About Randy Gollub, MD, PhD

Randy L. Gollub is Professor of Psychiatry at Harvard Medical School and Clinical Professor of Psychiatry with a secondary appointment in Radiology at MGH.  She has been on faculty here since 1993.

Dr. Gollub's work focuses on the interface between the technological advancement of neuroimaging acquisition and analysis methods and their application to basic and clinical neuroscience.  As one of the first investigators to use fMRI to study healthy and disordered human brains, her focus is on developing and disseminating best practices through publication of exemplar research studies in high impact journals augmented by a substantial investment in educational activities. The majority of the past studies in her lab have used multimodal magnetic resonance neuroimaging techniques, including BOLD fMRI, ASL, diffusion, and structural, to investigate pain and modulation of pain by placebo and integrative medical treatments in healthy subjects and in patients suffering from chronic pain disorders.

The other domain of Dr. Gollub's research program is the within and across site calibration and validation of medical imaging data vital to the development of viable imaging biomarkers. She has pursued this domain within her own laboratory, as site PI for multi-site clinical imaging investigations, and by curating images collected during routine clinical care to use for secondary research purposes. She led the work to develop the Medical Imaging Informatics Bench to Bedside (mi2b2) workbench, a software suite that allows regulated access to clinically acquired medical images from institutional repositories. This unique resource for accessing clinical images is integrated directly into the Research Patient Data Registry (RPDR) at Mass General Brigham. The RPDR, and mi2b2 tools are well supported with regular updates and improvements in usability and available data.  Together they situate the work of our institutional investigators at the forefront of clinical imaging informatics.

Dr. Gollub has a long-standing commitment to biomedical education. A member of the affiliate faculty of the Harvard Massachusetts Institute of Technology division of Health Sciences Technology (HST), she serves as Co-Training Director of the HST Neuroimaging Training Program, now in it's fourth funding cycle (years 16-20) and was the originating Course Director for HST.583 fMRI Data Acquisition and Analysis.

Departments, Centers, & Programs:



Medical Education

  • PhD, Duke University
  • MD, Duke University School of Medicine
  • Residency, Hospital of Saint Raphael
  • Residency, Yale New Haven Hospital

American Board Certifications

  • Psychiatry, American Board of Psychiatry and Neurology

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    • Murphy SN, Wang Y, Wang TD, Sack D, Reynolds N, Plesniak W, Andriole K, Wei J, Pieper S, Herrick C, Gollub RL. High throughput tools to access images from clinical archives for research, J Digit Imaging. 2015 Apr;28(2):194-204. doi: 10.1007/s10278-014-9733-9. PMID: 25316195. PMCID: PMC4359193.
    • Ou Y, Gollub RL, Retzepi K, Reynolds N, Pienaar R, Pieper S, Murphy SN, Grant PE, Zöllei L. Brain extraction in pediatric ADC maps, toward characterizing neuro-development in multi-platform and multi-institution clinical images. Neuroimage. 2015 Aug 7;122:246-261. doi: 10.1016/j.neuroimage.2015.08.002. PubMed PMID: 26260429. PMCID: PMC4966541.
    • Ou Y, Zöllei L, Retzepi K, Castro V, Bates SV, Pieper S, Andriole K, Murphy N, Gollub RL*, Grant PE*. Using Clinically-acquired MRI to Construct Age-Specific ADC Atlases: Quantifying Spatiotemporal ADC Changes from Birth to 6 Years Old, Human Brain Mapping 2017 May 16;88(20):1912-1918. doi: 10.1002/hbm.23573. PMID: 2837110. PMCID: PMC5426959.
    • Weiss RJ, Bates SV, Song Y, Zhang Y, Herzberg EM, Chen YC, Gong M, Chien I, Zhang L, Murphy SN, Gollub RL, Grant PE, Ou Y. Mining multi-site clinical data to develop machine learning MRI biomarkers: application to neonatal hypoxic ischemic encephalopathy. J Transl Med. 2019 Nov 21;17(1):385. doi:10.1186/s12967-019-2119-5. PubMed PMID: 31752923; PubMed Central PMCID: PMC6873573.

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