Publication | Open Access
Bonsai: An event-based framework for processing and controlling data streams
121
Citations
7
References
2014
Year
Unknown Venue
Event-driven ArchitectureEngineeringPresent BonsaiData Streaming ArchitectureSocial SciencesData ScienceComplex Event ProcessingData IntegrationNetwork PhysiologyMotor NeuroscienceData ManagementData ModelingNeuroinformaticsStreaming EngineKnowledge DiscoverySensorimotor IntegrationComputer ScienceData Stream ManagementNeural InterfaceParallel VisualizationBrain-computer InterfaceSystems NeuroscienceStimulation ParametersNeurological SimulationNeuroengineeringComputational NeuroscienceHuman NeuroscienceNeuroscienceParallel ProgrammingBrain ElectrophysiologyData StreamsBig Data
Abstract The design of modern scientific experiments requires the control and monitoring of many parallel 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 demonstrate how it allows for flexible and rapid prototyping of integrated experimental designs in neuroscience. We specifically highlight different possible applications which require the combination of many different hardware and software components, i0ncluding behaviour video tracking, electrophysiology and closed-loop control of stimulation parameters.
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