gamaleldin / CFRLinks
This code package is for the Corrected-Fisher-Randomization (CFR) method. This method generates random surrogate data that preserves a specified set of first and second order marginal moments of a data tensor, which makes it well equipped to test for the null hypothesis that a structure in data is an epiphenomenon of these specified set of prima…
☆10Updated 7 years ago
Alternatives and similar repositories for CFR
Users that are interested in CFR are comparing it to the libraries listed below
Sorting:
- 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
- Gaussian Process Factor Analysis☆30Updated 9 years ago
- Neyman-Scott point process model to identify sequential firing patterns in high-dimensional spike trains☆67Updated last year
- A very simple and barebones tensor decomposition library for CP decomposition a.k.a. PARAFAC a.k.a. TCA☆35Updated last year
- 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…☆35Updated 7 years ago
- CorBinian: A toolbox for modelling and simulating high-dimensional binary and count-data with correlations☆19Updated 3 years ago
- A TensorFlow 2.0 implementation of Latent Factor Analysis via Dynamical Systems (LFADS) and AutoLFADS.☆21Updated last year
- Python tools for analysis of neurophysiology data☆37Updated last year
- State space models for decoding hippocampal trajectories and determining their type using sorted or clusterless data☆49Updated 9 months ago
- Matlab interface for Latent Factor Analysis via Dynamical Systems (LFADS)☆49Updated 3 years ago
- Fitting and analysis of trial-based neural spike responses with Generalized Linear Model (GLM).☆70Updated 5 years ago
- Code accompanying Inferring stochastic low-rank RNNs from neural data. @matthijspals☆21Updated 2 months ago
- Code to train and analyze multi-region data-constrained RNNs and perform Current-Based Decomposition (CURBD)☆53Updated 4 years ago
- Code accompanying Steinmetz et al., 2019☆60Updated 3 years ago
- Dimensionality reduction of spikes trains☆48Updated 3 years ago
- Linear-Nonlinear-Poisson (LNP) model fitting via Maximally-Informative-Dimensions (MID) / maximum likelihood☆18Updated 7 years ago
- Fitting low-rank RNNs to neural trajectories (LINT method).☆17Updated 3 months ago
- ☆54Updated 2 years ago
- Simple tutorial on Gaussian and Poisson GLMs for single and multi-neuron spike train data☆94Updated 2 years ago
- non-parametric inference for convolutional filters in poisson glms☆13Updated 3 years ago
- Train excitatory-inhibitory recurrent neural networks for cognitive tasks.☆50Updated 9 years ago
- GLMCC: The generalized linear model for spike cross-correlation (Kobayashi et al., Nature Communications, 2019)☆35Updated 2 years ago
- ☆54Updated 3 months ago
- Recordings of 10k neurons during spontaneous behaviors☆52Updated last year
- Fitting and simulation of Poisson generalized linear model for single and multi-neuron spike trains (Pillow et al 2008).☆40Updated 5 years ago
- This reading list is centered around the practical application of linear dynamical systems models to predict neural data☆38Updated 3 years ago
- Short-term plasticity RNN models in Tensorflow☆34Updated 5 years ago
- Code for "Cortical areas interact through a communication subspace", Semedo et al. (Neuron, 2019)☆46Updated 5 years ago
- Tools for spike data analysis and visualization☆106Updated 2 years ago