# A dense longitudinal multimodal single-subject rs-fMRI dataset acquired by self-administered scanning

**Authors:** Evgeny D. Petrovskiy

PMC · DOI: 10.1038/s41597-026-06879-z · 2026-02-21

## TL;DR

A single person collected extensive brain scans over 11 months using a clinical MRI scanner, creating a dataset for studying brain function and variability over time.

## Contribution

This study provides a unique, dense longitudinal multimodal dataset collected through self-administered MRI scans, enabling methodological and educational applications.

## Key findings

- The dataset includes 85 hours of resting-state fMRI and multiple other modalities collected over 11 months.
- Self-administered scanning achieved sub-3 mm positioning reproducibility in later sessions.
- Quality control identified 58 hours of low-motion data suitable for analysis.

## Abstract

Dense longitudinal neuroimaging usually requires substantial institutional resources, yet can also be achieved by an individual using standard clinical MRI infrastructure. This work presents a multimodal single-subject dataset comprising 85 hours of resting-state fMRI acquired over 11 months, including 51.6 hours under a standardized protocol (paired eyes-open/-closed runs, 128 sessions over 7.5 months). Additional data include 195 T1-weighted structural scans, 54 diffusion MRI sessions, physiological recordings, pre-session behavioral assessments, and detailed medication and lifestyle logs. Scans were collected primarily via self-administered acquisition on a clinical 3 T system, with sub-3 mm between-session positioning reproducibility observed in later sessions. Quality control identified 58 hours of low-motion data (mean framewise displacement <0.2 mm), with higher-motion runs occurring predominantly during sleep. The acquisition period included antidepressant dose changes and seasonal variation, forming a single-subject naturalistic context with collinear factors that preclude causal inference. The dataset follows the BIDS standard and is intended for methodological development, reliability analyses, preprocessing benchmarking, and educational use.

## Full-text entities

- **Diseases:** attention failures (MESH:D051437), Sleepiness (MESH:D000077260), claustrophobia (MESH:D010698), withdrawal (MESH:D013375), movement disorders (MESH:D009069)
- **Chemicals:** Alcohol (MESH:D000438), ABV (MESH:C036986), Venlafaxine (MESH:D000069470), caffeine (MESH:D002110), PVT (-)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Figures

2 figures with captions in the complete paper: https://tomesphere.com/paper/PMC13035833/full.md

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Source: https://tomesphere.com/paper/PMC13035833