MD PhD, Professor of Physiology and the Pearl Seiden Chair in Sciences

Research Interests

(1) Biophysical and functional aspects of bio-electricity in proteins, cells and networks, focusing on mechanisms underlying emergence, dynamics and adaptation of bioelectrical phenomena at extended timescales. (2) Advancing a framework of relational physiology, focusing on the functional organization of systems that are embedded in a responsive and adaptive environment, implementing natural input statistics and closed-loop experimental designs.

(1) היבטים פיסיקליים ופיזיולוגיים של תופעות חשמליות בחלבונים, תאים ורשתות, והסתגלותן לסביבה דינמית בפרקי זמן ארוכים. (2) ניסוח מצע לפיזיולוגיה התייחסותית המדגישה התפתחות מערכות הגוף בסביבה מתגמלת ומסתגלת, תוך יישום סטטיסטיקת קלט טבעית ומערכֵי ניסוי בחוג סגור. 

(1) إنّ مجالات اهتمامي هي الجوانب الفيزيائية والفيزيولوجيةللظواهر الكهربائية في كل من البروتينات، الخلايا والشبكات العصبيةوكيفيّة التكيُّف مع البيئة الديناميكية على مدى فترات طويلة منالزمن. (2) اضافةً إلى تطوير مِنَصّة علم الفيزيولوجيا النسبيّة، الداعية لفكرة  تطوّر أنظمة الجسم تحت بيئتها المُحفِّزة والمُتَكيِّفة، بواسطة  تطبيق عِلْم “إحصاء المُدْخَلات الطبيعية” ونُظُم التجارب ذات الطابعالإرْتِجاعي (تجارب الحلقات المغلقة)

Contact information

Network Biology Laboratory, Faculty of Electrical Engineering, Fishbach Bldg. (Room 434), Technion, Haifa 32000, Israel.

Shimon Marom, Tel. +972-4-829-5752

Ms. Yael AbuhazeraTel. +972-4-8295089

Google Maps



S. Marom, Science, Psychoanalysis, and the Brain: Space for Dialogue  (Cambridge University Press, 2015); available in PDF, eBook, paperback and hardback formats.
Translated versions –
Hebrew:  ״פסיכואנליזה ונוירו־פיזיולוגיה: מקום לדיאלוג״; הוצאת רסלינג, 2018
Italian: due to appear in 2020 (Astrolabio-Ubaldini, Rome)



H. Ori, H. Hazan, E. Marder and S. Marom, Dynamic clamp constructed phase diagram for the Hodgkin and Huxley model of excitability. Proceedings of the National Academy of Sciences, 201916514 (pp. 1–8), DOI | 10.1073/pnas.1916514117 (2020

U. Gordon, S. Marom and N. Brenner, Visual detection of time-varying signals: Opposing biases and their timescales. PLoS ONE 14(11): e0224256. https://doi.org/10.1371/journal.pone.0224256 (2019)

H. Keren, J. Partzsch, S. Marom and CG. Mayr, A biohybrid setup for coupling biological and neuromorphic neural networks. Frontiers in Neuroscience, 443135 (2019)

N. Haroush and S. Marom, Inhibition increases response variability and reduces stimulus discrimination in random networks of cortical neurons. Scientific Reports, 9(1) number 4969 (2019)

H. Ori, E. Marder and S. Marom, Cellular function given parametric variation in the Hodgkin and Huxley model of excitability. Proceedings of the National Academy of Sciences, 201808552 (pp. 1–8), DOI | 10.1073/pnas.1808552115 (2018)
[a related Mathematica notebook is downloadable from Mendeley Data repository]

S. Marom, Emergence and Maintenance of Excitability: Kinetics over Structure. Current Opinion in Neurobiology, 40:66–71 (2016)

H. Keren and S. Marom, Long-range Synchrony and Emergence of Reentry in Neural Networks. Scientific Reports, 6:36837 (2016)

A. Wallach, et al., Closing Dewey’s Circuit. In: “Closed Loop Neuroscience” (A. El-Hady, Ed.), Academic Press (2016)

שמעון מרום, מקום לדיאלוג
(2016 ,״שיחות״ כתב-עת ישראלי לפסיכותרפיה (כרך ל’, חוב׳ מס׳ 3, יולי
[Space for Dialogue, Sihot\Dialogues–Israel Journal of Psychotherapy, Vol. L(3) 2016 (Hebrew)]

G.  Gigante, et al., Network Events on Multiple Space and Time Scales in Cultured Neural Networks and in a Stochastic Rate Model. PLoS Computational Biology (2015)

N.  Haroush and S. Marom, Slow Dynamics in Features of Synchronized Neural Network Responses. Front. Comput. Neurosci., doi | 10.3389/fncom.2015.00040 (2015)

E. Braun and S. Marom, Universality, Complexity and the Praxis of Biology: Two Case Studies. Studies in History and Philosophy of Biological and Biomedical Sciences, 53, pp. 68–72, doi | 10.1016/j.shpsc.2015.03.007 (2015) [for context see Hon & Carrier (2015) and Gilead (2015)]

H. Keren and S. Marom, Controlling neural network responsiveness: tradeoffs and constraints. Front. Neuroeng., doi | 10.3389/fneng.2014.00011 (2014)

S. Reinartz, et al., Synaptic dynamics contribute to long-term single neuron response fluctuations. Front. Neural Circuits, doi | 10.3389/fncir.2014.00071 (2014)

A. Gal and S. Marom, Single Neuron Response Fluctuations: A Self-organized Criticality Point of View. In: Criticality in Neural Systems, Plenz & Niebur (Eds.), Wiley (2014)

A. Gal and S. Marom, Self-organized criticality in single neuron excitability. Physical Review E, 88, 062717 (2013)

A. Gal and S. Marom, Entrainment of the intrinsic dynamics of single isolated neurons by natural-like input. The Journal of Neuroscience 33(18):7912–7918 (2013)

R. Vardi, et al., Synchronization by elastic neuronal latencies. Physical Review E, 87, 012724 (2013)

R. Vardi, et al., Synchronization with mismatched synaptic delays: A unique role of elastic neuronal latency. EPL (Europhysics Letters), 100, 48003, doi | 10.1209/0295-5075/100/48003 (2012)

A. Wallach and S. Marom, Interactions Between Network Synchrony and the Dynamics of Neuronal Threshold. J. of Neurophysiology 107:2926–2936, doi | 10.1152/jn.00876.2011 (2012)

O. Levy, N. E. Ziv and S. Marom, Enhancement of neural representation capacity by modular architecture in networks of cortical neurons. Europ. J. Neurosci. 35, pp. 1753–1760, doi | 10.1111/j.1460-9568.2012.08094.x (2012)

R. Vardi, et al., Synthetic reverberating activity patterns embedded in networks of cortical neurons. EPL (Europhysics Letters), 97, 66002, doi | 10.1209/0295-5075/97/66002 (2012)

S. Marom and A. Wallach, Relational Dynamics in Perception: Impacts on trial-to-trial variation. Front. Comput. Neurosci. 5:16, doi | 10.3389/fncom.2011.00016 (2011)

A. Wallach, et al., Neuronal Response Clamp. Front. Neuroeng. 4:3, doi | 10.3389/fneng.2011.00003 (2011)

A. Gal, et al., Dynamics of excitability over extended timescales in cultured cortical neurons. The Journal of Neuroscience, 30(48):16332–16342 (2010)

C. Zrenner, et al., A generic framework for real-time multichannel neuronal signal analysis, telemetry control and sub-millisecond latency feedback generation. Front. Neurosci., doi | 10.3389/fnins.2010.00173 (2010)

E. Kermany, et al., Tradeoffs and Constraints on Neural Representation in Networks of Cortical Neurons. The Journal of Neuroscience, July 14, 30(28):9588 –9596, (2010)

שמעון מרום, הפיתוי הנצחי
(2010) ,״אודיסאה״ חוב׳ מס׳ 6

S. Marom, Neural timescales or lack thereof.  Progress in Neurobiology 90:16–28, (2010)

J.P.M. Finberg, et al., Modulation of excessive neuronal activity by fibroblasts: potential use in treatment of Parkinson’s disease. Restorative Neurology and Neuroscience, Volume 28, Number 6, 803–815, doi | 10.3233/RNN-2010-055), (2010)

A. Minerbi, et al., Long-Term Relationships between Synaptic Tenacity, Synaptic Remodeling, and Network Activity. PLoS Biol 7(6): e1000136, doi | 10.1371/journal.pbio.1000136, (2009)

S. Marom, et al., On the precarious path of reverse neuro-engineering. Front. Comput. Neurosci., doi | 10.3389/neuro.10.005, (2009)

E. Braun and S. Marom, Learning Without Error. In: “Going Amiss in Experimental Research”, Hon, Schickore and Steinle (Eds.), Springer, ISBN 978-1-4020-8892-6 (2009)

S. Marom, Adaptive transition rates in excitable membranes. Front. Comput. Neurosci., doi | 10.3389/neuro.10.002, (2009)

G. Shahaf, et al., Order-based representation in random networks of cortical neurons. PLoS Comput Biol, 4(11), (2008)

A. Wallach, et al., Selective adaptation in networks of heterogeneous populations: Model, simulation, and experiment. PLoS Comput Biol, 4(2), (2008)

L. Yankelson, et al., Cell therapy for modication of the myocardial electrophysiological substrate. Circulation, 117(6):720–731, (2008)

J.P. Eckmann, et al., Leader neurons in population bursts of 2-D living neural networks. New Journal of Physics, 10(1):015011 (19pp), (2008)

D. Eytan and S. Marom, Dynamics and effective topology underlying synchronization in networks of cortical neurons. The Journal of Neuroscience, 26(33):8465–8476, (2006)

S. Marom and D. Eytan, Learning in ex-vivo developing networks of cortical neurons. Progress in Brain Research 147:189–199, (2005)

D. Eytan, et al., Dopamine-induced dispersion of correlations between action potentials in networks of cortical neurons. J Neurophysiol, 92(3):1817–1824, (2004)

M. R. Rosen, O. Binah and S. Marom, Cardiac memory and cortical memory: do learning patterns in neural networks impact on cardiac arrhythmias? Circulation, 108(15):1784–1789, (2003)

D. Eytan, N. Brenner and S. Marom, Selective adaptation in networks of cortical neurons. The Journal of Neuroscience, 23(28):9349–9356, (2003)

L. M. Manevitz and S. Marom, Modeling the process of rate selection in neuronal activity. J Theor Biol, 216(3):337–343, (2002)

S. Marom and G. Shahaf, Development, learning and memory in large random networks of cortical neurons: lessons beyond anatomy. Q Rev Biophys, 35(1):63–87, (2002)

Y. Feld, et al., Electrophysiological modulation of cardiomyocytic tissue by transfected broblasts expressing potassium channels: a novel strategy to manipulate excitability. Circulation, 105(4):522–529, (2002)

D. Tal, et al., Frequency tuning of input-output relation in a rat cortical neuron in-vitro. Neurosci Lett, 300(1):21–24, (2001)

G. Shahaf and S. Marom, Learning in networks of cortical neurons. The Journal of Neuroscience, 21(22):8782–8788, (2001)

M. Melamed-Frank and S. Marom, A global defect in scaling relationship between electrical activity and availability of muscle sodium channels in hyperkalemic periodic paralysis. Pflug. Arch., 438(2):213–217, (1999)

A. Toib, V. Lyakhov and S. Marom, Interaction between duration of activity and time course of recovery from slow inactivation in mammalian brain Na channels. The Journal of Neuroscience, 18(5):1893–1903, (1998)

S. Marom, Slow changes in the availability of voltage-gated ion channels: effects on the dynamics of excitable membranes. J Membr Biol, 161(2):105–113, (1998)

S. Marom, et al., Effects of density and gating of delayed-rectifier potassium channels on resting membrane potential and its fluctuations. J Membr Biol, 154(3):267–274, (1996)

S. Marom, A. Toib and E. Braun, Rich dynamics in a simplified excitable system. Adv Exp Med Biol, 382:61–66, (1995)

J. Kupper, et al., Intracellular and extracellular amino acids that influence c-type inactivation and its modulation in a voltage-dependent potassium channel. Pflug. Arch., 430(1):1–11, (1995)

S. Marom and L. F. Abbott, Modeling state-dependent inactivation of membrane currents. Biophysical Journal, 67(2):515–520, (1994)

S. Marom, A note on bistability in a simple synapseless point neuron model. Network: Computation in Neural Systems, 5(3):327–331, (1994)

S. Marom and I. B. Levitan, State-dependent inactivation of the Kv3 potassium channel. Biophysical Journal, 67(2):579–589, (1994)

S. Marom, et al., Mechanism and modulation of inactivation of the Kv3 potassium channel. Receptors & Channels, 1(1):81–88, (1993)

S. Marom, A 3-D approach to voltage clamp data. Journal of Theoretical Biology, 154(4):475–484, (1992)

O. Binah, et al., Immunological rejection of heart transplant: how lytic granules from cytotoxic T lymphocytes damage guinea pig ventricular myocytes. Pflug. Arch., 420(2):172–179, (1992)

S. Marom, D. Dagan and J. Winaver, New concepts emerge from single channel techniques applied to kidney proximal tubule apical membrane. News In Physiological Sciences (NIPS), 5:194–197, (1990)

O.S. Better, et al., The mechanism of muscle injury in the crush syndrome: ischemic versus pressure-stretch myopathy. Miner Electrolyte Metab, 16(4):181–184, (1990)

S. Marom, et al., Brush-border membrane cation conducting channels from rat kidney proximal tubules. Am J Physiol, 257(3 Pt 2):F328–35, (1989)

S. Marom and D. Dagan, Calcium current in growth balls from isolated Helix aspersa neuronal growth cones. Pflug. Arch., 409(6):578–581, (1987)


Past graduate students: Amir Toib (MA); Meira Frank (PhD); Dror Tal (PhD); Goded Shahaf (PhD); Shlomi Israelit (PhD); Danny Eytan (PhD); Eyal Jacobson (MD, PhD); Einat Kermany (PhD); Christoph Zrenner (MD, MA); Ofri Levy (PhD); Avner Wallach (PhD); Sebastian Reinharz (PhD); Asaf Gal (PhD); Netta Harush (PhD); Hanna Keren (PhD); Hillel Ori (PhD); Urit Gordon (PhD); Tal Knafo (PhD).

(Book) Science, Psychoanalysis, and the Brain: Space for Dialogue
Science, Psychoanalysis, and the Brain: Space for Dialogue, Cambridge University Press, 2015; ISBN 978-1-10710118-0; available in PDF, eBook, paperback and hardback formats.

Translated versions –
Hebrew:  ״פסיכואנליזה ונוירו־פיזיולוגיה: מקום לדיאלוג״; הוצאת רסלינג, 2018
Italian: due to appear 2020 (Astrolabio-Ubaldini, Rome)

Editorial reviews

  • Sets a new standard for the sought after bridge between two areas of discourse (depth-psychology and neurophysiology)
  • Relational approach by the author; he is present throughout the book as a subject
  • Rigorous, creative, engaging tour inside the possible-impossible relations between depth-psychology and neurophysiology


“Science, Psychoanalysis, and the Brain: Space for Dialogue is an important work; I am not aware of any other like it. The arguments are rigorous, creative, and down to earth. Shimon Marom proposes a relational neurophysiology arising in the space he has created between psychoanalysis and brain science. In his hands, this is not mere speculation, but a significant engagement with a great and important topic.” Leslie Brothers, MD, author of Mistaken Identity: The Mind-Brain Problem Reconsidered and Friday’s Footprints: How Society Shapes the Human Mind

“This book will be a landmark for researchers in neuroscience and depth psychology, clinicians, humanists, and intellectuals in general who seek to learn, teach, or deepen their understanding of the connections between depth psychology concepts and the realism of the underlying neuronal substrates. It is a complete exposition and formalization of the most essential theoretical concepts and experimental facts necessary for establishing a genuine dialogue between science and humanism, between neuroscience and depth psychology.” Gustavo Deco, PhD, Pompeu Fabra University, author of Computational Neuroscience of Vision and The Noisy Brain: Stochastic Dynamics as a Principle of Brain Function

“Shimon Marom confronts the belief of his own generation of neuroscientists that complex psychological phenomena can be understood by dissecting the brain down to its simplest parts, showing why this approach should be expected to fail. He then develops a unique dialogue across the chasm that separates neurophysiology and depth psychology, offering an alternate foundation for inquiry. The work is educational without being dry because it is rich in explanatory details that clarify by building on known concepts. It is also insightful, weaving historical theories and cutting-edge science into a new way of viewing a fundamental conundrum key to the core of human experience. This beautifully written volume is no less than an intellectual tour de force.” Steve A. N. Goldstein, MD, PhD, Brandeis University

Braitenberg Vehicle

In a small, seminal book titled Vehicles: Experiments in Synthetic Psychology, Valentino Braitenberg (1926–2011) – an admired neuroanatomist – describes a set of thought experiments in which agents with simple structure behave in human-like ways; Braitenberg blatantly put forward the hypothesis that the primitives for realizing such machines are cellular and synaptic processes that are amenable for physiological characterization. The reasoning and results presented in Shahaf et al (2008) make the realization of a Braitenberg’s vehicle that classifies objects in its visual field (using a large-scale network of biological neurons) a trivial matter. Such a Braitenberg’s vehicle is demonstrated in the above video clip that was prepared in Marom’s group by Danny Eytan, David Ben Shimol and Lior Lev-Tov.  A low resolution movie was published in the ‘supporting information’ section of the 2008 paper.

The main text and data of Shahaf et al (2008) show that the physical loci wherefrom stimuli are delivered to a recurrent, large scale random network of cortical neurons, albeit causing “noisy” neuronal responses, may be fully classified using the temporal order at which neurons are recruited by the different stimuli. Here, an application of this idea, in the form of a Braitenberg vehicle, is demonstrated: Inputs from the two (Right and Left) ultrasonic “eyes” of a Lego Mindstorms vehicle are sampled at 0.2 Hz and translated into stimulation of a large random network of cortical neurons at two different sites. The side corresponding to the nearest visual object (relative to vehicle’s longitudinal axis) is classified using an Edit (Levenshtein)-distance metric based on the recruitment order of 8 neurons; these 8 neurons equally respond to stimuli from each of the two eyes, but their recruitment order is unique to the stimulus side. Based on the classified activity, a command is sent to the appropriate motor attached to one of the wheels. The red trace on the left side of the movie frame represents the total network activity (points depict evoked activity); the blue numbers in front of vehicle’s “eyes” show distances (in cm) from the right and left sensed objects; the Edit distance of the evoked recruitment orders, from a predefined internal representation of the Right and Left objects, is shown in red numbers. Top left: time in seconds.

In Marom et al 2009, we have used the above vehicle to provide a sobering example for the limits of reverse engineering in neuroscience. We demonstrate that application of reverse engineering to the study of the design principle of this functional neuro-system, may result in a perfectly valid but wrong induction of the system’s design principle.  If in the very simple setup we bring here (static environment, primitive task and practically unlimited access to every piece of relevant information), it is difficult to induce a design principle, what are our chances of exposing biological design principles when more realistic conditions are examined?

Network Data
Download from Mendeley Data repository hours long recordings of spontaneous network activity, sampled over several days from rat cortical neurons in culture, 2–3 weeks following plating day (1st day postpartum).  The data are free, no authorship charged.

Lecture notes on cellular excitability: a Mathematica® (CDF) notebook
Download from Mendeley Data repository a computational document format to view and interact with course notebook (animations, manipulations, etc.).  

Bio-excitable Systems (course 048746)

מערכות ביו-אקסיטביליות

מזה מאתיים שנה ויותר מהוות מערכות ביו-אקסיטביליות מקור השראה לפיתוח כלים ותיאוריות הנדסיות. הקורס מכוון להקניית ידע מקיף ועדכני הנוגע להיבטים פיסיקליים והנדסיים של תופעות חשמליות בקרומים ביולוגיים אקסיטביליים, בהקשר הפיזיולוגי (לב, מוח, שריר שלד, שרירים לא רצוניים, רקמות אנדוקריניות).

Bio-excitable Systems

Over the past two-hundred years bio-excitable systems have continually inspired development of concepts and theories in the world of engineering. The course provides an extensive and updated knowledge pertaining to physical and engineering aspects of electrical excitability in biological membranes, within a physiologically relevant context (cardiac, neural, muscular and endocrine systems).


[1]  B. Hille. Ion channels of excitable membranes. Sinauer, 3rd edition (2001)
[2]  JD. Murray. Mathematical Biology. Springer, 3rd edition (2007)
[3]  J. Keener & J. Sneyd. Mathematical Physiology. Springer, 2nd edition (2008)

(278493 פסיכולוגיה ופיזיולוגיה: גישה התייחסותית (קורס

Psychology & Physiology: a Relational View

Analysis of fundamental constraints inherent to modern brain research aimed to understand human behavior in health and disease. Key issues in brain research (evolution, anatomy, development, adaptation and learning) will be examined using concepts from functionalist, pragmatist and relational psychoanalytic schools.

פסיכולוגיה ופיזיולוגיה: גישה התייחסותית

ניתוח אילוצים המובנים אל תוך התרבות העכשווית של חקר מוח המכוון להבנה יסודית של התנהגות אנושית, בבריאות וחולי. נשתמש במושגים אשר מקורם בהגות פונקציונלית, פרגמטיסטית, ופסיכואנליטית־התייחסותית, כדי לנתח שאלות ליבה בחקר המוח וההתנהגות: אבולוציה, אנטומיה, התפתחות, אדפטציה ולמידה.

חומר ההרצאות (מודפס בעברית) נגיש באתר הקורס הטכניוני

מבוא – שבוע ראשון
יותר זה אחר – שבוע שני
הנדסה מהופכת, רדוקציה – שבוע שלישי
השלכות, לטוב ולרע – שבוע רביעי
שפות מובנות, מעגלי אימות – שבוע חמישי
אובייקטים התייחסותיים בפסיכולוגיה – שבוע שישי
התפתחות המוח, שאלת המיקומיות – שבוע שביעי
מערכת עצבים מושגית – שבוע שמיני
דוקטרינת העצב, אסוציאציה, סימטריה – שבוע תשיעי
שבירת סימטריה, מבנית־תכניתית, פונקציונלית־דינמית – שבוע עשירי
אובייקטים, אמת, פתולוגיה ופיזיולוגיה התייחסותית – שבוע אחד־עשר
דוגמאות ליישום פיזיולוגיה התייחסותית: תא, רשת, אדם – שבוע שנים־עשר
סיכום: פיתוי נצחי – שבוע שלושה־עשר

Further reading:

More Is Different — One More Time  (Anderson, 2001)
The chess master and the computer (Kasparov, 2010)
On the Precarious Path of Reverse Neuro-engineering (Marom et al, 2009)
Universality, Complexity and the Praxis of Biology (Braun & Marom, 2015)
Biology and the Future of Psychoanalysis (Kandel, 1999)
The Case Against Neuropsychoanalysis  (Blass & Carmeli, 2007)
Exactitude in Science  (Jorge L. Borges, 1946)
Funes the Memories  (Jorge L. Borges, 1942)

Mourning and Melancholia  (Sigmund Freud, 1917)
The Social Brain: … Evolutionary Perspective (R.I.M. Dunbar, 2003)
Early Physiological Psychology (Ch. IV in J.C. Flügel, 1934)
The Reflex Arc Concept in Psychology (Dewey, 1896)
Cortical Plasticity (Buonomano & Merzenich, 1998)

Pragmatism’s Conception of Truth (James, 1907)
Meno (Plato, ca. 400BC)
Development of Visual Guided Behaviour (Held & Hein, 1963)