H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Engineering and Technology D-index 40 Citations 22,530 57 World Ranking 2488 National Ranking 999

Overview

What is he best known for?

The fields of study he is best known for:

  • Quantum mechanics
  • Neuroscience
  • Artificial neural network

Eugene M. Izhikevich mainly investigates Neuroscience, Artificial neural network, Bursting, Plasticity and Cerebral cortex. Neuroscience and Millisecond are frequently intertwined in his study. Eugene M. Izhikevich interconnects Limit cycle and Pure mathematics in the investigation of issues within Artificial neural network.

His study in Bursting is interdisciplinary in nature, drawing from both Neurophysiology, Exponential integrate-and-fire, Artificial intelligence, Spiking neural network and Topology. His Spiking neural network research includes themes of Cortical neurons, Biological system and Biological neuron model. His Cerebral cortex study incorporates themes from Nerve net and Visual cortex.

His most cited work include:

  • Simple model of spiking neurons (2840 citations)
  • Dynamical Systems in Neuroscience (2663 citations)
  • Which model to use for cortical spiking neurons (1716 citations)

What are the main themes of his work throughout his whole career to date?

His primary scientific interests are in Neuroscience, Artificial neural network, Topology, Control theory and Canonical model. His work on Neuroplasticity, Neuron and Human brain as part of general Neuroscience research is frequently linked to Plasticity and Diffusion MRI, bridging the gap between disciplines. His work on Spiking neural network and Models of neural computation as part of general Artificial neural network research is often related to Spike-timing-dependent plasticity, thus linking different fields of science.

His Topology research is multidisciplinary, relying on both Content-addressable memory, Bifurcation theory and Forcing. His Control theory research incorporates themes from Phase and Oscillation. His work deals with themes such as Nonlinear phenomena, Bursting and Hindmarsh–Rose model, which intersect with Theta model.

He most often published in these fields:

  • Neuroscience (25.71%)
  • Artificial neural network (18.57%)
  • Topology (18.57%)

What were the highlights of his more recent work (between 2010-2015)?

  • Theoretical computer science (10.00%)
  • Parallel processing (7.14%)
  • Neuromorphic engineering (7.14%)

In recent papers he was focusing on the following fields of study:

Eugene M. Izhikevich mostly deals with Theoretical computer science, Parallel processing, Neuromorphic engineering, Software and Plasticity. His Theoretical computer science study combines topics in areas such as SIMPLE and Parallel computing. The various areas that Eugene M. Izhikevich examines in his SIMPLE study include Artificial neural network, Computer hardware and Distributed computing.

His Plasticity research includes a combination of various areas of study, such as Low activity, Connection and Neuroscience. In his papers, Eugene M. Izhikevich integrates diverse fields, such as Neuroscience, Recall and Associative property. His Neuron research incorporates elements of Computer network and Real-time computing.

Between 2010 and 2015, his most popular works were:

  • Elementary network description for neuromorphic systems (89 citations)
  • Invariant pulse latency coding systems and methods (87 citations)
  • Elementary network description for efficient implementation of event-triggered plasticity rules in neuromorphic systems (67 citations)

In his most recent research, the most cited papers focused on:

  • Quantum mechanics
  • Neuroscience
  • Neuron

His primary areas of study are Software, Neuromorphic engineering, Parallel processing, Theoretical computer science and Plasticity. His Software research overlaps with Computer hardware, SIMPLE, Computer architecture and Event triggered. His study of Plasticity brings together topics like Neuron response, Neuroscience, Low activity and Connection.

The study incorporates disciplines such as Sensory input and Neuron network in addition to Neuron response.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Dynamical Systems in Neuroscience

Eugene M. Izhikevich.
(2006)

4671 Citations

Simple model of spiking neurons

E.M. Izhikevich.
IEEE Transactions on Neural Networks (2003)

4149 Citations

Which model to use for cortical spiking neurons

E.M. Izhikevich.
IEEE Transactions on Neural Networks (2004)

2961 Citations

NEURAL EXCITABILITY, SPIKING AND BURSTING

Eugene M. Izhikevich.
International Journal of Bifurcation and Chaos (2000)

2048 Citations

Weakly connected neural networks

Frank C. Hoppensteadt;Eugene M. Izhikevich.
(1997)

1509 Citations

Polychronization: Computation with Spikes

Eugene M. Izhikevich.
Neural Computation (2006)

1228 Citations

Large-scale model of mammalian thalamocortical systems

Eugene M. Izhikevich;Gerald M. Edelman.
Proceedings of the National Academy of Sciences of the United States of America (2008)

1077 Citations

Bursts as a unit of neural information: selective communication via resonance

Eugene M. Izhikevich;Niraj S. Desai;Elisabeth C. Walcott;Frank C. Hoppensteadt.
Trends in Neurosciences (2003)

625 Citations

Spike-timing dynamics of neuronal groups.

Eugene M. Izhikevich;Joseph A. Gally;Gerald M. Edelman.
Cerebral Cortex (2004)

575 Citations

Solving the distal reward problem through linkage of stdp and dopamine signaling

Eugene M. Izhikevich.
Cerebral Cortex (2007)

563 Citations

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