More comprehensive proprioceptive stimulation of the hand amplifies its cortical processing. Journal of neurophysiology, 128(3), 568-581.

Highlights

NIH Pathway to Independence Award (K99/R00)

Dr. Yohan Jun’s research focuses on developing novel MR acquisition and reconstruction techniques using MR physics and machine/deep-learning-based algorithms to accelerate MRI scans while achieving high-fidelity images. He works on the following research topics:

i. Rapid high-resolution quantitative imaging: Zero-shot self-supervised learning combined with subspace reconstruction technique (Zero-DeepSub) enables the acquisition of quantitative T1, T2, and proton density maps with high-fidelity using 3D-QALAS sequence. The self-supervised-learning-based mapping technique (SSL-QALAS) can also accelerate the quantitative mapping process without any external dataset or explicit dictionary.

ii. Highly accelerated distortion-free diffusion imaging: Phase Reversed Interleaved Multi-Echo acquisition (PRIME) enables distortion-free diffusion MRI by inserting an additional echo without prolonging TR, when generalized slice dithered enhanced resolution (gSlider) RF encoding is used for volumetric acquisition.

iii. Acceleration of structural MRI: Deep model-based MR image reconstruction algorithms (Joint-ICNet, DPI-net), which combine MR physical and deep-learning models, allow fast MRI up to 8-fold for TOF MRA, T1/T2-weighted, FLAIR, and post-contrast imaging.

iv. Automatic diagnosis of brain disorders: Artificial intelligence algorithms allow us to support the diagnosis of brain disorders, including brain metastases, meningioma, and glioblastoma, by using deep-learning-based diagnosis algorithms for automatic detection, segmentation, and grading.

Education

PhD in Electrical and Electronic Engineering, Yonsei University, South Korea

Select Publications

1. Jun, Y., Arefeen, Y., Cho, J., Fujita, S., Wang, X., Grant, P.E., Gagoski, B., Jaimes, C., Gee, M.S. and Bilgic, B., 2024. Zero‐DeepSub: Zero‐shot deep subspace reconstruction for rapid multiparametric quantitative MRI using 3D‐QALAS. Magnetic Resonance in Medicine, 91(6), pp.2459-2482.

2. Jun, Y., Cho, J., Wang, X., Gee, M., Grant, P.E., Bilgic, B. and Gagoski, B., 2023. SSL‐QALAS: Self‐Supervised Learning for rapid multiparameter estimation in quantitative MRI using 3D‐QALAS. Magnetic Resonance in Medicine, 90(5), pp.2019-2032.

3. Jun, Y., Shin, H., Eo, T., Kim, T. and Hwang, D., 2021. Deep model-based magnetic resonance parameter mapping network (DOPAMINE) for fast T1 mapping using variable flip angle method. Medical Image Analysis, 70, p.102017.

Highlights

2024 – ISMRM Junior Fellow

2024 – NIBIB R21 Trailblazer Award

2017-2024 – ISMRM 4 Summa Cum Laude & 2 Magna Cum Laude Merit Awards

Since joining the Department of Radiology at Massachusetts General Hospital in 2019, Teppei Matsubara has worked under Dr. Steven Stufflebeam at the Martinos Center, where he applies his expertise as a board-certified neurosurgeon and epileptologist to clinical neuroimaging, particularly with MEG and MRI. He has played a key role in diagnosing epilepsy, assessing approximately 100 patients annually, while also advancing research on neurophysiological functions in metabolic disorders, specifically studying the effects of elevated GABA levels on cognitive functions. His research, supported by grants from the Japan Society for the Promotion of Science and the Nakatani Foundation, aims to identify neurophysiological biomarkers and enhance imaging protocols. Teppei is also dedicated to training emerging researchers in MEG and MRI, co-founding YES-Japan, an ILAE-affiliated network to support young epilepsy researchers, and is committed to expanding his collaborative network to advance neurological sciences.

Education

MD, PhD

Select Publications

Matsubara T, Khan S, Sundaram P, Stufflebeam S, Aygun D, Dibacco M, Roullet JB, Pearl P, Okada Y: Delays in latencies of median-nerve evoked magnetic fields in patitents with succinic semialdehyde dehydrogenase deficiency. Clin Neurophysiol. 2024 161:52–8.

Matsubara T, Ahlfors SP, Mima T, Hagiwara K, Shigeto H, Tobimatsu S, Goto Y, Stufflebeam S. Bilateral representation of sensorimotor responses in benign adult familial myoclonus epilepsy: An MEG study. Front Neurol. 2021 Oct 26;12:759866.

Matsubara T, Hironaga N, Uehara T, Chatani H, Tobimatsu S, Kishida K. A novel method for extracting interictal epileptiform discharges in multi-channel MEG: Use of fractional type of blind source separation. Clin Neurophysiol. 2020 Feb;131(2):425–36.

Highlights

Overseas Research Fellowship for Young Scientists, Japan Society for the Promotion of Science (2022-2024)

The Nakatani Foundation for advancement of measuring technologies in biomedical engineering (2019-2022)

Research Fellowship for Young Scientists, Japan Society for the Promotion of Science (2020-2022)

Jian (Andrew) Li is an Instructor at the A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School. His research interests lie in the application of statistical signal and image processing and machine learning theory to modeling and analysis of neuroimaging data. Currently, he focuses on the development of computational methods for functional brain mapping and functional registration.

Education

Ph.D. in Electrical Engineering, University of Southern California

Select Publications

Li, J., Tuckute, G., Fedorenko, E., Edlow, B.L., Dalca, A.V. and Fischl, B., 2024. JOSA: Joint surface-based registration and atlas construction of brain geometry and function. Medical Image Analysis, 98, p.103292.

Li, J., Liu, Y., Wisnowski, J.L. and Leahy, R.M., 2023. Identification of overlapping and interacting networks reveals intrinsic spatiotemporal organization of the human brain. Neuroimage, 270, p.119944.

Li, J., Curley, W.H., Guerin, B., Dougherty, D.D., Dalca, A.V., Fischl, B., Horn, A. and Edlow, B.L., 2021. Mapping the subcortical connectivity of the human default mode network. Neuroimage, 245, p.118758.

Highlights

2021: Highlight, Poster Playlist, Organization for Human Brain Mapping

2019: Fellow, American Epilepsy Society

2019: Runner-up, Image Processing Best Paper Award, SPIE Medical Imaging

Websites

Laboratory for NeuroImaging of Coma and Consciousness

Jian (Andrew) Li

Dr. Zhou has over 10 years of experience in neuroscience and neuroimaging, utilizing advanced magnetic resonance imaging (MRI) and innovative neuro-techniques for translational studies in both animal and human brains. Early in her career, she investigated the degenerative brain functions related to cognitive impairment in Alzheimer’s disease and type 2 diabetes patients using high-field MRI. During her Ph.D. training under Prof. Perry Bartlett at the Queensland Brain Institute, Dr. Zhou focused on understanding the regulatory mechanisms behind the cognitive benefits of exercise in combating dementia and aging. Currently, at the Martinos Center for Biomedical Imaging, she is further developing novel MRI methodologies to study the mechanistic regulation of brain function in aging and neurodegeneration, collaborating with Dr. Xin Yu to optimize multimodal fMRI platforms, particularly focusing on single-vessel fMRI and astrocytic Ca2+ signaling in models of aging and degenerative diseases.

Education

PhD, University of Queensland

Select Publications

• Zhou XA, Zhang j, Chen Y, Ma T, Wang Y, Wang J, Zhang Z (2014). Aggravated cognitive and brain functional impairment in mild cognitive impairment patients with type 2 diabetes: a resting-state functional MRI study. Journal of Alzheimer’s Disease 41 (3), 925-935. PMID: 24705547
• Zhou XA, Blackmore DG, Zhuo J, Nasrallah FA, To XV, Kurniawan ND, Carlisle A, Vien KY, Chuang KH, Jiang T, Bartlett PF (2021). iScience, 103450. PMCID: PMC8633984
• Zhou XA, Jiang Y, Man W & Yu X (2023). Multimodal methods to help interpret resting-state fMRI. Advances in Resting-state Functional MRI: Methods, Interpretation, and Applications. Book chapter, paperback ISBN: 9780323916882

Highlights

AARFD Grant, Alzheimer’s Association
Summa Cun Laude Merit Award, ISMRM, 2024
Young Investigator Award, BBRF, 2024

Website

Translational Neuroimaging and Neural Control Lab

Dr. Coto Hernandez is an instructor at Harvard Medical School and Massachusetts General Hospital. Throughout his career, he has developed multiple hardware and software methods able to enhance effective spatial resolution and imaging depth and achieve label-free imaging.

Education

PhD

Select Publications

1. I. Coto Hernández, M. Castello, L. Lanzanò, M. d’Amora, P. Bianchini, A. Diaspro and G. Vicidomini. (2016) Two-Photon Excitation STED Microscopy with Time-Gated Detection. Sci Rep, 6, 19419.

2. L. Rishøj*, I. Coto Hernández *, N. Jowett, S. Ramachandran. (2022) Multiharmonic Imaging of Human Peripheral Nerves using a 1300 nm Ultrafast Fiber Laser. J. Biomed. Opt. 27(5), 056501.

3. I. Coto Hernández, S. Mohan, S. Minderler, N. Jowett. (2022) Super-Resolved Fluorescence Imaging of Peripheral Nerve.” Sci Rep 12, 12450. This article was on the Top 100 Neuroscience papers published in 2022

Highlights

2023: Mentored Quantitative Research Career Development Award (K25)

I am an Instructor in Radiology with expertise in magnetic resonance imaging (MRI) and positron emission tomography (PET). My PhD focused on using structural, diffusion, and functional MRI to study cognitive functions and related neuroanatomy in very preterm born adults. I completed my postdoctoral training at the Martinos Center where I was trained in PET. My research interest is in using neuroimaging to better understand the structure and function of the of the brain and how alterations lead to behavioral differences in psychiatric disorders, with a focus on autism spectrum disorder (ASD). My efforts towards this goal include the first investigations of in vivo neuroepigenetics in adults with ASD and bipolar disorder. In the long term, I hope my research can contribute to improving the quality of life of individuals with psychiatric disorders.

Education

PhD in Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King’s College London

Select Publications

1. Tseng CJ, McDougle CJ, Hooker JM, Zürcher NR. (2022). Epigenetics of Autism Spectrum Disorder: Histone deacetylases. Biological Psychiatry 91(11):922-933.

2. Tseng CJ*, Gilbert TM*, Catanese MC, Hightower BG, Peters AT, Parmar AJ, Kim M, Wang C, Roffman JL, Brown HE, Perlis RH, Zürcher NR, Hooker JM. (2020). In Vivo Human Brain Expression of Histone Deacetylases in Bipolar Disorder. Translational Psychiatry 10(1):224.

3. Zürcher NR, Loggia ML, Mullett JE, Tseng C, Bhanot A, Richey L, Hightower BG, Wu C, Parmar AJ, Butterfield RI, Dubois JM, Chonde DB, Izquierdo-Garcia D, Wey HY, Catana C, Hadjikhani N, McDougle CJ, Hooker JM. (2021). [11C]PBR28 MR-PET imaging reveals lower regional brain expression of translocator protein (TSPO) in young adult males with autism spectrum disorder. Molecular Psychiatry 26: 1659–1669.

Highlights

Certificate of Merit, MGH 8th Annual Radiology Research Celebration Poster Session, 2019

Dr. Jas completed his PhD from Telecom ParisTech. His thesis focused on automating MEG/EEG analysis pipelines. He is a proponent of open and reproducible science. He has been a key contributor to several open source
neuroimaging tools: most notably MNE-Python, MNE-BIDS, and HNN-core. He developed Autoreject, a tool for automatic annotation and repair of artifactual MEG/EEG data.

Currently, he is focusing on the development of next-generation MEG using optically pumped magnetometers(OPMs) and their application to new neuroscience problems.

Education

PhD in Image and Signal Processing, Télécom ParisTech

Select Publications

1. Jas, M., Engemann, D. A., Bekhti, Y., Raimondo, F., & Gramfort, A (2017). Autoreject: Automated artifact rejection for MEG and EEG data. NeuroImage, 159, 417-429.

2. Jas M, Thorpe R, Tolley N, Bailey C, Brandt S, Caldwell B, Cheng H, Daniels D, Pujol CF, Khalil M, Kanekar S, Kohl C, Kolozsvári O, Lankinen K, Loi K, Neymotin S, Partani R, Pelah M, Rockhill A, Sherif M, Hamalainen M, & Jones S (2023). HNN-core: a Python software for cellular and circuit-level interpretation of human MEG/EEG. Journal of Open Source Software, 8(92): 5848.

3. Jas, M., Larson, E., Engemann, D. A., Leppäkangas, J., Taulu, S., Hämäläinen, M., & Gramfort, A. (2018). A reproducible MEG/EEG group study with the MNE software: recommendations, quality assessments, and good
practices. Frontiers in neuroscience, 12, 530.

Highlights

2018: MILA best poster award (Montreal AI and Neuroscience conference)
2023: Student award at Brain and Human Modeling Conference

Dr. Jiang’s research focuses on multi-modal fMRI brain imaging technology in rodent models. He is developing a novel multichannel fiber-optic mediated extracellular glutamate and intracellular calcium recording with high-filed MRI to study different brain states. Dr. Jiang’s work also includes developing novel single-vessel fMRI methods and investigating the neurovascular dynamic changes underlying coma induction and reemergence in rodent models. He is now on the faculty at the Martinos Center and a member of the Translational Neuroimaging and Neural Control Laboratory

Education

Education: PhD , Technical University of Munich, 2017

Select Publications

Jiang, Y., Pais‐Roldán, P., Pohmann, R., & Yu, X. (2024). High Spatiotemporal Resolution Radial Encoding Single‐Vessel fMRI. Advanced Science, 2309218.

Zeng H, Jiang Y.#, Hammer S., Yu. X. (2022) Awake mouse fMRI and pupillary recordings in the ultra-high magnetic field. Frontiers in Neuroscience, p.1028.

Chen X.*, Jiang Y.*, Choi S., Pohmann R., Scheffler K., et al. (2021) Assessment of single-vessel cerebral blood velocity by phase contrast fMRI. PLOS Biology, 19(9): e3000923

Highlights

2023 Heitman Young Investigator Career Development Award.
Magna Cum Laude Merit Award, ISMRM 2023
Summa Cum Laude Merit Award, ISMRM 2018

Dr. Sclocco has a background in bioengineering and signal processing, with specific training in non-invasive neuroimaging (e.g., fMRI, EEG) and peripheral autonomic data analyses. Since the beginning of her career, she have been interested in the interactions between the central and peripheral autonomic nervous systems. Thus, she built her expertise in autonomic neuroimaging, combining fMRI with peripheral measurements (e.g., heart rate variability, skin conductance), in order to better understand the central autonomic network – i.e., the brain circuitry controlling and responding to autonomic modulation. During her postdoctorate training, she also gained expertise in applying the techniques above to investigate potential mechanisms supporting autonomic-based electrical transcutaneous neuromodulation – i.e., respiratory-gated transcutaneous vagus nerve stimulation (tVNS), specifically using ultrahigh- and high-field fMRI to assess response in autonomic brainstem nuclei.

Recently, she has begun to explore the brain-gut axis, with new projects combining brain and stomach imaging to assess the effects of tVNS on gastric function. She has started developing an analysis pipeline for 4D gastric MRI data that allows the evaluation of multiple aspects of gastric function (e.g., emptying, motility) with a single, non-invasive test.

Education

PhD in Bioengineering, Politecnico di Milano, Italy

Select Publications

1. Sclocco R, Beissner F, Desbordes G, Polimeni JR, Wald LL, Kettner NW, Kim J, Garcia RG, Renvall V, Bianchi AM, Cerutti S, Napadow V, Barbieri R. Neuroimaging brainstem circuitry supporting cardiovagal response to pain: a combined heart rate variability/ultrahigh-field (7 T) functional magnetic resonance imaging study. Philos Trans A Math Phys Eng Sci. 2016 May 13;374(2067):20150189. doi: 10.1098/rsta.2015.0189. PMID: 27044996; PMCID: PMC4822448.

2. Sclocco R, Garcia RG, Kettner NW, Isenburg K, Fisher HP, Hubbard CS, Ay I, Polimeni JR, Goldstein J, Makris N, Toschi N, Barbieri R, Napadow V. The influence of respiration on brainstem and cardiovagal response to auricular vagus nerve stimulation: A multimodal ultrahigh-field (7T) fMRI study. Brain Stimul. 2019 Jul-Aug;12(4):911-921. doi: 10.1016/j.brs.2019.02.003. Epub 2019 Feb 10. PMID: 30803865; PMCID: PMC6592731.

3. Sclocco R, Garcia RG, Kettner NW, Fisher HP, Isenburg K, Makarovsky M, Stowell JA, Goldstein J, Barbieri R, Napadow V. Stimulus frequency modulates brainstem response to respiratory-gated transcutaneous auricular vagus nerve stimulation. Brain Stimul. 2020 Jul-Aug;13(4):970-978. doi: 10.1016/j.brs.2020.03.011. Epub 2020 Mar 27. PMID: 32380448.

Highlights

2019: Young Investigator Forum, American Neurogastroenterology and Motility Society

2019: Poster of Distinction, American Gastroenterological Association

2016: Abstract Travel Award, National Science Foundation

Websites

Napadow Lab
Center for Integrative Pain Neuroimaging (CIPNi)

I have a broad background in neuroimaging, with specific training and expertise in analyzing and visualization of multi-modality neuroimaging datasets. I received my Ph.D. degree in machine learning and games theory from Bar-Ilan University in 2014, and in 2015 I started my position as a research fellow in the Athinoula A. Martinos Center for Biomedical Imaging, funded by the TRANSFORM-DBS program, which concluded in May 2019.

TRANSFORM-DBS (Transdiagnostic Repair of Affective Networks by Systematic, Function-Oriented, Real-time Modeling, and Deep Brain Stimulation) was a 5-year program sponsored by the Defense Advanced Research Projects Agency (DARPA). In my position, I had been responsible for building tools and algorithms for the group and visualize and analyze the highly complex collected datasets. For doing so, I had to collaborate with all the different labs and personal that are part of this project, deploy and install my tools in different environments and for different types of users, collect their feedback and suggestions to be able to improve my tools and algorithms.

As the leading developer of the multi-modality analysis and visualization tool (mmvt.mgh.harvard.edu), I laid the groundwork for developing a unique interactive platform to visualize and analyze highly complex multi-modalities neuroimaging datasets (e.g., EEG, MEG, fMRI, PET, and invasive electrodes). My research focuses mainly on developing new algorithms and analyzing epileptic activity using EEG, MEG, and invasive electrodes datasets based on source distribution, frequencies, and connectivity.

Most recently, I initiated a pilot with the director of functional neurosurgery at MGH, for using MMVT for analyzing new patients’ multi-modal datasets and preparing epileptic cases for the surgical planning session. By synergetic integrating the acquired multi-modal datasets, I will assist in the surgical planning sessions. I have also initiated such an initiative with the epilepsy centers in Boston Children’s Hospital and Texas Children’s Hospital.

Education

PhD in Neuroscience at Bar-Ilan University (Israel)

Selected Publications

Felsenstein O, Peled N*, Hahn E, et al. Multi-Modal Neuroimaging Analysis and Visualization Tool (MMVT). arXiv preprint arXiv:191210079. Published online 2019.

Peled N, Kraus S. A study of computational and human strategies in revelation games. Autonomous Agents and Multi-Agent Systems. 2015;29(1):73–97

Keren N, Peled N, Korngreen A. Constraining compartmental models using multiple voltage recordings and genetic algorithms. Journal of neurophysiology. Published online 2005

Highlights

Systems and Methods for Multi-Modal Bioimaging Data Integration

U.S. Patent Application No. 62/941,305

Dr. Chan joined the Athinoula A. Martinos Center for Biomedical Imaging at MGH in 2010 as an instructor.  Her current research focuses on imaging of cerebrovascular responses using ultrasound and MRI. She uses natural breathing/gaseous challenge to measure cerebrovascular responses in healthy subjects, patients with episodic migraine, traumatic brain injury, Huntington’s disease, atrial fibrillation and chronic fatigue syndrome.  She has developed a robust physiological model for the assessment of cerebrovascular reactivity under brief breath hold challenge.  Her model has been tested on patients to localize subtle cerebrovascular changes for disease diagnosis and monitoring of disease progression.

Education

PhD in Radiography/Ultrasound, Hong Kong Polytechnic University

Select Publications

Chan ST, Brook F, Ahuja A, Brown B, Metreweli C. Relationship of thyroid blood flow to reproductive events in normal Chinese females. Ultrasound Med Biol. 1999 Feb;25(2):233-40. doi: 10.1016/s0301-5629(98)00145-8. PMID: 10320312.

Chan ST, Tam Y, Lai CY, Wu HY, Lam YK, Wong PN, Kwong KK. Transcranial Doppler study of cerebrovascular reactivity: are migraineurs more sensitive to breath-hold challenge? Brain Res. 2009 Sep 29;1291:53-9. doi: 10.1016/j.brainres.2009.07.057. Epub 2009 Jul 25. PMID: 19635466.

Chan ST, Evans KC, Song TY, Selb J, van der Kouwe A, Rosen BR, Zheng YP, Ahn A, Kwong KK. Cerebrovascular reactivity assessment with O2-CO2 exchange ratio under brief breath hold challenge. PLoS One. 2020 Mar 24;15(3):e0225915. doi: 10.1371/journal.pone.0225915. PMID: 32208415.

Highlights

Over 40 peer-reviewed journal articles

Paul Raines, PhD, was initially hired at the center as a scientific programmer in the Freesurfer group. Within his first year he took over management of all of the Center’s computational infrastructure. He now manages a group of four IT specialists that maintains over 400 Linux analysis workstations, 80 Linux servers, 100 batch compute nodes and various other computational devices. He also has written several web applications for Center management including the core software used for scheduling and billing.

Education

PhD in Physics, University of Pennsylvania

As the Head of MR Physics at the Harvard University Center for Brain Science, Neuroimaging facility, Dr. Mair’s role involves investigation and implementation of novel MRI methods for neuroimaging using the 3.0T MRI scanner, along with facility management duties. His research time has been split between optimization of advanced fMRI techniques, and investigation of acceleration methods for anatomical neuroimaging for morphomertric analysis. Both areas have covered the use of highly-parallel array receive coils, high levels of in-plane parallel imaging acceleration, multiband/simultaneous multi-slice imaging techniques, and recently undersampling with compressed sensing. The position requires close collaborations with Siemens developers, senior engineers and my colleagues at the Martinos Center for Biomedical Imaging at Massachusetts General Hospital who carry out significant MRI method development through interactions with the Siemens staff based at that site.

Prior to moving to this position, Dr. Mair held the position of Staff Scientist (Physicist) at the Smithsonian Astrophysical Observatory (part of the Harvard-Smithsonian Center for Astrophysics) for nearly 10 years. In collaboration with Dr Ron Walsworth, he helped lead a pioneering program in NMR and MRI applications of hyperpolarized noble gases in biomedical and materials science. This multidisciplinary work, involving collaborators from institutions as diverse as Schlumberger-Doll Research, MIT, Brigham and Women’s Hospital, Massachusetts General Hospital and University of New Hampshire, included development of methods to probe long-distance pore geometry, connectivity and permeability in reservoir rocks and model systems; and a program to design and build an open-access, human MRI scanner to probe posture-dependent effects in lung function. This period yielded close to 30 refereed publications, numerous applications to present invited lectures or colloquia, and 10 funded grant applications.

Education

PhD, Swinburne University of Technology, Australia

Select Publications

1. Nielsen JA, Mair RW, Baker JT, Buckner, RL. Precision Brain Morphometry: Feasibility and Opportunities of Extreme Rapid Scans. 2018.

2. Harms MP, Somerville LH, Ances BM, Andersson J, Barch DM, Bastiani M, Bookheimer SY, Brown TB, Buckner RL, Burgess GC, Coalson TS, Chappell MA, Dapretto M, Douaud G, Fischl B, Glasser MF, Greve DN, Hodge C, Jamison KW, Jbabdi S, Kandala S, Li X, Mair RW, Mangia S, Marcus D, Mascali D, Moeller S, Nichols TE, Robinson EC, Salat DH, Smith SM, Sotiropoulos SN, Terpstra M, Thomas KM, Tisdall MD, Ugurbil K, van der Kouwe A, Woods RP, Zöllei L, Van Essen DC, Yacoub E. Extending the Human Connectome Project across ages: Imaging protocols for the Lifespan Development and Aging projects. Neuroimage. 2018 Dec;183:972-984.

3. Mair RW, Wong GP, Hoffmann D, Hurlimann MD, Patz S, Schwartz LM, Walsworth RL. Probing porous media with gas diffusion NMR. Phys Rev Lett. 1999 Oct 18;83(16):3324-7.

Highlights

2016: Contribution to multisite NIH award: Mapping the Human Connectome During Typical Development (Site Co-I)

2015: Contribution to NIH S10 award: Upgrade Siemens MAGNETOM Trio to MAGNETOM Prisma Fit 3T Human MRI System (Research Scientist)

2005: Contribution to NSF Major Research Intrumentation award: MRI – Development of Instrumentation for High-Yield, High-Rate Hyperpolarized Noble Gas Production (Research Scientist)

Website

Center for Brain Science, Neuroimaging Facility

Dr. Sheraz Khan is an Instructor (Research Faculty) at Massachusetts General Hospital (MGH), Harvard Medical School and Massachusetts Institute of Technology (MIT). He has developed novel signal processing methods for understanding neural underpinnings of autism. His publications, including Khan et al, BRAIN, 2015 and Khan et al, PNAS, 2013 shed new light on functional connectivity in autism. The neurophysiological metrics presented in these papers, can be used to blindly identify individuals with ASD with high accuracy and correlate with severity of autism.

Dr. Khan contributes to MEG/EEG processing packages (MNE/Brainstorm). These tools are routinely used in MEG/EEG research and have led to several high impact publications. Since 2010, Dr. Khan has been part of the teaching faculty for Annual Multi-modal Neuroimaging course organized by MGH/HST Martinos Center for Biomedical Imaging, in which participants from all over the world get trained in different neuroimaging modalities. He contributes to Harvard Medical School and MIT brain imaging courses and routinely mentors several scientist at undergraduate, graduate and postdoctoral level in imaging data acquisition, analysis, interpretation and statistics.

Education

PhD in Computational and Applied Mathematics, Ecole Polytechnique, France

Select Publications

1. Khan S, Cohen D. Using the magnetoencephalogram to noninvasively measure magnetite in the living human brain. Hum Brain Mapp. 2019 Apr 1;40(5):1654-1665.

2. Samuelsson JG, Khan S, Sundaram P, Peled N, Hämäläinen MS. Cortical Signal Suppression (CSS) for Detection of Subcortical Activity Using MEG and EEG. Brain  Topogr. 2019 Mar;32(2):215-228.

3. Mamashli F, Khan S, Obleser J, Friederici AD, Maess B. Oscillatory dynamics of cortical functional connections in semantic prediction. Hum Brain Mapp. 2019 Apr 15;40(6):1856-1866.

Highlights

2010: Young Investigator Award Ecole Polytechnique, France

2013: Posters of Distinction, Research Fellows Poster Celebration, Massachusetts General Hospital, USA

2018: Young Investigator Award, International society for Biomagnetism, USA

Websites

The David Cohen MEG Laboratory
Khan Lab

Dr. Hui Wang’s research interests include developing innovative optical techniques and combining with MRI to study the structural-functional relationship of the brain. Particularly, a key question to answer is how the brain is connected to form the substrates of complex functions and what goes wrong in brain diseases. She has developed novel polarization sensitive optical coherence tomography techniques for mapping the connectivity and associated neuronal architecture in ex-vivo human brains and investigating in-vivo neurovascular coupling in small animals at micrometer resolution. Using the techniques, She has been studying the circuitry and architecture disruptions with neurodegenerative diseases in the cerebrum and the cerebellum. By incorporating high-resolution microscopic images into MRI tools, the goal is to identify pathology-related alterations as potential diagnostic biomarkers and prospective therapeutic targets.

Education

PhD, University of Minnesota

Select Publications

1. Wang H, Magnain C, Wang R, Dubb J, Varjabedian A, Tirrell LS, Stevens A, Augustinack JC, Konukoglu E, Aganj I, Frosch MP, Schmahmann JD, Fischl B, Boas DA. as-PSOCT: Volumetric microscopic imaging of human brain architecture and connectivity. Neuroimage. 2018 Jan 15;165:56-68.

2. Wang H, Magnain C, Sakadžić S, Fischl B, Boas DA. Characterizing the optical properties of human brain tissue with high numerical aperture optical coherence tomography. Biomed Opt Express. 2017 Nov 14;8(12):5617-5636.

3. Wang H, Akkin T, Magnain C, Wang R, Dubb J, Kostis WJ, Yaseen MA, Cramer A, Sakadžić S, Boas D. Polarization sensitive optical coherence microscopy for brain imaging. Opt Lett. 2016 May 15;41(10):2213-6.

Highlights

2018: NIH K99/R00 Pathway to Independence Career Development Award

2016: UT Brain Seed Grant

2012: Doctoral Dissertation Fellowship at the University of Minnesota

Dr. Savoy received his academic training in applied mathematics at MIT (BS 1971; MS 1975) and experimental psychology at Harvard University (PhD 1980). This period included 10 years of work at Polaroid Corporation’s Vision Research Laboratory, after which he joined the newly formed Rowland Institute for Science, under the direction of the late Edwin Land, in 1981. In 1991 he first learned of the revolutionary work being conducted at the Massachusetts General Hospital’s Nuclear Magnetic Resonance (NMR) Center, using magnetic resonance imaging (MRI) to detect changes in neural activity (via the associated hemodynamic changes in blood flow, blood volume, and blood oxygenation level dependent (i.e., BOLD) contrast mechanisms). In 1993 Dr. Savoy joined that group and became the Director of Functional MRI Education in 1994. He has conducted fMRI training workshops regularly at the MGH NMR Center several times per year since 1994, attracting thousands of researchers from around the world. In addition, he has run similar programs at conferences and at other institutions in the United States, Europe, Asia and Australia. Dr. Savoy’s fMRI-based research interests are wide-ranging, including temporal resolution of functional MRI, stereopsis, language, American Sign Language, decision making, multivariate analysis, and dissociative identity disorder (multiple personalities). Dr. Savoy’s current primary activity is teaching, although he also conducts some research and is a research consultant for various investigators. In recent years he has developed two additions to the training programs a the Athinoula A. Martinos Center for Biomedical Imaging, associated with MGH, MIT and Harvard. One program is a two-week-long multi-modality workshop (started in 2007); and the other is on connectivity issues using both structural (diffusion-based) and functional (BOLD-based) MRI (started in 2012). Dr. Savoy has academic appoints at Harvard Medical School, Boston University, Massachusetts General Hospital and the University of Zagreb in Croatia.

Dr. Savoy has always taken particular interest in explaining the most complex of technical and scientific ideas to a wide range of audiences. Functional Brain Imaging is certainly based on complicated technologies, but there are a number of unifying and relatively simple underlying ideas. For a general audience, the focus is usually on the various ways in which functional brain imaging is being used to address long-standing questions in psychology, ethics and medicine. For a more technical audience, the emphasis is on supplying enough information to start designing and analyzing experiments.

In both cases, there is a clear focus on the overall scientific and social challenges, such as: “How can we evaluate and integrate the thousands of technical and popular reports coming from the world of functional brain imaging into a useful and believable overview of brain function that is scientifically valid? How does this information affect our daily interactions, as well as our activities in the context of legal and medical decision making?”

Education

PhD in Experimental Psychology, Harvard University

Select Publications

1. Savoy RL, Frederick BB, Keuroghlian AS, Wolk PC. Voluntary switching between identities in dissociative identity disorder: A functional MRI case study. Cogn Neurosci. 2012;3(2):112-9. Officially published online: http://dx.doi.org/10.1080/17588928.2012.669750

2. Savoy RL. Experimental design in brain activation MRI: cautionary tales. Brain Res Bull. 2005 Nov 15;67(5):361-7.

3. Savoy RL. Using small numbers of subjects in fMRI-based research. IEEE Eng Med Biol Mag. 2006 Mar-Apr;25(2):52-9.

Highlights

Functional Brain Imaging educational workshops at MGH and around the world, numbering more than 100.