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SpikeForest

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!


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.


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

SpikeGadgets

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.

HOPE

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.

Phenopy

April 17, 2019

In a recent Nature Protocol’s article, Edoardo Balzani and colleagues from Valter Tucci’s lab have developed and shared Phenopy, a Python-based open-source analytical platform for behavioral phenotyping.


Behavioral phenotyping of mice using classic methods can be a long process and is susceptible to high variability, leading to inconsistent results. To reduce variance and speed up to process of behavioral analysis, Balzani et al. developed Phenopy, an open-source software for recording and analyzing behavioral data for phenotyping. The software allows for recording components of a behavioral task in combination with electrophysiology data. It is capable of performing online analysis as well as analysis of recorded data on a large scale, all within a user-friendly interface. Information about the software is available in their publication, available from Nature Protocols.*

Check out the full article from Nature Protocols!


(*alternatively available on ResearchGate)

Telemetry System for Recording EEG

March 29, 2019

In a 2011 Journal of Neuroscience Methods article, Pishan Chang and colleagues shared their design for an open-source, novel telemetry system for recording EEG in small animals.


EEG monitoring in freely-behaving small animals is a useful technique for observing natural fluctuations in neural activity over time. Monitoring frequencies above 80 Hz continuously over a period of weeks can be a challenge. Chang et al. have shared their design for a system that combines an implantable telemetric sensor, radio-frequency transmission, and an open-source data acquisition software to collect EEG data over a span of up to 8 weeks. Various modifications to the system  have increased the longevity of the device and reduced transmission noise to provide continuous and reliable data. Schematics of the device, transmission system, and validation results in a population of epileptic rodents are available in their publication.

 

Learn more from the Journal of Neuroscience Methods!


PriED: An Open Source 3-D Printed Modular Micro-Drive System for Acute Neurophysiology

August 1, 2018

In a 2014 PLoS ONE article, Shaun R. Patel and colleagues share their design for PriED, an easy to assemble modular micro-drive system for acute primate neurophysiology.


Electrode micro-drives are a great tool that allow for independent positioning of multiple electrodes in primate neurophysiology, however, commercially available micro-drives are often expensive. Printed Electronic Device (PriED) is designed to advance existing micro-drive technology while staying inexpensive and requiring minimal skill and effort to assemble. The device combines 3D printed parts and affordable, commercially available steel and brass components which can then be controlled manually, or automatically with the addition of an optional motor. Using 3D printing technology researchers have the flexibility to be able to modify part designs and create custom solutions to specific recording needs. A public repository of drive designs has been made available where researchers can download PriED components to print for assembly. Additionally, researchers can upload modified designs with annotations for others to use. PriED is an innovative, inexpensive, and user friendly micro-drive solution for flexible multi-site cortical and subcortical recordings in non-human primates.

Read more here!

Or check out the repository here!


NeRD: an open-source neural recording device

July 16, 2018

In a special issue of Journal of Neural Engineering, Dominique Martinez and colleagues their share design for NeRD, an open source neural recording device for wireless transmission of local field potential (LFP) data in in freely-behaving animals.


Electrophysiological recording of local field potentials in freely-behaving animals is a prominent tool used by researchers for assessing the neural basis of behavior. When performing these recordings, cables are commonly used to transmit data to the recording equipment, which tethers the animals and can interfere with natural behavior. Wireless transmission of LFP data has the advantage of removing the cable between the animal and the recording equipment, but is hampered by the large number of data to be transmitted at a relatively high rate.
To reduce transmission bandwidth, Martinez et al. propose an encoder/decoder algorithm based on adaptive non-uniform quantization. As proof-of- concept, they developed a NeRD prototype that digitally transmits eight channels encoded at 10 kHz with 2 bits per sample. This lightweight device occupies a small volume and is powered with a small battery allowing for 2h 40min of autonomy. The power dissipation is 59.4 mW for a communication range of 8 m and transmission losses below 0.1%. The small weight and low power consumption offer the possibility of mounting the entire device on the head of a rodent without resorting to a separate head-stage and battery backpack. The use of adaptive quantization in the wireless transmitting neural implant allows for lower transmission bandwidths, preservation of high signal fidelity, and preservation of fundamental frequencies in LFPs from a compact and lightweight device.
Read more here!

Github