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Research Articles, Behavioral/Cognitive

Cortical Oscillatory Mechanisms Supporting the Control of Human Social–Emotional Actions

Bob Bramson, Ole Jensen, Ivan Toni and Karin Roelofs
Journal of Neuroscience 20 June 2018, 38 (25) 5739-5749; https://doi.org/10.1523/JNEUROSCI.3382-17.2018
Bob Bramson
1Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University Nijmegen, 6525 EN Nijmegen, The Netherlands,
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Ole Jensen
2School of Psychology, University of Birmingham, B15 2TT Birmingham, United Kingdom, and
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Ivan Toni
1Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University Nijmegen, 6525 EN Nijmegen, The Netherlands,
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Karin Roelofs
1Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University Nijmegen, 6525 EN Nijmegen, The Netherlands,
3Behavioural Science Institute, Radboud University Nijmegen, 6525 HR Nijmegen, The Netherlands
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    Figure 1.

    AA task and behavioral results. A, Schematic representation of the affect-congruent and affect-incongruent conditions in the AA task. B, Average reaction times for each participant (n = 40) and condition. Responses are slower during incongruent trials. *t(39) = −4.33, p < 0.001.

  • Figure 2.
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    Figure 2.

    Emotional control increases theta-band power in aPFC. A, Time–frequency plot of between conditions power differences (congruency effect: incongruent − congruent/congruent + incongruent) averaged over sensors with a significant effect (see B). Time 0: response onset. The dashed box shows the time–frequency interval with a significant congruency effect (−350 to −100 ms before response; 6 Hz). B, Topographic distribution of sensors with a significant congruency effect at 6 Hz (stars). C, Changes over time in theta-band power (6 Hz) averaged across significant sensors (see B). The epoch with a significant difference between conditions is marked in gray. D, Cortical distribution of theta-band congruency effects. E, Time series of 6 Hz activity extracted from right frontal pole/superior frontal gyrus (20 40 50). F, Cortical distribution of correlations between theta-band and behavioral congruency effects, with a significant cluster over aPFC (dashed black circle, MNI coordinates of local maximum: 40 48 −6). G, Correlation between theta-band and behavioral congruency effects. Black dots represent measurements from each participant. Theta-band power changes are extracted from the local maximum in aPFC.

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    Figure 3.

    Emotional control decreases beta-band power in parietal and frontal cortex. A, Time–frequency plot of between conditions power differences (congruency effect: incongruent − congruent/congruent + incongruent) averaged over sensors with a significant effect (see B). Time 0: response onset. The dashed box shows the time–frequency interval with a significant congruency effect (−600 to 0 ms before response; 14–26 Hz). B, Topographic distribution of sensors with a significant congruency effect at 14–26 Hz (stars). C, changes over time in beta-band power (14–26 Hz) averaged across significant sensors (see B). The epoch with a significant difference between conditions is marked in gray. D, Cortical distribution of beta-band congruency effects (center frequency, 18 Hz). E, Time series of 18 Hz activity extracted from superior parietal lobule (44 −40 56). F, Cortical distribution of correlations between beta-band (18 Hz) and behavioral congruency effects, with a significant cluster over right precentral gyrus (MNI coordinates of local maximum: 48 −2 36). G, Correlation between beta-band and behavioral congruency effects. Black dots represent measurements from each participant. Beta-band power changes are extracted from the right precentral maximum.

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    Figure 4.

    Emotional control increases connectivity between aPFC and frontoparietal areas. A, Cortical distribution (uncorrected for multiple comparisons) of correlations between beta-band congruency effects and theta-band congruency effects extracted from aPFC (in red, from Fig. 2E). The cluster over the right precentral gyrus (MNI coordinates of local maximum: 50 −10 36) is significant. B, Correlation between aPFC theta-band and precentral beta-band congruency effects. Black dots represent measurements from each participant. Beta-band power changes are extracted from the right precentral maximum.

  • Figure 5.
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    Figure 5.

    Emotional control increases gamma-band power in parietal and frontal cortex during peaks of theta-band oscillations in aPFC. A, Time–frequency plot of between conditions power differences (congruency effect: incongruent − congruent/congruent + incongruent) averaged over sensors with a significant effect (see B). Time 0: response onset. The dashed box shows the time–frequency interval with a significant congruency effect (−350 to −50 ms before response; 60–90 Hz). B, Topographic distribution of sensors with a significant congruency effect at 60–90 Hz (stars). C, Changes over time in gamma-band power (60–90 Hz) averaged across significant sensors (see B). D, Cortical distribution of relative gamma-band congruency effects, with a significant cluster around the left central sulcus (−28 −32 64). E, Time series of 60–90 Hz activity extracted from left central sulcus (−28 −32 64). F, Time–frequency plot of gamma-band power congruency effects extracted from the local maximum in the left central sulcus (F) phase-locked to the aPFC theta-band signal before response. Contours are drawn around significant clusters where power is stronger in incongruent versus congruent trials. G, Event-related field of the theta-band signal extracted from aPFC.

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The Journal of Neuroscience: 38 (25)
Journal of Neuroscience
Vol. 38, Issue 25
20 Jun 2018
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Cortical Oscillatory Mechanisms Supporting the Control of Human Social–Emotional Actions
Bob Bramson, Ole Jensen, Ivan Toni, Karin Roelofs
Journal of Neuroscience 20 June 2018, 38 (25) 5739-5749; DOI: 10.1523/JNEUROSCI.3382-17.2018

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Cortical Oscillatory Mechanisms Supporting the Control of Human Social–Emotional Actions
Bob Bramson, Ole Jensen, Ivan Toni, Karin Roelofs
Journal of Neuroscience 20 June 2018, 38 (25) 5739-5749; DOI: 10.1523/JNEUROSCI.3382-17.2018
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Keywords

  • approach–avoidance
  • frontal pole
  • MEG
  • phase-amplitude coupling
  • social–emotional control
  • theta-band oscillations

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