13 papers · ranked by Valyu relevance
Oscar Esteban, Christopher J. Markiewicz, Ross W. Blair, Craig A. Moodie + 12 more
Preprocessing of functional MRI (fMRI) involves numerous steps to clean and standardize data before statistical analysis. Generally, researchers create ad hoc preprocessing workflows for each new dataset, building upon a large inventory of tools available for each step. The complexity of these workflows has snowballed…
Jiayuan Ding, Zhongyu Xing, Yixin Wang, Renming Liu + 9 more
Preprocessing is a critical step in single-cell data analysis, yet current practices remain largely a black-box, trial-and-error process driven by user intuition, legacy defaults, and ad hoc heuristics. The optimal combination of steps such as normalization, gene selection, and dimensionality reduction varies across…
Lea Waller, Susanne Erk, Elena Pozzi, Yara J. Toenders + 7 more
The reproducibility crisis in neuroimaging has led to an increased demand for standardized data processing workflows. Within the ENIGMA consortium, we developed HALFpipe (Harmonized AnaLysis of Functional MRI pipeline), an open-source, containerized, user-friendly tool that facilitates reproducible analysis of…
Jianxun Ren, Ning An, Cong Lin, Youjia Zhang + 13 more
Neuroimaging has entered the era of big data. However, the advancement of preprocessing pipelines falls behind the rapid expansion of data volume, causing significant computational challenges. Here, we present DeepPrep, a pipeline empowered by deep learning and workflow manager. Evaluated on over 55,000 scans, DeepPrep…
Ranjan Debnath, George A. Buzzell, Santiago Morales, Maureen E. Bowers + 2 more
Compared to adult EEG, EEG signals recorded from pediatric populations have shorter recording periods and contain more artifact contamination. Therefore, pediatric EEG data necessitate specific preprocessing approaches in order to remove environmental noise and physiological artifacts without losing large amounts of…
Nadine S. J. Jacobsen, Daniel Kristanto, Suong Welp, Yusuf Cosku Inceler + 1 more
Preprocessing is necessary to extract meaningful results from electroencephalography (EEG) data. With many possible preprocessing choices, their impact on outcomes is fundamental. While previous studies have explored the effects of preprocessing on stationary EEG data, this research delves into mobile EEG, where…
Scott Huberty, James Desjardins, Tyler Collins, Mayada Elsabbagh + 1 more
EEG recordings are typically long and contain large amounts of data, making manual cleaning a time-consuming and error-prone task. Automated pre-processing pipelines can facilitate the efficient and objective extraction of artifacts, enabling standardized and reproducible analyses. However, automated pre-processing…
Lara Dular, Franjo Pernuš, Žiga Špiclin
Brain age is an estimate of chronological age obtained from T1-weighted magnetic resonance images (T1w MRI) and represents a simple diagnostic biomarker of brain ageing and associated diseases. While the current best accuracy of brain age predictions on T1w MRIs of healthy subjects ranges from two to three years…
Kay A. Robbins, Jonathan Touryan, Tim Mullen, Christian Kothe + 1 more
EEG preprocessing approaches have not been standardized, and even those studies that follow best practices contain variations in the ways that the recommended methods are applied. An open question for researchers is how sensitive the results of EEG analyses are to preprocessing methods and parameters. To address this…
Martin A. Lindquist, Stephan Geuter, Tor D. Wager, Brian S. Caffo
The preprocessing pipelines typically used in both task and restingstate fMRI (rs-fMRI) analysis are modular in nature: They are composed of a number of separate filtering/regression steps, including removal of head motion covariates and band-pass filtering, performed sequentially and in a flexible order. In this paper…
Jaap de Ruyter van Steveninck, Umut Güçlü, Richard van Wezel, Marcel van Gerven
Neural prosthetics may provide a promising solution to restore visual perception in some forms of blindness. The restored prosthetic percept is rudimentary compared to normal vision and can be optimized with a variety of image preprocessing techniques to maximize relevant information transfer. Extracting the most…
Ben Blamey, Salman Toor, Martin Dahlö, Håkan Wieslander + 6 more
This paper introduces the HASTE Toolkit, a cloud-native software toolkit capable of partitioning data streams in order to prioritize usage of limited resources. This in turn enables more efficient data-intensive experiments. We propose a model that introduces automated, autonomous decision making in data pipelines…
Joram van Driel, Christian N.L. Olivers, Johannes J. Fahrenfort
Traditionally, EEG/MEG data are high-pass filtered and baseline-corrected to remove slow drifts. Minor deleterious effects of high-pass filtering in traditional time-series analysis have been well-documented, including temporal displacements. However, its effects on time-resolved multivariate pattern classification…