D-Index & Metrics Best Publications

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Neuroscience D-index 33 Citations 6,805 97 World Ranking 4576 National Ranking 1989

Overview

What is he best known for?

The fields of study he is best known for:

  • Neuroscience
  • Artificial intelligence
  • Neuron

His main research concerns Neuroscience, Artificial intelligence, Facial recognition system, Computer vision and Patch clamp. Many of his research projects under Neuroscience are closely connected to Chemistry, Constant current and Subthreshold oscillations with Chemistry, Constant current and Subthreshold oscillations, tying the diverse disciplines of science together. His Artificial intelligence study incorporates themes from Encoding and Perspective.

His Facial recognition system research includes themes of Matching and Pattern recognition. His biological study spans a wide range of topics, including FERET database and Small set. Jean Marc Fellous works mostly in the field of Patch clamp, limiting it down to concerns involving Membrane potential and, occasionally, Inhibitory postsynaptic potential, Neocortex, Synaptic noise and Nerve net.

His most cited work include:

  • Face recognition by elastic bunch graph matching (2819 citations)
  • Face recognition by elastic bunch graph matching (1825 citations)
  • Fluctuating synaptic conductances recreate in vivo-like activity in neocortical neurons. (528 citations)

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

His primary areas of investigation include Neuroscience, Artificial intelligence, Inhibitory postsynaptic potential, Hippocampus and Neuron. In the field of Neuroscience, his study on Excitatory postsynaptic potential, Stimulus, Visual cortex and Prefrontal cortex overlaps with subjects such as Chemistry. His Artificial intelligence research includes elements of Machine learning, Spatial memory, Computer vision and Pattern recognition.

His specific area of interest is Computer vision, where Jean Marc Fellous studies Facial recognition system. Jean Marc Fellous has included themes like Cerebral cortex, AMPA receptor and Patch clamp in his Inhibitory postsynaptic potential study. Jean Marc Fellous has researched Neuron in several fields, including Biological system and Interneuron.

He most often published in these fields:

  • Neuroscience (56.39%)
  • Artificial intelligence (28.57%)
  • Inhibitory postsynaptic potential (22.56%)

What were the highlights of his more recent work (between 2015-2021)?

  • Artificial intelligence (28.57%)
  • Spatial memory (10.53%)
  • Neuroscience (56.39%)

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

Jean Marc Fellous mainly investigates Artificial intelligence, Spatial memory, Neuroscience, Hippocampus and Hippocampal formation. His study connects Pattern recognition and Artificial intelligence. His research on Spatial memory also deals with topics like

  • Reinforcement learning and related Latent learning and Hippocampal replay,
  • Computational model together with Complex system, Coding, Neuron, Ca1 pyramidal neuron and Spatial contextual awareness,
  • Robot and related Biological neural network, Computer vision and Virtual reality.

When carried out as part of a general Neuroscience research project, his work on Prefrontal cortex, Electrophysiology and Neuroplasticity is frequently linked to work in Population and Dementia, therefore connecting diverse disciplines of study. His Hippocampus study integrates concerns from other disciplines, such as Computational neuroscience, Context, Spatial cognition and Mnemonic. His Hippocampal formation course of study focuses on Dorsum and Representation.

Between 2015 and 2021, his most popular works were:

  • Hippocampal CA1 Ripples as Inhibitory Transients. (24 citations)
  • Explainable Artificial Intelligence for Neuroscience: Behavioral Neurostimulation (23 citations)
  • Explainable Artificial Intelligence for Neuroscience: Behavioral Neurostimulation (23 citations)

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

  • Artificial intelligence
  • Neuroscience
  • Neuron

Jean Marc Fellous focuses on Hippocampus, Neuroscience, Set, Context and Field. His Hippocampus research is multidisciplinary, incorporating perspectives in Hippocampal formation and Mnemonic. In his study, which falls under the umbrella issue of Hippocampal formation, Memory consolidation is strongly linked to Neural substrate.

His studies deal with areas such as Oxytocin, Nerve net and Inhibitory postsynaptic potential, Excitatory postsynaptic potential as well as Memory consolidation. Jean Marc Fellous interconnects Developmental psychology, Clinical psychology and Moderation in the investigation of issues within Context. Brain function, Artificial intelligence, Basic research, Neurostimulation and Intervention protocols are fields of study that intersect with his Field research.

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

Face recognition by elastic bunch graph matching

L. Wiskott;J.-M. Fellous;N. Kuiger;C. von der Malsburg.
IEEE Transactions on Pattern Analysis and Machine Intelligence (1997)

5136 Citations

Face recognition by elastic bunch graph matching

L. Wiskott;J.-M. Fellous;N. Kruger;C. von der Malsburg.
international conference on image processing (1997)

5073 Citations

Face recognition by elastic bunch graph matching

Laurenz Wiskott;Jean-Marc Fellous;Norbert Krüger;Christoph von der Malsburg.
Intelligent biometric techniques in fingerprint and face recognition (1999)

1830 Citations

Fluctuating synaptic conductances recreate in vivo-like activity in neocortical neurons.

Alain Destexhe;Michael Rudolph;J.-M. Fellous;Terrence J. Sejnowski;Terrence J. Sejnowski.
Neuroscience (2001)

660 Citations

A role for NMDA-receptor channels in working memory

John E. Lisman;Jean Marc Fellous;Xiao Jing Wang.
Nature Neuroscience (1998)

451 Citations

Regulation of spike timing in visual cortical circuits

Paul Tiesinga;Jean Marc Fellous;Terrence J. Sejnowski;Terrence J. Sejnowski.
Nature Reviews Neuroscience (2008)

395 Citations

A new correlation-based measure of spike timing reliability

Susanne Schreiber;Jean-Marc Fellous;D. Whitmer;Paul H. E. Tiesinga;Paul H. E. Tiesinga.
Neurocomputing (2003)

352 Citations

Cholinergic induction of oscillations in the hippocampal slice in the slow (0.5-2 Hz), theta (5-12 Hz), and gamma (35-70 Hz) bands.

Jean Marc Fellous;Terrence J. Sejnowski;Terrence J. Sejnowski.
Hippocampus (2000)

326 Citations

Emotions: from brain to robot

Michael A. Arbib;Jean Marc Fellous.
Trends in Cognitive Sciences (2004)

281 Citations

Synaptic background noise controls the input/output characteristics of single cells in an in vitro model of in vivo activity.

J. M. Fellous;Michael Rudolph;Alain Destexhe;Terrence J. Sejnowski;Terrence J. Sejnowski.
Neuroscience (2003)

268 Citations

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