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1 | | ---- |
2 | | -title: 'Unfold.jl: Regression models for Cognitive Neuroscience' |
3 | | -tags: |
4 | | - - Julia |
5 | | - - EEG |
6 | | - - neuroimaging |
7 | | -authors: |
8 | | - - name: Benedikt V. Ehinger |
9 | | - orcid: 0000-0002-6276-3332 |
10 | | - equal-contrib: false |
11 | | - affiliation: "1, 2" # (Multiple affiliations must be quoted) |
12 | | - |
13 | | -affiliations: |
14 | | - - name: Stuttgart Center for Simulation Science, University of Stuttgart, Germany |
15 | | - index: 1 |
16 | | - - name: Institute for Visualization and Interactive Systems, University of Stuttgart, Germany |
17 | | - index: 2 |
18 | | -date: 06 November 2023 |
19 | | -bibliography: paper.bib |
20 | 1 |
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21 | | - |
22 | | ---- |
23 | | - |
24 | | -# Summary |
25 | | - |
26 | | - |
27 | | -Overlapping event responses, (non-)linear effects and confounds, outliers, item effects - all pretty common features limiting the application of neuroimaging methods. Here, we focus on EEG without loss of generality. Especially event-related potentials in naturalistic paradigms (e.g. ET+EEG, VR+EEG, MoBi) but also classical paradigms (evidence Integration, language, even oddball tasks) require such techniques. |
28 | | - |
29 | | -Unfold.jl implements the model fitting based on the popular wilkinson~formula+syntax. It is feature-par with matlab-unfold. In addition it offers speed-improvements (up to 100x on GPUs) and extensions for outlier-robust fits, back2back regression, and mixed models. |
30 | | - |
31 | | -While implemented in Julia, it is straight forward to also call from Python and tutorials are available. |
32 | | - |
33 | | - |
34 | | - |
35 | | -# Statement of need |
36 | | - |
37 | | - |
38 | | - |
39 | | -# Mathematics |
40 | | - |
41 | | -Single dollars ($) are required for inline mathematics e.g. $f(x) = e^{\pi/x}$ |
42 | | - |
43 | | -Double dollars make self-standing equations: |
44 | | - |
45 | | -$$\Theta(x) = \left\{\begin{array}{l} |
46 | | -0\textrm{ if } x < 0\cr |
47 | | -1\textrm{ else} |
48 | | -\end{array}\right.$$ |
49 | | - |
50 | | -You can also use plain \LaTeX for equations |
51 | | -\begin{equation}\label{eq:fourier} |
52 | | -\hat f(\omega) = \int_{-\infty}^{\infty} f(x) e^{i\omega x} dx |
53 | | -\end{equation} |
54 | | -and refer to \autoref{eq:fourier} from text. |
55 | | - |
56 | | -# Citations |
57 | | - |
58 | | -Citations to entries in paper.bib should be in |
59 | | -[rMarkdown](http://rmarkdown.rstudio.com/authoring_bibliographies_and_citations.html) |
60 | | -format. |
61 | | - |
62 | | -If you want to cite a software repository URL (e.g. something on GitHub without a preferred |
63 | | -citation) then you can do it with the example BibTeX entry below for @fidgit. |
64 | | - |
65 | | -For a quick reference, the following citation commands can be used: |
66 | | -- `@author:2001` -> "Author et al. (2001)" |
67 | | -- `[@author:2001]` -> "(Author et al., 2001)" |
68 | | -- `[@author1:2001; @author2:2001]` -> "(Author1 et al., 2001; Author2 et al., 2002)" |
69 | | - |
70 | | -# Figures |
71 | | - |
72 | | -Figures can be included like this: |
73 | | - |
74 | | -and referenced from text using \autoref{fig:example}. |
75 | | - |
76 | | -Figure sizes can be customized by adding an optional second parameter: |
77 | | -{ width=20% } |
78 | | - |
79 | | -# Acknowledgements |
80 | | - |
81 | | -We acknowledge contributions from Brigitta Sipocz, Syrtis Major, and Semyeong |
82 | | -Oh, and support from Kathryn Johnston during the genesis of this project. |
83 | | - |
84 | | -# References |
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