Literature DB >> 17023651

Biologically based computational models of high-level cognition.

Randall C O'Reilly1.   

Abstract

Computer models based on the detailed biology of the brain can help us understand the myriad complexities of human cognition and intelligence. Here, we review models of the higher level aspects of human intelligence, which depend critically on the prefrontal cortex and associated subcortical areas. The picture emerging from a convergence of detailed mechanistic models and more abstract functional models represents a synthesis between analog and digital forms of computation. Specifically, the need for robust active maintenance and rapid updating of information in the prefrontal cortex appears to be satisfied by bistable activation states and dynamic gating mechanisms. These mechanisms are fundamental to digital computers and may be critical for the distinctive aspects of human intelligence.

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Year:  2006        PMID: 17023651     DOI: 10.1126/science.1127242

Source DB:  PubMed          Journal:  Science        ISSN: 0036-8075            Impact factor:   47.728


  111 in total

1.  The role of prefrontal dopamine D1 receptors in the neural mechanisms of associative learning.

Authors:  M Victoria Puig; Earl K Miller
Journal:  Neuron       Date:  2012-06-07       Impact factor: 17.173

2.  Motivated cognitive control: reward incentives modulate preparatory neural activity during task-switching.

Authors:  Adam C Savine; Todd S Braver
Journal:  J Neurosci       Date:  2010-08-04       Impact factor: 6.167

3.  Associatively mediated stopping: Training stimulus-specific inhibitory control.

Authors:  William A Bowditch; Frederick Verbruggen; Ian P L McLaren
Journal:  Learn Behav       Date:  2016-06       Impact factor: 1.986

4.  Working memory updating occurs independently of the need to maintain task-context: accounting for triggering updating in the AX-CPT paradigm.

Authors:  Yoav Kessler; Liad J Baruchin; Anat Bouhsira-Sabag
Journal:  Psychol Res       Date:  2015-10-20

5.  Examining Procedural Learning and Corticostriatal Pathways for Individual Differences in Language: Testing Endophenotypes of DRD2/ANKK1.

Authors:  Joanna C Lee; Kathryn L Mueller; J Bruce Tomblin
Journal:  Lang Cogn Neurosci       Date:  2015-10-07       Impact factor: 2.331

6.  Transient neuronal correlations underlying goal selection and maintenance in prefrontal cortex.

Authors:  Satoshi Tsujimoto; Aldo Genovesio; Steven P Wise
Journal:  Cereb Cortex       Date:  2008-03-20       Impact factor: 5.357

7.  Movement gating of beta/gamma oscillations involved in the N30 somatosensory evoked potential.

Authors:  Ana Maria Cebolla; Caty De Saedeleer; Ana Bengoetxea; Françoise Leurs; Costantino Balestra; Pablo d'Alcantara; Ernesto Palmero-Soler; Bernard Dan; Guy Cheron
Journal:  Hum Brain Mapp       Date:  2009-05       Impact factor: 5.038

8.  Characterizing switching and congruency effects in the Implicit Association Test as reactive and proactive cognitive control.

Authors:  Joseph Hilgard; Bruce D Bartholow; Cheryl L Dickter; Hart Blanton
Journal:  Soc Cogn Affect Neurosci       Date:  2014-05-07       Impact factor: 3.436

9.  Likelihood-free Bayesian analysis of memory models.

Authors:  Brandon M Turner; Simon Dennis; Trisha Van Zandt
Journal:  Psychol Rev       Date:  2013-04-15       Impact factor: 8.934

10.  A scalable neuristor built with Mott memristors.

Authors:  Matthew D Pickett; Gilberto Medeiros-Ribeiro; R Stanley Williams
Journal:  Nat Mater       Date:  2012-12-16       Impact factor: 43.841

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