Neural measures reveal individual differences in controlling access to working memory

[1]  Edward K Vogel,et al.  Fractionating Working Memory , 2005, Psychological science.

[2]  Yuhong V. Jiang,et al.  Visual short-term memory for two sequential arrays: One integrated representation or two separate representations? , 2004, Psychonomic bulletin & review.

[3]  Maro G. Machizawa,et al.  Neural activity predicts individual differences in visual working memory capacity , 2004, Nature.

[4]  C. Chabris,et al.  Neural mechanisms of general fluid intelligence , 2003, Nature Neuroscience.

[5]  R. Engle,et al.  Working-memory capacity and the control of attention: the contributions of goal neglect, response competition, and task set to Stroop interference. , 2003, Journal of experimental psychology. General.

[6]  M. D’Esposito,et al.  The Influence of Working-Memory Demand and Subject Performance on Prefrontal Cortical Activity , 2002, Journal of Cognitive Neuroscience.

[7]  J. Duncan,et al.  Filtering of neural signals by focused attention in the monkey prefrontal cortex , 2002, Nature Neuroscience.

[8]  E. Miller,et al.  An integrative theory of prefrontal cortex function. , 2001, Annual review of neuroscience.

[9]  G. Woodman,et al.  Storage of features, conjunctions and objects in visual working memory. , 2001, Journal of experimental psychology. Human perception and performance.

[10]  N. Cowan.  The magical number 4 in short-term memory: A reconsideration of mental storage capacity , 2001, Behavioral and Brain Sciences.

[11]  Newell,et al.  A neural basis for general intelligence , 2000, American journal of ophthalmology.

[12]  M. D’Esposito,et al.  Isolating the neural mechanisms of age-related changes in human working memory , 2000, Nature Neuroscience.

[13]  A. Miyake,et al.  Models of Working Memory: Mechanisms of Active Maintenance and Executive Control , 1999 .

[14]  R. Engle,et al.  Individual differences in working memory capacity and what they tell us about controlled attention, general fluid intelligence, and functions of the prefrontal cortex. , 1999 .

[15]  E. Vogel,et al.  Electrophysiological Evidence for a Postperceptual Locus of Suppression during the Attentional Blink Time-based Attention and the Attentional Blink , 1998 .

[16]  Earl K. Miller,et al.  Selective representation of relevant information by neurons in the primate prefrontal cortex , 1998, Nature.

[17]  Edward K. Vogel,et al.  The capacity of visual working memory for features and conjunctions , 1997, Nature.

[18]  R. Desimone,et al.  Neural Mechanisms of Visual Working Memory in Prefrontal Cortex of the Macaque , 1996, The Journal of Neuroscience.

[19]  G. Sperling,et al.  Is there feature-based attentional selection in visual search? , 1996, Journal of experimental psychology. Human perception and performance.

[20]  S. Hillyard,et al.  Selective attention to the color and direction of moving stimuli: Electrophysiological correlates of hierarchical feature selection , 1996, Perception & psychophysics.

[21]  R. Desimone,et al.  Neural mechanisms of selective visual attention. , 1995, Annual review of neuroscience.

[22]  H Pashler,et al.  Familiarity and visual change detection , 1988, Perception & psychophysics.

[23]  E. Donchin,et al.  Psychophysiology : systems, processes, and applications , 1987 .

[24]  C Bundesen,et al.  Measuring efficiency of selection from briefly exposed visual displays: a model for partial report. , 1984, Journal of experimental psychology. Human perception and performance.

[25]  George Sperling,et al.  The information available in brief visual presentations. , 1960 .