Machine learning helps scientists see how the brain adapts to different environments

In the brain, the authors explain, different life experiences, such as exposure to new environments and learning skills, are thought to induce changes at synapses, strengthening or weakening these connections to allow learning and memory. To do so, Bergles, Sulam, Charles, Huganir, and their colleagues turned to machine learning, a computational framework that allows flexible development of automatic data processing tools. Machine learning has been successfully applied to many domains across biomedical imaging, and in this case, the scientists leveraged the approach to enhance the quality of images composed of thousands of synapses. To convert these into higher quality images, the scientists trained a machine learning algorithm with images taken of brain slices (ex vivo) derived from the same type of genetically altered mice. Because these images weren't from living animals, it was possible to produce much higher quality images using a different microscopy technique, as well as low quality images—similar to those taken in live animals—of the same views.