Organized by Anton Arkhipov (Allen Institute, Seattle), Gaute Einevoll (NMBU/University of Oslo)
Partial abstract: Starting with the work of Hodgkin, Huxley, Cole, Rall, Katz, Eccles and others in the 1950s and 1960s, we have a reasonably good understanding of the biophysical principles by which single neurons operate. For neural circuits the understanding is much more limited. Most network studies have considered stylized models with a few populations of identical neurons and focused on explaining a particular experimental phenomenon. However, real neural networks consist of a variety of neuron types and have structured synaptic connections. Furthermore, real networks typically perform multiple functions and can be characterized by a variety of readouts from various measurement modalities, including spiking activity, local field potentials, and others. How can we move towards multipurpose models that incorporate the true biological complexity of neural circuits and faithfully reproduce multiple observables in many different situations?
More details, full abstract and speakers: https://www.eitn.org/index.php/calendar-event/eventdetail/750/-/workshop-on-towards-multipurpose-neural-network-models-ii-model-testing-and-model-fitting
Registration is free but mandatory.
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More details are available here : https://drive.google.com/file/d/1ZgurjL4HOMBZmLHpjsENSWE4ngTB_cZe/