Staff Bios
Peter A. Bandettini
Chief of Section on Functional Imaging Methods
Email: bandettini@nih.gov
Phone: (301) 402-1333
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.
Google Scholar: https://scholar.google.com/citations?user=X9OdRnYAAAAJ&hl=en
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.
Google Scholar: https://scholar.google.com/citations?user=CGQ3Lw4AAAAJ&hl=en
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.
Google Scholar: https://scholar.google.com/citations?user=rMRpQqUAAAAJ&hl=en&oi=sra
Burak graduated from Bilkent University with a B.Sc. in Electronics. Shortly after his graduation he joined to Turkey’s first national MR research center (UMRAM), where he started working with fMRI in various clinical and cognitive studies. After completing his master’s in biomedical engineering with bioelectricity & biomagnetism track, he started his PhD in University Medical Center Freiburg, where he worked with Dr. Pierre LeVan and Prof. Jürgen Hennig to understand dynamic interactions of brain networks by using fast fMRI. He is interested in multimodal brain imaging, fMRI acquisitions, processing pipelines and data visualization. He joined NIMH as a postdoctoral fellow in January 2021. He will be working on spatio-temporal characteristics of laminar fMRI and development of novel processing methods.
Google Scholar: https://scholar.google.com/citations?hl=en&user=GDsYRDgAAAAJ
Fernando Ramírez received his PhD in Psychology from the Humboldt Universität zu Berlin, Germany. His PhD work studied the representation of face orientation and viewpoint-invariant face recognition with a combined fMRI, multivariate pattern analysis, and computational modeling approach. He joined the Section on Functional Imaging Methods as a postdoctoral fellow in August 2021. His research relies on ultra-high field fMRI and computational models to investigate the representation of orientation and contrast information in human primary visual cortex, the biological meaning of pattern analyses of neuroimaging data, as well as feedback signals from higher-tier visual areas to primary visual cortex.
Google Scholar: https://scholar.google.com/citations?hl=en&user=0oSwdYYAAAAJ
Sharif I. Kronemer, PhD received a BA in Neuroscience and Philosophy from Ohio Wesleyan University (2012) and then completed a MSc in Cognitive Neuroscience from the University College London (2013). Dr. Kronemer completed his PhD at Yale University supervised by Hal Blumenfeld, MD, PhD (2021). His thesis research utilized innovative multimodal approaches, including fMRI and intracranial EEG to investigate the neural mechanisms of visual consciousness. Dr. Kronemer now serves as a postdoctoral fellow in the Section on Functional Imaging Methods at the National Institute of Mental Health. His current research aims to discriminate between the neural mechanisms for seen versus illusory visual conscious experiences and chart the intrinsic fluctuations in conscious perception with fMRI. Dr. Kronemer is a passionate science educator and outreach advocate. For more information about Dr. Kronemer, please follow this link: sharifkronemer.com .
Google Scholar: https://scholar.google.com/citations?hl=en&user=byaXSFsAAAAJ
Josh is a postdoctoral fellow in the Section on Functional Imaging Methods at the National Institute of Mental Health. His work focuses on understanding the brain as an interconnected, complex system. He received his Ph.D. in 2021 under the mentorship of Dr. Olaf Sporns, with funding support from the NSF GRFP program and the IU Graduate School. His doctoral work focused on examining brain architecture through the lens of network science and its applications, including community detection and edge-centric modeling. Josh graduated from the University of Southern California with a degree in neuroscience and cognitive science. When not thinking about brains, Josh prefers to spend his time consuming fine coffees & cheeses, prog rock, and televised sporting competitions of all kinds.
Google Scholar: https://scholar.google.com/citations?hl=en&user=GE4rM3QAAAAJ
Samika Kumar received her BA in Cognitive Science from the University of California, Berkeley, in 2017. Afterward, she worked at Dr. Matthew Walker's Center for Human Science, where she explored the potential of transcranial electrical brain stimulation to enhance sleep quality. Following research experiences in sleep and resting-state in four different labs, Samika grew interested in how information from different states of consciousness may lead to a more holistic understanding of mental health. In 2019, she began her PhD in Psychology with the National Institutes of Health Oxford-Cambridge Scholars Program, in which she is co-supervised by Dr. Peter Bandettini and Dr. Tristan Bekinschtein at the University of Cambridge. She uses multimodal imaging (fMRI, EEG) and machine learning methods to study brain network dynamics and mechanisms in the transition from wakefulness to sleep. Her proposed project aims to show that task-dependent changes in the brain are modulated by an individual's depth of drowsiness.
Google Scholar: https://scholar.google.com/citations?user=qcL0L2QAAAAJ&hl=en
Catherine is a Scientific Programmer in the Section on Functional Imaging Methods at the National Institute of Mental Health. She received her Ph.D. in 2023 from the University of California, Los Angeles, where she worked with Dr. Jesse Rissman to study individual differences in memory using behavioral and neuroimaging methods.
Google Scholar: https://scholar.google.com/citations?user=yVGwb1QAAAAJ&hl=en&oi=ao
Josh Dean graduated from Northwestern University in June 2023 with a major in biomedical engineering. At Northwestern, Josh worked with Dr. Molly Bright to investigate neural and vascular networks and sensorimotor task activation using fMRI. His last and most involved project was exploring the influence of a hypoxia intervention, which has previously shown positive health outcomes to spinal cord injury patients, on brain activation during a motor task. Josh joined SFIM in July 2023 to learn more about ultra-high-field functional MRI. After the conclusion of his fellowship, Josh plans to pursue an MD.
Marly Rubin graduated from American University in December 2023 with a major in neuroscience. As an undergraduate, she worked with Dr. Catherine Stoodley to investigate the role of the cerebellum in autism spectrum disorder. Her final project examined how cerebellar circuits contribute to functional connectivity alterations in ASD. She joined SFIM as a postbac IRTA in spring 2024 to further explore neuroimaging methods. Following her fellowship at the NIH, she plans to pursue a PhD in neuroscience.
Plyfaa Suwanamalik-Murphy graduated from the University of California, Davis, in the Spring of 2024, majoring in Cognitive Science. She has previously investigated the perception of iridescence, search performance within naturalistic scenes using eye-tracking, and how the C1 component reflects the initial feedforward signal in V1. Joining SFIM as a postbac IRTA in the Summer of 2024, Plyfaa aims to further build on her computational skills within research and explore neuroimaging methods. Upon completion of her fellowship at the NIH, she intends to pursue a Ph.D. in cognitive neuroscience.
