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)

 

Online workshop. Free to attend, but registration is mandatory.

 

REGISTER HERE.

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-institute-modeling-workshop-2020/ 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.