H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Neuroscience H-index 46 Citations 15,187 114 World Ranking 2687 National Ranking 117

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Neuroscience
  • Statistics

Alessandro Treves focuses on Neuroscience, Hippocampus, Attractor network, Hippocampal formation and Artificial neural network. His Neuroscience study frequently draws connections to other fields, such as Grid. Alessandro Treves has researched Hippocampus in several fields, including Neurophysiology and Recall.

The concepts of his Attractor network study are interwoven with issues in Feed forward, Process and Constant. He works in the field of Hippocampal formation, namely Pattern completion. His work in the fields of Artificial neural network, such as Hebbian theory and Connectionism, overlaps with other areas such as Dynamics.

His most cited work include:

  • Computational analysis of the role of the hippocampus in memory. (929 citations)
  • Neural networks and brain function (719 citations)
  • Distinct Ensemble Codes in Hippocampal Areas CA3 and CA1 (579 citations)

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

Alessandro Treves spends much of his time researching Neuroscience, Artificial intelligence, Artificial neural network, Hippocampus and Topology. His study in Hippocampal formation, Neuron, Entorhinal cortex, Sensory system and Dentate gyrus are all subfields of Neuroscience. His Artificial intelligence research incorporates elements of Natural language processing, Information theory, Metric and Pattern recognition.

His study on Content-addressable memory is often connected to Function as part of broader study in Artificial neural network. Alessandro Treves has researched Hippocampus in several fields, including Neurophysiology, Cognitive science, Recall and Episodic memory. His Topology study incorporates themes from Grid, Representation, Associative network and Transfer function.

He most often published in these fields:

  • Neuroscience (50.00%)
  • Artificial intelligence (32.61%)
  • Artificial neural network (24.78%)

What were the highlights of his more recent work (between 2016-2021)?

  • Grid (18.26%)
  • Neuroscience (50.00%)
  • Topology (23.04%)

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

His primary scientific interests are in Grid, Neuroscience, Topology, Semantic memory and Grid cell. The concepts of his Grid study are interwoven with issues in Pure mathematics, Formant, Diphthong, Vowel and Symmetry. His study of Computational neuroscience is a part of Neuroscience.

His research integrates issues of Cortical network, Frustration and Hamiltonian in his study of Topology. His Semantic memory research includes elements of Tree structure, Tensor and Categorization. His Grid cell research incorporates elements of Distributed computing, Partition and Space perception.

Between 2016 and 2021, his most popular works were:

  • Integration of grid maps in merged environments (29 citations)
  • Integration of grid maps in merged environments (29 citations)
  • A Mind Free to Wander: Neural and Computational Constraints on Spontaneous Thought. (18 citations)

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

  • Artificial intelligence
  • Neuroscience
  • Statistics

His main research concerns Neuroscience, Grid, Topology, Semantic memory and Partition. Alessandro Treves undertakes interdisciplinary study in the fields of Neuroscience and Ventromedial prefrontal cortex through his works. His biological study spans a wide range of topics, including Frustration, Type, Orientation, Modular design and Entorhinal cortex.

His studies in Topology integrate themes in fields like Coherence and Aggregate. His research in Semantic memory intersects with topics in Tree, Cognitive psychology, Autoassociative memory and Superordinate goals. The study incorporates disciplines such as Geometry, Grid cell and Space perception in addition to Partition.

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.

Top Publications

Computational analysis of the role of the hippocampus in memory.

Alessandro Treves;Edmund T. Rolls.
Hippocampus (1994)

1221 Citations

Neural networks and brain function

Edmund T. Rolls;Alessandro Treves.
(1997)

1179 Citations

Computational constraints suggest the need for two distinct input systems to the hippocampal CA3 network.

Alessandro Treves;Edmund T. Rolls.
Hippocampus (1992)

777 Citations

Distinct Ensemble Codes in Hippocampal Areas CA3 and CA1

Stefan Leutgeb;Jill K. Leutgeb;Alessandro Treves;Alessandro Treves;May-Britt Moser.
Science (2004)

773 Citations

Hippocampal remapping and grid realignment in entorhinal cortex

Marianne Fyhn;Torkel Hafting;Alessandro Treves;Alessandro Treves;May-Britt Moser.
Nature (2007)

682 Citations

Morphing Marilyn into Maggie dissociates physical and identity face representations in the brain

Pia Rotshtein;Richard N A Henson;Alessandro Treves;Jon Driver.
Nature Neuroscience (2005)

587 Citations

Analytical estimates of limited sampling biases in different information measures.

Stefano Panzeri;Alessandro Treves.
Network: Computation In Neural Systems (1996)

451 Citations

The upward bias in measures of information derived from limited data samples

Alessandro Treves;Stefano Panzeri.
Neural Computation (1995)

387 Citations

What determines the capacity of autoassociative memories in the brain

Alessandro Treves;Edmund T Rolls.
Network: Computation In Neural Systems (1991)

379 Citations

Mean-field analysis of neuronal spike dynamics

Alessandro Treves.
Network: Computation In Neural Systems (1993)

359 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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