By Doug Ramsey, 858-822-5825, email@example.com
San Diego, CA, October 4, 2006 -- Calit2 at UCSD played host over the weekend to the public portion of a three-day workshop on multi-level brain modeling. The weekend was organized by the Sloan/Swartz Center for Theoretical Neurobiology at the Salk Institute and UCSD's Swartz Center for Computational Neuroscience, and the meetings after Friday's talks at Calit2 took place at Rancho Santa Fe Inn.
Multi-level brain modeling explores the relationships between measurements that span multiple levels of the brain -- from the molecular properties of synapses, the dynamic properties of single neurons, the collective properties reflected in local field potentials, and the bulk properties of brain activity as measured with EEG, MEG and fMRI. According to Salk's Terry Sejnowski, an academic participant in Calit2 and UCSD's Institute of Neural Computation, who chaired the Atkinson Hall session, each of these levels has a substantial literature but too little effort has been put into understanding how they are related.
Sejnowski's introduction and four talks at Calit2 were aimed at a more general audience, and set up the discussion for ensuing technical talks. They are now archived and available for on-demand viewing. To view the streaming videos, click on the image or video link below [Real player and broadband connection required].
Multi-Level Brain Modeling
Terry Sejnowski (Salk Institute and UCSD) (Chair)
Length: 9:56 [video]
Multiple Time Scale of Neuronal Information Processing
Larry Abbott (Columbia University)
Length: 35:54 [video]
Neurogrid: Emulating a million neurons in the cortex
Kwabena Boahen (Stanford University)
Length: 35:38 [video]
Unpacking the brain into multiscale space: Methods, evidence and models
Michael Breakspear (University of Sydney)
Length: 31:33 [video]
Ultra high gamma in the human electrocorticogram
Robert Knight (UC Berkeley)
Length: 39:10 [video]
For details on the closed sessions Sept. 30 and Oct. 1, on topics ranging from "how the cortex behaves itself" to "statistical neural field theory", click here to view the conference agenda.