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dfConn: Dynamic Functional Connectivity Analysis
An implementation of multivariate linear process bootstrap (MLPB) method and sliding window technique to assess the dynamic functional connectivity (dFC) estimate by providing its confidence bands, based on Maria Kudela (2017) <doi: 10.1016/j.neuroimage.2017.01.056>. It also integrates features to visualize non-zero coverage for selected a-priori regions of interest estimated by the dynamic functional connectivity model (dFCM) and dynamic functional connectivity (dFC) curves for reward-related a-priori regions of interest where the activation-based analysis reported.
Getting started
Browse package contents
Package details |
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| Author | Zikai Lin [aut, cre], Maria Kudela [aut], Jaroslaw Harezlak [aut], Mario Dzemidzic [aut] |
| Maintainer | Zikai Lin <ziklin@iu.edu> |
| License | MIT + file LICENSE |
| Version | 0.2.1 |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
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