nmningmei
consciousness,metacognition,semantic processing,fMRI,M/EEG,generative models.
Shenzhen UniversityShenzhen, Guangdong, China
Pinned Repositories
BOLD5000_autoencoder
autoencoder trained on BOLD5000 dataset
Deep_learning_fMRI_EEG
Implementation of deep learning models in decoding fMRI/EEG data in a context of semantic processing
Get_Sleep_data
Get the EEG sleep data from OSF "Nap EEG"
intuitive_probability_games
metasema_encoding_based_RSA
METASEMA_encoding_model
Decoding and encoding models reveal the role of mental simulation in the brain representation of meaning
parametric_nonparametric_statistics_comparison
A comparion between parametric and nonparametric statistics using Python
plot_atlas
plot fMRI ROIs with different colors
preprocessing_pipelines
Preprocessing Pipelines for EEG (MNE-python), fMRI (nipype), MEG (MNE-python/autoreject) data
unconfeats
nmningmei's Repositories
nmningmei/preprocessing_pipelines
Preprocessing Pipelines for EEG (MNE-python), fMRI (nipype), MEG (MNE-python/autoreject) data
nmningmei/Deep_learning_fMRI_EEG
Implementation of deep learning models in decoding fMRI/EEG data in a context of semantic processing
nmningmei/BOLD5000_autoencoder
autoencoder trained on BOLD5000 dataset
nmningmei/plot_atlas
plot fMRI ROIs with different colors
nmningmei/Get_Sleep_data
Get the EEG sleep data from OSF "Nap EEG"
nmningmei/metacognition
Similar history biases for distinct prospective decisions of self-performance
nmningmei/parametric_nonparametric_statistics_comparison
A comparion between parametric and nonparametric statistics using Python
nmningmei/mask_image_FOREST
nmningmei/nmningmei
nmningmei/plot_chinese_character
nmningmei/unconfeats
nmningmei/intuitive_probability_games
nmningmei/agent_models
nmningmei/Brainhack_Donostia_NOV_2021
Brainhack Donistia Nov 2021 project
nmningmei/CogModelingRNNsTutorial
copy of CCN 2023 tutorial
nmningmei/Decode_confidence_dataset
nmningmei/Deep-Learning-NYU
Deep Learning Course instructed by Yann LeCun and Alfredo Canziani
nmningmei/indaba-pracs-2023
Notebooks for the Practicals at the Deep Learning Indaba 2023.
nmningmei/LevelUpPythonTutorial
Learn the basics of python from a level gaining process
nmningmei/netrep
Some methods for comparing network representations in deep learning and neuroscience.
nmningmei/Neuromatch-academy-certificates
nmningmei/scientific-visualization-book
An open access book on scientific visualization using python and matplotlib
nmningmei/SciMLBook
Parallel Computing and Scientific Machine Learning (SciML): Methods and Applications (MIT 18.337J/6.338J)
nmningmei/self-consistency_neural_network_simulation
A neural network simulation of self-consistency model of confidence
nmningmei/simple_tensorflow_logistic_regression_classifier
This is a simple logistic regression classifier implemented in tensorflow 2.0
nmningmei/socialcon_images
nmningmei/spytorch
Tutorial for surrogate gradient learning in spiking neural networks
nmningmei/SwapVAE
PyTorch implementation of Swap-VAE: A self-supervised approach for generating neural activity
nmningmei/thingsvision
Python package for extracting and analyzing image representations from state-of-the-art neural networks for computer vision
nmningmei/unconfeat_MEEG