F Ashby

Summary

Affiliation: University of California
Country: USA

Publications

  1. ncbi Information-integration category learning and the human uncertainty response
    Erick J Paul
    Department of Psychology, University of California, Santa Barbara, CA, 93106, USA
    Mem Cognit 39:536-54. 2011
  2. ncbi Category learning and multiple memory systems
    F Gregory Ashby
    Department of Psychology, University of California Santa Barbara, Santa Barbara, CA 93106, USA
    Trends Cogn Sci 9:83-9. 2005
  3. ncbi Human category learning
    F Gregory Ashby
    Department of Psychology, University of California Santa Barbara, Santa Barbara, CA 93106, USA
    Annu Rev Psychol 56:149-78. 2005
  4. ncbi FROST: a distributed neurocomputational model of working memory maintenance
    F Gregory Ashby
    University of California, Santa Barbara, CA 93106, USA
    J Cogn Neurosci 17:1728-43. 2005
  5. ncbi A neurobiological theory of automaticity in perceptual categorization
    F Gregory Ashby
    Department of Psychology, University of California, Santa Barbara, CA 93106, USA
    Psychol Rev 114:632-56. 2007
  6. ncbi The effects of positive versus negative feedback on information-integration category learning
    F Gregory Ashby
    Department of Psychology, University of California, Santa Barbara, California 93106, USA
    Percept Psychophys 69:865-78. 2007
  7. ncbi The Prep statistic as a measure of confidence in model fitting
    F Gregory Ashby
    Department of Psychology, University of California, Santa Barbara, California 93106, USA
    Psychon Bull Rev 15:16-27. 2008
  8. ncbi Fitting computational models to fMRI
    F Gregory Ashby
    Department of Psychology, University of California, Santa Barbara, California 93106, USA
    Behav Res Methods 40:713-21. 2008
  9. ncbi Cortical and basal ganglia contributions to habit learning and automaticity
    F Gregory Ashby
    Department of Psychology, University of California, Santa Barbara, CA 93106, USA
    Trends Cogn Sci 14:208-15. 2010
  10. ncbi Interactions between declarative and procedural-learning categorization systems
    F Gregory Ashby
    University of California, Santa Barbara, CA 93106, USA
    Neurobiol Learn Mem 94:1-12. 2010

Research Grants

  1. The Cognitive Neuroscience of Human Category Learning
    F Ashby; Fiscal Year: 2004
  2. The Cognitive Neuroscience of Human Category Learning
    F Ashby; Fiscal Year: 2007
  3. The Cognitive Neuroscience of Human Category Learning
    F Ashby; Fiscal Year: 2009

Detail Information

Publications36

  1. ncbi Information-integration category learning and the human uncertainty response
    Erick J Paul
    Department of Psychology, University of California, Santa Barbara, CA, 93106, USA
    Mem Cognit 39:536-54. 2011
    ..These results are considered in the light of recent models of category learning and metacognition...
  2. ncbi Category learning and multiple memory systems
    F Gregory Ashby
    Department of Psychology, University of California Santa Barbara, Santa Barbara, CA 93106, USA
    Trends Cogn Sci 9:83-9. 2005
    ....
  3. ncbi Human category learning
    F Gregory Ashby
    Department of Psychology, University of California Santa Barbara, Santa Barbara, CA 93106, USA
    Annu Rev Psychol 56:149-78. 2005
    ..Collectively, results from these four tasks provide strong evidence that human category learning is mediated by multiple, qualitatively distinct systems...
  4. ncbi FROST: a distributed neurocomputational model of working memory maintenance
    F Gregory Ashby
    University of California, Santa Barbara, CA 93106, USA
    J Cogn Neurosci 17:1728-43. 2005
    ..FROST successfully accounts for a wide variety of WM data, including single-cell recording data and human behavioral data...
  5. ncbi A neurobiological theory of automaticity in perceptual categorization
    F Gregory Ashby
    Department of Psychology, University of California, Santa Barbara, CA 93106, USA
    Psychol Rev 114:632-56. 2007
    ..A variety of simulations are described, showing that the model accounts for some classic single-cell recording and behavioral results...
  6. ncbi The effects of positive versus negative feedback on information-integration category learning
    F Gregory Ashby
    Department of Psychology, University of California, Santa Barbara, California 93106, USA
    Percept Psychophys 69:865-78. 2007
    ..It thus appears that, unlike rule-based learning, consistent information-integration learning requires full feedback. The theoretical implications of these findings for current models of information-integration learning are discussed...
  7. ncbi The Prep statistic as a measure of confidence in model fitting
    F Gregory Ashby
    Department of Psychology, University of California, Santa Barbara, California 93106, USA
    Psychon Bull Rev 15:16-27. 2008
    ..e., Prep) is derived for any two nested models. Simulations and empirical applications of this new statistic confirm its utility in studies in which data are collected from a few participants over many trials...
  8. ncbi Fitting computational models to fMRI
    F Gregory Ashby
    Department of Psychology, University of California, Santa Barbara, California 93106, USA
    Behav Res Methods 40:713-21. 2008
    ..In the present article, methods are described for solving each of these problems...
  9. ncbi Cortical and basal ganglia contributions to habit learning and automaticity
    F Gregory Ashby
    Department of Psychology, University of California, Santa Barbara, CA 93106, USA
    Trends Cogn Sci 14:208-15. 2010
    ..At the same time, other recent reports indicate that automatic behaviors are striatum- and dopamine-independent, and might be mediated entirely within cortex. Resolving this apparent conflict should be a major goal of future research...
  10. ncbi Interactions between declarative and procedural-learning categorization systems
    F Gregory Ashby
    University of California, Santa Barbara, CA 93106, USA
    Neurobiol Learn Mem 94:1-12. 2010
    ..Instead, these results support the hypothesis that declarative and procedural memory systems interact during category learning...
  11. ncbi A computational model of how cholinergic interneurons protect striatal-dependent learning
    F Gregory Ashby
    Department of Psychology, University of California, Santa Barbara, CA 93106, USA
    J Cogn Neurosci 23:1549-66. 2011
    ..A computational version of this theory accounts for a variety of single-cell recording data and some classic behavioral phenomena, including fast reacquisition after extinction...
  12. ncbi Human category learning 2.0
    F Gregory Ashby
    Department of Psychology, University of California Santa Barbara, CA 93106, USA
    Ann N Y Acad Sci 1224:147-61. 2011
    ..covered include (1) How do the various systems interact? (2) Are there different neural systems for categorization and category representation? (3) How does automaticity develop in each system? and (4) Exactly how does each system learn?..
  13. ncbi The neurobiology of category learning
    F Gregory Ashby
    Department of Psychology, University of California, Santa Barbara, CA 93106, USA
    Behav Cogn Neurosci Rev 3:101-13. 2004
    ....
  14. ncbi A neuropsychological theory of multiple systems in category learning
    F G Ashby
    Department of Psychology, University of California, Santa Barbara 93106, USA
    Psychol Rev 105:442-81. 1998
    ..One describes trial-by-trial learning, and the other describes global dynamics. The theory is tested on published neuropsychological data and on category learning data with normal adults...
  15. ncbi Suboptimality in human categorization and identification
    F G Ashby
    Department of Psychology, University of California at Santa Barbara, 93106, USA
    J Exp Psychol Gen 130:77-96. 2001
    ..The model assigns a key role to the striatum and assumes the observed suboptimality was largely due to massive convergence of visual cortical cells onto single striatal units...
  16. ncbi On the nature of implicit categorization
    F G Ashby
    Department of Psychology, University of California, Santa Barbara, CA 93106, USA
    Psychon Bull Rev 6:363-78. 1999
    ..On the basis of these results, a new category-learning model is proposed that makes no a priori assumptions about category structure and that relies on procedural learning and memory...
  17. ncbi Observational versus feedback training in rule-based and information-integration category learning
    F Gregory Ashby
    Department of Psychology, University of California, Santa Barbara, 93106, USA
    Mem Cognit 30:666-77. 2002
    ..The implications of these results for current theories of category learning are discussed...
  18. ncbi Category learning deficits in Parkinson's disease
    F Gregory Ashby
    Department of Psychology, University of California, Santa Barbara, 93106, USA
    Neuropsychology 17:115-24. 2003
    ..These results support the hypothesis that learning in these 2 tasks is mediated by functionally separate systems...
  19. ncbi On the dominance of unidimensional rules in unsupervised categorization
    F G Ashby
    Department of Psychology, University of California, Santa Barbara 93106, USA
    Percept Psychophys 61:1178-99. 1999
    ..These results contrast with those for supervised category learning; they support the hypothesis that in the absence of feedback, people are constrained to use unidimensional rules...
  20. ncbi A model of dopamine modulated cortical activation
    F Gregory Ashby
    Department of Psychology, University of California at Santa Barbara, Santa Barbara, CA 93106, USA
    Neural Netw 16:973-84. 2003
    ..As a preliminary test of the model, we show that it can account for some single-cell recording data that examined the effects of DA on the firing rate of glutamatergic cortical cells...
  21. ncbi Procedural learning in perceptual categorization
    F Gregory Ashby
    Department of Psychology, University of California, Santa Barbara, California 93106, USA
    Mem Cognit 31:1114-25. 2003
    ..The association to response positions also supports the hypothesis of a procedural-learning-based component to information integration categorization...
  22. ncbi A neuropsychological theory of positive affect and its influence on cognition
    F G Ashby
    Department of Psychology, University of California, Santa Barbara 93106, USA
    Psychol Rev 106:529-50. 1999
    ..For example, the theory assumes that creative problem solving is improved, in part, because increased dopamine release in the anterior cingulate improves cognitive flexibility and facilitates the selection of cognitive perspective...
  23. ncbi Response processes in information-integration category learning
    Brian J Spiering
    Department of Psychology, University of California, 551 University Road, Santa Barbara, CA 93106, USA
    Neurobiol Learn Mem 90:330-8. 2008
    ..In these experiments, a consistent association between a category and a response feature was sufficient. The implication of these results for the neurobiology of information-integration category learning is discussed...
  24. ncbi Category label and response location shifts in category learning
    W Todd Maddox
    Department of Psychology, Institute for Neuroscience, University of Texas, Austin, TX 78712, USA
    Psychol Res 74:219-36. 2010
    ..Implications for the neurobiological basis of these two learned associations are discussed...
  25. ncbi Implicit and explicit category learning by macaques (Macaca mulatta) and humans (Homo sapiens)
    J David Smith
    Department of Psychology, University at Buffalo, State University of New York, Buffalo, NY 14260, USA
    J Exp Psychol Anim Behav Process 36:54-65. 2010
    ..These results demonstrate an empirical continuity between human and nonhuman primate cognition, suggesting that nonhuman primates may have some structural components of humans' capacity for explicit cognition...
  26. ncbi Automaticity in rule-based and information-integration categorization
    Sebastien Helie
    Department of Psychology, University of California, Santa Barbara, California 93106 9660, USA
    Atten Percept Psychophys 72:1013-31. 2010
    ..These novel results are consistent with a theory assuming separate processing pathways for initial rule-based and information-integration category learning but a common processing pathway after the development of automaticity...
  27. ncbi Evidence for cortical automaticity in rule-based categorization
    Sebastien Helie
    Department of Psychology, University of California, Santa Barbara, Santa Barbara, California 93106 9660, USA
    J Neurosci 30:14225-34. 2010
    ..With extensive practice, the cortical system progressively becomes more caudal and dorsal, and is eventually centered around the premotor cortex...
  28. ncbi Disrupting feedback processing interferes with rule-based but not information-integration category learning
    W Todd Maddox
    University of Texas, Department of Psychology, Austin, Texas 78712, USA
    Mem Cognit 32:582-91. 2004
    ..No differences were observed in the information integration task. These results provide support for a multiple-systems approach to category learning and argue against the validity of single-system approaches...
  29. ncbi A role for the perceptual representation memory system in category learning
    Michael B Casale
    University of California, Santa Barbara, California 93106, USA
    Percept Psychophys 70:983-99. 2008
    ..These results support the hypothesis that (A, not A) performance was mediated by the PRS, but that (A, B) performance recruited other memory systems...
  30. ncbi The effects of category overlap on information-integration and rule-based category learning
    Shawn W Ell
    Cognition and Action Lab, Helen Wills Neuroscience Institute and Psychology Department, University of California, 3210 Tolman Hall 1650, Berkeley, CA 94720 1650, USA
    Percept Psychophys 68:1013-26. 2006
    ....
  31. ncbi Dissociating explicit and procedural-learning based systems of perceptual category learning
    W Todd Maddox
    Department of Psychology, 1 University Station A8000, University of Texas, Austin, TX 78712, USA
    Behav Processes 66:309-32. 2004
    ..We review nine studies that test six a priori predictions from COVIS, each of which is supported by the data...
  32. ncbi Multiple attention systems in perceptual categorization
    W Todd Maddox
    Department of Psychology, University of Texas, Austin 78712, USA
    Mem Cognit 30:325-39. 2002
    ..These theoretical analyses support the functional independence hypothesis and suggest that formal theories of categorization should model the effects of perceptual and decisional attention separately...
  33. ncbi Delayed feedback effects on rule-based and information-integration category learning
    W Todd Maddox
    Department of Psychology, University of Texas at Austin 78712, USA
    J Exp Psychol Learn Mem Cogn 29:650-62. 2003
    ..These results provide support for a multiple-systems approach to category learning and argue against the validity of single-system approaches...
  34. ncbi Initial training with difficult items facilitates information integration, but not rule-based category learning
    Brian J Spiering
    University of California, Santa Barbara, CA 93106, USA
    Psychol Sci 19:1169-77. 2008
    ..However, when the categorization rule was difficult to describe verbally (an information-integration task), participants who began with the most difficult items performed much better than participants in the other two conditions...
  35. ncbi Dynamical trajectories in category learning
    Shawn W Ell
    Psychology Department, University of California, Berkeley, California 94720 1650, USA
    Percept Psychophys 66:1318-40. 2004
    ..2) The magnitude of changes in decision strategy decreased with experience at a rate that was faster than that predicted by gradient descent. (3) Learning curves suffered from substantial identifiability problems...
  36. ncbi What makes a categorization task difficult?
    Leola A Alfonso-Reese
    Department of Psychology, San Diego State University, California 92182 4611, USA
    Percept Psychophys 64:570-83. 2002
    ..The remaining three factors do not explain performance results. We present a challenge to categorization theorists to design models that account for human performance as predicted by covariance complexity...

Research Grants8

  1. The Cognitive Neuroscience of Human Category Learning
    F Ashby; Fiscal Year: 2004
    ..abstract_text> ..
  2. The Cognitive Neuroscience of Human Category Learning
    F Ashby; Fiscal Year: 2007
    ..g., teaching radiologists to find tumors in x-rays). ..
  3. The Cognitive Neuroscience of Human Category Learning
    F Ashby; Fiscal Year: 2009
    ..g., teaching radiologists to find tumors in x-rays). ..