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Psychology

D-Index
69
Citations
26829
World Ranking
2333
National Ranking
1356

Overview

F. Gregory Ashby is affiliated with the University of California, Santa Barbara in the United States. Their research spans several interconnected fields including neuroscience, psychology, and computer science, with a particular focus on cognitive neuroscience and developmental and educational psychology.

Ashby's published work extensively covers themes such as child and animal learning development, memory and neural mechanisms, neural networks and applications, neural dynamics and brain function, reading and literacy development, neural and behavioral psychology studies, and Bayesian modeling and causal inference.

Significant recent papers authored or co-authored by Ashby include:

  • Just do it: A neuropsychological theory of agency, cognition, mood, and dopamine. (2024), published in Journal of Experimental Psychology General
  • State trace analysis: What it can and cannot do. (2022), published in Journal of Mathematical Psychology
  • A neurocomputational theory of how rule-guided behaviors become automatic. (2021), published in Psychological Review
  • When instructions don't help: Knowing the optimal strategy facilitates rule-based but not information-integration category learning. (2021), published in Journal of Experimental Psychology Human Perception & Performance
  • Linear separability, irrelevant variability, and categorization difficulty. (2021), published in Journal of Experimental Psychology Learning Memory and Cognition

Their frequent co-authors include Jeffrey B. Inglis, Paul Kovacs, Luke Rosedahl, Matthew J. Crossley, and Heidi A. Zetzer. Collaboration with these researchers has produced multiple publications across various psychological and neuroscientific topics.

Ashby's work has appeared repeatedly in the Journal of Mathematical Psychology, where they have published three articles, as well as contributions to Journal of Experimental Psychology General, Psychological Review, and Journal of Experimental Psychology Human Perception & Performance, among others.

The main fields of study represented in Ashby's body of work are:

  • Neuroscience
  • Psychology
  • Computer Science

Within these areas, subfields emphasized include:

  • Cognitive Neuroscience
  • Developmental and Educational Psychology
  • Artificial Intelligence
  • Social Psychology
  • Applied Psychology

Themes of Ashby's research reflect a focus on learning processes in both human and animal subjects, mechanisms underlying memory, the functioning and modeling of neural networks, and cognitive theories related to brain function and behavior.

Best Publications

  • A neuropsychological theory of positive affect and its influence on cognition.

    F. Gregory Ashby;Alice M. Isen;And U. Turken

  • The Stochastic Modeling of Elementary Psychological Processes

    James T. Townsend;F. Gregory Ashby

  • A neuropsychological theory of multiple systems in category learning.

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  • Human Category Learning

    F. Gregory Ashby;W. Todd Maddox

  • Varieties of perceptual independence.

    F. Gregory Ashby;James T. Townsend

  • Deconvolving BOLD activation in event-related designs for multivoxel pattern classification analyses.

    Jeanette A. Mumford;Benjamin O. Turner;F. Gregory Ashby;Russell A. Poldrack

  • Toward a Unified Theory of Similarity and Recognition

    F. Gregory Ashby;Nancy A. Perrin

  • Multidimensional models of perception and cognition.

    F. Gregory Ashby

  • Cortical and basal ganglia contributions to habit learning and automaticity

    F. Gregory Ashby;Benjamin O. Turner;Jon C. Horvitz

  • Methods of Modeling Capacity in Simple Processing Systems

    James T. Townsend;F. Gregory Ashby

  • Relations between prototype, exemplar, and decision bound models of categorization

    F. Gregory Ashby;W. Todd Maddox

  • Delayed feedback effects on rule-based and information-integration category learning.

    W. Todd Maddox;F. Gregory Ashby;Corey J. Bohil

  • Comparing decision bound and exemplar models of categorization

    W. Todd Maddox;F. Gregory Ashby

  • Human category learning 2.0

    F. Gregory Ashby;W. Todd Maddox

  • The effects of concurrent task interference on category learning: evidence for multiple category learning systems.

    Elliott M. Waldron;F. Gregory Ashby

  • The neurobiology of human category learning

    F.Gregory Ashby;Shawn W. Ell

  • Dissociating explicit and procedural-learning based systems of perceptual category learning

    W.Todd Maddox;F.Gregory Ashby

  • Category learning and multiple memory systems

    F. Gregory Ashby;Jeffrey B. O'Brien

  • Multidimensional models of categorization.

    F. Gregory Ashby

  • Measurement Scales and Statistics: The Misconception Misconceived

    James T. Townsend;F. Gregory Ashby

  • A neurobiological theory of automaticity in perceptual categorization.

    F. Gregory Ashby;John M. Ennis;Brian J. Spiering

Frequent Co-Authors

W. Todd Maddox
W. Todd Maddox The University of Texas at Austin
J. David Smith
J. David Smith Georgia State University
Michael J. Beran
Michael J. Beran Georgia State University
Robert G. Cook
Robert G. Cook Tufts University
J. Vincent Filoteo
J. Vincent Filoteo University of California, San Diego
Randolph C. Grace
Randolph C. Grace University of Canterbury
Alice M. Isen
Alice M. Isen Cornell University
Alan Pickering
Alan Pickering Goldsmiths University of London
William Prinzmetal
William Prinzmetal University of California, Berkeley
Peter D. Balsam
Peter D. Balsam Columbia University

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