March 13, 2019
Suhasa Kodandaramaiah from the University of Minnesota, Twin Cities, has shared the following about Craniobot, a computer numerical controlled robot for cranial microsurgeries.
The palette of tools available for neuroscientists to measure and manipulate the brain during behavioral experiments has greatly expanded in the previous decade. In many cases, using these tools requires removing sections of the skull to access the brain. The procedure to remove the sub-millimeter thick mouse skull precisely without damaging the underlying brain can be technically challenging and often takes significant skill and practice. This presents a potential obstacle for neuroscience labs wishing to adopt these technologies in their research. To overcome this challenge, a team at the University of Minnesota led by Mathew Rynes and Leila Ghanbari (equal contribution) created the ‘Craniobot,’ a cranial microsurgery platform that combines automated skull surface profiling with a computer numerical controlled (CNC) milling machine to perform a variety of cranial microsurgical procedures on mice. The Craniobot can be built from off-the-shelf components for a little over $1000 and the team has demonstrated its capability to perform small to large craniotomies, skull thinning procedures and for drilling pilot holes for installing bone anchor screws.
Read more about the Craniobot here. Software package for controlling the craniobot can be found on Github.
Ghanbari, L., Rynes, M. L., Hu, J., Schulman, D. S., Johnson, G. W., Laroque, M., . . . Kodandaramaiah, S. B. (2019). Craniobot: A computer numerical controlled robot for cranial microsurgeries. Scientific Reports, 9(1). doi:10.1038/s41598-018-37073-w
In a recent article, Jennifer Tegtmeier and colleagues have shared CAVE: an open-source tool in MATLAB for combined analysis of head-mounted calcium imaging and behavior.
Calcium imaging is spreading through the neuroscience field like melted butter on hot toast. Like other imaging techniques, the data collected with calcium imaging is large and complex. CAVE (Calcium ActiVity Explorer) aims to analyze imaging data from head-mounted microscopes simultaneously with behavioral data. Tegtmeier et al. developed this software in MATLAB with a bundle of unique algorithms to specifically analyze single-photon imaging data, which can then be correlated to behavioral data. A streamlined workflow is available for novice users, with more advanced options available for advanced users. The code is available for download from GitHub.
Read more from Frontiers in Neuroscience, or check it out directly from GitHub.
Tegtmeier, J., Brosch, M., Janitzky, K., Heinze, H., Ohl, F. W., & Lippert, M. T. (2018). CAVE: An Open-Source Tool for Combined Analysis of Head-Mounted Calcium Imaging and Behavior in MATLAB. Frontiers in Neuroscience, 12. doi:10.3389/fnins.2018.00958
February 6, 2019
Arne Meyer and colleagues recently shared their design and implementation of a head-mounted camera system for capturing detailed behavior in freely moving mice.
Video monitoring of animals can give great insight to behaviors. Most video monitoring systems to collect precise behavioral data require fixed position cameras and stationary animals, which can limit observation of natural behaviors. To address this, Meyer et al. developed a system which combines a lightweight head-mounted camera and head-movement sensors to detect behaviors in mice. The system, built using commercially available and 3D printed parts, can be used to monitor a variety of subtle behaviors including eye position, whisking, and ear movements in unrestrained animals. Furthermore, this device can be mounted in combination with neural implants for recording brain activity.
Read more here!
Meyer, A. F., Poort, J., O’Keefe, J., Sahani, M., & Linden, J. F. (2018). A Head-Mounted Camera System Integrates Detailed Behavioral Monitoring with Multichannel Electrophysiology in Freely Moving Mice. Neuron, 100(1). doi:10.1016/j.neuron.2018.09.020
January 23, 2019
Hot off the press in eLife, Andrea Giovannucci and colleagues have shared their open-source software library, CaImAn, for one and two-photon Calcium Imaging data Analysis.
In vivo calcium imaging has gained popularity in recent years for its ability to record large quantities of neural activity from multiple brain areas over extended time periods. With advanced tools for recording and collecting data comes large quantities of data. With large datasets comes a need for streamlined ways to analyze it. Giovannucci and colleagues have developed and shared a toolbox for analyzing complex calcium imaging datasets. CaImAn, developed in the open-source Python language (with optional implementation in MATLAB), is designed to correct for motion, estimate spikes, detect new neurons, and assess neuronal activity and locations in a given timeframe. The software can be used on pre-recorded data or can also enabled for real-time analysis. CaImAn is available to download with examples from GitHub, and more information can be obtained through reading the aforementioned manuscript.
Check out GitHub, or the article from eLife!
Giovannucci, A., Friedrich, J., Gunn, P., Kalfon, J., Brown, B. L., Koay, S. A., . . . Pnevmatikakis, E. A. (2019). CaImAn an open source tool for scalable calcium imaging data analysis. ELife, 8. doi:10.7554/elife.38173
December 12, 2018
Vladislav Voziyanov and colleagues have developed and shared the TRIO Platform, a low-profile in vivo imaging support and restraint system for mice.
In vivo optical imaging methods are common tools for understanding neural function in mice. This technique is often performed in head-fixed, anesthetized animals, which requires monitoring of anesthesia level and body temperature while stabilizing the head. Fitting each of the components necessary for these experiments on a standard microscope stage can be rather difficult. Voziyanov and colleagues have shared their design for the TRIO (Three-In-One) Platform. This system is compact and provides sturdy head fixation, a gas anesthesia mask, and warm water bed. While the design is compact enough to work with a variety of microscope stages, the use of 3D printed components makes this design customizable.
Read more about the TRIO Platform in Frontiers in Neuroscience!
The design files and list of commercially available build components are provided here.
Voziyanov, V., Kemp, B. S., Dressel, C. A., Ponder, K., & Murray, T. A. (2016). TRIO Platform: A Novel Low Profile In vivo Imaging Support and Restraint System for Mice. Frontiers in Neuroscience, 10. doi:10.3389/fnins.2016.00169
October 24, 2018
Qingchun Guo and colleagues share their cost-effective, multi-channel fiber photometry system in Biomedical Optics Express.
Fiber photometry is a viable tool for recording in vivo calcium activity in freely behaving animals. In combination with genetically encoded calcium indicators, this tool can be used to measure neuronal and population activity from a genetically defined subset of neurons. Guo and colleagues have developed a set-up to allow for recording from multiple brain regions, or multiple animals, simultaneously with the use of a galvano-mirror system. This creative and simple solution reduces the number of detectors necessary for multi-channel data collection. This expands the ability of researchers to collect calcium imaging data from many subjects in a cost-effective way.
Read more here!
Guo, Q., Zhou, J., Feng, Q., Lin, R., Gong, H., Luo, Q., … Fu, L. (2015). Multi-channel fiber photometry for population neuronal activity recording. Biomedical Optics Express, 6(10), 3919–3931. https://doi.org/10.1364/BOE.6.003919
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September 12, 2018
In Frontiers in Neuroinformatics, Jason Rothman and R. Angus Silver share NeuroMatic, an open-source toolkit for acquiring, analyzing and simulating electrophysiological data.
Data acquisition, analysis, and simulation are key components of understanding neural activity from electrophysiological recordings. Traditionally, these three components of ephys data have been handled by separate software tools. NeuroMatic was developed to merge these tools into a single package, capable of performing a variety of patch-clamp recordings, data analysis routines and simulations of neural activity. Additionally, due to its open-source, modular design in WaveMetrics Igor Pro, NeuroMatic allows users to develop their own analysis functions that can be easily incorporated into its framework. By integrating acquisition, analysis, and simulation together, researchers are able to conserve experimental metadata and track the analysis performed in real time, without involving separate softwares.
Read more about NeuroMatic here!
Or check out their website and GitHub.
August 29, 2018
In a recent bioRxiv preprint, Scott Owen and Anatol Kreitzer share PhotometryBox, an open-source solution for electronic control of fiber-based fluorescence measurements.
Fluorescence measurements from deep-brain structures through optical fibers (fiber photometry) represent a versatile, powerful, and rapidly growing neuroscience technique. A typical fiber photometry system consists of three
parts: (1) an implant with an optical fiber that is cemented to the skull, (2) optical components for generation of fluorescence excitation light and detection of emission light, and (3) electronic components for controlling light sources and acquiring signals. Excellent technical solutions are available for implants and optical components; however, currently available electronic control systems are not optimized for these experiments. The most commonly used electronic components are either over-engineered or unnecessarily inflexible. To address these issues, Owen et al have developed an open-source, low-cost solution for the electronic components. This system is based on a programmable microcontroller (MBED LPC1768) and can be assembled in ~1 hour (less than a day for an inexperienced user with limited soldering experience). The total estimated cost is about $650, less than one tenth the price of the most commonly used commercially available systems.
The design, development and implementation of this project is described in a manuscript now available on bioRxiv, while details regarding parts, construction and use are available on Hackaday.
Read more on bioRxiv
or check out the Hackaday page.
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!