Cosyne 2008 Workshops
March 3-4, 2008
Spiking Networks and Reinforcement Learning (2 day workshop)
This workshop will bring together eminent experimental biologists and theoretical scientists to discuss learning in spiking networks.
There have been abundant experimental and theoretical results on the dynamics of spiking neurons and networks, emphasizing the importance of precise firing patterns. Likewise, reinforcement learning (RL) has a long history as a research topic in machine learning. However, there have only been a few attempts to connect this theory to neuroscience and express RL in a framework of spiking neurons.
The goal of this workshop is to enable the participants to catch up on the most recent experimental data, to introduce new theories, and to see if we can bring the theory and experimental data more closely into agreement with each other.
|March 3, 08:00||Eugene Izhikevich||Solving the Distal Reward Problem through the linkage of Dopamine Signaling and STDP|
|March 3, 08:45||Razvan Florian||Relating reinforcement learning and STDP|
|March 3, 09:30||Florentin Woergoetter||Neural control and three-factor differential hebbian earning in behaving systems|
|March 3, 10:15||Mayank Mehta||Resonance Learning|
|March 3, 17:15||Gloster Aaron||Searching for organization in the activity of cortical networks|
|March 3, 18:00||Peter Latham||How noisy is the brain? A bottom up approach|
|March 3, 18:45||Ken Harris||Axonal backpropagation in real neuronal networks|
|March 4, 08:00||Harel Shouval||Learning Reward Timing using Reinforced Expression of Synaptic Plasticity|
|March 4, 08:45||Walter Senn||Reinforcement learning in populations of spiking neurons|
|March 4, 09:30||Wulfram Gerstner||Spike-based reinforcement learning of navigation|
|March 4, 10:15||Michael Hasselmo||Cortical mechanisms of memory-guided behavior: Oscillations, grid cells, arc length and RL|
|March 4, 17:15||Maxim Bazhenov||Control of sparseness of odor representations in the insect olfactory system|
|March 4, 18:00||Aristodemos Cleanthous||Can Networks of Leaky Integrate-and-Fire Neurons with Spike-based Reinforcement Learning Play Games?|
|March 4, 18:45||Robert Legenstein||Theoretical analysis of learning with reward-modulated spike-timing-dependent plasticity|