Imaging measurements for local brain activity at resting state
A list of the
curve_set containing the data,
coordinates (x,y) where the data have been observed (third dimension is 23),
the discrete factor
Group (1=Autism; 2=Control),
the discrete factor
Sex (1=Male; 2=Female),
and the continuous factor
The data are a small part of ABIDE fALFF data available at ABIDE: http://fcon_1000.projects.nitrc.org/indi/abide/ fALFF: http://fcp-indi.github.io/docs/user/alff.html and distributed under the CC BY-NC-SA 3.0 license, https://creativecommons.org/licenses/by-nc-sa/3.0/.
The data are fractional Amplitude of Low Frequency Fluctuations (fALFF) (Zou et al. 2008) for Autism Brain Imaging Data Exchange collected resting state functional magnetic resonance imaging (R-fMRI) datasets (Di Martino et al. 2013). This data set in GET contains only a tiny part of the whole brain, namely the region 9002 (the right Cerebelum Crus 1) at slice 23 (see Figure 2 in Mrkvicka et al., 2019) for 514 individuals with the autism spectrum disorder (ASD) and 557 typical controls (TC) as specified in the given Group variable. Further the sex and age of each subject is given.
Di Martino, A., Yan, C., Li, Q., Denio, E., Castellanos, F., Alaerts, K., Anderson, J., Assaf, M., Bookheimer, S., Dapretto, M., et al. (2013) The autism brain imaging data exchange: towards a large-scale evaluation of the intrinsic brain architecture in autism. Molecular psychiatry.
Tzourio-Mazoyer, N., Landeau, B., Papathanassiou, D., Crivello, F., Etard, O., Delcroix, N., Mazoyer, B., and Joliot, M. (2002), Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. Neuroimage, 15, 273-289.
Zou, Q.-H., Zhu, C.-Z., Yang, Y., Zuo, X.-N., Long, X.-Y., Cao, Q.-J., Wang, Y.-F., and Zang, Y.-F. (2008), An improved approach to detection of amplitude of low-frequency fluctuation (ALFF) for resting-state fMRI: fractional ALFF. Journal of neuroscience methods, 172, 137-141.
Mrkvička, T., Myllymäki, M., Kuronen, M. and Narisetty, N. N. (2022) New methods for multiple testing in permutation inference for the general linear model. Statistics in Medicine 41(2), 276-297. doi: 10.1002/sim.9236
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