Atelier en ligne de neuroscience computationnelles sur le thème « Towards multipurpose neural network models II: « Model testing and model fitting ».
Organisé par
Anton Arkhipov (Allen Institute, Seattle) et Gaute Einevoll (NMBU/University of Oslo)
avec le soutien de l’EITN.

Du mercredi 29 septembre au vendredi 1er octobre 2021

Atelier en ligne, gratuit sur inscription obligatoire.

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?

The first workshop on the topic was arranged in August 2020 (see https://alleninstitute.org/what-we-do/brain-science/events-training/ for program and videos of talks).

In this second (also virtual) workshop in the series we will focus on two key aspects of the overall endeavor: model testing and model fitting. Multipurpose network models mimicking real neural circuits will contain numerous model parameters that must be optimized. Efficient methods for fitting of model parameters to experimental data are thus needed. Further, the candidate models must be systematically tested against a variety of experimental data, requiring development of commonly accepted benchmarks and test suites. In the workshop these methodological challenges will be addressed from a variety of angles.

Intervenants :

Anton Arkhipov (Allen Institute)
Marcus Covert (Stanford)
Sharon Crook (Arizona State U.)
James DiCarlo (MIT)
Gaute Einevoll (NMBU/U. Oslo)
Julijana Gjorgjeva (Max Planck Institute and TUM)
Peder Jedlicka (U. Giessen)
Szabolcs Kali (Institute of Experimental Medicine, Budapest, Hungary)
Arvind Kumar (KTH Stockholm)
Jacob Macke (U. Tübingen)
Stefan Mihalas (Allen Institute)
Aaron Milstein (Rutgers U.)
Kanaka Rajan (Mount Sinai)
Atle Rimehaug (U. Oslo)
Frances Skinner (Krembil Brain Institute, University Health Network, and U. Toronto)
Carsen Stringer (Janelia)
Kristin Tøndel (NMBU).