ELSC Seminar Series

Understanding the input-output function of principle cortical neurons and its contribution to network dynamics constitutes a major landmark in deciphering the representation and coding of information in the cortex. Pyramidal neurons are complex computational devices, transforming the activity of thousands of synaptic inputs to an output pattern. These computations are mostly performed in an elaborated dendritic tree, which is the recipient of these thousands of synaptic contacts and is responsible for transforming input information to a neural code. Yet, what computations are performed by dendrites in vivo during a relevant behavior is unknown.

In this talk, I will present our recent findings regarding the dendritic mechanisms used by layer 5 pyramidal tract neurons to represent motor information in vivo during different motor tasks. Using two photon calcium imaging in head fixed mice performing different motor tasks, and an experimental and analysis pipeline we developed we could correlate with an unprecedented resolution between the structure of the dendritic tree and its function. I will describe that PT neurons are not a homogenouse population of neurons with regard to their dendritic structure and the way they process and represent motor information. I will also describe that dendrites of pyramidal tract neurons show pronounced independent activity, ultimately storing different motor memories in different tree compartments and generating papralell signals to drive various aspects of movement.