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compressed-predictive-information-coding

The repo for compressed predictive information coding

concavity

Concave Hull boundary polygon for an array of points and concave and convex polygon vertex detection

contrastive_predictive_coding

This is a modified version of contrastive predictive coding on time series

cpic

cv_paper_plots

Code for create plots for cv paper.

distributed-uoi_var

dynamicalcomponentsanalysis

Dynamical Components Analysis

ecogvis

Time series visualizer and data processing tools for Electrocorticography (ECoG) signals stored in NWB files, for Python.

ergm

Fit, Simulate and Diagnose Exponential-Family Models for Networks

fcca

fcca_analysis

fooof

Parameterizing neural power spectra - fitting oscillatory peaks and 1/f background.

gaussian-process-regression-network

Pytorch version of Gaussian Process Regression Network

hangulfontsdatasetgenerator

Scripts to generate the Hangul Fonts Dataset

info_measures

Python implementations of information theoretic measures

jpca-1

jPCA for Neural Data Analysis in Python

ml_4_prec_prognosis

mpi_utils

mpi4py array utilities

natural-sounds-visualizations

Python code by Vitto Resnick for importing and visualizing audio files as ndarrays.

nersc_python

Docker images and example slurm scripts

neurobiases

Identifying and mitigating statistical biases in neural models of tuning and functional coupling

neuroinference

Accurate inference in parametric models reshapes neuroscientific interpretation and improves data-driven discovery

neuropacks

A set of classes to parse various neuroscience datasets.

nsds_lab_to_nwb

Python package to convert NSDS Lab data to NWB files.

nwb_hackathons

Repository for collecting materials from nwb hackathons

originsofecog

orthogonal-stochastic-linear-mixing-model

This is the python implementation of the paper [Bayesian Inference in High-Dimensional Time-Series with the Orthogonal Stochastic Linear Mixing Model]. We propose a new regression framework to model multivariate output response data, which not only capture the complex input-dependent correlation across outputs, but also is effient for massive model and capable for single-trial analysis in neural data. Please refer our model for more details.

pdca

Probabilistic Dynamic Component Analysis

process_ecog

process_nwb

Functions for preprocessing timeseries data stored in the NWB format