A pathway to reproducible science: the Neuroscience Experiments System

The Neuroscience Experiments System (NES) is a by-product of the technology-transfer team of FAPESP's Research, Innovation and Dissemination Center for Neuromathematics. An open-source tool, it is used to manage clinical data gathered in hospitals and research institutions. It is also a relevant resource for reproducible science.

Officially launched in 2018, NES is a resource for managing data and metadata from EEG, EMG and TMS. It can also be used for managing data collected from questionnaires. Researchers may store information of participants involved in a study, such as sociodemographic data, social history and medical evaluations.

The NeuroMat technology-transfer team is led by Antonio Carlos Roque da Silva Filho. The specific team that has developed NES was led by Claudia Domingues Vargas, Kelly Rosa Braghetto and Marco Dimas Gubitoso.

Information on the tool may be found at its official page on Github. 

Data sharing

NES can also be used as a resource for data sharing. Scientific publications have increasingly requested researchers to provide openly data from their studies. This NeuroMat's tool allows for easy data transmission through an open database. Data from participants in an experiment managed with NES is anonymized before submission. Moreover, NES allows for anonymous participant registration, for instance, without the need to enter sensitive data such as ID number or address.

One may select --or not-- to make experimental data publicly available at the time of creating a new experiment in NES. There is a checkbox field called "Is public". At the time of experiment creation this field is unchecked by default. Just select it to make the experiment available for publication, which means data will be received and stored at the NeuroMat database after being reviewed by the database's curating committee.

In the NeuroMat database the experiment receives a Creative Commons license and the data is accessible through a URL. In this database, the experiment is versioned, which allows new data from the same experiment to be transmitted and a history of what happened with the experiment to be kept.

The Neuromat database works as a portal for viewing and downloading data and metadata from neuroscience experiments. It is also a Rest API that can be used by any application that has an internet connection. To request API access credentials it is necessary to contact the NeuroMat technology transfer team.

Open science

Further development of NES will include incorporating frictionless data specifications to data sharing. This remains a step to increment the use of this tool in reproducible science strategies. This further development has been granted Frictionless Data Tool Fund for incorporating the philosophy of Frictionless Data to NES. The goal is to adjust the data exportation module to reflect specifications for data and metadata interoperability and also to be in the Data Package format, as well as any other feature to be in accordance to the philosophy proposed. A major feature to be developed is a JSON file "descriptor" with initial information related to the experiment. As it was claimed in an interview on this award by the Open Knowledge Foundation, "To bring NES to the philosophy for Frictionless Data opens up an opportunity for scientists to have access not only to a universe of well-documented and labeled data, but also to understand the process that generated this data."

An early version of the tool was presented to the global community in Neuroinformatics 2016. In this presentation, it was said: "NES was developed to keep together experimental data and its fundamental provenance information, defined by the seven W's (Who, What, Where, Why, When, Which, (W) how). Examples of provenance information maintained by NES are: information about the scientists responsible for the experiment and collection of data and the description of the subject groups (who); the details about the recording protocol or behavioral data collection (e.g. the types of data collection performed) (what); the details of the experimental protocol used in the collection of primary data (how); the start/end date-time for data collection (when); the purpose of the experiment (why); the information about the experimental conditions to which the groups of subjects are submitted, such as tasks to perform and stimulus to apply (which); the information about the laboratory where data was collected (where) and even publications or other results that have arisen from the study of the collected data."


Ways to install NES are twofold. One can download directly on a machine or use a Docker image. Direct installation on a machine requires a specific environment setup, including the Postgres database and the LimeSurvey questionnaire system, as well as the Python virtual environment setup. To install using a Docker image, one just needs to download and run the package. Instructions for both ways of installation can be found on the NES documentation page.

Direct installation is supported on UNIX-based systems such as Linux and MacOS, while installation with the Docker image is possible on all Docker compatible systems.

For the installation, basic knowledge of Computer Networks and Operating Systems, especially UNIX-based systems, is recommended. For customization, basic knowledge of Python and Django is desirable.

Use and development

NES was designed to handle data from different equipments. It is the responsibility of the researcher to register information on the equipment. Metadata from the experiment, including the equipment configuration for each collection, will be stored and made available for download.

After registering information on the study, as well as the groups and participants and the experimental protocol for each group, the experiment is conducted by the researcher, who performs data collection. These data collections vary depending on the types of steps that were entered into the experimental protocol: instruction, quiz, stimulus, task, EEG, EMG, TMS, or generic data collection. For example, if the experiment has an EEG step, the researcher can upload the files generated by the equipment. If the experiment has a quiz step created in LimeSurvey and integrated with NES, the researcher can start filling in participant responses directly from NES - in this case NES will automatically link to LimeSurvey at the time of completing answers. When participants' data is collected, the researcher can export it to a compressed file and manage the experiment by removing, editing, or creating new collections with new or the same participants.

As a use milestone, the NeuroMat data-management tool was used to develop a documented database on Traumatic Brachial Plexus Injury.

NES is a free software and its source code is available for improvements and adaptations. Its development strategy has been described as communicative and collaborative, thus remaining exemplary. Bugs may be reported at the specific page on GitHub.

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