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- [ ] [Connecting cortex to machines: recent advances in brain interfaces](https://www.nature.com/articles/nn947) (2002)
- [ ] [Visual P300 Mind-Speller Brain-Computer Interfaces: A Walk Through t…
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# Introduction — Deep Learning for Brain-Signal Decoding from Electroencephalography (EEG)
[https://robintibor.github.io/eeg-deep-learning-phd-thesis/Introduction.html](https://robintibor.github.io…
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On top of the script that generates HTML reports to put in the documentation (https://github.com/nilearn/nilearn/blob/main/doc/visual_testing/reporter_visual_inspection_suite.py) that could probably b…
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### Objective
The goal of this issue is to implement a Graph Convolutional Neural Network (GCNs-Net) model for decoding time-resolved EEG motor imagery signals, as outlined in the paper "[GCNs-Net: A…
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> [!TIP]
> # **💻 🍁 For the [hacktoberfest](https://hacktoberfest.com/) contributors 🍁 💻**
>
> Make sure to:
> - read our [contributing guidelines](https://nilearn.github.io/stable/development.html#co…
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Our test suite is getting slower.
See stats over the past year (same thing for windows, macos has a discontunuity most likely due to an infrastructure change on the github side)
![Image](https://git…
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The goal is to study DL method for BCI classification:
- [Deep learning with convolutional neural networks for EEG decoding and visualization](https://pubmed.ncbi.nlm.nih.gov/28782865/), 1744 citati…
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My notes for future research on EMO_REACT
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According to the way of EEG production, there are two kinds: spontaneous EEG (EEG) and evoked EEG (EP).(按照脑电产生的方式可以分为自发脑电(EEG)和诱发脑电(EP)两种。)
The BCI system based on EEG realizes control by real-ti…
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I am currently employing GLMsingle with default parameters in Python for rapid event design analysis in fMRI research. My dataset consists of 9-11 runs per subject, with a TR of 1.5 seconds. Each tria…