Brain Imaging Lab

The Brain Imaging Lab is housed in the Molecular Imaging and Neuropathology Area at the New York State Psychiatric Institute and the Department of Psychiatry at Columbia University Irvine Medical Center. The lab conducts studies that increase our understanding of the neurobiology of mood disorders and suicide and the mechanisms of medication and psychotherapeutic interventions with a goal to develop more effective treatments. The lab also focuses on the development and application of a wide range of computational tools and statistical methods to address these topics using multimodal neuroimaging (functional, structural, and molecular in vivo neuroimaging) and genomics data in healthy humans and patients with mood disorders.

Lab Members


  • Jeffrey Miller, MD

    • Associate Professor of Clinical Psychiatry

    Dr. Miller uses multimodal brain imaging tools to study biological underpinnings of psychiatric illness, with a focus on depression and suicide risk. He co-directs a multidisciplinary brain imaging laboratory with expertise in quantification of Positron Emission Tomography (PET) and Magnetic Resonance Imaging (MRI) data. He studies pathophysiology of psychiatric conditions using PET imaging to interrogate a range of molecular targets. Dr Miller has been using PET imaging to quantify elements of the serotonin and kappa opioid neurotransmitter systems in depression. He has identified trait abnormalities of elevated serotonin 1A receptor binding in major depressive disorder, present both during active illness as well as during periods of sustained remission. He conducted the first study quantifying the kappa opioid receptor in major depressive disorder, identifying a trend-level relationship between kappa opioid receptor binding and activation of the hypothalamic-pituitary-adrenal axis. Secondary analyses using novel independent component analysis demonstrate relationships between regional kappa opioid receptor binding and depression severity in vivo for the first time in humans.

    Dr. Miller is principal investigator of a Breakthrough Award by the International OCD Foundation to examine neuroinflammation assessed by PET imaging as a predictor of treatment outcome with an anti-inflammatory treatment in obsessive compulsive disorder. He is an investigator on a Conte Center Grant from NIMH examining the relationship of neuroinflammation to depression and suicide attempt history, and has active collaborations across the department of psychiatry to use PET imaging as a tool to quantify molecular abnormalities in schizophrenia and eating disorders. In addition to his work with PET imaging, Dr. Miller uses functional MRI and diffusion tensor imaging to predict treatment outcome and examine treatment effects of pharmacologic and behavioral treatments for depression. Dr. Miller’s research has been funded by NIMH, the Brain and Behavior Research Foundation, The International OCD Foundation, the Davis Foundation, and the Hope for Depression Research Foundation.

  • Francesca Zanderigo, PhD

    • Associate Professor of Clinical Neurobiology (in Psychiatry)

    Dr. Francesca Zanderigo, PhD, is a Bioengineer, Associate Professor of Clinical Neurobiology (in Psychiatry) at Columbia University, and co-Director of Brain Imaging in the Molecular Imaging and Neuropathology Area (MIND) at the New York State Psychiatric Institute (NYSPI). She has worked for almost 20 years now in medical imaging research, performing extensive quantification, mathematical modeling and analysis of brain images and data from both Magnetic Resonance Imaging (MRI) and Positron Emission Tomography (PET) for the investigation of cerebral hemodynamics and neuroreceptor systems. Dr. Zanderigo's research focuses on the extraction of accurate quantitative information from medical data and images, for the purpose of improving disease prevention, diagnosis, and treatment. This includes the development of sophisticated methods for data quantification that simplify the acquisition of PET images, with the aim of promoting the translation of PET technique into clinical practice. These advanced methods allow investigators to reduce, and in some cases, eliminate the need for arterial blood sampling during imaging with PET, and have been applied to PET radiotracers used to image, for example, the translocator protein, monoamine oxidase A, the incorporation of arachidonic acid, the serotonin 1A receptor and transporter, and glucose metabolism. Further contributions from Dr. Zanderigo include creating approaches that overcome the problem posed by many targets of PET imaging, the absence of a valid reference region, to provide measurements of PET binding that are specific only to the target of interest. As well, her work includes developing other advanced methodologies in the field of in vivo brain imaging, ranging in scope from the generation of quantitative parametric images at the voxel level, to data-adaptive robust fitting approaches to improve statistical power and sensitivity of imaging studies, to model-free quantification for PET images. Dr. Zanderigo is currently Principal Investigator of an R01 funded by NIBIB (R01EB026481) that aims at developing noninvasive quantification methods for data acquired with next-generation portable brain PET cameras. Dr. Zanderigo is also sub-award PI in a NIH-funded R01 (1RF1AG070438-1), and co-Investigator in another 6 research grants funded by NIA, NIMH, and the Alzheimer’s Association. She has also been involved in 9 completed research grants as sub-award PI, co-Investigator, and Research Scientist. Within the past 10 years, she has mentored a total of 18 people, from undergraduate to graduate and pre-med students and post-docs. A complete list of Dr. Zanderigo’s publications can be found at the following link:

Principal Investigators and Faculty

  • Todd Ogden, PhD

    • Professor, Biostatistics (in Psychiatry)

    I am interested in statistical modeling of imaging data and, more broadly, in modeling of functional data and other high dimensional data sources.  A major focus of my recent work is on development of modeling solutions to various problems that arise in PET imaging applications. Recent contributions in that area have involved simultaneous (across regions and/or across subjects) modeling, methods for relaxing modeling assumptions, and non-parametric alternatives to the popular kinetic modeling approaches.

  • Spiro P. Pantazatos, PhD

    • Assistant Professor of Clinical Neurobiology (in Psychiatry)

    I have interests and experience in translational neuroinformatics, computational neuroimaging and psychiatric genomics. My work includes development and application of computational tools to accelerate mental health research. A primary research track applies data mining to brain imaging, molecular neuroanatomy and genomics data to identify and understand the etiology of anxiety, mood disorders and suicide in order to help guide treatment development for these disorders. I am also spearheading development of My Brain and Me, a web interface to crowdsource brain imaging and behavioral data while allowing participants to explore their own brain. The goal is to create a scalable approach that speeds up neuroimaging and mental health research and also increases public awareness and engagement with neuroscience. Other ongoing interests include birth season and neurobehavioral traits, political psychology and cognitive neuroscience, intuition and psychoinformatics. My publications can be accessed on Researchgate.

  • Dongrong Xu, PhD

    • Associate Professor of Clinical Neurobiology (in Psychiatry)

    Dongrong Xu's research interests are developing novel algorithms and methods for  neuroimaging data analysis, and their applications to various neuroscience, psychiatric and neurological  studies. Dr. Xu also develops virtual reality paradigms for neuroimaging studies. Please see the following link for more details and his recent publications:

  • Zhengchao Dong, PhD

    • Associate Professor of Clinical Neurobiology (in Psychiatry)

    Research Interest

    MR physics and MRI methodology

    •  MRI image reconstruction and processing   
    •   MR spectroscopic imaging techniques

    Applications of MRI in

    • Mental disorders
    • Metabolism and physiology


    Current Work

    Collaborating with colleagues on projects involving magnetic resonance spectroscopy (MRS). The MRS work includes:

    • Quantification of dynamic changes of metabolites during drug infusion/administration in patients with depression or bipolar disorders
    •  Quantification of change of metabolite levels in response to treatment in patients with depression or bipolar disorders.

    MRI methodology development

    • Dynamic or functional MRS
    • 1H MRS-based thermometry
    • 1H MRS imaging without water suppression
    • Magnetic resonance fingerprinting and MR spectroscopic fingerprinting
  • M. Elizabeth Sublette, MD, PhD

    • Professor of Clinical Psychiatry

    Dr. Sublette has a longstanding interest in brain mechanisms underlying mood disorders and suicide risk. She is particularly focused on the mechanisms of action of polyunsaturated fatty acids (PUFAs) on the brain. Her research in these areas encompasses a broad variety of translational approaches, including not only neuroimaging but clinical, biochemical, , genetic and epigenetic methodologies. Dr. Sublette is the Director of the Molecular Imaging and Neuropathology Division (MIND) Research Clinic and Core Leader for the Clinical Evaluation Core of the MIND Silvio O. Conte Center for Basic or Translational Mental Health Research (MH090964). In studying brain mechanisms related to PUFAs, depression and suicide risk, Dr. Sublette’s work has utilized multiple neuroimaging modalities, including structural magnetic resonance imaging (MRI), positron emission tomography (PET) and diffusion tensor imaging (DTI):


    Gopaldas, M., Zanderigo, F., Zhan, S., Ogden, R.T., Miller, J.M., Rubin-Falcone, H., Cooper, T.B., Oquendo M.A., Sullivan, G., Mann, J.J., Sublette, M.E., “Brain serotonin transporter binding, plasma arachidonic acid and depression severity: A positron emission tomography study of major depression.” Journal of Affective Disorders, in press.

    Zanderigo, F., Kang, Y., Kumar, D., Nikolopoulou, A., Mozley, P.D., Kothari, P., He, B., Schlyer, D., Rapoport, S., Oquendo, M., Vallabhajosula, S., Mann, J.J., Sublette, M.E.,  “[11C]arachidonic acid incorporation measurement in human brain: optimization for clinical use." Synapse (2018) 72(2). doi: 10.1002/syn.22018. Epub 2017 Nov 27. PubMed PMID: 29144569; PubMed Central PMCID: PMC6075823.

    Chhetry B.T., Hezghia A., Miller J.M., Lee S., Rubin-Falcone H., Cooper T.B., Oquendo M.A., Mann J.J., Sublette M.E., “Omega-3 polyunsaturated fatty acid supplementation and white matter changes in major depression.” Journal of psychiatric research (2016) 75:65-74. PMCID:PMC4948754

    Sublette, M.E., Milak, M.S., Galfalvy, H.C., Oquendo, M.A., Malone, K.M., Mann, J.J., “Regional brain glucose uptake distinguishes suicide attempters from non-attempters in Major Depression.” Archives of Suicide Research (2013) 17(4):434-447. PMCID: PMC3831169

    Sublette, M.E., Milak, M.S., Hibbeln, J.R., Freed, P.J., Oquendo, M.A., Malone, K.M., Parsey, R.V., John Mann, J., “Plasma polyunsaturated fatty acids and regional cerebral glucose metabolism in major depression.” Prostaglandins Leukotrienes & Essential Fatty Acids (2009) 80(1):57-64. PMCID: PMC2712826

  • Martin J. Lan, MD, PhD

    • Assistant Professor of Psychiatry

    My research utilizes neuroimaging with both PET and MRI to better understand the biological underpinnings of mood disorders.  I have a particular interest in the depressed phase of bipolar disorder.  One track of my research aims to identify and characterize biomarkers related to treatment response to medications.  Those studies aim to work out the mechanism of the medications, to elucidate the underlying pathophysiology that the medications reverse, and to move us towards developing a test that can identify which patients will respond to which medications.  Another track of my research uses PET and MRI to characterize clinically important aspects of mood disorders.  For example, past studies have focused on markers to distinguish bipolar and unipolar depression, or markers that are associated with suicidal ideation.

  • Noam Schneck, PhD

    • Assistant Professor of Clinical Medical Psychology (in Psychiatry)

    Dr. Schneck studies the way that people adapt to the suicide loss of a loved one. Specifically, his research aims to identify unconscious processes of coping with the loss that help people grow and adapt while also allowing them to remain engaged in current life demands. These unconscious processes are identified using a machine learning based approach to functional magnetic resonance brain imaging called neural decoding. The goal of this research is to ultimately develop a treatment technique that would entrain greater unconscious processing of the loss.

  • Elizabeth Bartlett, PhD

    • Assistant Professor of Clinical Neurobiology (in Psychiatry)

    Betsy is a biomedical engineer whose work focuses on development and use of state-of-the-art quantification techniques for in vivo human positron emission tomography (PET) brain imaging. These less invasive and non-invasive techniques simplify PET acquisition, minimize patient burden, and reduce cost, thereby reducing the barrier to entry for PET imaging, while preserving quantification accuracy. She is particularly interested in applying such methods to investigate biological mechanisms underlying the depressogenic effects of stress, and is currently doing so in multimodal PET/magnetic resonance imaging (MRI) studies, utilizing MRI modalities such as structural MRI (to derive brain volume and thickness) and MR spectroscopy (to quantify glutamate concentration). A list of Betsy’s publications can be found at:

Fellows and Assistant Research Scientists

  • Mike Schmidt, PhD

    • Postdoctoral Research Scientist

    Dr. Schmidt has a background in computer science and software engineering, and is currently a post-doctoral researcher working on improving neuroimaging methods. These methods are intended to better understand the temporal dynamics of brain states, as measured by functional MRI, and how those dynamics influence our moods and well-being. A specific methodological interest is in functional alignment strategies to improve multivoxel pattern analysis. Another is using dimensionality reduction and hidden Markov models to classify states and describe their changes over time. Publications are available at

  • Christina A. Michel, PhD

    • Paul Janssen Fellow in Translational Neuroscience Research

    Dr. Christina Michel is interested in the neural mechanisms underlying the processing of emotional stimuli and emotional memories in depressed and suicidal individuals. She received a B.A. in Psychology from Princeton University and a Ph.D. in Clinical Psychology from St. John’s University. Dr. Michel is currently a postdoctoral fellow working with Dr. John Mann and Dr. Lila Davachi. Dr. Michel’s present research utilizes functional magnetic resonance imaging (fMRI) to examine differences in the functioning and connectivity of the hippocampus and hippocampal-dependent networks during emotional memory paradigms in depressed individuals compared with healthy controls. Dr. Michel’s publications can be found here

  • Gjertrud Louise Laurell, PhD

    • Postdoctoral Researcher

    Gjertrud Louise Laurell, PhD, is a postdoctoral researcher working with kinetic modeling of brain Positron Emission Tomography (PET) data. Dr. Laurell received her PhD in Neuroscience from Copenhagen University, while working at the Neurobiology Research Unit (NRU) at Copenhagen University Hospital Rigshospitalet. While at the NRU, the focus of her work was development and evaluation of methods for analyzing PET experiments with pharmacological intervention. Dr. Laurell’s postdoctoral project focuses on non-invasive quantification of brain [18F]FDG PET using the novel quantification approach Source-to-Target Automatic Rotating Estimation (STARE).


    Laurell GL, Plavén-Sigray P, Johansen A, Raval NR, Nasser A, Madsen CA, Madsen J, Hansen HD, Donovan LL, Knudsen GM, Lammertsma AL, Ogden RT, Svarer C, Schain M. Kinetic models for estimating occupancy from single-scan PET displacement studies. Journal of Cerebral Blood Flow & Metabolism. 2023;43(9):1544-1556. DOI:10.1177/0271678X231168591

    Laurell GL, Plavén-Sigray P, Svarer C, Ogden RT, Knudsen GM, Schain M. Designing drug occupancy studies with PET neuroimaging: Sample size, occupancy ranges and analytical methods. NeuroImage. 2022;263:119620. DOI: 10.1016/j.neuroimage.2022.119620

    Laurell GL, Plavén-Sigray P, Jucaite A, Varrone A, Cosgrove KP, Svarer C, Knudsen GM, Karolinska Schizophrenia Project Consortium, Ogden RT, Zanderigo F, Cervenka S, Hillmer AT, Schain M. Nondisplaceable binding is a potential confounding factor in 11C-PBR28 translocator PET studies. The Journal of Nuclear Medicine. 2021; 62:412-417. DOI: 10.2967/jnumed.120.243717

  • Granville J. Matheson, PhD

    • Postdoctoral Researcher

    I am a postdoctoral researcher working in the Departments of Psychiatry and Biostatistics at Columbia University, and the Department of Clinical Neuroscience at Karolinska Institutet. For the past 12 years, I have been working with Positron Emission Tomography (PET), focusing on the reliability of quantified outcomes, replicability of results, as well as methodological improvements for making more optimal use of collected data. Most recently, I have been working alongside Prof. Todd Ogden on the development of novel kinetic modelling approaches making use of hierarchical models which borrow strength across multiple PET examinations at once to improve quantitative accuracy and inferential efficiency. I am also working on applying these new methodologies to derive novel clinical insights from existing datasets. I am interested in computational reproducibility and data sharing, and have been an active contributor to the BIDS specification for both PET and PET Preprocessing Derivatives. Finally, I am committed to open-source development of research tools, and am the primary author of R packages including kinfitr for PET kinetic modelling, as well as bloodstream which is a BIDS app for blood processing for PET data.


    Matheson, G. J., & Ogden, R. T. (2022). Simultaneous multifactor Bayesian analysis (SiMBA) of PET time activity curve data. Neuroimage, 256, 119195.

    Tjerkaski, J., Cervenka, S., Farde, L., & Matheson, G. J. (2020). Kinfitr—an open-source tool for reproducible PET modelling: validation and evaluation of test-retest reliability. EJNMMI research, 10, 1-11.

    Matheson, G. J. (2019). We need to talk about reliability: making better use of test-retest studies for study design and interpretation. PeerJ, 7, e6918.

    Matheson, G. J., Plavén-Sigray, P., Forsberg, A., Varrone, A., Farde, L., & Cervenka, S. (2017). Assessment of simplified ratio-based approaches for quantification of PET [11C] PBR28 data. EJNMMI research, 7(1), 1-6.

    Norgaard, M., Matheson, G. J., Hansen, H. D., Thomas, A., Searle, G., Rizzo, G., ... & Ganz, M. (2022). PET-BIDS, an extension to the brain imaging data structure for positron emission tomography. Scientific data, 9(1), 65.

Select Publications

  • Dynamic human brain imaging with the portable Positron Emission Tomography camera CerePET: comparison to a standard scanner Bartlett EA, Lesanpezeshki M, Anishchenko S, Shkolnik I, Ogden RT, Mann JJ, Beylin D, Miller JM, Zanderigo F Journal of Nuclear Medicine 2023; (in press)

  • In vivo serotonin transporter and 1A receptor binding potential and ecological momentary assessment (EMA) of stress in major depression and suicide Bartlett EA, Zanderigo F, Stanley B, Choo TH, Galfalvy HC, Pantazatos SP, Sublette ME, Miller JM, Oquendo MA, Mann JJ European Neuropsychopharmacology 2023; 70: 1-13

  • Ventral prefrontal serotonin 1A receptor binding: a neural marker of vulnerability for mood disorder and suicidal behavior? Pantazatos SP, Melhem N, Brent DA, Zanderigo F, Bartlett E, Lesanpezeshki M, Burke A, Miller JM, Mann JJ Molecular Psychiatry 2022; 27(10): 4136-4143

  • Serotonin Transporter Binding in Major Depressive Disorder: impact of serotonin system anatomy Bartlett EA, Zanderigo F, Shieh D, Miller JM, Hurley P, Rubin-Falcone H, Oquendo MA, Sublette ME, Ogden RT, Mann JJ Molecular Psychiatry 2022; 27(8):3417-3424

  • Source-to-Target Automatic Rotating Estimation (STARE) - a publicly-available, blood-free quantification approach for PET tracers with irreversible kinetics: Theoretical framework and validation for [18F]FDG Bartlett EA, Ogden RT, Mann JJ, Zanderigo F Neuroimage 2022; 249: 118901

  • Serotonin 1A Receptor Binding of [11C]CUMI-101 in Bipolar Depression with Positron Emission Tomography: Relationship to Psychopathology and Antidepressant Response Lan MJ, Zanderigo F, Pantazatos SP, Sublette ME, Miller J, Ogden RT, Mann JJ International Journal of Neuropsychopharmacology 2022; 25(7): 534-544

  • Large-Scale Network Dynamics in Neural Response to Emotionally Negative Stimuli Linked to Serotonin 1A Binding in Major Depressive Disorder Schneck N, Tu T, Rubin-Falcone H, Miller JM, Zanderigo F, Sublette ME, Oquendo MA, Stanley B, Burke A, Ochsner K, Sajda P, Mann JJ Molecular Psychiatry, 2021; 26: 2393–2401

  • Deficits of White Matter Axial Diffusivity in Bipolar Disorder Relative to Major Depressive Disorder: No Relationship to Cerebral Perfusion or Body Mass Index Lan MJ, Rubin-Falcone H, Sublette ME, Oquendo MA, Stewart JW, Hellerstein DJ, McGrath PJ, Zanderigo F, Mann JJ Bipolar Disorders, 2020; 22(3): 296-302

  • Brain serotonin transporter binding, plasma arachidonic acid and depression severity: A positron emission tomography study of major depression Gopaldas M, Zanderigo F, Zhan S, Ogden RT, Miller JM, Rubin-Falcone H, Cooper TB, Oquendo MA, Sullivan G, Mann JJ, Sublette ME J Affect Disord 2019; 257: 495-503

  • Variability in Suicidal Ideation is Associated with Affective Instability in Suicide Attempters with Borderline Personality Disorder Rizk MM, Choo TH, Galfalvy H, Biggs E, Brodsky BS, Oquendo MA, Mann JJ, Stanley B Psychiatry 2019; 82(2): 173-178

  • Quantifying Brain [18F]FDG Uptake Noninvasively by Combining Medical Health Records and Dynamic PET Imaging Data Roccia E, Mikhno A, Ogden T, Mann JJ, Laine A, Angelini E, Zanderigo F IEEE J Biomed Health Inform 2019 doi: 10.1109/JBHI.2018.2890459

  • 5-HT1A receptor, 5-HT2A receptor and serotonin transporter binding in the human auditory cortex in depression Steinberg LJ, Underwood MD, Bakalian MJ, Kassir SA, Mann JJ, Arango V J Psychiatry Neurosci 2019; 44(4): 1-8

  • Gray matter volumetric study of major depression and suicidal behavior Rizk MM, Rubin-Falcone H, Lin X, Keilp JG, Miller JM, Milak MS, Sublette ME, Oquendo MA, Ogden RT, Abdelfadeel NA, Abdelhameed MA, Mann JJ Psychiatry Res Neuroimaging 2019; 283: 16-23

  • Nonlinear Mixed-Effects Models for PET Data Chen Y, Goldsmith J, Ogden RT IEEE Trans Biomed Eng 2019; 66(3): 881-891

  • Cortisol Stress Response and in Vivo PET Imaging of Human Brain Serotonin 1A Receptor Binding Steinberg LJ, Rubin-Falcone H, Galfalvy HC, Kaufman J, Miller JM, Sublette ME, Cooper TB, Min E, Keilp JG, Stanley BH, Oquendo MA, Ogden RT, Mann JJ Int J Neuropsychopharmacol 2019; 22(5): 329-338

  • Kappa opioid receptor binding in major depression: A pilot study Miller JM, Zanderigo F, Purushothaman PD, DeLorenzo C, Rubin-Falcone H, Ogden RT, Keilp J, Oquendo MA, Nabulsi N, Huang YH, Parsey RV, Carson RE, Mann JJ Synapse 2018; 72(9): e22042

  • Longitudinal effects of cognitive behavioral therapy for depression on the neural correlates of emotion regulation Rubin-Falcone H, Weber J, Kishon R, Ochsner K, Delaparte L, Doré B, Zanderigo F, Oquendo MA, Mann JJ, Miller JM Psychiatry Res Neuroimaging 2018; 271: 82-90

  • In vivo relationship between serotonin 1A receptor binding and gray matter volume in the healthy brain and in major depressive disorder Zanderigo F, Pantazatos S, Rubin-Falcone H, Ogden RT, Chhetry BT, Sullivan G, Oquendo M, Miller JM, Mann JJ Brain Struct Funct 2018; 223(6): 2609-2625

  • [11C]arachidonic acid incorporation measurement in human brain: Optimization for clinical use Zanderigo F, Kang Y, Kumar D, Nikolopoulou A, Mozley PD, Kothari PJ, He B, Schlyer D, Rapoport SI, Oquendo MA, Vallabhajosula S, Mann JJ, Sublette ME Synapse 2018; 72(2)  

  • Statistical evaluation of test-retest studies in PET brain imaging Baumgartner R, Joshi A, Feng D, Zanderigo F, Ogden RT EJNMMI Res 2018; 8(1): 13

  • Altered effective connectivity in the default network of the brains of first-episode, drug-naïve schizophrenia patients with auditory verbal hallucinations Zhao Z, Li X, Feng G, Shen Z, Li S, Xu Y, Huang M, Xu D Frontiers 2018; 12:456

  • A Platform of Digital Brain Using Crowd Power Xu D, Dai F, Lu Y Frontiers of Information Technology and Electronic Engineering 2018; 19(1): 78-90

  • Quantification of Positron Emission Tomography Data Using Simultaneous Estimation of the Input Function: Validation with Venous Blood and Replication of Clinical Studies Bartlett EA, Ananth M, Rossano S, Zhang M, Yang J, Lin SF, Nabulsi N, Huang Y, Zanderigo F, Parsey RV, DeLorenzo C Mol Imaging Biol 2018; doi: 10.1007/s11307-018-1300-1

  • A hybrid deconvolution approach for estimation of in vivo non-displaceable binding for brain PET targets without a reference region Zanderigo F, Mann JJ, Ogden RT PLoS One 2017; 12(5): e0176636

  • Methods for scalar-on-function regression Reiss PT, Goldsmith J, Shang HL, Ogden RT Int Stat Rev 2017; 85(2): 228-249

  • Whole-transcriptome brain expression and exon-usage profiling in major depression and suicide: evidence for altered glial, endothelial and ATPase activity Pantazatos SP, Huang YY, Rosoklija GB, Dwork AJ, Arango V, Mann JJ Mol Psychiatry 2017; 22(5): 760-773

  • Altered Microstructure of Brain White Matter in Females with Anorexia Nervosa: a Diffusion Tensor Imaging Study Hu S, Feng H, Xu T, Zhang H, Zhao Z, Hu J, Qi H, Hu C, Zhang P, Lai J, Lu Q, Huang M, Xu W, Wei N, Mou T, Lu S, Lu J, Zhou W, Xu Y, Xu D (Nature) Scientific Reports, 2017

  • White matter correlates of impaired attention control in major depressive disorder and healthy volunteers Rizk MM, Rubin-Falcone H, Keilp J, Miller JM, Sublette ME, Burke A, Oquendo MA, Kamal AM, Abdelhameed MA, Mann JJ J Affect Disord 2017; 222: 103-111

  • Relationship of recent stress to amygdala volume in depressed and healthy adults Sublette ME, Galfalvy HC, Oquendo MA, Bart CP, Schneck N, Arango V, Mann JJ J Affect Disord 2016; 203: 136-142

  • Isoform-level brain expression profiling of the spermidine/spermine N1 Acetyltransferase1 (SAT1) gene in major depression and suicide Pantazatos SP, Andrews SJ, Dunning-Broadbent J, Pang J, Huang YY, Arango V, Nagy PL, Mann JJ Neurobiol Dis 2015; 79: 123-34

  • Proton MRS and MRSI of the brain without water suppression Dong Z Prog Nucl Magn Reson Spectrosc 2015; 86-87: 65-79. Review.

  • Prediction of individual season of birth using MRI Pantazatos SP Neuroimage 2014; 88: 61-8

  • Brain serotonin 1A receptor binding as a predictor of treatment outcome in major depressive disorder Miller JM, Hesselgrave N, Ogden RT, Zanderigo F, Oquendo MA, Mann JJ, Parsey RV Biol Psychiatry 2013; 74(10): 760-7