official live training from the CONN team
407 researchers from 215 institutions across 34 countries
students, postdocs, and researchers trained in the CONN workshop over the last five years (2021-2025)
American University, USA
Arizona State University, USA
Auburn University, USA
BarcelonaBeta Brain Research Center, Spain
Beth Israel Deaconess Medical Center, USA
Bielefeld University, Germany
Boston University, USA
Brigham and Women's Hospital, USA
Brown University, USA
Cambridge University, UK
Cardiff University, UK
Carelton University, Canada
Carl von Ossietzky University Oldenburg, Germany
Catholic University of Korea, South Korea
Center for Mind/Brain Sciences, Italy
Central Institute of Mental Health, Germany
Centre Hospitalier Universitaire de Saint Etienne, France
Champalimaud Foundation, Portugal
Charité-Universitätsmedizin Berlin, Germany
Charles University, Czech Republic
Chiba University, Japan
Child and Adolescents Health Service, Australia
Chonnam National University, South Korea
Christ University, India
Christian Albrecht University of Kiel, Germany
Colorado State University, USA
Columbia University, USA
Commonwealth Scientific and Industry Research Organisation, Australia
Concordia University, Canada
Cornell University, USA
Dartmouth College, USA
Dell Medical School, USA
Dr D Y Patil Medical College, India
Duke University, USA
Emma Pendleton Bradley Hospital
Emory University, USA
Federal University of Rio Grande do Norte, Brazil
Fundación Intecnus, Argentina
George Mason University, USA
Georgetown University, USA
Ghent University, Belgium
Griffith University, Australia
Hannover Medical School, Germany
Harvard University, USA
Hospital Clínico San Carlos, Spain
Hospital Italiano de Buenos Aires, Argentina
Hospital Universitari Joan XXIII, Spain
Icahn School of Medicine at Mount Sinai, USA
Indraprastha Institute of Information Technology, India
Institut National de la Santé Et de la Recherche Médicale, France
Institute for Advanced Studies (IUSS), Italy
Jagiellonian University, Poland
Johns Hopkins University, USA
Keio University, Japan
Kessler Foundation, USA
King Saud University, Saudi Arabia
King's College London, UK
Konkuk University, South Korea
KU Leuven University, Belgium
Kyoto University, Japan
Kyung Hee University, South Korea
Leibniz Institute for Neurobiology Magdeburg, Germany
Ludwig-Maximilians-Universität München, Germany
Mahidol University, Thailand
Marburg University, Germany
Massachusetts General Hospital (MGH), USA
Max Delbruck Center for Molecular Medicine, Germany
Max Planck Institute for Human Cognitive and Brain Sciences, Germany
McGill University, Canada
McLean Hospital, USA
McMaster University, Canada
Medical University of South Carolina, USA
Medical University Vienna, Austria
MIT (Massachusetts Institute of Technology), USA
Nanyang Technology University, Singapore
National Cheng Kung University Hospital, Taiwan
National Hospital for Paraplegia, Spain
National Hospital Organization Tokyo Medical Center, Japan
National Institute of Mental Health (NIMH), USA
National Institutes for Quantum Science and Technology, Japan
National Institutes of Information and Communications Technology, Japan
New York University Abu Dhabi, UAE
New York University, USA
Newcastle University, UK
Northeastern University, USA
Northwell Health, USA
Ohio University, USA
Örebro University, Sweden
Osaka University, Japan
Otto von Guericke University Magdeburg, Germany
Paris Brain Institute, Prance
Penn State University, USA
Instituto de Neurobiología UNAM, Mexico
Polish Academy of Sciences, Poland
Pontificia Universidad Javeriana, Colombia
Radboud University, Netherlands
Redeemer University, Canada
Reichman University, Israel
Rice University, USA
Royal Holloway University of London, UK
Royal's Institute of Mental Health Research, Canada
Ruhr-Universität Bochum, Germany
RWTH Aachen University, Germany
Samsung Medical Center, South Korea
San Diego State University, USA
Sapienza University of Rome, Italy
Scintillon Institute, USA
Semmelweis University, Hungary
Seoul National University, South Korea
Soonchunhyang University, South Korea
Spaulding Rehabilitation Hospital Boston, USA
St Jude Children's Research Hospital, USA
St Vincent's Hospital, Australia
Stanford University, USA
Technical University Dresden, Germany
Technical University of Munich, Germany
Texas A&M University, USA
Texas Woman's University, USA
Thomas Jefferson Hospital, USA
Ulsan National Institute of Science and Technology, South Korea
Umeå University, Sweden
Universidade de Santiago de Compostela, Spain
Università degli studi di Genova, Italy
Università degli Studi di Padova, Italy
Università degli Studi di Parma, Italy
Università degli Studi di Torino, Italy
Università degli Studi di Trento, Italy
Universitat Internacional de Catalunya, Spain
Universitat Jaume I, Spain
Universitat Pompeu Fabra, Spain
Universitätsklinik Regensburg, Germany
Universitätsmedizin Greifswald, Germany
Université Catholique de Louvain, Belgium
Université de Bordeaux, France
Université de Montréal, Canada
Université du Québec à Montréal, Canada
Université Grenoble Alpes, France
University College London (UCL), UK
University Health Network, Canada
University Hospital Bonn, Germany
University Hospital Jena, Germany
University Medical Center Goettingen, Germany
University Medical Center Groningen, Netherlands
University of Alabama at Birmingham, USA
University of Alabama, USA
University of Alberta, Canada
University of Amsterdam, Netherlands
University of Arizona, USA
University of Bern, Switzerland
University of British Columbia, Canada
University of California Irvine, USA
University of California Los Angeles, USA
University of California San Diego, USA
University of California San Francisco, USA
University of California Davis, USA
University of Cincinnati, USA
University of Colorado Anschutz, USA
University of Colorado Boulder, USA
University of Connecticut, USA
University of Delaware, USA
University of Deusto, Spain
University of Exeter, UK
University of Florida, USA
University of Freiburg, Germany
University of Geneva, Switzerland
University of Glasgow, UK
University of Haifa, Israel
University of Hong Kong, China
University of Illinois, USA
University of Innsbruck, Austria
University of Kentucky, USA
University of Liverpool, UK
University of Ljubljana, Slovenia
University of Luzern, Switzerland
University of Maryland Baltimore, USA
University of Maryland College Park, USA
University of Massachussets, USA
University of Michigan, USA
University of Minnesota, USA
University of Missouri, USA
University of Montreal, Canada
University of Muenster, Germany
University of Nebraska, USA
University of Newcastle, Australia
University of North Carolina at Chapel Hill, USA
University of North Carolina at Greensboro, USA
University of Nottingham, UK
University of Oldenburg, Germany
University of Oregon, USA
University of Oslo, Norway
University of Ottowa, Canada
University of Pittsburgh, USA
University of Queensland, Australia
University of Rochester, USA
University of Southern California, USA
University of Texas, USA
University of the Sunshine Coast, Australia
University of Tokyo, Japan
University of Toronto Scarborough, Canada
University of Toronto, Canada
University of Utah, USA
University of Vienna, Austria
University of Warsaw, Poland
University of Waterloo, Canada
University of Wisconsin Milwaukee, USA
University of Zürich, Switzerland
Uppsala University, Sweden
Upstate Medical University, USA
Uskudar University, Turkey
Vanderbilt University, USA
Virginia Tech University, USA
Wake Forest University, USA
Washington University in St. Louis, USA
West Virginia University, USA
Yale University, USA
Join this global community and learn how to best design, run, quality-control, interpret, and report functional connectivity MRI analyses at the next CONN workshop online, starting Sept 10th 2026!
next CONN workshop:
Course program details
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Course summary
The CONN Workshop is the official live training course for functional connectivity MRI analysis using CONN. It is recommended for students, postdocs, researchers, analysts, and labs that need practical training in fMRI connectivity analyses, including preprocessing, denoising, quality control, connectivity modeling, group-level inference, and interpretation. The course is taught by Alfonso Nieto-Castanon, neuroimaging researcher and lead developer of CONN, and is suitable for both new and experienced users.
Recommended for
The CONN Workshop is recommended for students, postdocs, researchers, analysts, and labs who need practical training in functional connectivity MRI analysis.
PIs and lab directors may consider recommending the CONN Workshop to trainees or research staff who will be responsible for preprocessing, denoising, quality control, connectivity modeling, statistical inference, or interpretation of fMRI data.
It is particularly relevant for:
researchers beginning a functional connectivity MRI or connectomics project
students or postdocs responsible for analyzing resting-state or task-based fMRI data
lab members learning how to preprocess, denoise, quality-control, and analyze fMRI data in CONN
PIs seeking structured fcMRI training for trainees or research staff
clinical, cognitive, developmental, psychiatric, and translational neuroscience labs using functional connectivity methods
experienced CONN users who want to strengthen their workflow, update their knowledge, or learn advanced techniques such as gPPI, ICA, graph measures, fc-MVPA, dynamic connectivity, scripting, or HPC workflows
Course description
Resting-state functional connectivity has taken the brain imaging community by storm. Five to ten minutes of MRI data collection from almost any subject or patient can reveal organized systems of activity in the brain that can be used in a wide variety of ways for basic and clinical research, and even to guide non-invasive brain stimulation.
CONN is one of the most popular software packages for functional connectivity Magnetic Resonance Imaging (fcMRI) analyses of resting state and task fMRI data, with over 7,500 published studies to date using CONN. It is ranked in the top 1% most frequently viewed and downloaded neuroimaging tools in NITRC, and it enjoys a large and active user community, with over 2,000,000 page-views and 15,000 user-support posts.
In this workshop the neuroimaging researcher and lead developer of CONN, Alfonso Nieto-Castanon, brings his exceptional expertise to offer a course covering all aspects of functional connectivity Magnetic Resonance Imaging (fcMRI) analyses. The course welcomes both new and experienced CONN users. It covers basic and advanced features of CONN presented alongside a comprehensive review of key topics and state-of-the-art methods in functional connectivity analyses. The course combines presentations, hands-on practice, open Q&A, and guided exercises to help participants perform robust and reproducible connectivity analyses on their own datasets. Course attendees receive a certificate of completion at the end of the workshop.
The CONN workshop is offered online through Zoom at least once per year (sometimes twice per year, during the Spring and Fall terms, depending on faculty availability).
The workshop is presented over five weeks, in ten live 3.5-hour classes held twice per week. Live meetings are recorded and made available to participants during the course and up to one month after the course ends for review. Optional practice assignments and offline Q&A are also available every week throughout the course.
In some years, an accelerated one-week in-person version of the CONN workshop is also offered at the Martinos Center for Biomedical Imaging in Boston. Course faculty and contents are the same as in the online workshop, except that homework assignments and video recordings are not offered in the in-person format due to the compressed schedule.
Please check the course schedule to see which workshop dates and formats are currently available.
Course contents include:
Essential topics in CONN such as data import, fMRI preprocessing pipelines, data denoising and quality control procedures, seed-based and ROI-to-ROI functional connectivity measures, or group-level General Linear Model (GLM) analyses and inferences
The theory and practice of all specialized functional connectivity methods available in CONN, including generalized Psycho-Physiological Interaction models, temporal modulation analyses, Independent Component Analyses, voxel-to-voxel connectivity measures, network- and cluster- level statistics, graph theory, functional connectivity MultiVariate Pattern Analyses, or dynamic connectivity analyses
Discussions about many practical aspects of fcMRI analyses, covering topics such as clinical applications of functional connectivity, how to design and report GLM analyses addressing specific research questions, or how to create batch scripts and use parallelization options in High Performance Computing environments
Use these links to explore the course program in more detail, check the course schedule, or register for the next CONN workshop.
Course speakers:
Alfonso Nieto-Castanon, Ph.D. (CNRLab/BU/MIT)
Susan Whitfield-Gabrieli, Ph.D. (MGH/Harvard/NEU/MIT)
Robert L. Savoy, Ph.D. (MGH/Harvard)
FAQ
1. How many individuals are accepted into the course?
Due to the highly interactive nature of this course only 40-50 people are accepted into each workshop. We apologize in advance if we cannot accommodate all who wish to attend
2. Are there any differences between the online/virtual and the in-person course?
Faculty, course contents, and live-class hours are identical in the two courses. Other than the venue, the only difference is that shared-documents or video-recordings are not offered during the in-person course due to time and logistic constraints
3. How much does the course cost?
Registration fees vary between €1,000 and €2,000 depending on course and applicable discounts. See course registration for details
4. Do postdocs qualify for the student rate?
No, sorry, only full-time graduate students qualify for the student rate (postdocs qualify for the academic rate)
5. I cannot pay by credit card. Do I have any other options?
Yes, you may request an invoice and pay by bank transfer. Initiate your registration normally and send an email to the course administrator requesting a bank transfer option. Please provide your institution details to be included in your invoice, and allow additional time (up to 5 days) for the transfer to be processed
6. When does registration close?
Registration automatically closes when a course is fully booked. Many registrations take place during the last few weeks before the start of the course. Consider registering earlier to avoid stress and guarantee your place in the workshop
7. How do I prepare for the course?
Before the start of the course you will be asked to prepare your computer and download a sample dataset using the instructions described in the computer setup section. You will also be asked to provide an informal biosketch (no more than two paragraphs in length), to be distributed to the faculty and to other course participants, briefly describing your background, experience, and what you most hope to get out of the program. A few days before the start of the course you will receive a welcome email with instructions to obtain your login credentials and access the course materials
8. I have a conflict and cannot attend some of the classes. Can I view the class recordings later?
Of course, in the online/virtual course all live Zoom meetings are recorded and uploaded to the course website after each class so participants may review them later (these recordings can be viewed at any time during the course and up to one month after the course ends)
9. I already have a dataset that I am working on. Can I use this during the course instead of the sample dataset?
Yes, of course! Using your own data during the course is highly encouraged (please note that due to time constraints particularly in the in-person course we may have limited ability to address or fix issues specific to your own dataset if we are not made aware of these well in advance)
10. I have some questions about my own analyses or data. Is it possible to get your comments on these?
Yes, of course! In addition to in-class Q&A, there is an Open Questions shared document where you can post any questions that you would like us to address during the course. We will try to address some of those questions directly during the live class hours when the topics most relevant to each question are discussed, but otherwise we will answer them in the same shared document (e.g. if the questions are too specific or if they require us to take a closer look at your data)
Looking for broader institutional training?
Centers, departments, imaging cores, and research institutes interested in supporting multiple labs through CONN training or broader educational partnerships are welcome to contact us to discuss available options.
Documentation: read CONN's manual and find installation and configuration instructions
Support: ask questions about CONN, report bugs or request features
Tutorials: find self-guided tutorials to learn about CONN and start using it right away