Neural networks typically make use of simplified, stereotypical single neuron units, while in reality neurons show fascinating and diverse properties that give them a range of computational and representational powers. The emerging ability that molecular techniques provide to identify, record from and manipulate the activity of different cell types highlights the gap between the network and biophysical levels of understanding of neural computation. We will discuss some of the computational properties of single neurons and two studies in which we consider the interaction between single neuron and network level function.
Lunch 11:45, seminar 12-1:00