Partial analyses to accompany "Uncovering temporal structure in hippocampal output patterns".

Repo containing computational neuroscience notebooks and a project detecting latent states in neural activity using Hidden Markov Models on spiking data, made during the Neuromatch Academy 2020.

Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filte…

Repository to host materials for the summer workshop on the dynamic brain

Deep inspection of Python objects

GGNB Short Method Course "Spike-train analysis with Python" in the Gollisch Lab

MATLAB data analysis of a Interspike Intervals of neurons in a monkey's brain and removing noise from spike train data.

IASBS Theoretical Neuroscience Group toolbox, to analysis the time series, spike trains and graphs in python.

Correlated Spike Trains Python class

Neural Spike Train Analysis

analysis for neuronal spike train data

Collection of functions to investigate correlations in spike trains and membrane potentials

CoNNECT: Convolutional Neural Network for Estimating synaptic Connectivity from spike Trains. Endo et al., bioRxiv (2020).

Analyze spike trains exported from multi-electrode arrays

Accompanying code for Aljadeff et al., 'Analysis of Neuronal Spike Trains, Deconstructed', Neuron (2016)

Code to explore spike train rhythmicity in striatal data

A series of scripts that can be used to classify activity patterns in neural spike trains

Analytical methods for efficient inference of integrate-and-fire circuit models from single-trial spike trains

Code implements the LN model used to describe spike trains of MEC neurons based on the animal's position, head direction, speed, and theta phase information. Used in Hardcastle et al., 2017.

Supplementary material for the paper "Detecting pairwise correlations in spike trains: an objective comparison of methods and application to the study of retinal waves"

Fitting and simulation of Poisson generalized linear model for single and multi-neuron spike trains (Pillow et al 2008).

Neural Spike Train Analysis Toolbox for Matlab

Neyman-Scott point process model to identify sequential firing patterns in high-dimensional spike trains

Code for fitting neural spike trains with nonparametric hidden Markov and semi-Markov models built upon mattjj's PyHSMM framework.

Simple tutorial on Gaussian and Poisson GLMs for single and multi-neuron spike train data

Sample python notebook demonstrating synaptic plasticity.

Python tools for analysing body movements across space and time

Extended edit similarity measurement for high dimensional discrete-time series signal (e.g., multi-unit spike-train).