Leonardo Lupori and Raffaele Mazziotti are active in the field of neuroscience at Tommaso Pizzorusso’s lab at Neuroscience Institute CNR of Pisa respectively as molecular biologist and experimental psychologist. They created an Arduino-based and MATLAB-controlled tool called IOSIC (Intrinsic Optical Signal Imaging Chamber), powered by an Arduino Micro and focused on intrinsic optical signal (IOS) imaging apparatus to run experiments on the plasticity of the brain.
Intrinsic optical signal (IOS) imaging is a functional imaging technique that has revolutionized our understanding of cortical functional organization and plasticity since it was first implemented, around 30 years ago. IOS is produced by the brain when processing information and is similar to the information recorded with the plethysmograph (the instrument to measure heart rate from a finger) and it is useful to investigate how the brain works. The researchers are especially interested to investigate how the brain is able to adapt to the environment to store information but also acquire new skills and these studies are really useful to understand what happens to the brain when is in good health or during a disease.
Even if their lab has a long-standing expertise in electrophysiological studies, they decided to developed a fully functional apparatus for IOS with tools already available and low-cost:
To set up the entire system we used a mix of components commercially available and custom-made. The most expensive tool we used is an imaging camera from Hamamatsu (it is necessary because we need to analyze data quantitatively), but you can also use a cheaper camera (at least with a CCD chip 12-bit depth is recommended). The rest is stuff collected from old tools of the lab. For example, the microscope, that in our case is an old Olympus confocal microscope, but any transmitted light microscope or macroscope should be ok, was already in the lab and is currently used also for other purposes. For light illumination, we used a custom made crown-shaped LED holder that can be attached to the objective and provide a really stable light source. Afterwards, we wrote a MATLAB script to control the camera and then we built an imaging chamber to analyze the animal preparation. The imaging chamber is essential to keep the animal stable during the imaging session (about 7 minutes) and also to maintain its physiological temperature during the time course of anesthesia. An additional feature added to the chamber is the possibility to change the animal’s visual field automatically allowing us to measure rapidly, efficiently and repeatedly a very important parameter of plasticity called ocular dominance. The chamber is composed by a 3D printed structure on which an Arduino MICRO, two servo motors, a heating pad, an IR thermometer and a magnetic ring have been installed. Currently we are using this system with success and we hope to discover something really relevant.