A new approach has been developed that allows researchers to broadly survey learning-related changes in synapse properties. The researchers used machine-learning algorithms to analyze thousands of images from the cerebral cortex. This allowed them to identify synapses from an entire cortical region, revealing unanticipated information about how synaptic properties change during development and learning.