kaihwang Goto Github PK

analyzing_neural_time_series

python implementations of Analyzing Neural Time Series Textbook

bggraph

BG/Striatal lesions

brainx

Tools for analysis of brain imaging-derived networks, based on NetworkX

circlewm

clock

Scripts to analyze MEG clock data

ecoggca_simulation

example_graph_pipeline

fc_scripts

Collection of scripts to preprocesses rs-fcMRI data and performing connectivity analyses.

funcparcel

Functional parcellation of (subcortical) brain structures and followup graph analyses.

git-fundamentals

A starting point for discovering the wonderful world of Git, GitHub, and Git Annex (Assistant)

hcp-processing

Scripts to organize and process HCP data

htb-mne

HTB EEG data, collected with Biosemi. Compare MNE/Python v Fieldtrip/Matlab

htb-tha

htb_mri

HTB MRI pilot

introduction-to-pandas

Materials for the D-Lab's pandas workshop

kaihwang.github.io

my website.

lesionnetwork

littlenoisybrain

lth

Neuropsychological evidence of multi-domain network hubs in the human thalamus

ncku

pandas-cookbook

Recipes for using Python's pandas library

probabilistic-programming-and-bayesian-methods-for-hackers

aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)

psy4025

PSY4025 Laboratory in Cognitive Neuroscience

psych216

A translation of Kendrick's MATLAB statistics class materials into Python

pythondatasciencehandbook

Jupyter Notebooks for the Python Data Science Handbook

r_graphics_dlab

Materials for Graphics in R Workshop, D-Lab, UC Berkeley

r_useful_dlab

Materials for Useful Stuff in R Workshop, D-Lab, UC Berkeley

simpace_litreview

making plots for simpace project literature review, trying out ggplot in python....

statistical-analysis-python-tutorial

Statistical Data Analysis in Python

statistical-rethinking-with-python-and-pymc3

Python/PyMC3 port of the examples in " Statistical Rethinking A Bayesian Course with Examples in R and Stan" by Richard McElreath