Pixy is an open source computer vision system. Mostafa Nashaat, Robert Sachdev, and colleagues including Matthew Larkum have developed software for use with the Pixy, that can be used to track mouse behavior, including free movement around an enclosure (top image), or track the movement of individual whiskers (bottom image), all at 50 Hz. Here’s
We recently tweeted about a preprint from Eftychios A Pnevmatikakis and Andrea Giovannucci (code). The preprint is on motion correction for calcium imaging data. It is a nice quick read and discusses earlier work in the area. (That’s Eftychios of constrained-non-negative-matrix-factorization-for-calcium-imaging-analysis fame). Marius Pachitariu recognized the algorithm as very similar to one that he uses
SpikeGadgets makes hardware and software for extracellular array recording. They make nice looking hardware, both for recording from arrays, and for controlling experiments. They sell a few accessories as well, including this commutator. Their software is open source. MATLAB and Python code is also part of the project. The company’s run by Mattias Karlsson (worked
Orange is a user friendly, graphical data mining package built with Python, from the University of Ljubljana. Check it out. They have a good blog for the project too.
Results are similar to the slow version of TurboReg, but it runs about twice as fast as the fast version of TurboReg. Here’s the paper. Here’s the code.
Peng Xi (Peking University) shared this resource his lab has developed: software for processing images for structured illumination (a superresolution technique). Here’s the Github repository. And here’s the paper (pay wall). Previously on Labrigger… Structured illumination Notes from an email exchange with the late Mats Gustafsson, a pioneer of structured illumination microscopy
I tweeted about this last fall. This is the best algorithm I’ve seen for segmenting and extracting time course from calcium imaging data. Eftychios Pnevmatikakis developed the code in Liam Paninski’s lab. The work is reported in a pair of papers in Neuron, and the code is freely available (links below). The source separation works
It’s still early days, but this looks impressively good. Ufora might be one of the easiest-to-try ways to use parallel computing. With just a couple of lines of code, you can run your existing Python code on aws or another worker system.
Collaborative Approach for eNhanced Denoising under Low-light Excitation, or CANDLE, is a denoising algorithm specialized for the type of images that are acquired in 2-photon imaging applications. There’s code for both ImageJ and MATLAB available at that link. Here’s a write up on it. The raw images are on the left, and the denoised (via
Stephan (currently in the Gilbert lab @ Rockefeller) wrote in to share his code for analyzing calcium signalling data in MATLAB. Thanks, Stephan! Stephan writes… I made a MATLAB GUI that automatically extracts ROIs from calcium imaging data. You can also add behavior data. Take a look if you feel like, try it out and
Michael Graupner has coded a nice program for browsing and managing hdf5 files (closely related to MATLAB files) called hdf5Manager. And it’s open source.
Following up SIMA, which has been covered here before: The SIMA team has released a new version of its toolbox that includes a spike inference algorithm developed by Eftychios Pnevmatikakis and Liam Paninski’s group. This approach permits the efficient estimation of the most likely spike train underlying a sequence of calcium imaging observations. The new
Carson Chow recently shared his post-MATLAB suite of programming tools, and it involves RStudio, which is open-source. “I had planned to replace Matlab with Python, Julia, and R but I have found that R and Julia have been sufficient for my requirements.” It’s a nice environment and something to try if you’re looking for an
Jeremy Freeman and his lab are developing tools for analyzing data using a workflow that is fundamentally more scalable not only in terms of computing power and data set size, but also in collaboration and sharing. The one-person, one-machine approach to data analysis can be highly efficient, but collaboration and scaling up computational power can
Dylan Muir and Bjorn Kampa created some MATLAB code for two-photon calcium imaging experiments. First up is FocusStack, which provides a suite of analysis tools. Next up is StimServer, which coordinates visual stimulus generation and presentation. The paper is open access. In particular, Dylan’s MATLAB functions MappedTensor and TIFFStack are worth checking out. Both provide
- GCaMP6 now available on
- Sourcing small parts on
- Analysis algorithms: performance quantification and ground truth on
- Laser pointers and quantum mechanics on
- Pixy for easy Arduino machine vision on
- Constrained non-negative matrix factorization for calcium imaging data analysis on
- Series resistance in patch clamp experiments on
- Checking PMT performance over time on
- GCaMP6 reporter mice on
- GCaMP6 reporter mice on
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