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Category: Neural Recording

MNE Scan: Software for real-time processing of electrophysiological data

July 9, 2020

In a 2018 Journal of Neuroscience Methods article, Lorenz Esch and colleagues present MNE Scan, a software that provides real-time acquisition and processing of electrophysiological data.

MNE Scan is a state-of-the-art real-time processing software for clinical MEG and EEG data. By allowing for real-time analysis of neuronal activity, MNE Scan enables the optimization of input stimuli and permits the use of neurofeedback. MNE Scan is based on the open-source MNE-CPP library. Written in C++, MNE-CPP is a software framework that processes standard electrophysiological data formats and is compatible with Windows, Mac, and Linux. Compared to other open-source real-time electrophysiological processing software, MNE Scan is designed to meet medical regulatory requirements such as the IEC 62304. This makes MNE Scan ideal for clinical studies and is already in active use with an FDA approved pediatric MEG system. MNE Scan has also been validated in several different use cases, making it a robust solution for the processing of MEG and EEG data in a variety of scenarios.

Read more in the paper here!

Or check it out right from their website!


May 21, 2020

Hot off the eLife press, Jeremy Magland and colleagues have shared SpikeForest, a tool for validating automated neural spike sorters.

Spike sorting is a crucial step in neural data analysis. Manual spike sorting is time consuming and sensitive to human error, so much effort has been placed into developing automated algorithms to perform this necessary step. However, even with rapid development and sharing of these tools, there is little information to guide researchers for which algorithm may best serve their needs and that it offers the accuracy needed to give a complete scope of the data. To address this, Magland and colleagues across 11 research groups have developed and contributed data for SpikeForest. This python based software suite utilizes a large database of ephys recordings featuring ground truth units (units that have spike patterns known a priori), a parallel processing pipeline to benchmark algorithm performance, and a web interface for users to explore results. This tool can be used to assess which algorithm works best to extract data from different recording and experimental methods (in vivo, ex vivo, tetrode, etc) and provides accurate evaluation metrics for comparison. Information about the spike sorting algorithms that SpikeForest can compare are available in the recent publication, as well as a preliminary comparison of these algorithms based on community provided datasets. The SpikeForest Interface also allows users to sort their own data with a few modifications to the code, which is discussed in the publication. Be sure to check it out!

Read about SpikeForest here!

Or explore the SpikeForest web interface here!


April 30, 2020

Jeffrey P. Gill and colleagues have developed and shared a new toolbox for synchronizing video and neural signals, cleverly named neurotic!

Collecting neural data and behavioral data are fundamental to behavioral neuroscience, and the ability to synchronize these data streams are just as important as collecting the information in the first place. To make this process a little simpler, Gill et al. developed an open-source option called neurotic, a NEUROscience Tool for Interactive Characterization. This tool is programmed in Python and includes a simple GUI, which makes it accessible for users with little coding experience. Users can read in a variety of file formats for neural data and video, which they can then process, filter, analyze, annotate and plot. To show the effectiveness across species and signal types, the authors tested the software with aplysia feeding behavior and human beam walking. Given its open-source nature and strong integration of other popular open-source packages, this software will continue to develop and improve as the community uses it.

Read more about neurotic here!

Check out the documentation here.

Gill, J. P., Garcia, S., Ting, L. H., Wu, M., & Chiel, H. J. (2020). Neurotic: Neuroscience Tool for Interactive Characterization. Eneuro. doi:10.1523/eneuro.0085-20.2020

Toolboxes for Spike and LFP Analysis

April 9, 2020

There are a number of open source toolboxes available for neural data analysis, especially for spike and local field potential data. With more options comes a more difficult decision when it comes to selecting the toolbox that’s right for your data. Fortunately, Valentina Unakafova and Alexander Gail have compared several toolboxes for spike and LFP analysis, connectivity analysis, dimensionality reduction, and generalized linear modeling. They discuss the major features of software available for Python and MATLAB (Octave) including Brainstorm, Chronux, Elephant, FieldTrip, gramm, Spike Viewer, and SPIKY. They include succinct tables for assessing system and program requirements, quality of documentation and support, and data types accepted by each toolbox. Using an open-access dataset, they assess the functionality of the programs and finish their comparison with highlighting advantages of each toolbox to consider when trying to find the one that works best for your data. The files they used to compare toolboxes are all available from GitHub to supplement their paper.

Analysis of spike and local field potential (LFP) data is an essential part of neuroscientific research.

Read their full comparison here.

Check out their GitHub for the project here.

Rigbox: an open source toolbox for probing neurons and behavior

January 30, 2020

In a recent preprint, Jai Bhagat, Miles J. Wells and colleagues shared a toolbox, developed by Christopher Burgess, for streamlining behavioral neuroscience experiments.

In behavioral neuroscience, it’s important to keep track of both behavioral data and neural data, and have it done so in a way that makes analysis simpler later on. One of the best ways to achieve this is by having a centralized system for running behavioral and neural recording software while streaming all the data. To address this, Burgess and team developed Rigbox, a high-performance, open-source software toolbox that facilitates a modular approach to designing experiments. Rigbox runs in MATLAB (with some Java and C for network communication and processing speed improvements), and its main submodule, Signals, allows intuitive programming of behavioral tasks. While it was originally developed for behavioral analysis from mice in a steering wheel driven task, the authors show its feasibility for human behavioral tasks (psychophysics & pong game), highlighting the broad array of ways this toolbox can be used in neuroscience.
For more, check out the full preprint!
Or jump right in on Github.

RatHat: A self-targeting printable brain implant system

JANUARY 9, 2020

Leila Allen and colleagues in Tim Allen’s lab at Florida International University recently developed RatHat, a self-targeting printable brain implant system. Below they describe their project:

“There has not been a major change in how neuroscientists approach stereotaxic methods in decades. Here we present a new stereotaxic method that improves on traditional approaches by reducing costs, training, surgical time, and aiding repeatability. The RatHat brain implantation system is a 3D printable stereotaxic device for rats that is fabricated prior to surgery and fits to the shape of the skull. RatHat builds are directly implanted into the brain without the need for head-leveling or coordinate-mapping during surgery. The RatHat system can be used in conjunction with the traditional u-frame stereotaxic device, but does not require the use of a micromanipulator for successful implantations. Each RatHat system contains several primary components including the implant for mounting intracranial components, the surgical stencil for targeting drill sites, and the protective cap for impacts and debris. Each component serves a unique function and can be used together or separately. We demonstrate the feasibility of the RatHat system in four different proof-of-principle experiments: 1) a 3-pole cannula apparatus, 2) an optrode-electrode assembly, 3) a fixed-electrode array, and 4) a tetrode hyperdrive. Implants were successful, durable, and long-lasting (up to 9 months). RatHat print files are easily created, can be modified in CAD software for a variety of applications, and are easily shared, contributing to open science goals and replications. The RatHat system has been adapted to multiple experimental paradigms in our lab and should be a useful new way to conduct stereotaxic implant surgeries in rodents.

RatHat is freely available to academic researchers, achieving open science goals. Academic and non-profit researchers interested in receiving the 3D files can contact Dr. Timothy Allen (tallen@fiu.edu). We will first provide you a simple noncommercial license to be executed by your institution, and upon completion, printable and editable 3D files of the implant system. Our responses are fast, and all files are provided immediately after receiving the aforementioned document. Our goals are noncommercial, and our only interests are to share RatHat as widely as possible in support of our open science goals and to improve the pace of discovery using chronic brain implant systems for behavioral studies.”


The Allen lab has provided a video tutorial on how to implant RatHat, which you can view here on youtube.


For more details, you can check out the preprint here.


3D Printed Headcap and Microdrive

SEPTEMBER 26, 2019

In their 2015 Journal of Neurophysiology article, the Paré Lab at the Center for Molecular and Behavioral Neuroscience at Rutgers University describe their novel head-cap and microdrive design for chronic multi-electrode recordings in rats through the use of 3D printing technology and highlight the impact of 3D printing technology on neurophysiology:

There is a need for microdrives and head-caps that can accommodate different recording configurations. Many investigators implant multiple individual drives aiming to record from numerous areas. However, this extends surgery time, impairs animal recovery, and complicates experiments. Other strategies rely on more expensive custom-machined drive assemblies that are specifically built for a particular set of regions, limiting their adaptability. Some proposed designs allow targeting of multiple regions, but recording sites must be within a few millimeters so are only suitable for mice and not for accessing areas of larger brains (like in rats, for example).

Utilizing 3D printing technology to create a novel design concept of microdrives and head-caps, this group’s design allows for recording of multiple brain regions in different configurations. In their article, the lab reviews the basic principles of 3D design and printing and introduce their approach to multisite recording, explaining how to construct the individual required components. The 3D printed head cap and electrode microdrive enables investigators to perform chronic multi-site recordings in rats. The head cap is composed of five components and there are three types of microdrives that can be used in different combinations or positions to study different targets. The different microdrive designs have different functionality including for extended driving depths, targeting of thin layers, and allowing many microdrives to be placed in a small area.

To show the viability of their new designs, the lab presents LFP recordings obtained throughout the cortico-hippocampal loop using 3D printed components. The lab suggests investigators modify their designs to best suit their research needs and give changeable versions of the three parts most important in modification. The investigators also provide a detailed explanation of the printing, assembly, and implantation of the head caps and microdrives. Finally, they indicate the ways 3D printing advancements can change how chronic implants are designed and used, notably 3D scanning and new material development.

For more information on the microdrive and headcap, see their paper’s Appendix, which has full instructions and advice on building these devices.

Headley, D. B., DeLucca, M. V., Haufler, D., & Paré, D. (2015). Incorporating 3D-printing technology in the design of head-caps and electrode drives for recording neurons in multiple brain regions. Journal of Neurophysiology, 113(7), 2721–2732. https://doi.org/10.1152/jn.00955.2014


AUGUST 22, 2019

We’d like to highlight groups and companies that support an open-source framework to their software and/or hardware in behavioral neuroscience. One of these groups is SpikeGadgets, a company co-founded by Mattias Karlsson and Magnus Karlsson.

SpikeGadgets is a group of electrophysiologists and engineers who are working to develop neuroscience hardware and software tools. Their open-source software, Trodes, is a cross-platform software suite for neuroscience data acquisition and experimental control, which is made up of modules that communicate with a centralized GUI to visualize and save electrophysiological data. Trodes has a camera module and a StateScript module, which is a state-based scripting language that can be used to program behavioral tasks through using lights, levels, beam breaks, lasers, stimulation sources, audio, solenoids, etc. The camera module can be used to acquire video that can synchronize to neural recordings; the camera module can track the animal’s position in real-time or play it back after the experiment. The camera module can work with USB webcams or GigE cameras.

Paired with the Trodes software and StateScript language is the SpikeGadgets hardware that can be purchased on their website. The hardware is used for data acquisition (Main Control Unit, used for electrophysiology) and behavioral control (Environmental Control Unit).  SpikeGadgets also provides both Matlab and Python toolboxes on their site that can be used to analyze both behavioral and electrophysiological data. Trodes can be used on Windows, Linux, or Mac, and there are step-by-step instructions for how to install and use Trodes on the group’s bitbucket page.

Spikegadgets mission is “to develop the most advanced neuroscience tools on the market, while preserving ease of use and science-driven customization.”


For more information on SpikeGadgets or to download or purchase their software or hardware, check out their website here.

There is additional documentation on their BitBucket Wiki, with a user manual, instructions for installation, and FAQ.

Check out their entire list of collaborators, contributors, and developers here.


July 12, 2019

Sebastien Delcasso from the Graybiel lab at MIT published a method for developing a brain implant called “HOPE” for combining with optogenetics, pharmacology, and electrophysiology:

HOPE (hybrid-drive combining optogenetics, pharmacology, and electrophysiology) is a method that simplifies the construction of a drivable and multi-task recording implant. HOPE is a new type of implant that can support up to 16 tetrodes, and allows for recordings of two different brain areas in a mouse at the same time, along with simultaneous optogenetic or pharmacological manipulation. The HOPE implants are open-source and can be recreated in CAD software and subsequently 3D printed, drastically lowering the cost of an electrophysiological implant. Additionally, instead of waiting months for a custom-made implant, these can be printed within a few hours.

The manuscript provides detailed instructions on constructing the implant, and allows for users to individually modify it for their own needs (and can be modified to be used in rats or non-human primates). Additionally, HOPE is meant to be used in experiments with paired electrophysiological experiments with either optogenetic or pharmacological manipulations, which will inevitably open the door to many more experiments. The implant is intended for microdrive recordings, and the actual implant is only made up of six 3D printed parts, an electrode interface board (EIB), and five screws.

The authors validate the implant by first successfully recording striatal neurons, using transgenic PV-Cre mice to optogenetically inhibit parvalbumin interneurons, and then using muscimol infused into the striatum in a head-fixed mouse preparation. HOPE is a novel open-source neural implant that can be paired with multiple methods (recordings, optogenetics, and pharmacology) to help in manipulating and subsequently recording brain activity.



More details of their implant can be found on their project site and on the project GitHub.

Delcasso, S., Denagamage, S., Britton, Z., & Graybiel, A. M. (2018). HOPE: Hybrid-Drive Combining Optogenetics, Pharmacology and Electrophysiology. Frontiers in neural circuits, 12, 41.


3D Printed Headstage Implant

June 6, 2019

Richard Pinnell from Ulrich Hofmann’s lab has three publications centered around open-source and 3D printed methods for headstage implant protection and portable / waterproof DBS and EEG to pair with water maze activity. We share details on the three studies below:

Most researchers opt to single-house rodents after rodents have undergone surgery. This helps the wound heal and prevent any issues with damage to the implant. However, there is substantial benefits to socially-housing rodents, as social isolation can create stressors for them. As a way to continue to socially-house rats, Pinnell et al. (2016a) created a novel 3D-printed headstage socket to surround an electrode connector. Rats were able to successfully be pair housed with these implants and their protective caps.

The polyamide headcap socket itself is 3D printed, and a stainless steel thimble can be screwed into it. The thimble can be removed by being unscrewed to reveal the electrode connector. This implant allows both for increased well-being of the rodent post-surgery, but also has additional benefits in that it can prevent any damage to the electrode implant during experiments and keeps the electrode implant clean as well.

The 3D printed headcap was used in a second study (Pinnell et al., 2016b) for wireless EEG recording in rats during a water maze task. The headstage socket housed the PCB electrode connector and the waterproof wireless system was attached. In this setup, during normal housing conditions, this waterproof attachment was replaced with a standard 18×9 mm stainless-steel sewing thimble, which contained 1.2 mm holes drilled at either end for attachment to the headstage socket. A PCB connector was manufactured to fit inside the socket, and contains an 18-pin zif connector, two DIP connectors, and an 18-pin Omnetics electrode connector for providing an interface between the implanted electrodes and the wireless recording system.

Finally, the implant was utilized in a third study (Pinnell et al., 2018) where the same group created a miniaturized, programmable deep-brain stimulator for use in a water maze. A portable deep brain stimulation (DBS) device was created through using a PCB design, and this was paired with the 3D printed device. The 3D printed headcap was modified from its use in Pinnell et al., 2016a to completely cover the implant and protect the PCB. The device, its battery, and housing weighs 2.7 g, and offers protection from both the environment and from other rats, and can be used in DBS studies during behavior in a water maze.

The portable stimulator, 3D printed cap .stl files, and more files from the publications can be found on https://figshare.com/s/31122e0263c47fa5dabd.

Pinnell, R. C., Almajidy, R. K., & Hofmann, U. G. (2016a). Versatile 3D-printed headstage implant for group housing of rodents. Journal of neuroscience methods, 257, 134-138.

Pinnell, R. C., Almajidy, R. K., Kirch, R. D., Cassel, J. C., & Hofmann, U. G. (2016b). A wireless EEG recording method for rat use inside the water maze. PloS one, 11(2), e0147730.