neuromethods / fokker-planck-based-spike-rate-modelsLinks
Rate model implementations for (adaptive) integrate-and-fire neurons based on the Fokker-Planck equation: (i) numerical (finite volume) solution of the full FP PDE, (ii) low-dim. ODE via spectral decomposition of the FP operator, (iii) low-dim. ODE via a linear-nonlinear cascade semianalytically fit to the FP model.
☆10Updated 6 years ago
Alternatives and similar repositories for fokker-planck-based-spike-rate-models
Users that are interested in fokker-planck-based-spike-rate-models are comparing it to the libraries listed below
Sorting:
- A framework for simulating mean-field neural mass models of spiking neurons, comparing them to large network simulations, and predicting …☆17Updated 5 years ago
- Code for Galgali et al, 2023☆13Updated 2 years ago
- Supplementary code for the paper "Linking connectivity, dynamics and computations in low-rank recurrent neural networks" by F. Mastrogius…☆34Updated 6 years ago
- Code to train low-rank RNNs on cognitive tasks & reproduce experiments from populations paper☆28Updated 2 months ago
- Short-term plasticity RNN models in Tensorflow☆34Updated 5 years ago
- repository for grid cell network code☆61Updated 2 years ago
- ☆52Updated 2 years ago
- ☆23Updated 7 months ago
- A SciUnit library for validation testing of spiking neural network models.☆16Updated 10 months ago
- jPCA for Neural Data Analysis in Python☆50Updated last year
- This code package is for the Tensor-Maximum-Entropy (TME) method. This method generates random surrogate data that preserves a specified …☆18Updated 7 years ago
- Analytical methods for efficient inference of integrate-and-fire circuit models from single-trial spike trains☆10Updated 5 years ago
- Official code for Conformal Isometry of Lie Group Representation in Recurrent Network of Grid Cells (NeurIPS workshop on Symmetry and Geo…☆11Updated 2 years ago
- Neyman-Scott point process model to identify sequential firing patterns in high-dimensional spike trains☆66Updated last year
- Fitting low-rank RNNs to neural trajectories (LINT method).☆16Updated 2 months ago
- GLMCC: The generalized linear model for spike cross-correlation (Kobayashi et al., Nature Communications, 2019)☆35Updated 2 years ago
- Open-source, graph-based Python code generator and analysis toolbox for dynamical systems (pre-implemented and custom models). Most pre-i…☆82Updated 9 months ago
- Code accompanying Inferring stochastic low-rank RNNs from neural data. @matthijspals☆20Updated last month
- ☆23Updated 3 years ago
- A very simple and barebones tensor decomposition library for CP decomposition a.k.a. PARAFAC a.k.a. TCA☆35Updated last year
- Meta-learning local synaptic plasticity for continual familiarity detection☆16Updated 2 years ago
- This repository contains code for (1) generating example neural responses from an Izhikevich model, and (2) fitting a GLM to neural respo…☆11Updated 2 years ago
- Matlab interface for Latent Factor Analysis via Dynamical Systems (LFADS)☆49Updated 3 years ago
- Matlab exercises with solutions to implement and visualise concepts from Sara Solla's talk on World Wide Neuro (Apr 29, 2020)☆20Updated 4 years ago
- Exercises and examples for the latent dynamics workshop☆17Updated last year
- This repository serves as a container for material around the Brian simulator, such as presentations and tutorials.☆40Updated 5 months ago
- Fitting and simulation of Poisson generalized linear model for single and multi-neuron spike trains (Pillow et al 2008).☆40Updated 5 years ago
- ☆20Updated last year
- A Guide to Reconstructing Dynamical Systems from Neural Measurements Using Recurrent Neural Networks☆37Updated last year
- FixedPointFinder: A Tensorflow toolbox for identifying and characterizing fixed points in recurrent neural networks☆97Updated 10 months ago