Merav's Pic

Postdoctoral Fellow,
Applied Mathematics,
University of Washington, Seattle.

PhD graduate,
ELSC Center for Brain Science,
Hebrew University, Jerusalem.
In collaboration with:
The Center for Theoretical Neuroscience,
Columbia University, New York.

Msc graduate,
Racah Institute of Physics,
Hebrew University, Jerusalem.
Selected Classes:
University of Amsterdam, Amsterdam.

Bsc graduate,
Einstein Institute of Mathematics &
Racah Institute of Physics
Hebrew University, Jerusalem.

Merav Stern

Neural Network Theory Research


The complexity of our brains, of the multiple tasks they simultaneously perform in multiple ways, of the many circuits they include and the ways these interact, brings upon us a great challenge when we try to explain them.
This is perhaps the greatest scientific challenge of our lifetime. Related questions arise that are interesting as well: "What approaches should we take to study the brain?", "Which areas within the brain should we study?", "What level of details (molecules, neurons, networks or cognitive modules) would be most informative to study?", "Can we learn solely from observation or must we have some models to test?", "Do we have the necessary physical and mathematical tools we need?" are examples of such questions.

I don't think that I have the right definitive answers. I'm not even sure such answers exist. But I have come to the conclusion that discussing these questions is important. Read More

Image By Marylka Yoe Uusisaari


Dynamics of Clustered Networks

With Haim Sompolinsky and Larry Abbott
Dynamics of Random Neural Networks with Bistable Units - Read the paper

Dynamics of Networks with Sub-Groups

With Yonatan Aljadeff and Tatyana Sharpee
Transition to chaos in random networks with cell-type-specific connectivity - Read the paper

Piriform Cortex

With Kevin Franks and Larry Abbott.
A Transformation from Latency to Ensemble Coding in a Model of Piriform Cortex - Read the paper

Motherhood and the Olfactory Bulb

With Amit Vinograd, Yael Fuchs-Shlomai, Diptendu Mukherjee, Yuan Gao, Ami Citri, Ian Davison and Adi Mizrahi;
Functional plasticity of Odor Representations during Motherhood - Read the paper

Block Structured Random Matrices

With David Renfrew and Yonatan Aljadeff
Eigenvalues of Block Structured Asymmetric Random Matrices - Read our paper

The Olivo-Cerebellar Loop

With Yosi Yarom, ICNC rotation project
Memory in Purkinje Cells - View our poster

Black Holes in String Theory

(My former life as a high energy physicist) With Amit Giveon and Dan Gorbonos
Fundamental Strings and Higher Derivative Corrections to d-Dimensional Black Holes - Read the paper

On-Going Projects

Learning in Mice and Models

In collaboration with the Allen institute for brain science.
With Eric Shea-Brown, Shawn Olsen, Sahar Manavi, Doug Ollerenshaw, Matt Valley, Yulia Oganian, Michael Bause and Katheleen Champion
In the Footsteps of Learning: Changes in Network Dynamics and Dimensionality with Task Acquisition - View my COSYNE 18 poster

Random Neural Networks with tight Excitation and Inhibition balace

With Gabe Ocker.
We thank Haim Sompolinsky and Larry Abbott for their notes.
From Connectivity to Rate Dynamics - Successes and failures of the Mean-Field Approach - View my Bernstein meeting talk review

Inferring Spiking Rate from Wide-Field Calcium Imaging

With Daniela Witten
Stay tuned...

Exploring the Tempotron

With Hannes Rapp
We thank the OIST at Okinawa for hosting us at the OCNC course

Neural Network Analysis for better Public Transportantion

With Daniel Dewlsky and Nathan Kutz
Stay tuned...


Notes on Mean-Field Calculation of Random Network Dynamics and their related Lyaponuv Exponents

The notes are the details behind the paper "Chaos in RNN" by Sompolinsky et al. 88'
They are based on Larry Abbott class notes (equations 1-36)
And were extended to include the second half of the paper by myself, with his blessing (equations 37-end)the notes

The transition line from chaos to fixed points

A Detailed calculation of the transition in my Paper with Haim Sompolonsky and Larry Abbott
Stay tuned...


Teaching experience:
  • 2013-2014 Teacher Assistant, Computational Neuroscience, Columbia University.
  • 2007-2011 Lecturer, Jerusalem College of Engineering.
  • 2006-2011 Teacher and Program Content Developer, the Youth Science Center, HU.
  • 2005-2007 Teacher Assistant, Mechanics and Electricity for MD students, HU.
Other employment:
  • Summers 2008-2011 Key Staff, New Jersey "Y" camps.
ניסיון הדרכה והתנדבות נוסף
  • מנחת תלמידי תיכון לקראת עבודת גמר במעבדות בלמונטה
  • רכזת פעילות ישראל במחנות הקיץ NJY בארה"ב
  • מורה במכינה במכללה להנדסה
  • שליחת הסוכנות היהודית - מדריכת רולר, קפואה ועברית במחנות הקיץ הרלם ורמה ניו אינגלד בארה"ב
  • מדריכה ומאמנת החלקה אומנותית על גלגיליות - מרמת מתחילים ועד נבחרת
  • מדריכה ופעילה בתנועת הנוער אילנוער