Deep_learning_fMRI_EEG
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nmningmei
Implementation of deep learning models in decoding fMRI/EEG data in a context of semantic processing
Deep_learning_fMRI
Implementation of deep learning models in decoding fMRI data in a context of semantic processing
Goal:
- [x] To illustrate basic concepts of deep neural network models (DNN and CNN implementation so far)
- [x] To illustrate how to utilize deep neural network models to decode fMRI data
- [x] To illustrate principle ways of cross-validating the deep neural network models
- [x] To illustrate how upsupervised learning model is more straightforward to implement in deep neural network models than scit-kit learning implementation
- [x] To Propose a way to visualize the learned latent representations of the unsupervised models
- [x] To illustrate simulation experiments with CNN models
- [x] To illustrate representational similarity analysis
- [x] To illustrate the implementation of searchlight algorithm
- [ ] To show how the literature has been using the deep neural network models in classification
- [ ] To demonstrate how deep neural network models can decode conscious states
nmningmei