neural-data-analysis

python implementations of Analyzing Neural Time Series Textbook

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.

Decoding and geometrical analysis of neural activity with built-in best practices

A generalised Gaussian process method for learning vector fields over non-Euclidean domains. Particularly useful for EEG data analysis and to regularise vector fields using global structures.

MATLAB implementation of a rectified latent variable model for analysis of neural time series data.

Exemplar code for: Gava, G.P. et al. Integrating new memories into the hippocampal network activity space. Nat Neurosci 24, 326–330 (2021).

We present a probabilistic model for neural spike counts that can capture arbitrary single neuron and joint statistics with their modulation by external covariates.

Independent research software for data-free controller-style neural time-series methods. Contributions welcome.

Python code for the Neural Signal Processing and Analysis Course given by Mike X Cohen.

Simulates EEG data representing sensorimotor rhythms. Develops and compares spatial filters for neural source reconstruction.

Modeling Perception using Curriculum Learning, Transfer Learning to make incremental steps towards a generalizable model of perception and its AI applications

Classifies rock-paper-scissors hand gestures from optically pumped magnetometer (OPM) data recorded at the University of Nottingham.

Analyzes motor imagery from EEG data to extract ERD/ERS curves as part of the Neuroengineering Python workshop at the Technical University of Munich.

Implements EEG-based neurofeedback experiments with PsychoPy. Analyzes neural activity for performance changes.

ZPE-Neuro V0.0: DETERMINISTIC NEURAL SIGNAL CODEC: Extracellular Spikes | Neuropixels | DANDI-Anchored | IBL Validated | Spike Train Transport

Neural Data Analysis Program is designed to process and analyze neural data.

Bioinformatics-inspired approaches to BCI data analysis — sequence alignment concepts applied to neural signal patterns.

Predicts people’s stress levels from their resting-state EEG recordings in the LEMON dataset.

This repository contains MATLAB scripts for analysing neural data, with a focus on documentation and collaboration.