ecog

MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python

The MATLAB toolbox for MEG, EEG and iEEG analysis

Parameterizing neural power spectra into periodic & aperiodic components.

A list of openly available datasets in (mostly human) electrophysiology.

A Python Toolbox for Multimode Neural Data Representation Analysis - A Representational Analysis Toolbox for Neuroscience, including Neural Pattern Similarity (NPS), Representational Similarity Analysis (RSA), Spatiotemporal Pattern Similarity (STPS) & Inter-Subject Correlation (ISC)

A list of openly available software tools for (mostly human) electrophysiology.

Package to analyze EEG, ECoG and other electrophysiology formats. It allows for visualization of the results and for a GUI that can be used to score sleep stages.

[PNAS'21] The neural architecture of language: Integrative modeling converges on predictive processing

3D Visualization of Brain MRI

Systems Neuroscience Computing in Python: user-friendly analysis of large-scale electrophysiology data

Matlab toolbox for univariate and multivariate analysis of EEG data in the time and frequency domains

Methodological considerations for analyzing and interpreting neural oscillations.

ECoG/EEG neural network decoder that can generalize to unseen participants and recording modalities. Replicates our published results: https://doi.org/10.1088/1741-2552/abda0b.

This repository provides analysis code to analyze intracranial electrophysiological data with data-driven spatial filters.

Real-time analysis of intracranial neurophysiology recordings.

Topological Data Analysis (TDA) Techniques Enhance Hand Pose Classification from ECoG Neural Recordings

3D visualization tool

Web-based Electrode Visualization

A Matlab software for Clinical Neural Engineering Laboratory.

A general purpose BCI platform designed to work with Neuralynx

Time series analysis codes used in the company's data science projects.

Custom MATLAB code for Mostame et al. NeuroImage 2020 https://www.sciencedirect.com/science/article/pii/S1053811920305371?via%3Dihub

Functions for preprocessing timeseries data stored in the NWB format

Visual working memory and workload components in ECoG during n-Back task

An open-source software package for working with electrophysiological data.

In this research project we used a shift-invariant k-means algorithm to learn a preictal and interictal codebook of prototypical waveforms that can be used to summarize the occurrence of recurrent waveforms and to classify between preictal and interictal segments. We use the common spatial patterns (CSP) method to spatially filter the multichannel ECoG segments before doing the waveform learning.

see GRIDGEN

Data and code for the research paper "Bone conducted responses in the neonatal rat auditory cortex" (Makarov et. al., 2021)