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. 2014 Jul 30;34(31):10438-52.
doi: 10.1523/JNEUROSCI.3099-13.2014.

Neural communication patterns underlying conflict detection, resolution, and adaptation

Carina R Oehrn  1 , Simon Hanslmayr  2 , Juergen Fell  1 , Lorena Deuker  3 , Nico A Kremers  1 , Anne T Do Lam  1 , Christian E Elger  1 , Nikolai Axmacher  4
Affiliations

Neural communication patterns underlying conflict detection, resolution, and adaptation

Carina R Oehrn et al. J Neurosci. .

Abstract

In an ever-changing environment, selecting appropriate responses in conflicting situations is essential for biological survival and social success and requires cognitive control, which is mediated by dorsomedial prefrontal cortex (DMPFC) and dorsolateral prefrontal cortex (DLPFC). How these brain regions communicate during conflict processing (detection, resolution, and adaptation), however, is still unknown. The Stroop task provides a well-established paradigm to investigate the cognitive mechanisms mediating such response conflict. Here, we explore the oscillatory patterns within and between the DMPFC and DLPFC in human epilepsy patients with intracranial EEG electrodes during an auditory Stroop experiment. Data from the DLPFC were obtained from 12 patients. Thereof four patients had additional DMPFC electrodes available for interaction analyses. Our results show that an early θ (4-8 Hz) modulated enhancement of DLPFC γ-band (30-100 Hz) activity constituted a prerequisite for later successful conflict processing. Subsequent conflict detection was reflected in a DMPFC θ power increase that causally entrained DLPFC θ activity (DMPFC to DLPFC). Conflict resolution was thereafter completed by coupling of DLPFC γ power to DMPFC θ oscillations. Finally, conflict adaptation was related to increased postresponse DLPFC γ-band activity and to θ coupling in the reverse direction (DLPFC to DMPFC). These results draw a detailed picture on how two regions in the prefrontal cortex communicate to resolve cognitive conflicts. In conclusion, our data show that conflict detection, control, and adaptation are supported by a sequence of processes that use the interplay of θ and γ oscillations within and between DMPFC and DLPFC.

Keywords: Stroop; dorsolateral prefrontal cortex; dorsomedial prefrontal cortex; oscillations; γ; θ.

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Figures

Figure 1.
Figure 1.
Electrode locations mapped onto MNI templates. A, DMPFC electrodes (n = 4). One contact per patient was chosen based on the minimal distance to a reference coordinate within the DMPFC, where conflict-associated changes in BOLD signal had been previously found in an fMRI experiment using an identical paradigm (Haupt et al., 2009) (in the contrast of conflict vs nonconflict trials in the phonetic condition; MNI coordinates: 2, 18, 46). Green represents the selected contact for each patient. Red represents the reference coordinate. B, DLPFC electrodes (n = 12; note that one patient did not have a preimplantation MRI which is necessary to determine MNI coordinates). Electrodes were selected correspondingly, with bilateral reference points in the DLPFC based on previous fMRI results (in the contrast of conflict vs nonconflict trials in the phonetic condition; MNI coordinates: 40, 16, 32 and −48, 18, 10).
Figure 2.
Figure 2.
Paradigm and behavioral results. A, Experimental design. Patients responded to the words “high” and “low” spoken in a high or low pitch, resulting in consistent (nonconflict) and inconsistent (conflict) stimuli. Two tasks were performed: indication of word meaning (semantic task) or indication of tone pitch (phonetic task). Conflict was only expected to occur during the phonetic task. B, Behavioral results related to conflict detection: Reaction times and accuracy for nonconflict and conflict trials. During the phonetic task, patients reacted significantly slower and less correctly to conflict words, whereas there was no behavioral effect of consistency during the semantic task. *p < 0.05; **p < 0.01. C, Behavioral effects of consistency as a function of the previous trial (conflict adaptation). During both tasks, patients reacted faster and more accurately during two subsequent conflict stimuli (II) than to conflict trials preceded by nonconflict trials (CI). *p < 0.05.
Figure 3.
Figure 3.
Frequency-specific power distribution in the DMPFC and DLPFC. Plots represent mean power ± SEM values across patients. Within each patient, values had been averaged across all time points (1500 ms intertrial interval, 3000 ms trial period), trials, tasks (semantic task, phonetic task), and stimuli (inconsistent, consistent, control).
Figure 4.
Figure 4.
Conflict processing modulates preresponse DMPFC θ power and sustained DLPFC γ power. A, E, Time-frequency plots during conflict processing (i.e., differences between conflict and nonconflict trials in the phonetic condition). Power differences are expressed in percentage of baseline power; significant clusters are highlighted. Conflict processing was associated with preresponse increases in DMPFC θ power and DLPFC γ power enhancements throughout the trial. B, F, Time series of mean power ± SEM across the respective significant frequencies for conflict (red) and nonconflict (blue) stimuli. For illustrative purposes, the DLPFC γ power time series (F) had been smoothed with a moving average of a 250 ms surrounding window. C, Illustration of the location of the observed DMPFC θ power test statistic (red) within the distribution of surrogate values (green): sum of t values. D, Plots illustrating conflict-related θ power in the DMPFC for all individual patients with electrodes in this region. For illustrative purposes, significant time periods are shaded in gray. G, Bar plot representing conflict-related power increases (conflict − nonconflict items) in near compared with distant electrodes from the respective target coordinate across patients. *p < 0.05; **p < 0.01.
Figure 5.
Figure 5.
Inconsistent stimuli do not elicit DMPFC or DLPFC power changes during the semantic task. A, B, Time-frequency plots contrasting power values during inconsistent and consistent stimuli during the semantic task in the DMPFC and DLPFC. This contrast did not reveal any significant changes.
Figure 6.
Figure 6.
Conflict was not associated with power changes in the motor cortex. A, B, Response-locked analysis of oscillatory activity in the primary motor cortex. Signal quality and electrode location were confirmed by response-locked analyses (independent of stimulus type). All motor electrodes exhibited typical functional signatures of the primary motor cortex (a pronounced periresponse beta power decrease and postresponse beta power increase). It should be noted that power values were calculated independent of experimental conditions and are shown as percentage of their baseline. As the images do not represent differences between conditions as all other contrasts (inconsistent − consistent), values fluctuate ∼100% (baseline level) instead of zero. C, D, Stimulus-locked analysis of oscillatory activity in the primary motor cortex. Time-frequency-resolved illustration of conflict-associated changes of power in the motor cortex of 2 patients. Within-subjects statistics did not reveal any significant clusters. E, F, Bar plot illustrating the distribution of θ and γ power values in both conditions (inconsistent vs consistent) across trials.
Figure 7.
Figure 7.
Conflict-related changes in CFC within the DLPFC and phase synchronization and CFC between DMPFC and DLPFC. Significant clusters are highlighted, and the location of the observed test statistic (red) within the surrogate distribution (green) is shown for all analyses with n = 4 patients and n = 15 possible surrogate permutations (C, K; cluster size as sum of t values). When <15 clusters are indicated, the remaining permutations did not reveal any significant clusters. A, B, D, Time-frequency plots of DMPFC-DLPFC PSVs during conflict processing (conflict vs nonconflict trials). Conflict was associated with synchronization increases at 5 Hz before and after average response latency (highlighted). E–G, Intraregional CFC within the DLPFC during conflict compared with nonconflict trials. During conflict, early DLPFC γ power was transiently locked to DLPFC θ phases. E, Time-dependent magnitude of the modulation of γ power by low-frequency phases. F, Time-dependent CFC at 5 Hz, where significant conflict-associated changes had been found. G, DLPFC γ power during conflict trials as a function of low-frequency phases within the significant time window. H–J, L, Conflict-related increase in inter-regional CFC between DMPFC θ phase and DLPFC γ power before and after average response latency.
Figure 8.
Figure 8.
GC analyses. Directionality of interactions between DMPFC and DLPFC during conflict processing. A, Time- and frequency-resolved GC ([DMPFC → DLPFC] − [DLPFC → DMPFC]). Whereas early in the trial, oscillatory activity in the θ range within the DMPFC predicted DLPFC activity significantly better than the other way around, the predominant direction of information flow reversed closer to the mean response time. B, Time series of GC between the DMPFC and DLPFC (mean ± SEM) between 4 and 8 Hz. For illustrative purposes, significant time periods are shaded in gray. C, Position of empirical cluster sizes (red) within the distribution of 15 cluster sizes obtained from random permutations (green): as measured in sum of t values. When <15 random test statistics are shown, the remaining permutations did not reveal any significant clusters. D, Plots showing conflict-related GC from 4 to 8 Hz for each patient separately.
Figure 9.
Figure 9.
Summary. Outline of the time course of conflict-associated time-frequency patterns within and between DMPFC and DLPFC. Bottom, Power changes within the DMPFC. Top, Power effects and CFC within the DLPFC. Middle, Measures of interactions between the two regions, such as phase synchronization (phase sync) and inter-regional CFC. Shaded red and blue boxes represent the directionality of interactions, as measured by GC. Dashed line indicates mean response time. Color coding represents behavioral effects.
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