Dear colleagues, The European Institute for Theroretical Neurosience (EITN) is happy to invite you all to its next online workshop taking place online this week from Wednesday to Friday. It is open to everyone upon registration. You will find all the information at the end of this email. Kind regards, Zélie, for the EITN team *_____* **** * * *Workshop on "Towards multipurpose neural network models II: Model testing and model fitting"* /Organized by Anton Arkhipov (Allen Institute, Seattle), Gaute Einevoll (NMBU/University of Oslo)/ *_Dates:_*Wednesday 29 September – Friday October 1st *_Time:_*5PM – 9.15PM (CET) <https://www.eitn.org/images/events/TMNNM-II-MTaMF_Flyer.pdf> Online workshop. Free to attend, but registration is mandatory. *REGISTER HERE.* <https://cnrs.zoom.us/webinar/register/WN_saMXfg31Roe4tqHbWtTdFg> *https://cnrs.zoom.us/webinar/register/WN_saMXfg31Roe4tqHbWtTdFg* *_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/allen-in... <https://nam12.safelinks.protection.outlook.com/?url=https%3A%2F%2Falleninstitute.org%2Fwhat-we-do%2Fbrain-science%2Fevents-training%2Fallen-institute-modeling-workshop-2020%2F&data=04%7C01%7C%7C85a32f2e858144a5158d08d9067df76b%7C32669cd6737f4b398bddd6951120d3fc%7C0%7C0%7C637547960368151649%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C1000&sdata=alZIBcfaXeYgfhAiFljpP%2BAE6gkzldMkzCf6mLqRbco%3D&reserved=0> 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. *_Confirmed speakers:_*__ 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) * * *Wednesday, September 29, 2021* *Time (PDT)* *Time (CEST)* *Speaker* *Affiliation* *Title* 8:00 am – 8:15 am 5:00 pm – 5:15 pm Gaute Einevoll NMBU/U. Oslo Introduction 8:15 am – 8:55 am 5:15 pm – 5:55 pm Jacob Macke U. Tübingen *Keynote* Simulation-based inference: Bridging the gap between mechanistic models and machine learning. 8:55 am – 9:25 am 5:55 pm – 6:25 pm Aaron Milstein Rutgers U. Nested parallel simulation and multi-objective optimization of neuronal cell and circuit models 9:25 am – 9:40 am 6:25 pm – 6:40 pm Break 9:40 am – 10:10 am 6:40 pm – 7:10 pm Atle Rimehaug U. Oslo Enhancing model constraints by utilizing current source densities 10:10 am – 10:40 am 7:10 pm – 7:40 pm Kristin Tøndel NMBU Facilitating optimization using metamodelling 10:40 am – 10:50 am 7:40 pm – 7:50 pm Break 10:50 am – 11:20 am 7:50 pm – 8:20 pm Frances Skinner Krembil Brain Institute, University Health Network, and University of Toronto Clarity in model development and goals leads to model linkages and biological insights 11:20 am – 12:10 pm 8:20 pm – 9:10 pm _Panel debate – All participants of the day._ *Thursday, September 30, 2021* *Time (PDT)* *Time (CEST)* *Speaker* *Affiliation* *Title* 8:00 am – 8:15 am 5:00 pm – 5:15 pm Anton Arkhipov Allen Institute Introduction 8:15 am – 8:55 am 5:15 pm – 5:55 pm James DiCarlo MIT *Keynote* Reverse Engineering Visual Intelligence 8:55 am – 9:25 am 5:55 pm – 6:25 pm Sharon Crook Arizona State U. Testing the Data-driven Model 9:25 am – 9:40 am 6:25 pm – 6:40 pm Break 9:40 am – 10:10 am 6:40 pm – 7:10 pm Szabolcs Kali Institute of Experimental Medicine, Budapest, Hungary Systematic construction and evaluation of models of rodent hippocampal neurons 10:10 am – 10:40 am 7:10 pm – 7:40 pm Peter Jedlicka U. Giessen Building consistent and robust models of hippocampal granule cells and CA1 pyramidal cells 10:40 am – 10:50 am 7:40 pm – 7:50 pm Break 10:50 am – 11:20 am 7:50 pm – 8:20 pm Stefan Mihalas Allen Institute Computing with a mess: How nonstationary, heterogeneous and noisy components help the brain’s computational power 11:20 am – 12:10 pm 8:20 pm – 9:10 pm _Panel debate – All participants of the day._ *Friday, October 1, 2021* *Time (PDT)* *Time (CEST)* *Speaker* *Affiliation* *Title* 8:00 am – 8:40 am 5:00 pm – 5:40 pm Markus Covert Stanford *Special lecture* Simultaneous cross-evaluation of heterogeneous E. coli datasets via mechanistic simulation 8:40 am – 9:20 am 5:40 pm – 6:20 pm Kanaka Rajan Mount Sinai *Keynote* Data-constrained neural network models of adaptive learning in the brain 9:20 am – 9:40 am 6:20 pm – 6:40 pm Break 9:40 am – 10:10 am 6:40 pm – 7:10 pm Julijana Gjorgjeva Max Planck Institute and TUM Biologically plausible learning in developing networks 10:10 am – 10:40 am 7:10 pm – 7:40 pm Carsen Stringer Janelia Rastermap: Extracting structure from high-dimensional neural data 10:40 am – 10:50 am 7:40 pm – 7:50 pm Break 10:50 am – 11:20 am 7:50 pm – 8:20 pm Arvind Kumar KTH Stockholm Structure and activity dynamics relationship in biological neuronal networks: Measurements and models 11:20 am – 12:10 pm 8:20 pm – 9:10 pm _Panel debate – All participants of the day._