python implementations of Analyzing Neural Time Series Textbook
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Updated
Nov 1, 2021 - Jupyter Notebook
python implementations of Analyzing Neural Time Series Textbook
Decoding and geometrical analysis of neural activity with built-in best practices
Package for the data-driven representation of non-linear dynamics over manifolds based on a statistical distribution of local phase portrait features. Includes specific example on dynamical systems, synthetic- and real neural datasets. https://agosztolai.github.io/MARBLE/
Exemplar code for: Gava, G.P. et al. Integrating new memories into the hippocampal network activity space. Nat Neurosci 24, 326–330 (2021).
MATLAB implementation of a rectified latent variable model for analysis of neural time series data.
Rock paper scissors classfication from optically pumped magnetometers (OPM) data
Modeling Perception using Curriculum Learning, Transfer Learning to make incremental steps towards a generalizable model of perception and its AI applications
Neural Data Analysis Program is designed to process and analyze neural data.
We present a probabilistic model for neural spike counts that can capture arbitrary single neuron and joint statistics with their modulation by external covariates.
This repository contains MATLAB scripts for analysing neural data, with a focus on documentation and collaboration.
MATLAB tools for analysis and visualization of neural data
EEG analysis tutorial for extracting ERD/ERS curves from motor imagery data.
This is a neural data science project to investigate relationships between music and depression using Neural Data Science Techniques
Official repo for NeurReps 2022 paper, "On the Level Sets and Invariance of Neural Tuning Landscapes". Analyze level sets on the tuning landscape of neurons and artificial units
Analysis of the neural simulation data from NEST Simulator. The following analysis is part of solution for the semestral project for Informatics and Cognitive Science II from Faculty of Math and Physics of Charles University in Prague.
The Humphries' lab manual
Simulate EEG data reflecting sensorimotor oscillations. Develop and compare spatial filters, evaluating their effectiveness in extracting neural sources.
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