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Creating and controlling visual environments using BonVision

Real-time rendering of closed-loop visual environments is important for next-generation understanding of brain function and behaviour, but is often prohibitively difficult for non-experts to implement and is limited to few laboratories worldwide. We developed BonVision as an easy-to-use open-source...

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Detalles Bibliográficos
Autores principales: Lopes, Gonçalo, Farrell, Karolina, Horrocks, Edward AB, Lee, Chi-Yu, Morimoto, Mai M, Muzzu, Tomaso, Papanikolaou, Amalia, Rodrigues, Fabio R, Wheatcroft, Thomas, Zucca, Stefano, Solomon, Samuel G, Saleem, Aman B
Formato: Online Artículo Texto
Lenguaje:English
Publicado: eLife Sciences Publications, Ltd 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8104957/
https://www.ncbi.nlm.nih.gov/pubmed/33880991
http://dx.doi.org/10.7554/eLife.65541
Descripción
Sumario:Real-time rendering of closed-loop visual environments is important for next-generation understanding of brain function and behaviour, but is often prohibitively difficult for non-experts to implement and is limited to few laboratories worldwide. We developed BonVision as an easy-to-use open-source software for the display of virtual or augmented reality, as well as standard visual stimuli. BonVision has been tested on humans and mice, and is capable of supporting new experimental designs in other animal models of vision. As the architecture is based on the open-source Bonsai graphical programming language, BonVision benefits from native integration with experimental hardware. BonVision therefore enables easy implementation of closed-loop experiments, including real-time interaction with deep neural networks, and communication with behavioural and physiological measurement and manipulation devices.