@article{Abdulrahman2016,
    title={Effect of trial-to-trial variability on optimal event-related fMRI design: Implications for Beta-series correlation and multi-voxel pattern analysis},
    author={Abdulrahman, Hunar and Henson, Richard N},
    journal={NeuroImage},
    volume={125},
    pages={756--766},
    year={2016},
    publisher={Elsevier}
}

@article{Allen2011,
	AUTHOR={Allen, Elena and Erhardt, Erik and Damaraju, Eswar and Gruner, William and Segall, Judith and Silva, Rogers and Havlicek, Martin and Rachakonda, Srinivas and Fries, Jill and Kalyanam, Ravi and Michael, Andrew and Caprihan, Arvind and Turner, Jessica and Eichele, Tom and Adelsheim, Steven and Bryan, Angela and Bustillo, Juan and Clark, Vincent and Feldstein Ewing, Sarah and Filbey, Francesca and Ford, Corey and Hutchison, Kent and Jung, Rex and Kiehl, Kent and Kodituwakku, Piyadasa and Komesu, Yuko and Mayer, Andrew and Pearlson, Godfrey and Phillips, John and Sadek, Joseph and Stevens, Michael and Teuscher, Ursina and Thoma, Robert and Calhoun, Vince},
	TITLE={A Baseline for the Multivariate Comparison of Resting-State Networks},
	JOURNAL={Frontiers in Systems Neuroscience},
	VOLUME={5},
	PAGES={2},
	YEAR={2011},
	URL={https://www.frontiersin.org/article/10.3389/fnsys.2011.00002},
	DOI={10.3389/fnsys.2011.00002},
	ISSN={1662-5137},
	ABSTRACT={As the size of functional and structural MRI datasets expands, it becomes increasingly important to establish a baseline from which diagnostic relevance may be determined, a processing strategy that efficiently prepares data for analysis, and a statistical approach that identifies important effects in a manner that is both robust and reproducible. In this paper, we introduce a multivariate analytic approach that optimizes sensitivity and reduces unnecessary testing. We demonstrate the utility of this mega-analytic approach by identifying the effects of age and gender on the resting-state networks (RSNs) of 603 healthy adolescents and adults (mean age: 23.4 years, range: 12–71 years). Data were collected on the same scanner, preprocessed using an automated analysis pipeline based in SPM, and studied using group independent component analysis. RSNs were identified and evaluated in terms of three primary outcome measures: time course spectral power, spatial map intensity, and functional network connectivity. Results revealed robust effects of age on all three outcome measures, largely indicating decreases in network coherence and connectivity with increasing age. Gender effects were of smaller magnitude but suggested stronger intra-network connectivity in females and more inter-network connectivity in males, particularly with regard to sensorimotor networks. These findings, along with the analysis approach and statistical framework described here, provide a useful baseline for future investigations of brain networks in health and disease.}
}
