Neural Mechanisms of Interference Control in Working Memory: Effects of Interference Expectancy and Fluid Intelligence

Background A critical aspect of executive control is the ability to limit the adverse effects of interference. Previous studies have shown activation of left ventrolateral prefrontal cortex after the onset of interference, suggesting that interference may be resolved in a reactive manner. However, we suggest that interference control may also operate in a proactive manner to prevent effects of interference. The current study investigated the temporal dynamics of interference control by varying two factors – interference expectancy and fluid intelligence (gF) – that could influence whether interference control operates proactively versus reactively. Methodology/Principal Findings A modified version of the recent negatives task was utilized. Interference expectancy was manipulated across task blocks by changing the proportion of recent negative (interference) trials versus recent positive (facilitation) trials. Furthermore, we explored whether gF affected the tendency to utilize specific interference control mechanisms. When interference expectancy was low, activity in lateral prefrontal cortex replicated prior results showing a reactive control pattern (i.e., interference-sensitivity during probe period). In contrast, when interference expectancy was high, bilateral prefrontal cortex activation was more indicative of proactive control mechanisms (interference-related effects prior to the probe period). Additional results suggested that the proactive control pattern was more evident in high gF individuals, whereas the reactive control pattern was more evident in low gF individuals. Conclusions/Significance The results suggest the presence of two neural mechanisms of interference control, with the differential expression of these mechanisms modulated by both experimental (e.g., expectancy effects) and individual difference (e.g., gF) factors.

[1]  Hannah S. Locke,et al.  Flexible neural mechanisms of cognitive control within human prefrontal cortex , 2009, Proceedings of the National Academy of Sciences.

[2]  A. Diamond All or none hypothesis: a global-default mode that characterizes the brain and mind. , 2009, Developmental psychology.

[3]  E. Aarts,et al.  Anticipatory activity in anterior cingulate cortex can be independent of conflict and error likelihood. , 2008, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[4]  Andrew R. A. Conway,et al.  Variation in working memory , 2008 .

[5]  David Badre,et al.  Left ventrolateral prefrontal cortex and the cognitive control of memory , 2007, Neuropsychologia.

[6]  Marc G. Berman,et al.  Neural mechanisms of proactive interference-resolution , 2007, NeuroImage.

[7]  Mark V. Albert,et al.  Anticipation of conflict monitoring in the anterior cingulate cortex and the prefrontal cortex , 2007, Proceedings of the National Academy of Sciences.

[8]  C. Lustig,et al.  Inhibitory Mechanisms and the Control of Attention , 2007 .

[9]  T. Braver,et al.  Explaining the many varieties of working memory variation: Dual mechanisms of cognitive control. , 2007 .

[10]  R. O’Reilly Biologically Based Computational Models of High-Level Cognition , 2006, Science.

[11]  Sharon L. Thompson-Schill,et al.  Resolving conflict: A response to Martin and Cheng (2006) , 2006, Psychonomic bulletin & review.

[12]  Todd S. Braver,et al.  A model of dual control mechanisms through anterior cingulate and prefrontal cortex interactions , 2006, Neurocomputing.

[13]  J. Jonides,et al.  Brain mechanisms of proactive interference in working memory , 2006, Neuroscience.

[14]  Michael F. Bunting,et al.  Proactive interference and item similarity in working memory. , 2006, Journal of experimental psychology. Learning, memory, and cognition.

[15]  David Badre,et al.  Frontal lobe mechanisms that resolve proactive interference. , 2005, Cerebral cortex.

[16]  Kathryn M. McMillan,et al.  N‐back working memory paradigm: A meta‐analysis of normative functional neuroimaging studies , 2005, Human brain mapping.

[17]  Randi C. Martin,et al.  Dissociations among tasks involving inhibition: A single-case study , 2005, Cognitive, affective & behavioral neuroscience.

[18]  Irene P. Kan,et al.  Effect of name agreement on prefrontal activity during overt and covert picture naming , 2004, Cognitive, affective & behavioral neuroscience.

[19]  T C Gunter,et al.  Dissociable brain mechanisms for inhibitory control: effects of interference content and working memory capacity. , 2003, Brain research. Cognitive brain research.

[20]  L. Jacoby,et al.  Strategy-dependent changes in memory: Effects on behavior and brain activity , 2003, Cognitive, affective & behavioral neuroscience.

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

[22]  R. Engle,et al.  The role of prefrontal cortex in working-memory capacity, executive attention, and general fluid intelligence: An individual-differences perspective , 2002, Psychonomic bulletin & review.

[23]  Robert T. Knight,et al.  Effects of frontal lobe damage on interference effects in working memory , 2002, Cognitive, affective & behavioral neuroscience.

[24]  J. Desmond,et al.  Prefrontal regions involved in keeping information in and out of mind. , 2001, Brain : a journal of neurology.

[25]  M. Botvinick,et al.  Conflict monitoring and cognitive control. , 2001, Psychological review.

[26]  Paul Whitney,et al.  Measuring Central Executive Functioning: What's in a Reading Span? , 2001, Brain and Cognition.

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

[28]  Randall W Engle,et al.  Working memory, short-term memory, and general fluid intelligence: a latent-variable approach. , 1999, Journal of experimental psychology. General.

[29]  E E Smith,et al.  The neural substrate and temporal dynamics of interference effects in working memory as revealed by event-related functional MRI. , 1999, Proceedings of the National Academy of Sciences of the United States of America.

[30]  Karl J. Friston,et al.  Analysis of fMRI Time-Series Revisited , 1995, NeuroImage.

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

[32]  Matthew Flatt,et al.  PsyScope: An interactive graphic system for designing and controlling experiments in the psychology laboratory using Macintosh computers , 1993 .

[33]  James L. McClelland,et al.  On the control of automatic processes: a parallel distributed processing account of the Stroop effect. , 1990, Psychological review.

[34]  Lynn Hasher,et al.  Working Memory, Comprehension, and Aging: A Review and a New View , 1988 .

[35]  J. Raven,et al.  Manual for Raven's progressive matrices and vocabulary scales , 1962 .