Dr. Shein-Idelson holds a MA in Physics (Technion), a BA in Physics (Tel-Aviv University) and a PhD in Electrical Engineering (Tel Aviv University). He completed a post-doctoral study in at the Max-Planck Institute for Brain Research in Frankfurt. He joined the Department of Neurobiology at Tel Aviv University on 2018.
Dr. Mark Shein-Idelson
Biography
Research Interests
Our lab is set to understand how collective neuronal activity is organized and how this organization sub-serves coding in the brain. We seek to expose the simple, most fundamental principles that underlie the multi-scale complexity of neuronal systems. To extract these principles, we take a unique perspective by exploring the “simpler” brains of reptiles. This choice is motivated by the acknowledgement that brains and neuronal coding schemes are products of evolution and can be flashed out by comparative approaches and optimal models systems.
Methodology
We employ a wide set of techniques to study the hitherto under-explored reptilian brain. Specifically, we use large-scale (thousands of electrodes) extra-cellular electrophysiology and intra-cellular electrophysiology to study circuits both ex-vivo and in-vivo. We develop data analysis approaches to deal with the overgrowing richness of our data sets. We couple our experiments with quantitative behavioral analysis to place brain dynamics in context. We build computational models to test ideas and develop theories.
Recent Publications
Shein-Idelson M, Pammer L, Hemberger M and Laurent G (2017). Large-scale mapping of cortical synaptic projections with extracellular electrode arrays. Nature Methods 14(9):882-890. Link
Shein-Idelson M*,Ondracek J M*, Liaw H, Reiter S, Laurent G (2016). Slow Waves, Sharp-waves, Ripples and REM in Sleeping Dragons. Science. 352 (6285), 590-595. Link
Fournier J, Mueller C M, Shein-Idelson M, Hemberger M, Laurent G (2016). Consensus-Based Sorting of Neuronal Spike Waveforms. PLoS ONE 11(8): e0160494. Link
Shein-Idelson M, Cohen G, Ben-Jacob E, Hanein Y (2016). Modularity induced gating and delays in neuronal networks. PLoS Computational Biolology 12(4): e1004883. Link
Naumann R K, Ondracek J M, Reiter S, Shein-Idelson M, Tosches M A, Yamawaki T M, Laurent G (2015). The reptilian brain. Current Biology 25 (8), 317–321. Link
Shein-Idelson M, Ben-Jacob E, Hanein Y (2011). Engineered neuronal circuits: A new platform for studying the role of modular topology. Frontiers in Neuroengineering 4:10. Link
Herzog N, Shein-Idelson M, Hanein Y (2011). Optical validation of in vitro extra-cellular neuronal recordings. Journal of Neural Engineering 8(6),056008. Link
Shein-Idelson M, Ben-Jacob E, Hanein Y (2010). Innate synchronous oscillations in freely-organized small neuronal circuits. PLoS One5(12), e14443. Link
Greenbaum A, Anava S, Ayali A, Shein M, David-Pur M, Ben-Jacob E, Hanein Y (2009). One-to-one neuron-electrode interfacing. Journal of Neuroscience Methods 182(2), 219-224. Link
Shoval A, Adams C, David-Pur M, Shein M, Hanein Y, Sernagor E, (2009). Carbon nanotube electrodes for effective interfacing with retinal tissue. Frontiers in Neuroengineering 2, 4. Link
Shein M, Greenbaum A, Gabay T, Sorkin R, David-Pur M, Ben-Jacob E, Hanein Y (2009). Engineered neuronal circuits shaped and interfaced with carbon nanotube microelectrode arrays. Biomedical Microdevices 11(2), 495-501. Link
Shein M, Volman V, Raichman N, Hanein Y, Ben-Jacob E (2008). Management of synchronized network activity by highly active neurons. Physical Biology 5(3), 036008. Link
Baruchi I, Volman V, Raichman N, Shein M, Ben-Jacob E (2008). The emergence and properties of mutual synchronization in in vitro coupled cortical networks. European Journal of Neuroscience 28(9), 1825-1835. Link
Rubinsky L, Raichman N, Baruchi I, Shein M, Lavee J, Frenk H, Ben-Jacob E (2007). Study of hypothermia on cultured neuronal networks using multi-electrode arrays. Journal of Neuroscience Methods 160(2), 288-293. Link
Baruchi I, Grossman D, Volman V, Shein M, Hunter J, Towle VL, Ben-Jacob E (2006). Functional holography analysis: simplifying the complexity of dynamical networks. Chaos 16(1), 015112. Link