Data Analysis

Mesmerize is a platform for the annotation and analysis of neuronal calcium imaging data. Mesmerize encompasses the entire process of calcium imaging analysis from raw data to interactive visualizations. Mesmerize allows you to create FAIR-functionally linked datasets that are easy to share.

A batch management system for calcium imaging analysis using the CaImAn library. It contains pandas.DataFrame and pandas.Series extensions that interface with CaImAn for running the various algorithms and organizing input & output data.

TopMouseTacker is a Python library based on OpenCV made for object tracking in videos. It uses a color camera and depth camera to infer the position of objects in the arena.

Advances in fluorescence microscopy enable monitoring larger brain areas in-vivo with finer time resolution. The resulting data rates require reproducible analysis pipelines that are reliable, fully automated, and scalable to datasets generated over the course of months.

CASCADE translates calcium imaging ΔF/F traces into spiking probabilities or discrete spikes. CASCADE is based on deep networks and runs on Python (Linux/Windows/Mac); it can be used either as a web application (Colaboratory notebook), or locally on a CPU or GPU.

DANNCE (3-Dimensional Aligned Neural Network for Computational Ethology) is a convolutional neural network (CNN) that calculates the 3D positions of user-defined anatomical landmarks on behaving animals from videos taken at multiple angles.

Pingouin is an open-source statistical package written in Python 3 and based mostly on Pandas and NumPy. Some of its main features are listed below. For a full list of available functions, please refer to the API documentation.

YASA (Yet Another Spindle Algorithm) is a command-line sleep analysis toolbox in Python. The main functions of YASA are: Automatic sleep staging of polysomnography data (see preprint article). Event detection: sleep spindles, slow-waves and rapid eye movements, on single or multi-channel EEG data.

Fiber photometry (FP) is an adaptable method for recording in vivo neural activity in freely behaving animals. It has become a popular tool in neuroscience due to its ease of use, low cost, the ability to combine FP with freely moving behavior, among other advantages.

Nervous system development and plasticity involves changes in cellular morphology, making morphological analysis a valuable exercise in the study of nervous system development, function and disease. Morphological analysis is a time-consuming exercise requiring meticulous manual tracing of cellular contours and extensions.