World's Best Scientists 2026 revealed!

D-Index & Metrics

Neuroscience

D-Index
53
Citations
11141
World Ranking
5074
National Ranking
421

Psychology

D-Index
51
Citations
10870
World Ranking
5206
National Ranking
547

Overview

Bradley C. Love is affiliated with University College London in the United Kingdom. Their research spans multiple fields, with significant contributions to neuroscience and computer science.

Their recent papers cover a range of topics and include:

  • Ventromedial prefrontal cortex compression during concept learning, 2020, published in Nature Communications
  • Large language models surpass human experts in predicting neuroscience results, 2024, published in Nature Human Behaviour
  • Reassessing hierarchical correspondences between brain and deep networks through direct interface, 2022, published in Science Advances
  • Levels of biological plausibility, 2020, published in Philosophical Transactions of the Royal Society B Biological Sciences
  • A neural network account of memory replay and knowledge consolidation, 2022, published in Cerebral Cortex

Frequent coauthors in their work include:

  • Xiaoliang Luo
  • Brett D. Roads
  • Robert M. Mok
  • Kaustubh R. Patil
  • Felipe Yáñez

The venues where they most commonly publish comprise:

  • arXiv (Cornell University)
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Science Advances
  • Trends in Cognitive Sciences
  • Cognition

Bradley C. Love's main fields of study are:

  • Neuroscience
  • Computer Science

Within these areas, the focus is further refined into subfields such as:

  • Cognitive Neuroscience
  • Artificial Intelligence
  • Developmental and Educational Psychology
  • Computer Vision and Pattern Recognition
  • Experimental and Cognitive Psychology

The main research topics addressed by their publications include:

  • Neural dynamics and brain function
  • Memory and Neural Mechanisms
  • Child and Animal Learning Development
  • Neural and Behavioral Psychology Studies
  • Face Recognition and Perception
  • Functional Brain Connectivity Studies
  • Explainable Artificial Intelligence (XAI)

Best Publications

  • Variability in the analysis of a single neuroimaging dataset by many teams

    Rotem Botvinik-Nezer;Rotem Botvinik-Nezer;Felix Holzmeister;Colin F. Camerer;Anna Dreber;Anna Dreber

  • SUSTAIN: A Network Model of Category Learning.

    Bradley C. Love;Douglas L. Medin;Todd M. Gureckis

  • Bayesian Fundamentalism or Enlightenment? On the explanatory status and theoretical contributions of Bayesian models of cognition.

    Matt Jones;Bradley C. Love

  • Feature Centrality and Conceptual Coherence

    Steven A. Sloman;Bradley C. Love;Woo Kyoung Ahn

  • Comparing supervised and unsupervised category learning.

    Bradley C. Love

  • Real-Time Strategy Game Training: Emergence of a Cognitive Flexibility Trait

    Brian D. Glass;W. Todd Maddox;Bradley C. Love

  • Approaches to Analysis in Model-based Cognitive Neuroscience

    Brandon M. Turner;Birte U. Forstmann;Bradley C. Love;Thomas J. Palmeri

  • Relations versus Properties in Conceptual Combination

    Edward J. Wisniewski;Bradley C. Love

  • Decoding the Brain’s Algorithm for Categorization from Its Neural Implementation

    Michael L. Mack;Alison R. Preston;Bradley C. Love

  • Dynamic updating of hippocampal object representations reflects new conceptual knowledge.

    Michael L. Mack;Bradley C. Love;Bradley C. Love;Alison R. Preston

  • Learning the Exception to the Rule: Model-Based fMRI Reveals Specialized Representations for Surprising Category Members

    Tyler Davis;Bradley C. Love;Alison R. Preston

  • Sharing or Piracy? An Exploration of Downloading Behavior

    Robert LaRose;Ying Ju Lai;Ryan Lange;Bradford Rodney Love

  • Building concepts one episode at a time: The hippocampus and concept formation.

    Michael L. Mack;Bradley C. Love;Bradley C. Love;Alison R. Preston

  • Schematic influences on category learning and recognition memory.

    Yasuaki Sakamoto;Bradley C. Love

  • Ventromedial prefrontal cortex compression during concept learning

    Michael L. Mack;Alison R. Preston;Bradley C. Love;Bradley C. Love

  • Learning nonlinearly separable categories by inference and classification

    Takashi Yamauchi;Bradley C Love;Arthur B Markman

  • When more is less: Feedback effects in perceptual category learning

    W. Todd Maddox;Bradley C. Love;Brian D. Glass;J. Vincent Filoteo

  • Exploring Psychosocial Support Online: A Content Analysis of Messages in an Adolescent and Young Adult Cancer Community

    Bradley C. Love;Brittani Crook;Charee M. Thompson;Sarah Zaitchik

  • Beyond common features: The role of roles in determining similarity

    Matt Jones;Bradley C. Love

  • SUSTAIN: a model of human category learning

    Bradley C. Love;Douglas L. Medin

  • Categorization Inside and Outside the Laboratory: Essays in Honor of Douglas L. Medin

    Woo-kyoung Ahn;Robert L. Goldstone;Bradley C. Love;Arthur B. Markman

Frequent Co-Authors

W. Todd Maddox
W. Todd Maddox The University of Texas at Austin
Arthur B. Markman
Arthur B. Markman The University of Texas at Austin
Alison R. Preston
Alison R. Preston The University of Texas at Austin
Jean M. Vettel
Jean M. Vettel United States Army Research Laboratory
Bharat B. Biswal
Bharat B. Biswal New Jersey Institute of Technology
Jean-Baptiste Poline
Jean-Baptiste Poline Montreal Neurological Institute and Hospital
Russell A. Poldrack
Russell A. Poldrack Stanford University
Olivier Collignon
Olivier Collignon Université Catholique de Louvain
Douglas L. Medin
Douglas L. Medin Northwestern University
Felix Hoffstaedter
Felix Hoffstaedter Forschungszentrum Jülich

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