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An introduction to the practicing neuroscientist to data analysis in Python
A Python implementation of Partial Least Squares (PLS) decomposition
"rsync for cloud storage" - Google Drive, S3, Dropbox, Backblaze B2, One Drive, Swift, Hubic, Wasabi, Google Cloud Storage, Azure Blob, Azure Files, Yandex Files
Noisy network measurement with stan
A neuroscience library for Python, intended to complement the existing nibabel library.
Convert biological neuronal networks to artificial recurrent neuronal networks
Light package for connectivity estimation and analysis of neuroimaging data (e.g. fMRI). It relies on the multivariate Ornstein-Uhlenbeck process (MOU).
This is sample of python implementation for detecting the changes in the synchronous oscillatory networks, based on dynamical Bayesian inference.
Easy whole-brain modeling for computational neuroscientists 🧠💻👩🏿🔬
Freestanding implementations of electrostatic forward models for extracellular measurements of neural activity in multicompartment neuron models.
Neural oscillation event detection and analysis
Julia package for simulating Dynamics on Networks
Methodological considerations for analyzing and interpreting neural oscillations.
The Book of Statistical Proofs
A C++ package for low-frequency bio-electromagnetism solving forward problems in the field of EEG and MEG.
Pre-trained models and utilities for deep learning on medical images in Python
A fast medical imaging analysis library in Python with algorithms for registration, segmentation, and more.
The MVGC Multivariate Granger Causality toolbox (Version 2) for Granger-causal inference from time-series data. CURRENTLY IN EARLY DEVELOPMENT - UNTESTED!
Load MATLAB 7.3 .mat files. I.e. load hdf5 into Python datatypes.
Fixes mojibake and other glitches in Unicode text, after the fact.