2014
DOI: 10.1101/006791
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Bonsai: An event-based framework for processing and controlling data streams

Abstract: The design of modern scientific experiments requires the control and monitoring of many different data streams. However, the serial execution of programming instructions in a computer makes it a challenge to develop software that can deal with the asynchronous, parallel nature of scientific data. Here we present Bonsai, a modular, high-performance, open-source visual programming framework for the acquisition and online processing of data streams. We describe Bonsai's core principles and architecture and demons… Show more

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Cited by 38 publications
(47 citation statements)
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References 10 publications
(15 reference statements)
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“…Video data with timestamps for the two eyes and overhead camera were acquired at 30 frames per second using Bonsai [26] . We used DeepLabCut [27] for markerless estimation of mouse and cricket position from overhead videos.…”
Section: Mouse and Cricket Trackingmentioning
confidence: 99%
“…Video data with timestamps for the two eyes and overhead camera were acquired at 30 frames per second using Bonsai [26] . We used DeepLabCut [27] for markerless estimation of mouse and cricket position from overhead videos.…”
Section: Mouse and Cricket Trackingmentioning
confidence: 99%
“…All trials were recorded with a Raspberry Pi 3B+ equipped with a V1 camera module (https://www.raspberrypi.org/documentation/hardware/camera/) and using Raspivid version 1.3.12 as 1296x972 pixel, 30 frame/second MP4 video files. Automated analysis was carried out with custom scripts written in Bonsai version 2.4-preview (Lopes et al, 2015). A researcher blinded to the treatment assessed and scored the exploration time manually after automated analysis.…”
Section: Rnamentioning
confidence: 99%
“…Video recording was performed using a Sony camera (HDR HC7E) connected to a computer running Virtual Dub software to acquire images. Off-line analysis of videos was performed using Bonsai [11] and the behaviour of the female was analysed using MATLAB. The latency of first entry, the number of entries and re-entries (when the female returns to the same male's compartment) into the male's compartment, as well as the time spent in each male box were scored.…”
Section: Behavioural Analysismentioning
confidence: 99%