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Structural and functional interpretation of brain maps.

EMUsort is an enhanced software package designed for high-performance spike sorting of motor unit action potentials (MUAPs) from intramuscular recordings. It is an extension of Kilosort4 optimized for complex MUAP datasets encountered in motor neuroscience.

A software tool for the automated testing and systematic comparison of detailed models of hippocampal neurons based on electrophysiological data. This package contains validation tests for models of hippocampus, based on the SciUnit framework and the NeuronUnit package. The purpose of this repository is to provide examples on how to run the validation tests of HippoUnit on models of the hippocampal CA1 pyramidal cell available in the literature and on ModelDB. Current tests cover somatic behavior and signal propagation and integration in apical dendrites of hippocampal CA1 pyramidal cell models. Feature errors: Z-score (the difference of model feature value from the exerimental mean feature value in the unit of the experimental SD.). git clone https://github.com/KaliLab/hippounit.git.

HySimODE is a Python framework designed to automate hybrid stochastic-deterministic simulations. It is used for modeling complex biochemical systems that incorporate both low-copy stochastic dynamics and high-abundance deterministic processes.

Decodanda is a Python toolbox designed for analyzing neural population activity. It provides best-practice methods for decoding variables and quantifying geometric features of neural representations, useful in neuroscience and BCIs.

A general-purpose workflow and library built around MMPose for state-of-the-art pose estimation and quantification of animal movements in various complex scenarios.

iS2C2 is a novel cointelligent platform that merges rigorous computational algorithms with the contextual reasoning of Large Language Models (LLMs) to automatically generate interpretable hypotheses from single-cell RNA-seq and spatial transcriptomics data. It specializes in mechanistic discovery of disease-related cellular crosstalk.

DNNBrain is a unifying toolbox for mapping deep neural networks and brains.

Toolkit for Oscillatory Real-time Tracking and Estimation (TORTE).

Tensorpac is an Python open-source toolbox for computing Phase-Amplitude Coupling (PAC) using tensors and parallel computing for an efficient, and highly flexible modular implementation of PAC metrics both known and novel. Check out our documentation for details.

Open source, Python based, hardware and software for controlling behavioural neuroscience experiments.

An Accessible and Flexible Python Package for Training Recurrent Neural Network Models on Cognitive Tasks.

A Python Toolbox of Representational Analysis from Multi-modal Neural Data. A Python Toolbox for Multimode Neural Data Representation Analysis. NeuroRA is an easy-to-use toolbox based on Python, which can do some works about RSA among nearly all kinds of neural data, including behavioral, EEG, MEG, fNIRS, sEEG, ECoG, fMRI and some other neuroelectrophysiological data. In addition, users can do Neural Pattern Similarity (NPS), Spatiotemporal Pattern Similarity (STPS) & Inter-Subject Correlation (ISC) on NeuroRA.

A simulation framework for whole-brain neural mass modeling. To browse the source code of neurolib visit out GitHub repository. Read the gentle introduction to neurolib for an overview of the basic functionality and some background information on the science behind whole-brain simulations.

Frites is a Python toolbox for assessing information-theorical measures on human and animal neurophysiological data (M/EEG, Intracranial). The aim of Frites is to extract task-related cognitive brain networks (i.e modulated by the task). The toolbox also includes directed and undirected connectivity metrics such as group-level statistics.

AMVOC (Analysis of Mouse VOcal Communication) A deep, unsupervised method for rapid detection, analysis, and classification of ultrasonic vocalizations.

A new software tool for interpreting the cellular and network origin of human MEG/EEG data | The Human Neocortical Neurosolver (HNN) is a software tool that gives researchers/clinicians the ability to develop/test hypotheses on circuit mechanisms underlying EEG/MEG data | Click here to join our Google Group | Human Neocortical Neurosolver (HNN) is a user-friendly software tool that provides a novel solution to this challenge | Electro- and magneto-encephalography (EEG MEG) are among the most powerful technologies to non-invasively record human brain activity with millisecond resolution

Python toolbox for the analysis of fiber photometry data.