Human research · Neuroimaging
From anatomy
to observed activity.
Inspect real imaging data, preserve its spatial and temporal context, and continue in an editable research notebook.
Adult movie-watching cohort
Loading real fMRI participants
Inspect one participant, then compare functional connectivity across recordings using the same atlas and signal stage.
OpenNeuro ds000228 / Nilearn preprocessed BOLD, paired with TemplateFlow Schaefer 100 in MNI152NLin2009cAsym. A demonstration of the selected individual recording. Cohort comparisons below use separate participants watching the same movie.
The image viewer shows the published BOLD volume. This choice changes the time series, correlation and notebook input below; it does not rerun or undo upstream fMRIPrep.
Loading participant ROI signals…
Your recordings
Import ROI or sensor time series
CSV / TSV: first row contains unique ROI or channel IDs; remaining rows contain samples. An optional first column named time_s supplies timestamps in seconds. Analysis stays in this browser until you choose to create a notebook.
2–256 channels · 3–20,000 uniformly spaced samples · ≤1 million values · 4 MiB. Prepare continuous epochs explicitly. EDF/BDF/FIF, sensor positions, source localization and artifact pipelines are not yet integrated.
Inspect a BIDS-style JSON sidecar
Metadata only; it does not silently change the sampling settings above.
Available now, with explicit boundaries
| Research area | Implemented | Not yet integrated |
|---|---|---|
| MRI / fMRI | NIfTI viewing, same-space example atlas, real ROI sample, signed FC, time series, notebooks, multi-participant quality checks and FC comparisons | DICOM conversion, registration, full fMRI preprocessing, raw-data cohort preprocessing |
| EEG / MEG | CSV / TSV / JSON channel series, sampling checks, waveform, spectra, correlation | EDF/BDF/FIF, montage/topography, source localization, artifact rejection |
| Connectivity / dynamics | Versioned biological structures, labeled SC/FC matrix inspection, structural simulation notebooks | Automatic fitting to empirical data, paired multimodal inference, clinical prediction |