In memoriam: Naftali Tishby Lab

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Prof. Naftali Tishby passes away at the age of 68
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Ruth & Stan Flinkman Family Endowment Fund Chair in Brain Research

Tishby's Lab

NEWS

The 2019 IBT Award in Mathematical Neuroscience – THANKS!

Our Information Bottleneck Theory of Deep Learning has recently been noticed – at last!

See the Quanta-Magazine article on our work and my June 2017 Berlin Deep Learning Workshop talk which triggered it.

A longer talk given at Yandex, Moscow, October 10, 2017.

Recent & popular talks

ACDL, Siena, July 2019
MPI, Gottingen, July 2019
ISIT, Paris, July 2019
CBMM, Italy, June 2019
Gatsby triCenter meeting, London, June 2019
IPAM, Geometry of Big Data, UCLA, May 2019
Columbia University Economics, May 2019
IMVC, Tel-Aviv, April 2019
CERN, Geneva, ML for HEP, April 2019
BrainTech, Tel-Aviv, March 2019
ICERM, Brown University, February 2019
Deep Learning & the Brain, ELSC, Jerusalem, January 2019
Directions in Theoretical Physics, Edinburgh, January 2019
Statistical Physics and Machine Learning: A 30 Year Perspectives, APS Physics Next Workshop, October 2018
Part I of a Mini-Course on The Information Theory of Deep Learning, ICTP, Trieste, November 2018
Part II of a Mini-Course on The Information Theory of Deep Learning, ICTP, Trieste, November 2018
Part III of a Mini-Course on The Information Theory of Deep Learning, ICTP, Trieste, November 2018
“What Makes Us Human: From Genes to Machines”, June 6, 2018, Jerusalem.
A Talk at the Israel Academy of Science, June 6, 2018, Jerusalem
Interview on the future of Artificial Intelligence, The AI Summit, Berlin, June 2018.
Interview at SISSA , Trieste, Italy, before my physics colloquium, May 2018.
Perimeter Institute Physics Colloquium, Waterloo, Canada, April 2018.
S tanford CSE Colloquium, April 4, 2018.
Simons Institute, Berkeley, Public talk, April 9, 2018.
Simons Institute, Berkeley, “Brain & Computation program”, March 2018.
Human creativity, Music & Deep Learning, BIU, Nov. 29, 2017.
The Synergy between Information and Control
שבוע אמנות ומוח 2016 דוד גרוסמן ופרופ’ נפתלי תשבי בדיאלוג על מוח, מחשבה, דמיון ויצירה

My Current Lab:

Selected Research Projects

We work at the interface between computer science, physics, and biology which provides some of the most challenging problems in today’s science and technology. We focus on organizing computational principles that govern information processing in biology, at all levels. To this end, we employ and develop methods that stem from statistical physics, information theory and computational learning theory, to analyze biological data and develop biologically inspired algorithms that can account for the observed performance of biological systems. We hope to find simple yet powerful computational mechanisms that may characterize evolved and adaptive systems, from the molecular level to the whole computational brain and interacting populations. An example is the Information Bottleneck method that provides a general principle for extracting relevant structure in multivariate data, characterizes complex processes, and suggests a general approach for understanding optimal adaptive biological behavior

Zaslavsky N, Kemp C, Tishby N, Regier T.

Communicative need in colour naming

Cogn Neuropsychol. (2020)

Levi-Aharoni, H., & Tishby, N.

The value–complexity trade-off for reinforcement learning based braincomputer interfaces

Journal of Neural Engineering (2020)

Jonathan Rubin, Nahum Ulinovsky, Israel Nelken and Naftali Tishby

The Representation of Prediction Error in Auditory Cortex

PLoS Comput Biol 12(8) e1005058 (2016)

Nori Jacoby, Naftali Tishby, and Dmitri Tymoczko

An Information Theoretic Approach to Chord Categorization and Functional Harmony

Journal of New Music Research Volume 44, 2015 - Issue 3 (2015)

Nori Jacoby, Peter E. Keller, Bruno H. Repp, Naftali Tishby, Merav Ahissar

Lower bound on the accuracy of parameter estimation methods for linear sensorimotor synchronization models : quantifying the problem and suggesting a solution

Timing & Time Perception, Volume 3: Issue 1-2 (2015)

Nori Jacoby, Naftali Tishby, Bruno H. Repp, Merav Ahissar and Peter E. Keller

Parameter Estimation of Linear Sensorimotor Synchronization Models: Phase Correction, Period Correction, and Ensemble Synchronization

Timing & Time Perception, Volume 3: Issue 1-2 (2015)

S. Sabato, N. Srebro and N. Tishby

Distribution-Dependent Sample Complexity of Large Margin Learning

Journal of Machine Learning Research, 14(Jul):2119-2149 (2013)

Amir Globerson, Eran Stark, Eilon Vaadia, and Naftali Tishby

The minimum information principle and its application to neural code analysis

PNAS March 3, 2009 106 (9) 3490-3495; (2009)

Chechik G, Anderson MJ, Bar-Yosef O, Young ED, Tishby N, Nelken I.

Reduction of information redundancy in the ascending auditory pathway

Neuron. 2006 Aug 3;51(3):359-68. (2006)

Israel Nelken, Nachum Ulanovsky, Liora Las, Omer Bar-Yosef, Michael Anderson, Gal Chechik, Naftali Tishby, Eric D. Young

Transformation of stimulus representation in the ascending auditory system

Auditory Signal Processing pp 264-273 (2003)

Schneidmann E., Segev I., and Tishby N.

Information capacity and robustness of stochastic neuron models

Advances in neural information processing systems · February 2000 (2000)

Abeles M, Bergman H, Gat I, Meilijson I, Seidemann E, Tishby N, Vaadia E.

Cortical activity flips among quasi-stationary states

Proc Natl Acad Sci U S A. 1995 Sep 12;92(19):8616-20. (1995)

Seung HS, Sompolinsky H, Tishby N.

Statistical mechanics of learning from examples

Phys. Rev. A 45, 6056 – Published 1 April 1992 (1992)

H. Sompolinsky, N. Tishby, and H. S. Seung

Learning from examples in large neural networks

Phys. Rev. Lett. 65, 1683 – Published 24 September 1990 (1990)

H. Sompolinsky and N. Tishby

Learning in a Two-Layer Neural Network of Edge Detectors

Europhysics Letters 13, 567 (1990)

In memoriam: Naftali Tishby

Professor

https://naftali-tishby.mystrikingly.com

Prof. Naftali Tishby passes away at the age of 68
Read More

Ruth & Stan Flinkman Family Endowment Fund Chair in Brain Research

Tishby's Lab

NEWS

The 2019 IBT Award in Mathematical Neuroscience – THANKS!

Our Information Bottleneck Theory of Deep Learning has recently been noticed – at last!

See the Quanta-Magazine article on our work and my June 2017 Berlin Deep Learning Workshop talk which triggered it.

A longer talk given at Yandex, Moscow, October 10, 2017.

Recent & popular talks

My Current Lab:

Selected Research Projects

People

David Beniaguev

Post Doc

Adi Kaduri Amichai

PhD Student

Amir Dudai

PhD Student

Benjamin Weiner

PhD Student

Shiran Michael

PhD Student

Stav Hertz

PhD Student

Vitaly Lerner

PhD Student

Yair Deitcher

PhD Student

Neta Zylbermann

Lab Manager

Publications

David Beniaguev, Sapir Shapira, Idan Segev, Michael London

Dendro-plexing of Single Input Spikes via Multiple Synaptic Contacts Can Enhance Cortical Neuron Computation and Reduce Axonal Wiring

The Journal of neuroscience : the official journal of the Society for Neuroscience (2026)

Bradley C Rauscher, Natalie Fomin-Thunemann, Sreekanth Kura, Patrick R Doran, Pablo D Perez, Kıvılcım Kılıç, Emily A Martin, Dora Balog, Nathan X Chai, Francesca A Froio, Patrick F Bloniasz, Kate E Herrema, Rockwell P Tang, Scott G Knudstrup, Andrew Garcia, John X Jiang, Jeffrey P Gavornik, Michael London, David Kleinfeld, Michael E Hasselmo, Laura D Lewis, Sava Sakadzic, Lei Tian, Gal Mishne, Emily P Stephen, Martin Thunemann, David A Boas, Anna Devor

The neurovascular impulse response function differentially reflects intrinsic neuromodulation across cortical regions

Nature neuroscience (2026)

Qixin Yang, Shulamit Baror-Sebban, Rotem Kipper, Michael London, Yoav Adam

All-optical electrophysiology reveals behavior-dependent dynamics of excitation and inhibition in the hippocampus

Neuron (2026)

Hertz S, Weiner B, Perets N, London M.

Temporal structure of mouse courtship vocalizations facilitates syllable labeling

Commun Biol. (2020)

Dudai A, Yayon N, Soreq H, London M.

Cortical VIP+ /ChAT+ interneurons: from genetics to function

J Neurochem (2020)

Dudai D., Yayon N., Lerner V., Tasaka G., Deitcher Y., Niederhoffe N., Mizrahi A., Soreq H., London M.

Functional characterization of cortical ChAT/VIP interneurons and their effect on the circuit in vivo.

PLoS Biology (2020)

Dudai A, Yayon N, Lerner V, Tasaka Gi, Deitcher Y, et al.

Barrel cortex VIP/ChAT interneurons suppress sensory responses in vivo

PLoS Biology (2020)

Amir Dudai, Michael Doron, Idan Segev and Michael London

Synaptic input and ACh modulation regulate dendritic Ca2+ spike duration in pyramidal neurons, directly affecting their somatic output

Journal of Neuroscience, JN-RM-1470-21 (2021)

David Beniaguev, Idan Segev, Michael London

Single cortical neurons as deep artificial neural networks

Neuron, ISSN 0896-6273 (2021)

Eyal Gal, Rodrigo Perin, Henry Markram, Michael London, Idan Segev

Neuron Geometry Underlies a Universal Local Architecture in Neuronal Networks

bioRxiv preprint first posted online May. 31, 2019 (2019)

David Beniaguev, Idan Segev, Michael London

Single Cortical Neurons as Deep Artificial Neural Networks

bioRxiv preprint first posted online Apr. 18, 2019; (2019)

Christina Labarrera, Yair Deitcher, Amir Dudai, Benjamin Weiner, Adi Kaduri Amichai, Neta Zylbermann, Michael London

Adrenergic Modulation Regulates the Dendritic Excitability of Layer 5 Pyramidal Neurons In Vivo

Cell reports 23 (4), 1034-1044 (2018)

Adar Adamsky*, Adi Kol*, Tirzah Kreisel, Adi Doron, Nofar Ozeri-Engelhard, Talia Melcer, Ron Refaeli, Henrike Horn, Limor Regev, Maya Groysman, Michael London, Inbal Goshen

Astrocytic activation generates de-novo neuronal potentiation and memory enhancement

Cell, Volume 174, Issue 1, 28 June 2018, Pages 59-71 (2018)

N Yayon, A Dudai, N Vrieler, O Amsalem, M London, H Soreq

Intensify3D: Normalizing signal intensity in large heterogenic image stacks

Scientific Reports, volume 8, Article number: 4311 (2018)

N Perets, S Hertz, M London, D Offen

Intranasal administration of exosomes derived from mesenchymal stem cells ameliorates autistic-like behaviors of BTBR mice

Molecular autism 9 (1), 57 (2018)

D Offen, N Perets, S Hertz, M London

Intranasal administration of exosomes derived from mesenchymal stem cells improves autistic-like behaviors of BTBR mice

Cytotherapy 20 (5), S23 (2018)

Z Zalevsky, M London, E Cohen, A Shemer, D Malka

Multi optically-coupled channels module and related methods of computation

US Patent App. 15/755,138 (2018)

Perets N, Segal-Gavish H, Gothelf Y, Barzilay R, Barhum Y, Abramov N, Hertz S, Morozov D, London M, Offen D

Long term beneficial effect of neurotrophic factors-secreting mesenchymal stem cells transplantation in the BTBR mouse model of autism

Behavioural Brain Research Volume 331, Pages 254-260 (2017)

Eyal Gal, Michael London, Amir Globerson, Srikanth Ramaswamy, Michael W Reimann, Eilif Muller, Henry Markram & Idan Segev

Rich cell-type-specific network topology in neocortical microcircuitry

Nature Neuroscience, VOLUME 20 | NUMBER 7 | JULY 2017 (2017)

Cohen E, Malka D, Shemer A, Zalevsky Z and London M

Neural networks within multi-core optic fibers

Scientific Reports volume 6, Article number: 29080 (2016)

Weiner B, Hertz S, Perets N, London M

Social Ultrasonic Vocalization in Awake Head-Restrained Mouse

Frontiers in Behavioral Neuroscience, 10:236 (2016)

London M, Segev I.

synaptic music in dendrites

Nat Neurosci. 2004 Sep;7(9):904-5. (2004)

London M, Segev I.

Synaptic scaling in vitro and in vivo

Nat Neurosci. 2001 Sep;4(9):853-5. (2002)

London M, Schreibman A, Häusser M, Larkum ME, Segev I.

The information efficacy of a synapse

Nat Neurosci. 2002 Apr;5(4):332-40. (2002)

Steinmetz PN, Manwani A, Koch C, London M, Segev I.

Subthreshold voltage noise due to channel fluctuations in active neuronal membranes

J Comput Neurosci. 2000 Sep-Oct;9(2):133-48. (2000)

Segev I, London M.

Untangling dendrites with quantitative models

Science. 2000 Oct 27;290(5492):744-50 (2000)

Michael London, Claude Meunier and Idan Segev

Signal transfer in passive dendrites with non-uniform membrane conductance

Journal of Neuroscience 1 October 1999, 19 (19) 8219-8233 (1999)

Open Positions

At this time there are no available positions in the lab.

Additional Information

Website:
Lab Website
ELSC Program in Theoretical Neuroscience

Michael London

Associate Professor

Email: mickey.london@mail.huji.ac.il

Phone: +972-2-6586337

Michael London CV

@mikilon

Address: The Edmond and Lily Safra Center for Brain Sciences
The Suzanne and Charles Goodman Brain Sciences Building,
Level 1, Room 2103, Edmond J. Safra Campus,
The Hebrew University of Jerusalem, 9190401

https://www.mikilon.org