Attention-deficit/hyperactivity disorder (ADHD) is the most common neurodevelopmental disorder, affecting 5-10% of children worldwide. It is typically diagnosable by primary school age and persists into adulthood in about half of cases. The disorder is associated with significant distress and dysfunction in daily life for patients and families, and to high direct and indirect social costs.

The diagnostic, prognostic, and treatment decisions in patients with ADHD are primarily based on clinical judgment, as biomarkers to support clinicians have not yet been identified. One of the aims of neuroimaging in ADHD is to provide such biomarkers to advance personalized medicine.

The Clínica Universidad de Navarra Methylphenidate (CUNMET) Study was conducted at the outpatient unit of the Department of Psychiatry and Clinical Psychology at Clínica Universidad de Navarra in Pamplona (Navarra, Spain) between 2017-2021 as a proof-of -concept examination of the neural correlates of differential treatment response to stimulants (methylphenidate and lisdexamfetamine) in boys and girls with ADHD treated in a naturalistic context. Magnetic resonance imaging (MRI) data were acquired using a 3 Tesla Siemens MAGNETOM Skyra scanner, and included anatomical (MPRAGE), resting-state functional magnetic resonance imaging (R-fMRI), and perfusion/arterial spin labeling (ASL). The design of the study and data analysis were informed by consultations by colleagues from the Department of Child and Adolescent Psychiatry at NYU Grossman School of Medicine, the Center for the Developing Brain at the Child Mind Institute, and the Center for Biomedical Imaging and Neuromodulation at the Nathan Kline Institute, all based in New York (USA).

The study recruited 68 boys and girls with ADHD (ages 7-17) divided into four groups: [1] responders to methylphenidate (MPH group, n=21), [2] non-responders to methylphenidate who later responded to lisdexamfetamine (LDX group, n=21), [3] non-responders to stimulants who responded to guanfacine, a non-stimulant medication (GFC group, n=3), and [4] treatment-naive patients (NAIVE, n=23, 8 of whom underwent pre- and post-treatment scans). The study was initially planned to recruit a sample of N=80 (n=20/group), which was not attained. The statistical analyses comprised cross-sectional comparisons of anatomically-registered R-fMRI data from 56 subjects (18 MPH, 18 LDX, 20 NAIVE); the remaining data were not used due to small subgroup sample size, or sub-standard data quality (due to head motion and/or artifacts or incidental findings).

The uploaded dataset, organized according to Brain Imaging Data Structure (BIDS) format includes de-identified and de-faced brain images (MPRAGE, R-fMRI, and ASL) and de-identified phenotypic data from the 51 subjects for whom explicit consent for open-science sharing of data was obtained (of whom 44 were included and 7 were excluded from the analyses conducted by the CUNMET research team).

The CUNMET study was ethically reviewed and approved by the Ethics Committee for Medications Research of Navarra (Spain) (Comité de Ética de la Investigación con medicamentos, CEIm de Navarra) on June 21, 2017, with the code CUNMET-2017-01 EO17/11, which also approved an amended protocol on May 22, 2019. This study was compliant with the research ethics principles of the Declaration of Helsinki (seventh edition, 2013), taking into account the specific principles for research with children and adolescents. Parents agreeing to their child’s participation were asked to read and sign an informed consent form, explicitly providing their consent for an fMRI scan, a blood test (if applicable, including genetic tests), and public sharing of the de-identified clinical and neuroimaging data.

The study was also registered as a ‘post-authorization study with a design different from a prospective follow-up’ by the Spanish Agency of Drugs and Medical Products (Agencia Española de Medicamentos y Productos Sanitarios, AEMPS) on March 27, 2017, with the registration code CUN-MET-2017-01 (the registration protocol included details on the overarching hypotheses, goals, and methods, without preprocessing and statistical analysis details). The statistical group analysis plan was registered at Open Science Framework after the recruitment had already started and before statistical analyses were conducted.

The research procedures of the CUNMET study (all the fMRI scans and some extra neuropsychological tests) were supported by private funds from the Department of Psychiatry and Medical Psychology, Clínica Universidad de Navarra (Fondo de Reservas N.2222, PI Dr. de Castro-Manglano).

Data Release Download

The data are available for download in an Amazon Web Services S3 bucket: s3://fcp-indi/data/Projects/CUNMET/

Each file in the S3 bucket can only be accessed using HTTP (i.e., no ftp or scp ). You can obtain a URL for each desired file and then download it using an HTTP client such as a web browser, wget, or curl. Each file can only be accessed using its literal name - wildcards (i.e. "*") will not work.

Here are the links of every files in S3 bucket: AWS Links (right click and save). In combination of the list, a simple script will download everything.

There are file transfer programs that can handle S3 natively and will allow you to navigate through the data using a file browser. Cyberduck is one such program that works with Windows and Mac OS X (New Cyberduck version might not work, please try version 5.03.). Cyberduck also has a command line version that works with Windows, Mac OS X, and Linux. Instructions for using the Cyberduck program are as follows:


Project lead: Principal investigator: Core Research Team: Data Organization:

Usage Agreement


Consistent with the policies of the CUNMET Study, and as approved by the local Ethics Committee, data usage is unrestricted for non-commercial research purposes. We kindly request that the specific datasets included in analyses be specified appropriately, and that their funding sources be acknowledged. As per INDI protocol, we simply require that users register with the NITRC and CUNMET Study to gain access.


Note: You must be logged into NITRC to download the CUNMET Study dataset.

Phenotypic Dataset

Phenotypic Dataset

Phenotypic Key

Phenotypic Key

Key explaining the values used for phenotypic and quality control variables in the sample's phenotypic dataset file.