Conferences & Symposia

About:

Many network models for modeling cortical function are built with single compartment units using a variety of more or less simple integrate and fire dynamics.  On the other hand, many biologically oriented research groups place great emphasis on the complex and detailed properties of active processing in pyramidal neuron dendrites.  The question to be addressed in this workshop is whether by omitting such properties from network models we lose essential computational properties of biological cortical networks.  Potentially which ones?  Finally, could such properties be formalized in simpler ways than using full biophysical detail and substantially add to the function of more abstract network modeling?

When: 

Tuesday, December 7, 2021 10 am to 1 pm EST

Where: 

We expect to live stream the recording through the Emory TMLS YouTube Channel https://www.youtube.com/c/EmoryTMLS . Please register at the link below to be updated of any changes. 

Register: 

Register here

Selected Speakers:

Arnd Roth, University College London

Brent Doiron, University of Chicago 

Bartlett Mel, University of Southern California 

Yiota Poirazi, IMBB-FORTH Crete 

Andreas Stöckel, University of Waterloo 

Xiao-Jing Wang, New York University  

Tentative Schedule: 

All times are in Eastern Standard Time (EST).

10:00 am Dieter Jaeger, Emory University, Introduction

10:10 am   Arnd Roth, University College London “Active dendrites enable strong but sparse inputs to determine orientation selectivity”

10:35 am   Brent Doiron, University of Chicago “Cell specific inhibitory plasticity in assembly formation”

 11:00 am    Bartlett Mel, University of Southern California "How to optimize a dendrite for binary subunit pooling”

11:25 am    Yiota Poirazi, IMBB-FORTH Crete  “Dendritic solutions to logical operations in models of human neurons”

11:50 am    Andreas Stöckel, University of Waterloo.  “Passive Dendrites as a Computational Resource in the Neural Engineering Framework”

12:15 pm    Xiao-Jing Wang, New York University “Dendritic gating in the whole neocortex”

12:40 pm   General Discussion

1:00 pm  End of Workshop

Organizers:

Dr. Dieter Jaegar (Emory University)

Sponsors:

About:

Identification of stereotyped features of movements and their changes in health and disease have been a common step towards understanding and modeling movements and mechanisms of motor control that give rise to them. However, we can often recognize individuals by the way they move, and differences in motor control and movement are influenced by prior experience, training, personality, and disease mechanisms.

In other words, stereotypy is not that stereotyped! What is to be gained by looking past regularities in movement across individuals and understanding aspects of movement and motor control unique to individuals? To what extent are data considered stereotypical through one lens, but variable through another can help us in understanding movements and their neural generation? What are the techniques that allow us to identify and characterize stereotypy versus individuality to help us understand normal and impaired movement?

Our speakers will explore these and other related questions using methods from biomechanics, neural control of movement, and machine learning, and by addressing basic science, technology development, and clinical questions. Each speaker will deliver a 10 minute bold, provocative talk to sketch the current boundaries of the field and chart its future developments. Ample time will be set aside for moderated questions and discussion.

When: 

Thursday, March 18, 2021 10 am to 1 pm EST

Where: 

We expect to live stream the recording through the Emory TMLS YouTube Channel https://www.youtube.com/c/EmoryTMLS . Please register at the link below to be updated of any changes. 

Register: 

https://forms.gle/BHH1KUJLfgDdPi4V9

Selected Speakers:

• Monica Daley, PhD (University of California, Irvine)
• Gordon Berman, PhD (Emory University)
• Gelsy Torres-Oviedo, PhD (University of Pittsburgh)
• Nidhi Seethapathi, PhD (University of Pennsylvania)
• Jose L. Contreras-Vidal, PhD (University of Houston)
• Mackenzie Mathis, PhD (Ecole Polytechnique Fédérale de Lausanne (EPFL), Switzerland)

Organizers:

Dr. Lena Ting (Emory University and Georgia Institute of Technology)
Dr. Trisha Kesar (Emory University) 

Sponsors:

The SARS-CoV-2 pandemic is awash in data, including daily, spatially-resolved COVID case data, virus sequence data, patients `omics data, and mobility data. Journals are now also awash in studies that make use of quantitative modeling approaches to gain insight into the geographic spread of SARS-CoV-2 and its temporal dynamics, as well as studies that predict the impact of control strategies on SARS-CoV-2 circulation. Some, but by no means all, of these studies are informed by the massive amounts of available data. Some, but by no means all, of these studies have been useful — in that their predictions revealed something beyond simple back of the envelope calculations.

To summarize some of these findings, in this symposium, we will address questions such as: What do we want from models of disease spread? What can and should be predicted? Which data are the most useful for predictions? When do we need mechanistic models? What have we learned about how to model disease spread from unmet and/or conflicting predictions? The workshop speakers will explore these questions from different perspectives on what data need to be considered and how models can be evaluated. 

As in other TMLS workshops, each speaker will deliver a 10-minute talk with ample time set aside for moderated questions/discussion. We expect the talks to be provocative and bold, while respecting different perspectives.

When: Thursday, January 21, from 10am to 2pm EST

Where: We expect to live stream the recording through the Emory TMLS YouTube Channel https://www.youtube.com/c/EmoryTMLS . Please register at the link below to be updated of any changes. 

Register: https://tinyurl.com/y9nkdxz5

More Info: will be posted at http://livingtheory.emory.edu/news-events/conferences-symposia.html

Speakers:

• Rachel Baker (Princeton University)
• Caroline Buckee (Harvard University)
• Sarah Cobey (University of Chicago)
• Nigel Goldenfeld and Sergei Maslov (UIUC)
• Ruian Ke (LANL)
• Stephen Kissler (Harvard University)
• Lauren Ancel Meyers (University of Texas)
• Isabel Rodriguez-Barraquer (UCSF)
• Sam Scarpino (Northeastern University)
• Michael Worobey (University of Arizona)
• Joshua Weitz (Georgia Institute of Technology)

Organizers: Katia Koelle, Daniel Weissman, Rustom Antia

Emory TMLS: Ilya Nemenman, Tiera Ward 

Description: We both agreed that typical workshop formats wouldn’t necessarily translate well to the virtual domain and thought to organize around one question:

“Now that we can track (most) everything, what can we do with the data?”

Given the recent dramatic advances in technology, we now have behavioral data sets with orders of magnitude more accuracy, dimensionality, diversity, and size than we had even a few years ago.  That being said, there is still little agreement as to what theoretical frameworks can inform our understanding of these data sets and suggest new experiments we can perform.  We hope that after this workshop we’ll see a variety of new ideas and perhaps gain some inspiration.

Organizers: Gordon Berman (Emory University), Greg Stephens (Vrije Universiteit Amsterdam, Okinawa Institute of Science and Technology)

Speakers: Andre Brown (Imperial College), William Bialek (Princeton University), Ann Kennedy (California Institute of Technology), Ugne Klibaite (Harvard University), Alexander Mathis (Harvard University), Nicholas Ouellette (Stanford University), Samuel Reiter (Okinawa Institute of Science and Technology), Ariana Strandburg-Peshkin (University of Konstanz)

Description: There has been a surge of publications on using machine learning (ML) on experimental data from physical systems: social, biological, statistical, and quantum. However, can these methods discover new physics? It can be that their biggest impact is in better data preprocessing, while inferring new physics is unrealistic without specifically adapting the learning machine to find what we are looking for — that is, without the “intuition” — and hence without having a good a priori guess about what we will find.

Organizers: Ilya Nemenman (Emory University)

 Speakers: Aleksandra Walczak (Centre national de la recherche scientifique/École Normale Supérieure Paris), David Schwab (City University of New York), Sam Greydanus (Google Brain), Max Tegmark (Massachusetts Institute of Technology), Bryan Daniels (Arizona State University), Andrea Liu (University of Pennsylvania), Roger Melko (University of Waterloo), Lucy Colwell (Cambridge University)

Organizers: Samuel Sober (Emory University), Gordon Berman (Emory University)

Speakers: Amy Bastian (Kennedy Krieger Institute), Rui Costa (Columbia University), Amy Orsborn (University of Washington), Chethan Pandarinath (Emory University and Georgia Tech University), Abigail Person (University of Colorado), Andrew Pruszynski (Western University), Flip Sabes (University of California San Francisco and Neuralink), Lena Ting (Emory University /Georgia Tech University)

Discussants:
Gordon Berman (Emory University)
Megan Carey (Champalimaud Centre for the Unknown)       
Ilya Nemenman (Emory University)   
Sam Sober (Emory University) 

Organizers: Jennifer Rieser (Georgia Tech University), Daniel Sussman (Emory University)

Speakers: Michael Brenner (Harvard University), Eleni Katifori (University of Pennsylvania), Cristina Marchetti (University of California, Santa Barbara), Chase Broedersz (Ludwig Maximilian University), Joshua Shaevitz (Princeton University), Michael Murrell (Yale University), Symone Alexander (Georgia Tech University), Orit Peleg (University of Colorado, Boulder)

Session 1: What Is Linked Selection Doing To Populations?

Natural selection affects not only selected alleles, but also indirectly affects all alleles linked to selected sites. An increasing body of evidence suggests that this linked selection is an important driver of allele frequency dynamics throughout the genomes of many species, implying that we need to substantially revise our basic understanding of molecular evolution and the tempo and mode of adaptation. This session brings together early-career researchers working towards a quantitative understanding of linked selection, bringing together data from many different systems as well as models of different forms of linked selection

Session 2: What Determines Microbial Diversity?

Microbes make up the vast majority of the tree of life. While we know very little about most microbial species, large-scale sequencing is giving us glimpses of the diversity that exists both within species and in ecosystems.The challenge now is to find the patterns in this diversity and understand them. This session features provocative talks on attempts to meet that challenge. 

Organizers: Daniel B. Weissman (Emory University)

Speakers: Christelle Fraïsse (Institute of Science and Technology Austria/Centre National de la recherche scientifique), Derek Setter (University of Edinburgh), Kimberley Gilbert (University of Lausanne/University of Bern), Ivana Cvijovic (Stanford University), Erik van Nimwegen (University of Basel), Jacopo Grilli (International Centre for Theoretical Physics), Maitreya Dunham (University of Washington), Nandita Garud (University of California, Los Angeles)

Description: Which features of biological data are predictable? Should theorists interested in quantitative predictions focus on different questions, not typically asked by biologists? Which types of models are best suited to making quantitative predictions in different fields? Why do theories work, when there’s no general reason for them to? Do large, multidimensional datasets make theories (and which theories?) more or less likely to succeed? This will be an unapologetically theoretical physics workshop — we won’t focus on a specific subfield of biology, but will explore these questions across the fields, hoping that the underlying theoretical frameworks will help us find the missing connections. 

Organizers: Ilya Nemenman (Emory University)

 Speakers: Ned Wingreen (Princeton University), Jane Kondev (Brandeis University), Arvind Murugan (University of Chicago), Boris Shraiman (Kavli Institute for Theoretical Physics / University of California, Santa Barbara), Greg Stephens (Vrije University Amsterdam/Okinawa Institute of Science and Technology), Thierry Mora (ENS/CNRS), Leennoy Meshulam (University of Washington), Audrey Sederberg (Emory University), Eve Marder (Brandeis University)

Description: When was the last time you ran into a giant? Chances are never. Almost 100 years ago, JBS Haldane posed an outwardly simple yet complex question—what is the most optimal size (fora biological system)? The living world around us contains a huge diversity of organisms, each with its own characteristic size. Even the size of subcellular organelles is tightly controlled. Inabsence of physical rulers, how do cells and organisms truly “know” how large is large enough? What are the mechanisms in place to enforce size control?

Organizers: Sandeep Choubey, (Max Planck Institute for the Physics of Complex Systems), Shashank Shekhar (Emory University)

 Speakers: Dan Fletcher (University of California, Berkeley), Kinneret Keren (Technion), Karl Niklas (Cornell University), Lishibanya Mohapatra (Rochester Institute of Technology), Marija Zanic (Vanderbilt), Stephanie Weber (McGill University), Wallace Marshall (University of California San Francisco), Ken Andersen (Technical University of Denmark)

Organizers: Chethan Pandarinath (Emory University/Georgia Tech University)

Speakers: Adrienne Fairhall (University of Washington), Mehrdad Jazayeri (Massachusetts Institute of Technology), John Krakauer (John Hopkins), Francesca Mastrogiuseppe (Gatsby / University of College London) Abigail Person (University of Colorado, Boulder), Abigail Russo (Princeton University), Krishna Shenoy (Stanford University), Saurabh Vyas (Columbia University)