Oscillatory Mechanisms of Response Conflict Elicited by Color and Motion Direction: An Individual Differences Approach

Goal-directed behavior requires control over automatic behavior, for example, when goal-irrelevant information from the environment captures an inappropriate response and conflicts with the correct, goal-relevant action. Neural oscillations in the theta band (∼6 Hz) measured at midfrontal electrodes are thought to form an important substrate of the detection and subsequent resolution of response conflict. Here, we examined the extent to which response conflict and associated theta-band activity depend on the visual stimulus feature dimension that triggers the conflict. We used a feature-based Simon task to manipulate conflict by motion direction and stimulus color. Analyses were focused on individual differences in behavioral response conflict elicited across different stimulus dimensions and their relationship to conflict-related midfrontal theta. We first confirmed the presence of response conflict elicited by task-irrelevant motion and stimulus color, demonstrating the usefulness of our modified version of the Simon task to assess different sensory origins of response conflict. Despite titrating overall task performance, we observed large individual differences in the behavioral manifestations of response conflict elicited by the different visual dimensions. These behavioral conflict effects were mirrored in a dimension-specific relationship with conflict-related midfrontal theta power, such that, for each dimension, individual midfrontal theta power was generally higher when experienced response conflict was high. Finally, exploratory analyses of interregional functional connectivity suggested a role for phase synchronization between frontal and parietal scalp sites in modulating experienced conflict when color was the task-relevant visual dimension. Highlighting the importance of an individual differences approach in cognitive neuroscience, these results reveal large individual differences in experienced response conflict depending on the source of visual interference, which are predicted by conflict-related midfrontal theta power.

[1]  Michael X. Cohen,et al.  Subcortical, modality-specific pathways contribute to multisensory processing in humans , 2013 .

[2]  R. Proctor,et al.  The influence of irrelevant location information on performance: A review of the Simon and spatial Stroop effects , 1995, Psychonomic bulletin & review.

[3]  K. R. Ridderinkhof,et al.  “Don׳t” versus “Won׳t”: Principles, mechanisms, and intention in action inhibition , 2014, Neuropsychologia.

[4]  Arnaud Delorme,et al.  EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis , 2004, Journal of Neuroscience Methods.

[5]  K. R. Ridderinkhof,et al.  Version unknown SOURCE ( OR PART OF THE FOLLOWING SOURCE ) : Type article Title To head or to heed ? Beyond the surface of selective action inhibition : a review , 2022 .

[6]  J. Palva,et al.  Functional Roles of Alpha-Band Phase Synchronization in Local and Large-Scale Cortical Networks , 2011, Front. Psychology.

[7]  M. Frank,et al.  Frontal theta as a mechanism for cognitive control , 2014, Trends in Cognitive Sciences.

[8]  Johannes J. Fahrenfort,et al.  Pre-SMA Gray-matter Density Predicts Individual Differences in Action Selection in the Face of Conscious and Unconscious Response Conflict , 2011, Journal of Cognitive Neuroscience.

[9]  Edward E. Smith,et al.  Attention Enhances the Neural Processing of Relevant Features and Suppresses the Processing of Irrelevant Features in Humans: A Functional Magnetic Resonance Imaging Study of the Stroop Task , 2008, The Journal of Neuroscience.

[10]  Michael X. Cohen,et al.  Subthreshold muscle twitches dissociate oscillatory neural signatures of conflicts from errors , 2014, NeuroImage.

[11]  Tobias Egner,et al.  Right Ventrolateral Prefrontal Cortex Mediates Individual Differences in Conflict-driven Cognitive Control , 2011, Journal of Cognitive Neuroscience.

[12]  Adam Gazzaley,et al.  Top-down modulation of visual feature processing: The role of the inferior frontal junction , 2010, NeuroImage.

[13]  W. Klimesch,et al.  The Electrophysiological Dynamics of Interference during the Stroop Task , 2008, Journal of Cognitive Neuroscience.

[14]  S. Pollmann,et al.  Adaptation to recent conflict in the classical color-word Stroop-task mainly involves facilitation of processing of task-relevant information , 2015, Front. Hum. Neurosci..

[15]  Katharina N. Seidl-Rathkopf,et al.  Functions of the human frontoparietal attention network: Evidence from neuroimaging , 2015, Current Opinion in Behavioral Sciences.

[16]  J. R. Simon,et al.  CHOICE REACTION TIME AS A FUNCTION OF ANGULAR STIMULUS-RESPONSE CORRESPONDENCE AND AGE , 1963 .

[17]  T. Egner,et al.  Cognitive control mechanisms resolve conflict through cortical amplification of task-relevant information , 2005, Nature Neuroscience.

[18]  G. Caplovitz,et al.  Color synesthesia improves color but impairs motion perception , 2014, Trends in Cognitive Sciences.

[19]  K. Richard Ridderinkhof,et al.  When global information and local information collide: a brain potential analysis of the locus of interference effects , 1995, Biological Psychology.

[20]  M. Corbetta,et al.  Control of goal-directed and stimulus-driven attention in the brain , 2002, Nature Reviews Neuroscience.

[21]  Manfred Herrmann,et al.  Comparison of two Simon tasks: Neuronal correlates of conflict resolution based on coherent motion perception , 2006, NeuroImage.

[22]  E. Vogel,et al.  CURRENT DIRECTIONS IN PSYCHOLOGICAL SCIENCE How to Exploit Diversity for Scientific Gain Using Individual Differences to Constrain Cognitive Theory , 2022 .

[23]  Bernhard Hommel,et al.  Codes and their vicissitudes , 2001 .

[24]  B. Hommel.  The Simon effect as tool and heuristic. , 2011, Acta psychologica.

[25]  Michael X Cohen,et al.  Analyzing Neural Time Series Data: Theory and Practice , 2014 .

[26]  P. Nunez,et al.  Comparison of the effect of volume conduction on EEG coherence with the effect of field spread on MEG coherence , 2007, Statistics in medicine.

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

[28]  V. Walsh,et al.  Synesthesia for Color Is Linked to Improved Color Perception but Reduced Motion Perception , 2013, Psychological science.

[29]  K. R. Ridderinkhof,et al.  EEG Source Reconstruction Reveals Frontal-Parietal Dynamics of Spatial Conflict Processing , 2013, PloS one.

[30]  K. Amunts,et al.  Individual variability is not noise , 2013, Trends in Cognitive Sciences.

[31]  Cameron S Carter,et al.  Stimulus and response conflict processing during perceptual decision making , 2009, Cognitive, affective & behavioral neuroscience.

[32]  K. R. Ridderinkhof,et al.  Function and Structure of the Right Inferior Frontal Cortex Predict Individual Differences in Response Inhibition: A Model-Based Approach , 2008, The Journal of Neuroscience.

[33]  John-Stuart Brittain,et al.  Distinct mechanisms mediate speed-accuracy adjustments in cortico-subthalamic networks , 2017, eLife.

[34]  John J. B. Allen,et al.  Prelude to and Resolution of an Error: EEG Phase Synchrony Reveals Cognitive Control Dynamics during Action Monitoring , 2009, The Journal of Neuroscience.

[35]  K. R. Ridderinkhof,et al.  UvA-DARE ( Digital Academic Repository ) ( No ) time for control : frontal theta dynamics reveal the cost of temporally guided conflict anticipation , 2015 .

[36]  C. Eriksen,et al.  Effects of noise letters upon the identification of a target letter in a nonsearch task , 1974 .

[37]  Bernhard Pastötter,et al.  Dynamic Adjustments of Cognitive Control: Oscillatory Correlates of the Conflict Adaptation Effect , 2013, Journal of Cognitive Neuroscience.

[38]  Sean T. Stevens,et al.  Comparing the time course and efficacy of spatial and feature-based attention , 2007, Vision Research.

[39]  Michael X. Cohen,et al.  Dynamic Interactions between Large-Scale Brain Networks Predict Behavioral Adaptation after Perceptual Errors , 2012, Cerebral cortex.

[40]  Peter Brown,et al.  Midline Frontal Cortex Low-Frequency Activity Drives Subthalamic Nucleus Oscillations during Conflict , 2014, The Journal of Neuroscience.

[41]  Michael X. Cohen,et al.  Theta Dynamics Reveal Domain-specific Control over Stimulus and Response Conflict , 2012, Journal of Cognitive Neuroscience.

[42]  B. Forstmann,et al.  Frontosubthalamic Circuits for Control of Action and Cognition , 2016, The Journal of Neuroscience.

[43]  John J. Foxe,et al.  Anticipatory Attentional Suppression of Visual Features Indexed by Oscillatory Alpha-Band Power Increases:A High-Density Electrical Mapping Study , 2010, The Journal of Neuroscience.

[44]  K. R. Ridderinkhof,et al.  Aging affects medial but not anterior frontal learning-related theta oscillations , 2014, Neurobiology of Aging.

[45]  Michael X. Cohen,et al.  A neural microcircuit for cognitive conflict detection and signaling , 2014, Trends in Neurosciences.

[46]  Michael X. Cohen,et al.  Reply to “Higher response time increases theta energy, conflict increases response time” , 2013, Clinical Neurophysiology.

[47]  Pratik Mukherjee,et al.  Neuroanatomy Original Research Article , 2022 .

[48]  T. Jung,et al.  Two Independent Frontal Midline Theta Oscillations during Conflict Detection and Adaptation in a Simon-Type Manual Reaching Task , 2017, The Journal of Neuroscience.

[49]  Borís Burle,et al.  Dynamics of facilitation and interference in cue-priming and Simon tasks , 2005 .

[50]  P. Nunez,et al.  EEG and MEG coherence: Measures of functional connectivity at distinct spatial scales of neocortical dynamics , 2007, Journal of Neuroscience Methods.

[51]  Manfred Herrmann,et al.  Two Simon tasks with different sources of conflict: An ERP study of motion- and location-based compatibility effects , 2008, Biological Psychology.

[52]  C. Tenke,et al.  Principal components analysis of Laplacian waveforms as a generic method for identifying ERP generator patterns: II. Adequacy of low-density estimates , 2006, Clinical Neurophysiology.

[53]  R. Nigbur,et al.  Theta power as a marker for cognitive interference , 2011, Clinical Neurophysiology.

[54]  Michael X. Cohen,et al.  Midfrontal conflict-related theta-band power reflects neural oscillations that predict behavior. , 2013, Journal of neurophysiology.

[55]  Wolfgang Prinz,et al.  A Simon effect with stationary moving stimuli. , 2004, Journal of experimental psychology. Human perception and performance.

[56]  Robert Oostenveld,et al.  Population activity in the human dorsal pathway predicts the accuracy of visual motion detection. , 2007, Journal of neurophysiology.

[57]  Simon Hanslmayr,et al.  Neural Communication Patterns Underlying Conflict Detection, Resolution, and Adaptation , 2014, The Journal of Neuroscience.

[58]  S. Hillyard,et al.  Spatio-temporal analysis of feature-based attention. , 2007, Cerebral cortex.

[59]  B. Hommel.  Action control according to TEC (theory of event coding) , 2009, Psychological research.

[60]  Jonathan D. Cohen,et al.  Conflict monitoring and anterior cingulate cortex: an update , 2004, Trends in Cognitive Sciences.

[61]  Stefan Scherbaum,et al.  Higher response time increases theta energy, conflict increases response time , 2013, Clinical Neurophysiology.

[62]  Richard Ridderinkhof.  Micro- and macro-adjustments of task set: activation and suppression in conflict tasks , 2002, Psychological research.

[63]  Michael X. Cohen,et al.  Single-Trial Regression Elucidates the Role of Prefrontal Theta Oscillations in Response Conflict , 2011, Front. Psychology.

[64]  A. Osman,et al.  Dimensional overlap: cognitive basis for stimulus-response compatibility--a model and taxonomy. , 1990, Psychological review.