Staff Bios

Dr. Bandettini received his B.S. in Physics from Marquette University in 1989 and his Ph.D. in Biophysics from the Medical College of Wisconsin in 1994, where he and his fellow graduate student, Eric Wong, played a role in the early development of magnetic resonance imaging of human brain function using blood oxygenation contrast. During his postdoctoral fellowship at the Massachusetts General Hospital, he continued his investigation of methods to increase the interpretability, resolution, and applicability of functional MRI techniques. In March of 1999, he joined NIMH as an Investigator in the Laboratory of Brain and Cognition and as the Director of the NIH Functional MRI core facility. In 2001, he was awarded the Scientific Director's Merit Award for his efforts in establishing the NIH FMRI core facility and in 2007 the team that he created was also awarded the Scientific Director's Merit Award for their outstanding work. In 2002, he was awarded the Wiley Young Investigator's Award at the annual Organization for Human Brain Mapping Meeting.

Dr. Bandettini is currently Editor-In-Chief of the journal NeuroImage. He has been deeply involved with the Organization for Human Brain Mapping (OHBM) since 1997, serving as President from 2005-2007, Chair of the Program Committee from 2011-present and from 2001-2003, Secretary from 1999-2001, Chair of the Education Committee from 2000-2001. He has been a member of the OHBM scientific program committee for all years since 1997 except 1998, and 2008-11. He has also been very active in the International Society for Magnetic Resonance in Medicine (ISMRM), serving on their program committee from 2007-2010.

His laboratory is currently developing MRI methods improve resolution, sensitivity, interpretability, and applicability of functional MRI. His specific scientific interests are in the areas of fMRI decoding, multiple simultaneously embedded contrast fMRI, resting state fMRI, and multi-modal imaging. He also is very much motivated to move fMRI from a niche technique for understanding brain function in mostly healthy individuals and groups to a robust and informative technique that is used in the clinic on individuals to help diagnose disease and help predict treatment outcome. He strongly feels fMRI has considerable untapped potential for revealing a wealth of neuronal and physiologic information from individuals.

Publications

Google Scholar: https://scholar.google.com/citations?user=X9OdRnYAAAAJ&hl=en 

Ultra-high resolution blood volume fMRI and BOLD fMRI in humans at 9.4 T: Capabilities and challenges. 
Huber L, Tse DHY, Wiggins CJ, Uludağ K, Kashyap S, Jangraw DC, Bandettini PA, Poser BA, Ivanov D.
Neuroimage. 2018 Sep;178:769-779. doi: 10.1016/j.neuroimage.2018.06.025. Epub 2018 Jun 8.
PMID:29890330

Trait paranoia shapes inter-subject synchrony in brain activity during an ambiguous social narrative. 
Finn ES, Corlett PR, Chen G, Bandettini PA, Constable RT.
Nat Commun. 2018 May 23;9(1):2043. doi: 10.1038/s41467-018-04387-2.
PMID:29795116

Towards a new approach to reveal dynamical organization of the brain using topological data analysis. 
Saggar M, Sporns O, Gonzalez-Castillo J, Bandettini PA, Carlsson G, Glover G, Reiss AL.
Nat Commun. 2018 Apr 11;9(1):1399. doi: 10.1038/s41467-018-03664-4.
PMID: 29643350

Statistical power comparisons at 3T and 7T with a GO / NOGO task. 
Torrisi S, Chen G, Glen D, Bandettini PA, Baker CI, Reynolds R, Yen-Ting Liu J, Leshin J, Balderston N, Grillon C, Ernst M.
Neuroimage. 2018 Jul 15;175:100-110. doi: 10.1016/j.neuroimage.2018.03.071. Epub 2018 Apr 3.
PMID:29621615

The Integration of Functional Brain Activity from Adolescence to Adulthood. 
Kundu P, Benson BE, Rosen D, Frangou S, Leibenluft E, Luh WM, Bandettini PA, Pine DS, Ernst M.
J Neurosci. 2018 Apr 4;38(14):3559-3570. doi: 10.1523/JNEUROSCI.1864-17.2018. Epub 2018 Feb 27.
PMID:29487126

Ridding fMRI data of motion-related influences: Removal of signals with distinct spatial and physical bases in multiecho data. 
Power JD, Plitt M, Gotts SJ, Kundu P, Voon V, Bandettini PA, Martin A.
Proc Natl Acad Sci U S A. 2018 Feb 27;115(9):E2105-E2114. doi: 10.1073/pnas.1720985115. Epub 2018 Feb 12.
PMID:29440410

Frequency-dependent tACS modulation of BOLD signal during rhythmic visual stimulation. 
Chai Y, Sheng J, Bandettini PA, Gao JH.
Hum Brain Mapp. 2018 May;39(5):2111-2120. doi: 10.1002/hbm.23990. Epub 2018 Feb 1.
PMID:29389051

High-Resolution CBV-fMRI Allows Mapping of Laminar Activity and Connectivity of Cortical Input and Output in Human M1. 
Huber L, Handwerker DA, Jangraw DC, Chen G, Hall A, Stüber C, Gonzalez-Castillo J, Ivanov D, Marrett S, Guidi M, Goense J, Poser BA, Bandettini PA.
Neuron. 2017 Dec 20;96(6):1253-1263.e7. doi: 10.1016/j.neuron.2017.11.005. Epub 2017 Dec 7.
PMID:29224727

View Dr. Bandettini’s PubMed Publications 

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In 2001, Dr. Gonzalez-Castillo received a B.S. and M.S in Electrical and Computer Engineering (Ingenieria de Telecomunicaciones) from Universidad Politecnica de Madrid, Spain. Following graduation, he spent one year as a research assistant in HP-Labs, Bristol (UK) working on electronic-commerce automation technologies; followed by three more years as an IT consultant for Hewlett-Packard Spain. Those years in IT industry helped Dr. Gonzalez-Castillo develop key skills in the areas of computer science, data analytics, and project management. In the early 2000s, Dr. Gonzalez-Castillo decided to change professional tracks and find ways to apply his engineering skills to solving biological problems. In 2004, he was awarded a Fulbright Fellowship to pursue a Ph.D. in Biomedical Engineering at Purdue University, West Lafayette, IN. During his time at Purdue, he worked on several language-related fMRI studies under the mentorship of Prof. Thomas Talavage and was awarded a Bilsland Dissertation Fellowship for his dissertation research. In December 2009, Dr. Gonzalez-Castillo graduated from Purdue and joined the Section on Functional Imaging Methods (SFIM) at the National Institute of Mental Health (NIMH) in Bethesda, MD as a post-doctoral fellow. In 2014, Dr. Gonzalez-Castillo was promoted to Staff Scientist within the Section. His research at the SFIM focuses on three main topics: development of novel fMRI analytical methods that help increase fMRI’s ability to precisely answer both clinical and basic neuroscientific questions; understanding the most dynamical aspects of functional connectivity (e.g., fast reconfigurations that happen within the constraints of individual scans), and modeling sources of non-clinical day-to-day and subject-to-subject variability in fMRI so that clinically relevant information present in fMRI scans can be isolated and more easily interpreted.

Publications

Scopus ID: 35810107500
Google Scholar https://scholar.google.com/citations?user=CGQ3Lw4AAAAJ&hl=en 

Towards a new approach to reveal dynamical organization of the brain using topological data analysis. 
Saggar M, Sporns O, Gonzalez-Castillo J, Bandettini PA, Carlsson G, Glover G, Reiss AL.
Nat Commun. 2018 Apr 11;9(1):1399. doi: 10.1038/s41467-018-03664-4.
PMID: 29643350

Extended amygdala connectivity changes during sustained shock anticipation. 
Torrisi S, Gorka AX, Gonzalez-Castillo J, O'Connell K, Balderston N, Grillon C, Ernst M.
Transl Psychiatry. 2018 Jan 31;8(1):33. doi: 10.1038/s41398-017-0074-6. Review.
PMID: 29382815

High-Resolution CBV-fMRI Allows Mapping of Laminar Activity and Connectivity of Cortical Input and Output in Human M1. 
Huber L, Handwerker DA, Jangraw DC, Chen G, Hall A, Stüber C, Gonzalez-Castillo J, Ivanov D, Marrett S, Guidi M, Goense J, Poser BA, Bandettini PA.
Neuron. 2017 Dec 20;96(6):1253-1263.e7. doi: 10.1016/j.neuron.2017.11.005. Epub 2017 Dec 7.
PMID: 29224727

A functional connectivity-based neuromarker of sustained attention generalizes to predict recall in a reading task. 
Jangraw DC, Gonzalez-Castillo J, Handwerker DA, Ghane M, Rosenberg MD, Panwar P, Bandettini PA.
Neuroimage. 2018 Feb 1;166:99-109. doi: 10.1016/j.neuroimage.2017.10.019. Epub 2017 Oct 12.
PMID: 29031531
Direct modulation of aberrant brain network connectivity through real-time NeuroFeedback. 
Ramot M, Kimmich S, Gonzalez-Castillo J, Roopchansingh V, Popal H, White E, Gotts SJ, Martin A.
Elife. 2017 Sep 16;6. pii: e28974. doi: 10.7554/eLife.28974.
PMID: 28917059
Task-based dynamic functional connectivity: Recent findings and open questions. 

Gonzalez-Castillo J, Bandettini PA.
Neuroimage. 2017 Aug 3. pii: S1053-8119(17)30653-5. doi: 10.1016/j.neuroimage.2017.08.006. [Epub ahead of print] Review.
PMID: 28780401
Whole-brain connectivity dynamics reflect both task-specific and individual-specific modulation: A multitask study. 
Xie H, Calhoun VD, Gonzalez-Castillo J, Damaraju E, Miller R, Bandettini PA, Mitra S.
Neuroimage. 2017 May 23. pii: S1053-8119(17)30449-4. doi: 10.1016/j.neuroimage.2017.05.050. [Epub ahead of print] Review.
PMID: 28549798

Introducing Alternative-Based Thresholding for Defining Functional Regions of Interest in fMRI. 
Degryse J, Seurinck R, Durnez J, Gonzalez-Castillo J, Bandettini PA, Moerkerke B.
Front Neurosci. 2017 Apr 21;11:222. doi: 10.3389/fnins.2017.00222. eCollection 2017.
PMID: 28484367

View Dr. Gonzalez-Castillo’s PubMed Publications 

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Daniel Handwerker received a B.S. in Biomedical Engineering and a B.A. in Computer Science from Johns Hopkins University in 2000 where he first started working with fMRI in neuroscience and psychology labs. He received his Ph.D. from the University of California at Berkeley and San Francisco Joint Graduate Group in Bioengineering in 2005. For his doctoral research, he worked with Marc D’Esposito to examine the range of observable hemodynamic response variation in fMRI across brain regions and with aging as well as finding ways to account for this variation during data acquisition and analysis. After a postdoctoral fellowship at UCSF with Roland Henry to use fMRI and DTI to study neural changes with dementia and other conditions, Dr. Handwerker joined Peter Bandettini’s Section on Functional Imaging Methods at NIMH as a postdoctoral fellow in 2007. In SFIM, he has become an expert in fMRI connectivity analyses with a specific focus on connectivity dynamics and finding ways to more precisely remove non-neural noise from fMRI data. He has worked to find ways to systematically identify non-neural vascular variation using breath holding and the Valsalva maneuver. Since becoming a Staff Scientist in SFIM in 2014, Dr. Handwerker has used his neuroscience, fMRI acquisition, and data analysis expertise to support many of the research projects in SFIM.

Publications

Scopus ID: 22835013200
Google Scholar: https://scholar.google.com/citations?user=rMRpQqUAAAAJ&hl=en&oi=sra 

High-Resolution CBV-fMRI Allows Mapping of Laminar Activity and Connectivity of Cortical Input and Output in Human M1. 
Huber L, Handwerker DA, Jangraw DC, Chen G, Hall A, Stüber C, Gonzalez-Castillo J, Ivanov D, Marrett S, Guidi M, Goense J, Poser BA, Bandettini PA.
Neuron. 2017 Dec 20;96(6):1253-1263.e7. doi: 10.1016/j.neuron.2017.11.005. Epub 2017 Dec 7.
PMID: 29224727

A functional connectivity-based neuromarker of sustained attention generalizes to predict recall in a reading task. 
Jangraw DC, Gonzalez-Castillo J, Handwerker DA, Ghane M, Rosenberg MD, Panwar P, Bandettini PA.
Neuroimage. 2018 Feb 1;166:99-109. doi: 10.1016/j.neuroimage.2017.10.019. Epub 2017 Oct 12.
PMID: 29031531

Techniques for blood volume fMRI with VASO: From low-resolution mapping towards sub-millimeter layer-dependent applications. 
Huber L, Ivanov D, Handwerker DA, Marrett S, Guidi M, Uludağ K, Bandettini PA, Poser BA.
Neuroimage. 2018 Jan 1;164:131-143. doi: 10.1016/j.neuroimage.2016.11.039. Epub 2016 Nov 18.
PMID: 27867088

Evaluation of multi-echo ICA denoising for task based fMRI studies: Block designs, rapid event-related designs, and cardiac-gated fMRI. 
Gonzalez-Castillo J, Panwar P, Buchanan LC, Caballero-Gaudes C, Handwerker DA, Jangraw DC, Zachariou V, Inati S, Roopchansingh V, Derbyshire JA, Bandettini PA.
Neuroimage. 2016 Nov 1;141:452-468. doi: 10.1016/j.neuroimage.2016.07.049. Epub 2016 Jul 27.
PMID: 27475290

The brain imaging data structure, a format for organizing and describing outputs of neuroimaging experiments. 
Gorgolewski KJ, Auer T, Calhoun VD, Craddock RC, Das S, Duff EP, Flandin G, Ghosh SS, Glatard T, Halchenko YO, Handwerker DA, Hanke M, Keator D, Li X, Michael Z, Maumet C, Nichols BN, Nichols TE, Pellman J, Poline JB, Rokem A, Schaefer G, Sochat V, Triplett W, Turner JA, Varoquaux G, Poldrack RA.
Sci Data. 2016 Jun 21;3:160044. doi: 10.1038/sdata.2016.44.
PMID: 27326542

Long-term neural and physiological phenotyping of a single human. 
Poldrack RA, Laumann TO, Koyejo O, Gregory B, Hover A, Chen MY, Gorgolewski KJ, Luci J, Joo SJ, Boyd RL, Hunicke-Smith S, Simpson ZB, Caven T, Sochat V, Shine JM, Gordon E, Snyder AZ, Adeyemo B, Petersen SE, Glahn DC, Reese Mckay D, Curran JE, Göring HH, Carless MA, Blangero J, Dougherty R, Leemans A, Handwerker DA, Frick L, Marcotte EM, Mumford JA.
Nat Commun. 2015 Dec 9;6:8885. doi: 10.1038/ncomms9885.
PMID: 26648521

Tracking ongoing cognition in individuals using brief, whole-brain functional connectivity patterns. 
Gonzalez-Castillo J, Hoy CW, Handwerker DA, Robinson ME, Buchanan LC, Saad ZS, Bandettini PA.
Proc Natl Acad Sci U S A. 2015 Jul 14;112(28):8762-7. doi: 10.1073/pnas.1501242112. Epub 2015 Jun 29.
PMID: 26124112

Effects of thoracic pressure changes on MRI signals in the brain. 
Wu P, Bandettini PA, Harper RM, Handwerker DA.
J Cereb Blood Flow Metab. 2015 Jun;35(6):1024-32. doi: 10.1038/jcbfm.2015.20. Epub 2015 Feb 25.
PMID:
25712496

View Dr. Handwerker’s PubMed Publications 

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Dr. Peter Molfese received his B.A. in Computer Science and Psychology from DePauw University in 2003, a M.A. in Experimental Psychology from the University of Louisville in 2005, and a Ph.D. in Developmental Psychology from the University of Houston in 2009. He completed postdoctoral fellowships at both the Yale Child Study Center and Haskins Laboratories in 2009 and 2010. Peter joined the research faculty at Haskins Laboratories from 2010-2017, where his research looked at bilingualism, implicit memory, and reading development in children. Before joining SFIM, Peter served as the inaugural Director of Operations for the University of Connecticut's Brain Imaging Research Center (BIRC) from 2014-2017.

Peter specializes in quantitative methods (Multivariate Statistics, Structural Equations Modeling, Multi-Level Modeling, and Machine Learning) and the integration of multi-modal neuroimaging methods (fMRI, EEG, MEG, and NIRS).

Publications

Scopus ID: 6506325362
Google Scholar: https://scholar.google.com/citations?user=5EEOhkIAAAAJ&hl=en&oi=sra 

Individual Differences in Reading Skill Are Related to Trial-by-Trial Neural Activation Variability in the Reading Network. 
Malins JG, Pugh KR, Buis B, Frost SJ, Hoeft F, Landi N, Mencl WE, Kurian A, Staples R, Molfese PJ, Sevcik R, Morris R.
J Neurosci. 2018 Mar 21;38(12):2981-2989. doi: 10.1523/JNEUROSCI.0907-17.2018. Epub 2018 Feb 12.
PMID: 29440534

Ventricular and Periventricular Anomalies in the Aging and Cognitively Impaired Brain. 
Todd KL, Brighton T, Norton ES, Schick S, Elkins W, Pletnikova O, Fortinsky RH, Troncoso JC, Molfese PJ, Resnick SM, Conover JC; Alzheimer’s Disease Neuroimaging Initiative.
Front Aging Neurosci. 2018 Jan 12;9:445. doi: 10.3389/fnagi.2017.00445. eCollection 2017.
PMID: 29379433

The BDNF Val66Met polymorphism is associated with structural neuroanatomical differences in young children. 
Jasińska KK, Molfese PJ, Kornilov SA, Mencl WE, Frost SJ, Lee M, Pugh KR, Grigorenko EL, Landi N.
Behav Brain Res. 2017 Jun 15;328:48-56. doi: 10.1016/j.bbr.2017.03.014. Epub 2017 Mar 27.
PMID: 28359883

Prefrontal cortex, temporal cortex, and hippocampus volume are affected in suicidal psychiatric patients. 
Gosnell SN, Velasquez KM, Molfese DL, Molfese PJ, Madan A, Fowler JC, Christopher Frueh B, Baldwin PR, Salas R.
Psychiatry Res Neuroimaging. 2016 Oct 30;256:50-56. doi: 10.1016/j.pscychresns.2016.09.005. Epub 2016 Sep 13.
PMID: 27685801

The BDNF Val66Met Polymorphism Influences Reading Ability and Patterns of Neural Activation in Children. 
Jasińska KK, Molfese PJ, Kornilov SA, Mencl WE, Frost SJ, Lee M, Pugh KR, Grigorenko EL, Landi N.
PLoS One. 2016 Aug 23;11(8):e0157449. doi: 10.1371/journal.pone.0157449. eCollection 2016.
PMID: 27551971

Universal brain signature of proficient reading: Evidence from four contrasting languages. 
Rueckl JG, Paz-Alonso PM, Molfese PJ, Kuo WJ, Bick A, Frost SJ, Hancock R, Wu DH, Mencl WE, Duñabeitia JA, Lee JR, Oliver M, Zevin JD, Hoeft F, Carreiras M, Tzeng OJ, Pugh KR, Frost R.
Proc Natl Acad Sci U S A. 2015 Dec 15;112(50):15510-5. doi: 10.1073/pnas.1509321112. Epub 2015 Nov 30.
PMID: 26621710

Print-Speech Convergence Predicts Future Reading Outcomes in Early Readers. 
Preston JL, Molfese PJ, Frost SJ, Mencl WE, Fulbright RK, Hoeft F, Landi N, Shankweiler D, Pugh KR.
Psychol Sci. 2016 Jan;27(1):75-84. doi: 10.1177/0956797615611921. Epub 2015 Nov 20.
PMID: 26589242

Functionally integrated neural processing of linguistic and talker information: An event-related fMRI and ERP study. 
Zhang C, Pugh KR, Mencl WE, Molfese PJ, Frost SJ, Magnuson JS, Peng G, Wang WS.
Neuroimage. 2016 Jan 1;124(Pt A):536-549. doi: 10.1016/j.neuroimage.2015.08.064. Epub 2015 Sep 4.
PMID:
26343322

View Dr. Molfese’s PubMed Publications 

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Dr. Emily Finn received a B.A. in Linguistics (2009) and Ph.D. in neuroscience (2017) from Yale University. Her graduate work focused on individual differences in functional brain connectivity measured with fMRI and how these relate to behavior. At NIMH under the mentorship of Dr. Peter Bandettini, she is exploring how to use resting state and various tasks, including naturalistic paradigms, to tease out meaningful individual variation in brain activity and connectivity. She is especially interested in individual differences related to cognitive abilities, personality traits, and risk factors for psychiatric illness.

Publications

Google Scholar: https://scholar.google.com/citations?user=95oJGacAAAAJ&hl=en 

Trait paranoia shapes inter-subject synchrony in brain activity during an ambiguous social narrative. 
Finn ES, Corlett PR, Chen G, Bandettini PA, Constable RT.
Nat Commun. 2018 May 23;9(1):2043. doi: 10.1038/s41467-018-04387-2.
PMID: 29795116

Considering factors affecting the connectome-based identification process: Comment on Waller et al. 
Horien C, Noble S, Finn ES, Shen X, Scheinost D, Constable RT.
Neuroimage. 2018 Apr 1;169:172-175. doi: 10.1016/j.neuroimage.2017.12.045. Epub 2017 Dec 15.
PMID: 29253655

Individual differences in functional connectivity during naturalistic viewing conditions. 
Vanderwal T, Eilbott J, Finn ES, Craddock RC, Turnbull A, Castellanos FX.
Neuroimage. 2017 Aug 15;157:521-530. doi: 10.1016/j.neuroimage.2017.06.027. Epub 2017 Jun 16.
PMID: 28625875

Can brain state be manipulated to emphasize individual differences in functional connectivity? 
Finn ES, Scheinost D, Finn DM, Shen X, Papademetris X, Constable RT.
Neuroimage. 2017 Oct 15;160:140-151. doi: 10.1016/j.neuroimage.2017.03.064. Epub 2017 Mar 31. Review.
PMID: 28373122

Characterizing Attention with Predictive Network Models. 
Rosenberg MD, Finn ES, Scheinost D, Constable RT, Chun MM.
Trends Cogn Sci. 2017 Apr;21(4):290-302. doi: 10.1016/j.tics.2017.01.011. Epub 2017 Feb 23. Review.
PMID: 28238605

Using connectome-based predictive modeling to predict individual behavior from brain connectivity. 
Shen X, Finn ES, Scheinost D, Rosenberg MD, Chun MM, Papademetris X, Constable RT.
Nat Protoc. 2017 Mar;12(3):506-518. doi: 10.1038/nprot.2016.178. Epub 2017 Feb 9.
PMID: 28182017

Multisite reliability of MR-based functional connectivity. 
Noble S, Scheinost D, Finn ES, Shen X, Papademetris X, McEwen SC, Bearden CE, Addington J, Goodyear B, Cadenhead KS, Mirzakhanian H, Cornblatt BA, Olvet DM, Mathalon DH, McGlashan TH, Perkins DO, Belger A, Seidman LJ, Thermenos H, Tsuang MT, van Erp TGM, Walker EF, Hamann S, Woods SW, Cannon TD, Constable RT.
Neuroimage. 2017 Feb 1;146:959-970. doi: 10.1016/j.neuroimage.2016.10.020. Epub 2016 Oct 13.
PMID: 27746386

Individual variation in functional brain connectivity: implications for personalized approaches to psychiatric disease. 
Finn ES, Todd Constable R.
Dialogues Clin Neurosci. 2016 Sep;18(3):277-287. Review.
PMID: 27757062

View Dr. Finn's PubMed Publications 

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Yuhui Chai received his Ph.D. degree in Medical Physics from Peking University in Beijing, China in 2016. During his Ph.D., he worked on neuronal current MRI studies. Following graduation, he joined Section on Functional Imaging Methods (SFIM) group at NIH as a postdoctoral fellow. Currently Yuhui is working on neuromodulation fMRI.

Publications

Google Scholar: https://scholar.google.com/citations?user=m9O2xxcAAAAJ&hl=en 

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Dr. Laurentius Huber received his doctoral degree in physics at the Max Planck Institute for Human Cognitive and Brain Sciences in Leipzig, Germany in 2015. His work at NIH is focusing on methods development to map brain activity changes at sub-millimeter scales in humans.

You can follow Dr. Huber on Twitter, @layerfMRI (https://twitter.com/layerfMRI ). On Github, where he is writing a standalone layering software LAYNII (https://github.com/layerfMRI ). Or on the blog layerfMRI.com (https://layerfmri.com/ ), where he writes about layer-fMRI acquisition, its acquisition, evaluation and research field. 

Publications

Dissertation (https://drive.google.com/file/d/1OU5fUJHS87VCQPvVIbNPgVZynJI5wmUb/view?usp=sharing )
Google Scholar: https://scholar.google.de/citations?user=Ad1-QG4AAAAJ&hl=en 

Ultra-high resolution blood volume fMRI and BOLD fMRI in humans at 9.4 T: Capabilities and challenges. 
Huber L, Tse DHY, Wiggins CJ, Uludağ K, Kashyap S, Jangraw DC, Bandettini PA, Poser BA, Ivanov D.
Neuroimage. 2018 Sep;178:769-779. doi: 10.1016/j.neuroimage.2018.06.025. Epub 2018 Jun 8.
PMID: 29890330

Social competence and psychopathology in early childhood: a systematic review. 
Huber L, Plötner M, Schmitz J.
Eur Child Adolesc Psychiatry. 2018 Apr 10. doi: 10.1007/s00787-018-1152-x. [Epub ahead of print]
PMID: 29637284

High-Resolution CBV-fMRI Allows Mapping of Laminar Activity and Connectivity of Cortical Input and Output in Human M1. 
Huber L, Handwerker DA, Jangraw DC, Chen G, Hall A, Stüber C, Gonzalez-Castillo J, Ivanov D, Marrett S, Guidi M, Goense J, Poser BA, Bandettini PA.
Neuron. 2017 Dec 20;96(6):1253-1263.e7. doi: 10.1016/j.neuron.2017.11.005. Epub 2017 Dec 7.
PMID: 29224727

Non-BOLD contrast for laminar fMRI in humans: CBF, CBV, and CMRO2. 
Huber L, Uludağ K, Möller HE.
Neuroimage. 2017 Jul 20. pii: S1053-8119(17)30609-2. doi: 10.1016/j.neuroimage.2017.07.041. [Epub ahead of print]
PMID: 28736310

Techniques for blood volume fMRI with VASO: From low-resolution mapping towards sub-millimeter layer-dependent applications. 
Huber L, Ivanov D, Handwerker DA, Marrett S, Guidi M, Uludağ K, Bandettini PA, Poser BA.
Neuroimage. 2018 Jan 1;164:131-143. doi: 10.1016/j.neuroimage.2016.11.039. Epub 2016 Nov 18.
PMID: 27867088

Physiological basis of vascular autocalibration (VasA): Comparison to hypercapnia calibration methods. 
Kazan SM, Huber L, Flandin G, Ivanov D, Bandettini P, Weiskopf N.
Magn Reson Med. 2016 Nov 9. doi: 10.1002/mrm.26494. [Epub ahead of print]
PMID: 27851867

Optimization of simultaneous multislice EPI for concurrent functional perfusion and BOLD signal measurements at 7T. 
Ivanov D, Poser BA, Huber L, Pfeuffer J, Uludağ K.
Magn Reson Med. 2017 Jul;78(1):121-129. doi: 10.1002/mrm.26351. Epub 2016 Jul 28.
PMID: 27465273

Lamina-dependent calibrated BOLD response in human primary motor cortex. 
Guidi M, Huber L, Lampe L, Gauthier CJ, Möller HE.
Neuroimage. 2016 Nov 1;141:250-261. doi: 10.1016/j.neuroimage.2016.06.030. Epub 2016 Jun 27.
PMID: 27364473

Baseline oxygenation in the brain: Correlation between respiratory-calibration and susceptibility methods. 
Fan AP, Schäfer A, Huber L, Lampe L, von Smuda S, Möller HE, Villringer A, Gauthier CJ.
Neuroimage. 2016 Jan 15;125:920-931. doi: 10.1016/j.neuroimage.2015.11.007. Epub 2015 Nov 5.
PMID: 26549301

Functional cerebral blood volume mapping with simultaneous multi-slice acquisition. 
Huber L, Ivanov D, Guidi M, Turner R, Uludağ K, Möller HE, Poser BA.
Neuroimage. 2016 Jan 15;125:1159-1168. doi: 10.1016/j.neuroimage.2015.10.082. Epub 2015 Oct 30.
PMID: 26522423

Vascular autorescaling of fMRI (VasA fMRI) improves sensitivity of population studies: A pilot study. 
Kazan SM, Mohammadi S, Callaghan MF, Flandin G, Huber L, Leech R, Kennerley A, Windischberger C, Weiskopf N.
Neuroimage. 2016 Jan 1;124(Pt A):794-805. doi: 10.1016/j.neuroimage.2015.09.033. Epub 2015 Sep 28.
PMID: 26416648

Cortical lamina-dependent blood volume changes in human brain at 7 T. 
Huber L, Goense J, Kennerley AJ, Trampel R, Guidi M, Reimer E, Ivanov D, Neef N, Gauthier CJ, Turner R, Möller HE.
Neuroimage. 2015 Feb 15;107:23-33. doi: 10.1016/j.neuroimage.2014.11.046. Epub 2014 Dec 3.
PMID: 25479018

Simultaneous acquisition of cerebral blood volume-, blood flow-, and blood oxygenation-weighted MRI signals at ultra-high magnetic field. 
Krieger SN, Huber L, Poser BA, Turner R, Egan GF.
Magn Reson Med. 2015 Aug;74(2):513-7. doi: 10.1002/mrm.25431. Epub 2014 Sep 5.
PMID: 25195774

Regional reproducibility of calibrated BOLD functional MRI: implications for the study of cognition and plasticity. 
Krieger SN, Gauthier CJ, Ivanov D, Huber L, Roggenhofer E, Sehm B, Turner R, Egan GF.
Neuroimage. 2014 Nov 1;101:8-20. doi: 10.1016/j.neuroimage.2014.06.072. Epub 2014 Jul 5.
PMID: 25008001

Investigation of the neurovascular coupling in positive and negative BOLD responses in human brain at 7 T. 
Huber L, Goense J, Kennerley AJ, Ivanov D, Krieger SN, Lepsien J, Trampel R, Turner R, Möller HE.
Neuroimage. 2014 Aug 15;97:349-62. doi: 10.1016/j.neuroimage.2014.04.022. Epub 2014 Apr 15.
PMID: 24742920

Anatomical brain imaging at 7T using two-dimensional GRASE. 
Trampel R, Reimer E, Huber L, Ivanov D, Heidemann RM, Schäfer A, Turner R.
Magn Reson Med. 2014 Nov;72(5):1291-301. doi: 10.1002/mrm.25047. Epub 2013 Dec 17.
PMID:  24443053

Using carbogen for calibrated fMRI at 7Tesla: comparison of direct and modelled estimation of the M parameter. 
Krieger SN, Ivanov D, Huber L, Roggenhofer E, Sehm B, Turner R, Egan GF, Gauthier CJ.
Neuroimage. 2014 Jan 1;84:605-14. doi: 10.1016/j.neuroimage.2013.09.035. Epub 2013 Sep 24.
PMID: 24071526

Slab-selective, BOLD-corrected VASO at 7 Tesla provides measures of cerebral blood volume reactivity with high signal-to-noise ratio. 
Huber L, Ivanov D, Krieger SN, Streicher MN, Mildner T, Poser BA, Möller HE, Turner R.
Magn Reson Med. 2014 Jul;72(1):137-48. doi: 10.1002/mrm.24916. Epub 2013 Aug 20.
PMID: 23963641

Fast accurate MR thermometry using phase referenced asymmetric spin-echo EPI at high field. 
Streicher MN, Schäfer A, Ivanov D, Müller DK, Amadon A, Reimer E, Huber L, Dhital B, Rivera D, Kögler C, Trampel R, Pampel A, Turner R.
Magn Reson Med. 2014 Feb;71(2):524-33. doi: 10.1002/mrm.24681.
PMID: 23440917

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Arman graduated from George Mason University with a Neuroscience, B.Sc., and a Minor in Computational and Data Sciences. He has previously studied schizophrenia, functional connectivity, neuroimaging theory, and graph theory in the Clinical and Translational Neuroscience Branch (NIMH).

Arman joined SFIM as a post-bac fellow in May 2018; He is working on fMRI methods, development, and analysis.

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Eli is a post-baccalaureate IRTA Fellow in the Section on Functional Imaging Methods at the National Institute of Mental Health. He graduated from the University of Virginia in 2018 with a double major in B.Sc. Engineering Science and B.A. Chemistry. At Virginia, he worked in the Department of Pharmacology with Dr. Helena Snyder, Dr. Mark Kester and Dr. Craig Slingluff, optimizing the use of nanoparticle liposomes carrying melanoma helper peptides as a vaccine for patients with metastatic melanoma. He is currently involved in projects using fMRI and EEG data in order to localize epilepsy seizure sites and determine surgery viability. He is also applying to medical school and hopes to earn his M.D.