localizer first level dataset

Access

See nilearn.datasets.fetch_localizer_first_level.

Notes

Single subject dataset from the “Neurospin Localizer”. It is a fast event related design: during 5 minutes, 80 events of the following types are presented :

• ‘audio_computation’,

• ‘audio_left_hand_button_press’,

• ‘audio_right_hand_button_press’,

• ‘horizontal_checkerboard’,

• ‘sentence_listening’,

• ‘sentence_reading’,

• ‘vertical_checkerboard’,

• ‘visual_computation’,

• ‘visual_left_hand_button_press’,

• ‘visual_right_hand_button_press’

The data was preprocessed and is in MNI305 space.

The protocol described is the so-called “ARCHI Standard” functional localizer task.

For details on the task, please see Pinel et al.[1].

Direct download link from OSF: https://osf.io/2bqxn

Content

• epi_img: str. Full path the 4D BOLD nifti image.

• events: str. Full path to TSV file describing the paradigm.

• slice_time_ref: float. Slice timing reference used during slice timing correction.

• t_r: float. Repetition time in seconds.

• template: str. The standardized space of analysis in which the data is provided.

References

[1]

Philippe Pinel, Bertrand Thirion, Sébastien Meriaux, Antoinette Jobert, Julien Serres, Denis Le Bihan, Jean-Baptiste Poline, and Stanislas Dehaene. Fast reproducible identification and large-scale databasing of individual functional cognitive networks. BMC Neuroscience, 2007. URL: https://pmc.ncbi.nlm.nih.gov/articles/PMC2241626/, doi:10.1186/1471-2202-8-91.

License

unknown