Explore the words cloud of the SMARTLABCAM project. It provides you a very rough idea of what is the project "SMARTLABCAM" about.
The following table provides information about the project.
Coordinator |
SCUOLA INTERNAZIONALE SUPERIORE DI STUDI AVANZATI DI TRIESTE
Organization address contact info |
Coordinator Country | Italy [IT] |
Total cost | 0 € |
EC max contribution | 150˙000 € (0%) |
Programme |
1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC)) |
Code Call | ERC-2019-PoC |
Funding Scheme | ERC-POC-LS |
Starting year | 2020 |
Duration (year-month-day) | from 2020-03-01 to 2021-08-31 |
Take a look of project's partnership.
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1 | SCUOLA INTERNAZIONALE SUPERIORE DI STUDI AVANZATI DI TRIESTE | IT (TRIESTE) | coordinator | 150˙000.00 |
Rodents have become very popular models of cognitive functions, such as perception, memory and decision-making. Understanding the neuronal substrates of these processes requires performing neurophysiological recordings in awake animals, engaged in complex behavioral tasks. This, in turn, calls for tracking in real-time the motor behavior of the animal, to relate it to the underlying brain activity. Custom, as well as commercial, solutions exist that allows tracking basic behaviors in rodents – e.g., the 2D position and orientation of an animal over the arena where he navigates. However, while carrying out the research of the ERC project LEARN2SEE, we realized that methods for 3D reconstruction of some key behavioral features (e.g., pose of the head and gaze direction) are not commercially available, and the custom solutions found in the literature lack generality and are hard to implement and replicate. This prompted us to develop innovative, minimally invasive and user-friendly solutions to head/eye tracking in rodents. Yet, we soon faced another challenge – in order to perform high-throughput experiments, by testing in parallel many subjects (one of the advantages of rodent models over larger laboratory animals), our head/eye trackers would need to be re-engineered to make them easily replicable for series production. Critically, this would also allow transforming them into commercial devices for the ever-growing market of neurophysiology laboratories that, especially in the field of vision science, are employing rodents as model organisms. Here, we present our plan to achieve this goal, by migrating the tracking algorithms we developed for the LEARN2SEE project to smart cameras, engineered for real-time, on-board processing of head/eye video streams. These cameras will become a new product line of CyNexo, a recently established SISSA startup that operates in the market of laboratory equipment and is looking to expand its products’ package to videography tools.
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The information about "SMARTLABCAM" are provided by the European Opendata Portal: CORDIS opendata.