Displaying 1 to 20 from 48 results

psychopy - For running psychology and neuroscience experiments

  •    Python

PsychoPy is an open-source package for creating psychology stimuli in Python (A real and free alternative to Matlab). PsychoPy combines the graphical strengths of OpenGL with the easy Python syntax to give psychophysics a free and simple stimulus presentation and control package. The goal is to provide, for the busy scientist (including me!), tools to control timing and windowing and a simple set of pre-packaged stimuli and methods. The code is platform independent, using Python and C libraries that are widely available.

course-content - NMA Computational Neuroscience course

  •    Jupyter

Objectives: Introduce traditional and emerging computational neuroscience tools, their complementarity, and what they can tell us about the brain. A main focus is on modeling choices, model creation, model evaluation and understanding how they relate to biological questions.

nengo - A Python library for creating and simulating large-scale brain models

  •    Python

Nengo is a Python library for building and simulating large-scale neural models. Nengo can create sophisticated spiking and non-spiking neural simulations with sensible defaults in a few lines of code. Yet, Nengo is highly extensible and flexible. You can define your own neuron types and learning rules, get input directly from hardware, build and run deep neural networks, drive robots, and even simulate your model on a completely different neural simulator or neuromorphic hardware. Nengo depends on NumPy, and we recommend that you install NumPy before installing Nengo. If you're not sure how to do this, we recommend using Anaconda.

awesome-neuroscience - A curated list of awesome neuroscience libraries, software and any content related to the domain

  •    

Curated list of awesome neuroscience libraries, software and any content related to the domain. Neuroscience is the study of how the nervous system develops, its structure, and what it does. Neuroscientists focus on the brain and its impact on behavior and cognitive functions. Traditionally, neuroscience has been seen as a branch of biology, but it has grown to encompass a wide range of interdisciplinary fields that work together toward elucidating brain function at multiple levels of investigation.




PreSti - The Neuroscience Stimuli Presentation Software

  •    CSharp

PreSti is stimuli delivery and experimental control program for neuroscience developed in C#, based on DirecX and NShapes framework.

Emotiv Engine Client

  •    DotNet

Provides an event-driven .NET framework wrapper around the managed Emotiv EPOC neuroheadset API.

brian2 - Brian is a free, open source simulator for spiking neural networks.

  •    Python

Brian is a free, open source simulator for spiking neural networks. It is written in the Python programming language and is available on almost all platforms. We believe that a simulator should not only save the time of processors, but also the time of scientists. Brian is therefore designed to be easy to learn and use, highly flexible and easily extensible. Brian2 is released under the terms of the CeCILL 2.1 license.


dyfunconn - A dynamic functional connectivity module in python.

  •    Python

A neuroimaging module for dynamic functional connectivity. dyfunconn is specifically tailored for functional connectivity, synchrony estimators and graph analysis in the context of Functional Connectivity Microstates (FCμstates) analyzing Time-Varying Functional Connectivity Graphs (TVFCGs). The primary focus in the FCμstates paradigm is twofold; to represent the input time-varying connectivity into a small number-repertoire (data reduction) of features (feature extraction) while preserving the temporal dynamics of the connectivity patterns.

c2s - A toolbox for inferring spikes from calcium traces.

  •    Python

Tools for the prediction of spike trains from calcium traces. If you are a neuroscientist and want to reconstruct spikes from fluorescence/calcium traces or similar signals, please see the main documentation. If you are a developer and want to use c2s in your own Python code, please see the API documentation.

dvid - Distributed, Versioned, Image-oriented Dataservice

  •    Go

Status: In production use at Janelia. See wiki page for outside lab use of DVID. See the DVID Wiki for more information including installation and examples of use.

python-in-neuroscience-tutorials - Collection of tutorials about methods of computational neuroscience using Python

  •    Jupyter

The view the tutorials you can use the excellent nbviewer. To go to the table of contents follow the link. (You can also open them on Github, but nbviewer gives a nicer user experience).

CoreNeuron - Simulator optimized for large scale neural network simulations.

  •    C++

CoreNEURON is a simplified engine for the NEURON simulator optimised for both memory usage and computational speed. Its goal is to simulate massive cell networks with minimal memory footprint and optimal performance. If you are a new user and would like to use CoreNEURON, this tutorial will be a good starting point to understand complete workflow of using CoreNEURON with NEURON.

eFEL - Electrophys Feature Extraction Library

  •    C++

The Electrophys Feature Extraction Library (eFEL) allows neuroscientists to automatically extract features from time series data recorded from neurons (both in vitro and in silico). Examples are the action potential width and amplitude in voltage traces recorded during whole-cell patch clamp experiments. The user of the library provides a set of traces and selects the features to be calculated. The library will then extract the requested features and return the values to the user. The core of the library is written in C++, and a Python wrapper is included. At the moment we provide a way to automatically compile and install the library as a Python module. Instructions on how to compile the eFEL as a standalone C++ library can be found here.

neurocurator - Desktop application (GUI) to perform systematic and collaborative curation of neuroscientific literature

  •    Python

Desktop application to perform systematic and collaborative curation of neuroscientific literature. This is a Graphical User Interface (GUI) for the Python package NeuroAnnotation Toolbox (NAT).

BluePyOpt - Blue Brain Python Optimisation Library

  •    Python

The Blue Brain Python Optimisation Library (BluePyOpt) is an extensible framework for data-driven model parameter optimisation that wraps and standardises several existing open-source tools. It simplifies the task of creating and sharing these optimisations, and the associated techniques and knowledge. This is achieved by abstracting the optimisation and evaluation tasks into various reusable and flexible discrete elements according to established best-practices.

machine_learning_and_neuroscience - This is the code for "Machine Learning & Neuroscience" By Siraj Raval on Youtube

  •    Javascript

This is the code from this video on Youtube by Siraj Raval. An interactive network visualization tool for exploring functional brain connectivity using d3.js. See this for an example of SpectraVis in action.

neuroshapes - Open SHACL schemas for F.A.I.R. neuroscience data

  •    Scala

The goal of Neuroshapes is the development of open, use case driven and shared validatable data models (schemas, vocabularies) to enable the FAIR principles (Findable, Accessible, Interoperable and Reusable) for basic, computational and clinical neuroscience (meta)data. The data models developed thus far entities for electrophysiology, neuron morphology, brain atlases, in vitro electrophysiology and computational modeling. Future developments could include brain imaging, transcriptomic and clinical form data, as determined by community interests. the use of standard semantic markups and linked data principles as ways to structure metadata and related data: the W3C RDF format is leveraged, specifically its developer friendly JSON-LD serialization. The adoption of linked data principles and JSON-LD will ease federated access and discoverability of distributed neuroscience (meta)data over the web.

crcnsget - cli for downloading data from crcns.org

  •    Python

First, make sure you are have an account at at crcns.org. If you do not, you can request one https://crcns.org/request-account/fg_base_view_p3. crcnsget will then prompt for your password.






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