Extension of the dataset published in Hanke et al. (2014; doi:10.1038/sdata.2014.3) with additional acquisitions for 15 of the original 20 particpants. These additions include: retinotopic mapping, a localizer paradigm for higher visual areas (FFA, EBA, PPA), and another 2h movie recording with 3T full-brain BOLD fMRI with simultaneous 1000 Hz eyetracking.

The StudyForrest project centers around the use of the movie Forrest Gump, which provides complex sensory input that is both reproducible and is also richly laden with real-life-like content and contexts. Since its initial release, the StudyForrest dataset has grown and been extended substantially, and now encompasses many hours of fMRI scans, structural brain scans, eye-tracking data, and extensive annotations of the movie. It is a one-of-a-kind resource for studying high-level cognition in the human brain under complex, natural stimulation. The versatility of the provided data (some individuals have nearly ten hours of fMRI data) enables studies far beyond this main focus. This covers a vast range from studies of low-level signal properties and brain structure, to sensory integration and attentional processes, to computational modeling of representational spaces and brain area interactions.

This dataset contains the annotation of speech spoken in the research cut (Hanke et al. 2014; Hanke et al., 2016) of the movie "Forrest Gump" (Zemeckis, 1994) and its audio-description that was broadcast as an additional audio track (Koop et al., 2009) for visually impaired listeners on Swiss public television. The corresponding paper is hosted on github (https://github.com/psychoinformatics-de/studyforrest-paper-speechannotation) and published in f1000research (https://doi.org/10.12688/f1000research.27621.1).

Collection description

Subject species

homo sapiens

Modality

fMRI-BOLD

Cognitive paradigm (task)

film viewing

Map type

Z

A denoised audio-visual movie watching fMRI data in studyforrest dataset

Note: This dataset is compatible with the BIDS v1.3.0-dev as a standalone derivative dataset. Due to that the OpenNeuro.org does not support the BIDs v1.3.0 yet (_desc-

Source data

We here provide a denoised version of the 3T movie-watching fMRI raw data in the studyforrest project (https://openneuro.org/datasets/ds000113). The raw data was originally hosted on OpenfMRI.org as ds000113d. However, ds000113d on OpenfMRI.org has been combined along with other related datasets and now is simply referred to as ds000113 on OpenNeuro.org. For more information about the studyforrest project visit: http://studyforrest.org.

Pipeline description

A four-step denoising procedure were applied on the movie-watching fMRI data in the studyforrest dataset, producing a denoised version of that.
1. Preprocessing: motion correction, slice timing correction, brain extraction, high-pass temporal filtering (200s cutoff) and OPTIONAL spatial smoothing (Gaussian kernel; FWHM = 5 mm) with FEAT in FSL v6.00
2. ICA decomposition: with FSL’s MELODIC v3.15
3. IC manual classification
4. Artefacts removal: with fsl_regfilt in FSL’s MELODIC v3.15
Source code can be found at https://github.com/xingyu-liu/studyforrest_denoise.

Dataset content overview

After the four-step denoising procedure, 4 kinds of data were produced for each run of each participant.
1. the denoised fMRI data
./sub-xx/ses-movie/func/sub-xx_ses-movie_task-movie-run-x_desc-denoisedSm5/denoisedUnsm_bold.nii.gz
2. spatial maps of decomposed ICs
./sub-xx/ses-movie/func/sub-xx_ses-movie_task-movie-run-x_desc-MELODICSm5/MELODICUnsm_components.nii.gz
3. timeseries of decomposed ICs
./sub-xx/ses-movie/func/sub-xx_ses-movie_task-movie-run-x_desc-MELODICSm5/MELODICUnsm_mixing.tsv
4. Labels of decomposed ICs
./sub-xx/ses-movie/func/sub-xx_ses-movie_task-movie-run-x_desc-MELODICSm5/MELODICUnsm_componentLabels.txt

This component contains the data of the analysis that we ran as a validation of the annotation of speech spoken in the research cut (Hanke et al., 2016) of the movie "Forrest Gump" (Zemeckis, 1994) and its audio-description. The corresponding paper is hosted on github (https://github.com/psychoinformatics-de/studyforrest-paper-speechannotation) and published in f1000research (https://doi.org/10.12688/f1000research.27621.1).

Response to ambient music exceeds the mean of the responses to other musical genres.

Collection description

The twenty participants were repeatedly stimulated with a total of 25 music clips, with and without speech content, from five different genres using a slow event-related paradigm. The data release includes raw fMRI data, as well as precomputed structural alignments for within-subject and group analysis. In addition to fMRI, simultaneously recorded cardiac and respiratory traces, as well the complete implementation of the stimulation paradigm, including stimuli, are provided. An initial quality control analysis reveals distinguishable patterns of response to individual genres throughout a large expanse of areas known to be involved in auditory and speech processing.

Subject species

homo sapiens

Modality

fMRI-BOLD

Cognitive paradigm (task)

auditory scene perception

Map type

Z

Response to heavy metal exceeds the mean of the responses to other musical genres.

Collection description

The twenty participants were repeatedly stimulated with a total of 25 music clips, with and without speech content, from five different genres using a slow event-related paradigm. The data release includes raw fMRI data, as well as precomputed structural alignments for within-subject and group analysis. In addition to fMRI, simultaneously recorded cardiac and respiratory traces, as well the complete implementation of the stimulation paradigm, including stimuli, are provided. An initial quality control analysis reveals distinguishable patterns of response to individual genres throughout a large expanse of areas known to be involved in auditory and speech processing.

Subject species

homo sapiens

Modality

fMRI-BOLD

Cognitive paradigm (task)

auditory scene perception

Map type

Z

This dataset contains key characteristics about the data described in the Data Descriptor A manually denoised audio-visual movie watching fMRI dataset for the studyforrest project. Contents:

    1. human readable metadata summary table in CSV format


    2. machine readable metadata file in JSON format 


      Versioning Note:Version 2 was generated when the metadata format was updated from JSON to JSON-LD. This was an automatic process that changed only the format, not the contents, of the metadata.

Extension of a matching fMRI dataset (Sengupta, et al., 2017; OpenFMRI ds000113c) on participants performing a central fixation task while being stimulated with oriented visual gratings. This dataset extends the previous one with acquisitions for 3 matching spatial resolutions (1.4, 2.0, and 3.0 mm) at 3T (complementing the previous 7T acquisitions at 0.8, 1.4, 2.0, and 3.0 mm). Five of the total of seven participants are identical in both datasets. All participants are part of the studyforrest.org project.

This repository contains the fMRI data, annotations, analysis scripts to generate the results, and results in Häusler C.O. & Hanke M. (submitted) as Datalad datasets (https://github.com/datalad).

geography, room geography, new setting, old setting > body, bodypart, face & head, object, female person, male person

Collection description

This collection comprises unthresholded z-maps of seven contrasts aiming to isolate the "Parahippocampal Place Area" by reusing the audio-only version of the movie "Forrest Gump" as part of the studyforrest-dataset (studyforrest.org; Hanke et. al, 2014, A high-resolution 7-Tesla fMRI dataset from complex natural stimulation with an audio movie). For further information feel free to send an email to der.haeusler@gmx.net

Subject species

homo sapiens

Modality

fMRI-BOLD

Analysis level

group

Cognitive paradigm (task)

audio narrative

Map type

Z

FSL5.0

Collection description

This collection comprises unthresholded z-maps of seven contrasts aiming to isolate the "Parahippocampal Place Area" by reusing the audio-only version of the movie "Forrest Gump" as part of the studyforrest-dataset (studyforrest.org; Hanke et. al, 2014, A high-resolution 7-Tesla fMRI dataset from complex natural stimulation with an audio movie). For further information feel free to send an email to der.haeusler@gmx.net

Subject species

homo sapiens

Modality

fMRI-BOLD

Analysis level

group

Cognitive paradigm (task)

audio narrative

Map type

Z

Collection description

Faces and face related variables in studyForrest + music

Subject species

homo sapiens

Modality

fMRI-BOLD

Analysis level

group

Cognitive paradigm (task)

None / Other

Map type

V

Activation for character transitions occurring independently, without another transition within 2 seconds

Collection description

Whole-brain activation maps for different type of transitions in naturalistic stimuli (using Studyforrest database)

Subject species

homo sapiens

Modality

fMRI-BOLD

Analysis level

group

Cognitive paradigm (task)

movie watching task

Map type

T