Subject
The brain can be thought of as a computer, with its very peculiar hardware and software. While decades of research have been dedicated to the study of the hardware (neurons, synapses, channels, etc.), it is only recently that new technologies have allowed us to simultaneously record tens, hundreds or even thousands of neurons, providing a first glimpse into how individual processing units coordinate their activity to produce a coherent outcome. This new possibility has its challenges, mainly related to the processing and interpretation of big neural data. In the lab, we use several techniques for neural recording and manipulation in behaving rodents, complementing them with analytical and computational modelling. Our main focus is the study of two brain algorithms: the one behind the formation of new memories and the one in charge of the representation of the world and the self that allows for spatial orientation. Both are functions of the hippocampus and surrounding structures in the mammalian brain. Some of our current projects focus on the hippocampus. How do adult-born neurons participate in the formation of new memories? How does naturally occurring Alzhemier’s Disease affect spatial representations? Other projects put the focus on a neighboring area, the entorhinal cortex. How do representations of different dimensionality coexist in grid cells, mostly thought of as a universal metric system? How does the GPS cope with acceleration?
Our work is mainly aimed to the better understanding of basic brain functions, but down the road it will contribute to the global fight against neurodegenerative diseases on one hand and to the development of domestic scale self-navigating artifacts on the other.

Approach
We use in vivo electrophysiology, optogenetics, calcium imaging and computational models to understand the algorithms that guide information processing in the GPS of the mammalian brain, in both healthy rodents and models of neurodegenerative disease.

Advances
The members of the laboratory have participated in the discovery of some of the main pieces of brain GPS: speed cells (neurons that encode the speed of movement) and border cells (neurons that are activated in the perimeter of an environment). We also proposed the first computational model suggesting how the brain's GPS can self-organize through experience and learning, a line of research we continue to develop. Finally, the laboratory activity has an applied side, where we use brain-inspired information processing techniques (machine learning) to address the analysis of large databases in practical problems from various disciplines or activities.