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Neuroscience

D-Index
58
Citations
20009
World Ranking
4093
National Ranking
28

Research.com Recognitions

  • 2017 - Mathematical Neuroscience Prize, Israel Brain Technologies (IBT)

Overview

Misha Tsodyks is affiliated with the Weizmann Institute of Science in Israel and has contributed extensively to research in Neuroscience and Computer Science. Their work spans various subfields including Cognitive Neuroscience, Artificial Intelligence, Experimental and Cognitive Psychology, Cellular and Molecular Neuroscience, and Electrical and Electronic Engineering.

The scientist's main research topics include:

  • Topic Modeling
  • Memory and Neural Mechanisms
  • Memory Processes and Influences
  • Neural Networks and Applications
  • Domain Adaptation and Few-Shot Learning
  • Neural dynamics and brain function
  • Advanced Memory and Neural Computing

Misha Tsodyks has authored several papers in well-known journals. Recent publications include:

  • "Multiscale representation of very large environments in the hippocampus of flying bats," 2021, Science
  • "Fundamental Law of Memory Recall," 2020, Physical Review Letters
  • "Retroactive interference model of forgetting," 2021, The Journal of Mathematical Neuroscience
  • "Biases and Variability from Costly Bayesian Inference," 2021, Entropy
  • "Mathematical models of human memory," 2022, Journal of Mathematical Physics

Their frequent co-authors include Mikhail Katkov, Antonios Georgiou, Michelangelo Naim, Tankut Can, and Weishun Zhong, indicating a collaborative research network.

Publication venues where Misha Tsodyks has contributed multiple works include:

  • bioRxiv (Cold Spring Harbor Laboratory)
  • arXiv (Cornell University)
  • Physical Review Letters
  • Current Opinion in Neurobiology
  • Learning & Memory

In recognition of their academic contributions, Misha Tsodyks received the Mathematical Neuroscience Prize from Israel Brain Technologies (IBT) in 2017.

Best Publications

  • The neural code between neocortical pyramidal neurons depends on neurotransmitter release probability

    Misha V. Tsodyks;Henry Markram

  • Synaptic theory of working memory.

    Gianluigi Mongillo;Omri Barak;Omri Barak;Misha Tsodyks;Misha Tsodyks

  • Differential signaling via the same axon of neocortical pyramidal neurons

    Henry Markram;Yun Wang;Misha Tsodyks

  • Neural networks with dynamic synapses

    Misha Tsodyks;Klaus Pawelzik;Henry Markram

  • Spontaneously emerging cortical representations of visual attributes

    Tal Kenet;Tal Kenet;Dmitri Bibitchkov;Misha Tsodyks;Amiram Grinvald

  • Redistribution of synaptic efficacy between neocortical pyramidal neurons

    Henry Markram;Misha Tsodyks

  • Linking Spontaneous Activity of Single Cortical Neurons and the Underlying Functional Architecture

    M. Tsodyks;T. Kenet;A. Grinvald;A. Arieli

  • The Enhanced Storage Capacity in Neural Networks with Low Activity Level

    M. V. Tsodyks;M. V. Feigel'man

  • Population dynamics and theta rhythm phase precession of hippocampal place cell firing: a spiking neuron model.

    Misha V. Tsodyks;William E. Skaggs;Terrence J. Sejnowski;Terrence J. Sejnowski;Bruce L. McNaughton

  • Synchrony generation in recurrent networks with frequency-dependent synapses.

    Misha Tsodyks;Asher Uziel;Henry Markram

  • Paradoxical Effects of External Modulation of Inhibitory Interneurons

    Misha V. Tsodyks;William E. Skaggs;Terrence J. Sejnowski;Terrence J. Sejnowski;Bruce L. McNaughton

  • Quantitative study of attractor neural network retrieving at low spike rates: I. substrate—spikes, rates and neuronal gain

    Daniel J Amit;M V Tsodyks

  • Coding of Temporal Information by Activity-Dependent Synapses

    Galit Fuhrmann;Idan Segev;Henry Markram;Misha Tsodyks

  • Working models of working memory.

    Omri Barak;Misha Tsodyks

  • RAPID STATE SWITCHING IN BALANCED CORTICAL NETWORK MODELS

    M V Tsodyks;M V Tsodyks;T Sejnowski;T Sejnowski

  • The emergence of Up and Down states in cortical networks.

    David Holcman;Misha Tsodyks;Misha Tsodyks

  • An Algorithm for Modifying Neurotransmitter Release Probability Based on Pre- and Postsynaptic Spike Timing

    Walter Senn;Henry Markram;Misha Tsodyks

  • Quantitative study of attractor neural networks retrieving at low spike rates: II. Low-rate retrieval in symmetric networks

    Daniel J Amit;M V Tsodyks

  • Conversion of temporal correlations between stimuli to spatial correlations between attractors

    M. Griniasty;M. V. Tsodyks;Daniel J. Amit

  • A unifying principle underlying the extracellular field potential spectral responses in the human cortex

    Ella Podvalny;Niv Noy;Niv Noy;Michal Harel;Stephan Bickel

  • Neural networks and perceptual learning

    Misha Tsodyks;Charles Gilbert

Frequent Co-Authors

Henry Markram
Henry Markram École Polytechnique Fédérale de Lausanne
Dov Sagi
Dov Sagi Weizmann Institute of Science
Terrence J. Sejnowski
Terrence J. Sejnowski Salk Institute for Biological Studies
Amos Arieli
Amos Arieli Weizmann Institute of Science
Jean-Rémi King
Jean-Rémi King École Normale Supérieure
Amiram Grinvald
Amiram Grinvald Weizmann Institute of Science
Stanislas Dehaene
Stanislas Dehaene Collège de France
Gilad Silberberg
Gilad Silberberg Karolinska Institute
Idan Segev
Idan Segev Hebrew University of Jerusalem
Walter Senn
Walter Senn University of Bern

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