Final Program

June 25, Quantitative Neuron Modeling: Detailed models

9:00 - 10:20 Multicompartment modeling

• Lyle Graham (CNRS Paris): Detailed models, channels, and spike timing
• Mickey London (UCL London): Detailed models and synaptic transmission
• 10:20 Announcements

10:50 - 12:50 Nonlinear dendrites and nonlinear spike generation

• Panayiota Poirazi (IMBB, Greece): Dendrites as neurons, neurons as neural networks (EMBO Young Investigator lecture)
• Walter Senn (University of Berne): Dendritic-somatic interaction in a 3-compartment model
• Enno de Lange and Martin Hasler (EPFL): Predicting spikes with the Hindmarsh-Rose model

13:00 - 14:00 Lunch Breack

14:00 - 16:00 Methods for fitting Multicompartment models

• Arnd Roth (UCL London): Multicompartmental models of cerebellar Purkinje cells
• Pablo Achard (University of Antwerp): Neurofitter: a parameter tuning package for electrophysiological neuron models
• Quentin Huys (UCL London): Parameter optimization as a convex problem

16:30 - 18:30 Detailed Large-Scale modeling projects

• Idan Segev (Hebrew University): Overview and Challenges of large scale modeling projects (Heidelberg Project and Blue-Brain Project)
• Shaul Druckmann, Idan Segev and Felix Schuermann (EPFL): Neuron Fitting in the Blue Brain Project
• Arnd Roth: Short report on results from multicompartment competition (Challenges C and D)
• Discussion - Do we know enough to fit detailed neuron models?

June 26, Quantitative Neuron Modeling: Simple models

9:00 - 10:20 Nonlinear Integrate-and-fire models

• Nicolas Brunel (Paris 5): Exponential Integrate-and-Fire model
• Magnus Richardson (Warwick University) and Laurent Badel (EPFL): The pre and post-spike dynamic I-V relations of layer-5 pyramidal cells

10:50 - 12:50 Simplified neuron models

• Wulfram Gerstner and Renaud Jolivet (EPFL) Predicting spikes with a Spike Response Model with dynamic threshold
• Alain Destexhe and Martin Pospischil (CNRS Gif-sur-Yvette): Fitting diverse neuron types with minimal number of channels
• Petr Lansky (CAS): Predicting spikes with a Integrate-and-Fire Model
• Poster Spotlight: Ryota Kobayashi (Winner of Challenge A)

13:00 - 14:00 Lunch Breack

14:10 - 15:30 Systems-level models of neural response to visual input I

• Tim Gollisch and Markus Meister (Harvard University): Predicting first-spike latencies of retinal ganglion cells
• Jonathan Pillow (UC London): Spike train prediction in multiple neurons: a coupled model of population spike responses in retina

16:00 - 17:20 Systems-level models of neural response to visual input II

• Fritz Sommer (Redwood Institute, UC Berkeley) Modeling spike trains and the transmission of information in LGN
• Jack Gallant (Berkeley): Modeling Neural Systems by Nonlinear System Identification

17:20 - 18:30 Quality measures and experimental protocols for quantitative neuron modeling

• 17:20-17:30 Competition on Predicting single-neuron behavior (Challenges A and B): Experiences and results
  
• 17:30-17:40 Jack Gallant (Berkeley): Experiences and results from the Berkeley `Neural Prediction Challenge'
• 17:40-18:30 Discussion: What is an optimal protocol for quantitative model fitting?

20h15 Conference Diner