The following is a text template that may be useful for briefly describing the NSD dataset in a paper that uses the NSD data. Of course, you may need to modify or expand as necessary.
Natural Scenes Dataset
A detailed description of the Natural Scenes Dataset (NSD; http://naturalscenesdataset.org ) is provided elsewhere {cite Allen et al., Nature Neuroscience, 2021}. The NSD dataset contains measurements of fMRI responses from 8 participants who each viewed 9,000–10,000 distinct color natural scenes (22,000–30,000 trials) over the course of 30–40 scan sessions. Scanning was conducted at 7T using whole-brain gradient-echo EPI at 1.8-mm resolution and 1.6-s repetition time. Images were taken from the Microsoft Common Objects in Context (COCO) database {cite Lin 2014}, square cropped, and presented at a size of 8.4° x 8.4°. A special set of 1,000 images were shared across subjects; the remaining images were mutually exclusive across subjects. Images were presented for 3 s with 1-s gaps in between images. Subjects fixated centrally and performed a long-term continuous recognition task on the images. The fMRI data were pre-processed by performing one temporal interpolation (to correct for slice time differences) and one spatial interpolation (to correct for head motion). A general linear model was then used to estimate single-trial beta weights. Cortical surface reconstructions were generated using FreeSurfer, and both volume- and surface-based versions of the beta weights were created.
Natural Scenes Dataset (extremely abbreviated)
The NSD dataset contains measurements of 7T fMRI responses (1.8 mm, 1.6 s) from 8 participants who each viewed 9,000–10,000 distinct color natural scenes (22,000–30,000 trials). Subjects fixated centrally and performed a long-term continuous recognition task on the images.Natural Scenes Dataset Synthetic Experiment
The NSD synthetic dataset is an addition to the main NSD experiment. The dataset contains measurements of fMRI responses from the same 8 participants of the main NSD experiment. Participants viewed 284 carefully controlled synthetic images in one additional 7T fMRI scan session. Images were presented for 2 s with 2-s gaps in between images. Subjects performed a fixation task and a one-back task in alternating runs.
Other snippets of text that might be useful as a template:
The dataset includes additional measures including structural (T1, T2), diffusion, and resting-state data.
In this paper, we used the 1.8-mm volume preparation of the NSD data and version 3 of the NSD single-trial betas (betas_fithrf_GLMdenoise_RR).
We used the ‘nativesurface’ preparation of the NSD betas.
We used the nsd01–nsd10 scan sessions from all 8 NSD subjects.
If you make use of the NSD dataset, please cite the NSD data paper:
Allen, St-Yves, Wu, Breedlove, Prince, Dowdle, Nau, Caron, Pestilli, Charest, Hutchinson, Naselaris*, & Kay*. A massive 7T fMRI dataset to bridge cognitive neuroscience and artificial intelligence. Nature Neuroscience (2021).
If you make use of the NSD synthetic dataset, please also cite the NSD synthetic paper:
In addition, please acknowledge the NSD funding sources using wording similar to:
Collection of the NSD dataset was supported by NSF IIS-1822683 and NSF IIS-1822929.