awillats / dynamics-in-neuro-reading-listLinks
This reading list is centered around the practical application of linear dynamical systems models to predict neural data
☆41Updated 4 years ago
Alternatives and similar repositories for dynamics-in-neuro-reading-list
Users that are interested in dynamics-in-neuro-reading-list are comparing it to the libraries listed below
Sorting:
- Code to train and analyze multi-region data-constrained RNNs and perform Current-Based Decomposition (CURBD)☆55Updated 5 years ago
- Open-source, graph-based Python code generator and analysis toolbox for dynamical systems (pre-implemented and custom models). Most pre-i…☆86Updated this week
- Package for the data-driven representation of non-linear dynamics over manifolds based on a statistical distribution of local phase portr…☆96Updated 5 months ago
- A repository of neural manifold techniques described and compared in "Neural manifold analysis of brain circuit dynamics in health and di…☆30Updated 2 years ago
- Library to perform Slice Tensor Component Analysis (sliceTCA)☆58Updated 10 months ago
- ☆60Updated 3 years ago
- Code accompanying Steinmetz et al., 2019☆60Updated 4 years ago
- State space models for decoding hippocampal trajectories and determining their type using sorted or clusterless data☆52Updated 3 months ago
- Preferential Subspace Identification Algorithm☆54Updated 3 weeks ago
- Fitting and analysis of trial-based neural spike responses with Generalized Linear Model (GLM).☆72Updated 5 years ago
- Tutorial☆11Updated 4 years ago
- Notebooks from the workshop tutorial implementing and discussing a range of generative models commonly used in neuroscience.☆39Updated 2 years ago
- NEural MOdelS, a statistical modeling framework for neuroscience.☆116Updated this week
- jPCA for Neural Data Analysis in Python☆52Updated 2 years ago
- Code accompanying Inferring stochastic low-rank RNNs from neural data. @matthijspals☆25Updated this week
- Neyman-Scott point process model to identify sequential firing patterns in high-dimensional spike trains☆70Updated 2 years ago
- Neuroelectrophysiology object model and data analysis in Python.☆50Updated 5 months ago
- Simple tutorial on Gaussian and Poisson GLMs for single and multi-neuron spike train data☆98Updated 3 years ago
- A Guide to Reconstructing Dynamical Systems from Neural Measurements Using Recurrent Neural Networks☆41Updated last year
- ☆41Updated 5 months ago
- Code for "Cortical areas interact through a communication subspace", Semedo et al. (Neuron, 2019)☆46Updated 6 years ago
- Python-module for calculation of extracellular potentials from multicompartment neuron models and networks☆84Updated 2 months ago
- Elephant is the Electrophysiology Analysis Toolkit☆230Updated last week
- Code to train low-rank RNNs on cognitive tasks & reproduce experiments from populations paper☆34Updated 9 months ago
- A dimensionality reduction framework for disentangling the flow of signals between populations of neurons☆32Updated 4 months ago
- Code to reproduce figures for "Mice alternate between discrete strategies during perceptual decision-making" from Ashwood, Roy, Stone, IB…☆55Updated 2 years ago
- A dimensionality reduction framework for characterizing the multi-dimensional, concurrent flow of signals across multiple neuronal popula…☆15Updated 9 months ago
- State-space Oscillator Modeling And Time-series Analysis (SOMATA) is a Python library for state-space neural signal processing algorithms…☆32Updated last year
- ☆56Updated last year
- Modules for processing extracellular electrophysiology data from Neuropixels probes☆122Updated last year