Note
This page is a reference documentation. It only explains the function signature, and not how to use it. Please refer to the user guide for the big picture.
5.2.2. sammba.data_fetchers.fetch_zurich_anesthesiant¶
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sammba.data_fetchers.fetch_zurich_anesthesiant(subjects=range(0, 30), url=None, data_dir=None, resume=True, verbose=1)¶ Download and loads the ETH-Zurich anesthesiant dataset.
- Parameters
subjects : sequence of int or None, optional
ids of subjects to load, default to loading all subjects.
data_dir: string, optional
Path of the data directory. Used to force data storage in a specified location. Default: None
resume: bool, optional (default True)
If true, try resuming download if possible.
verbose: int, optional (default 0)
Defines the level of verbosity of the output.
- Returns
data : sklearn.datasets.base.Bunch
Dictionary-like object, the interest attributes are: - ‘func’: string list. Paths to functional images. - ‘anesthesiant’: string list. Information on used anesthesiant.
Notes
This dataset is composed of 30 male mice with different anesthesia protocols.
References
- Download
- Reference
Optimization of anesthesia protocol for resting-state fMRI in mice based on differential effects of anesthetics on functional connectivity patterns. NeuroImage 102 (2014): 838-847. J. Grandjean and A. Schroeter and I. Batata and M. Rudin.