Posts in Category: software
Ethoscopy and Ethoscope-lab
- Ethoscopy is Python software for analysis of ethoscope data – and more! – created by Laurence Blackhurst
- Ethoscope-lab is a pre-baked Docker container featuring an installation of the multi user Jupyter Hub with Python and R kernels, ready to be used with Ethoscopy and Rethomics.
Why using ethoscope-lab?
Let me simply explain how we use it in our lab. We arranged a powerful workstation that acts as lab server and run a dockerized ethoscope-lab on it. The workstation has a local copy of all our ethoscope data (about 8 Terabyte as I type) and ethoscope-lab has local access on those, offering the quickest loading time. Users can then use their computer, or tablet to connect to the workstation and perform data analysis directly from the browser. The setup frees them from working at their desk and allows access to their data from anywhere in the world, guaranteeing at the same time the fastest computational performance even when they work on their laptops. Moreover, the system uses Jupyter notebook as default, meaning each analysis can be nicely annotated and exported to be shared with the world post-publication, along the original raw data.
To give a practical example: this series of repositories on zenodo contains the entire dataset of our latest paper (316Gb) and it’s paired to all the notebooks we used to generate each figure. Readers can download the dataset freely, install ethoscope-lab as docker container on any computer (irrespective of the operating system they adopt) and reproduce all our analyses!
Video tracking and analysis of sleep in Drosophila melanogaster
Nat Protoc. 2012 Apr 26;7(5):995-1007.
Video tracking and analysis of sleep in Drosophila melanogaster.
Giorgio F. Gilestro
In the past decade, Drosophila has emerged as an ideal model organism for studying the genetic components of sleep as well as its regulation and functions. In fruit flies, sleep can be conveniently estimated by measuring the locomotor activity of the flies using techniques and instruments adapted from the field of circadian behavior. However, proper analysis of sleep requires degrees of spatial and temporal resolution higher than is needed by circadian scientists, as well as different algorithms and software for data analysis. Here I describe how to perform sleep experiments in flies using techniques and software (pySolo and pySolo-Video) previously developed in my laboratory. I focus on computer-assisted video tracking to monitor fly activity. I explain how to plan a sleep analysis experiment that covers the basic aspects of sleep, how to prepare the necessary equipment and how to analyze the data. By using this protocol, a typical sleep analysis experiment can be completed in 5-7 d.
pyREM: a crowd trained machine learning approach to automatic analysis of EEG data
pyREM: a crowd trained machine learning approach to automatic analysis of EEG data
Quentin Geissmann, and Giorgio F Gilestro
EEG data are at the basis of a plethora of neuroscientific questions: from sleep to consciousness and attention, many aspects of neuroscience heavily rely on electrophysiological correlates of brain activity. Yet, EEG analysis heavily relies on subjective scoring and interpretation to the point that many neuroscientists consider it an art, more than a systematic tool.
Can we teach this art to a computer?
Attempts at creating an objective way of scoring EEG data have been less than perfect so far, mainly because humans are reluctant about trusting the judgement of a machine, programmed according to hard-coded values and thresholds.
pyREM aims at solving this issue, using a machine learning approach to automatically analyse EEG data. pyREM learns how to classify EEG directly from humans, mimicking all the human’s principles and criteria without any apriori knowledge of what an EEG means. The overall goal of the project is to teach pyREM how 1, 10, 100 or 1000 laboratories score EEG so that the software will be able to automatically grasp and isolate the key fundamental criteria and become, in this way, the universal scorer.
If you are a laboratory interested in being part of this, please get in touch.
If you want to know more, you can
- read pyrem_poster
- read an early draft of the manuscript
- read the pyREM documentation
- get in touch!
Ethoscopes: An Open Platform For High-Throughput Ethomics
PLOS Biology, 19 Oct 2017; 15(10): e2003026
Ethoscopes: An Open Platform For High-Throughput Ethomics
Quentin Geissmann, Luis Garcia Rodriguez, Esteban J. Beckwith, Alice S. French, Arian R Jamasb, and Giorgio F Gilestro
We present ethoscopes, machines for high-throughput analysis of behaviour in Drosophila and other animals. Ethoscopes provide a software and hardware solution that is reproducible and easily scalable. They perform, in real-time, tracking and profiling of behaviour using a supervised machine learning algorithm; can deliver behaviourally-triggered stimuli to flies in a feedback-loop mode; are highly customisable and open source. Ethoscopes can be built easily using 3D printing technology and rely on Raspberry Pi microcomputers and Arduino boards to provide affordable and flexible hardware. All software and construction specifications are available at http://lab.gilest.ro/ethoscope.
Supplementary material.
Supplementary material 1 – webGL model of the ethoscope.
Supplementary material 2 – instruction booklet for the LEGOscope.
Supplementary material 3 – instruction booklet for the PAPERscope.
Supplementary Video 1 – Introduction to the ethoscope platform.
Supplementary Video 2 – The optogenetics component of the optomotor in action.
Featured in:
- 3-D–Printed Ethoscopes Lower Barriers to Large-Scale Fly Behavior Studies – The Scientist
- 3D printed device studies the life of flies for a better understanding of AI – 3Dprintingindustry.com
- Ethoscope – MagPi (the official Raspberry PI magazine)
- Apparently Fruitflies like a Raspberry PI – Hackaday.com
- DIY goes in vivo – LabAnimal