Beta-band modulation in the human hippocampus during a conflict response task

Understanding the human conflict processing network: A review of the literature on direct neural recordings during performance of a modified stroop task

The Stroop Task is a well-known neuropsychological task developed to investigate conflict processing in the human brain. Our group has utilized direct intracranial neural recordings in various brain regions during performance of a modified color-word Stroop Task to gain a mechanistic understanding of non-emotional human conflict processing. The purpose of this review article is to: 1) synthesize our own studies into a model of human conflict processing, 2) review the current literature on the Stroop Task and other conflict tasks to put our research in context, and 3) describe how these studies define a network in conflict processing. The figures presented are reprinted from our prior publications and key publications referenced in the manuscript. We summarize all studies to date that employ invasive intracranial recordings in humans during performance of conflict-inducing tasks. For our own studies, we analyzed local field potentials (LFPs) from patients with implanted stereotactic electroencephalography (SEEG) electrodes, and we observed intracortical oscillation patterns as well as intercortical temporal relationships in the hippocampus, amygdala, and orbitofrontal cortex (OFC) during the cue-processing phase of a modified Stroop Task. Our findings suggest that non-emotional human conflict processing involves modulation across multiple frequency bands within and between brain structures.

Beta-band power modulation in the human amygdala differentiates between go/no-go responses in an arm-reaching task

Objective. Traditionally known for its involvement in emotional processing, the amygdala's involvement in motor control remains relatively unexplored, with sparse investigations into the neural mechanisms governing amygdaloid motor movement and inhibition. This study aimed to characterize the amygdaloid beta-band (13-30 Hz) power between 'Go' and 'No-go' trials of an arm-reaching task.Approach. Ten participants with drug-resistant epilepsy implanted with stereoelectroencephalographic (SEEG) electrodes in the amygdala were enrolled in this study. SEEG data was recorded throughout discrete phases of a direct reach Go/No-go task, during which participants reached a touchscreen monitor or withheld movement based on a colored cue. Multitaper power analysis along with Wilcoxon signed-rank and Yates-correctedZtests were used to assess significant modulations of beta power between the Response and fixation (baseline) phases in the 'Go' and 'No-go' conditions.Main results. In the 'Go' condition, nine out of the ten participants showed a significant decrease in relative beta-band power during the Response phase (p⩽ 0.0499). In the 'No-go' condition, eight out of the ten participants presented a statistically significant increase in relative beta-band power during the response phase (p⩽ 0.0494). Four out of the eight participants with electrodes in the contralateral hemisphere and seven out of the eight participants with electrodes in the ipsilateral hemisphere presented significant modulation in beta-band power in both the 'Go' and 'No-go' conditions. At the group level, no significant differences were found between the contralateral and ipsilateral sides or between genders.Significance.This study reports beta-band power modulation in the human amygdala during voluntary movement in the setting of motor execution and inhibition. This finding supplements prior research in various brain regions associating beta-band power with motor control. The distinct beta-power modulation observed between these response conditions suggests involvement of amygdaloid oscillations in differentiating between motor inhibition and execution.

Prediction of dispositional dialectical thinking from resting-state electroencephalography

This study aims to explore the possibility of predicting the dispositional level of dialectical thinking using resting-state electroencephalography signals. Thirty-four participants completed a self-reported measure of dialectical thinking, and their resting-state electroencephalography was recorded. After wave filtration and eye movement removal, time-frequency electroencephalography signals were converted into four frequency domains: delta (1-4 Hz), theta (4-7 Hz), alpha (7-13 Hz), and beta (13-30 Hz). Functional principal component analysis with B-spline approximation was then applied for feature reduction. Five machine learning methods (support vector regression, least absolute shrinkage and selection operator, K-nearest neighbors, random forest, and gradient boosting decision tree) were applied to the reduced features for prediction. The model ensemble technique was used to create the best performing final model. The results showed that the alpha wave of the electroencephalography signal in the early period (12-15 s) contributed most to the prediction of dialectical thinking. With data-driven electrode selection (FC1, FCz, Fz, FC3, Cz, AFz), the prediction model achieved an average coefficient of determination of 0.45 on 200 random test sets. Furthermore, a significant positive correlation was found between the alpha value of standardized low-resolution electromagnetic tomography activity in the right dorsal anterior cingulate cortex and dialectical self-scale score. The prefrontal and midline alpha oscillations of resting electroencephalography are good predictors of the dispositional level of dialectical thinking, possibly reflecting these brain structures' involvement in dialectical thinking.

Hippocampal and Orbitofrontal Theta Band Coherence Diminishes During Conflict Resolution

OBJECTIVE

Coherence between the hippocampus and other brain structures has been shown with the theta frequency (3-8 Hz). Cortical decreases in theta coherence are believed to reflect response accuracy efficiency. However, the role of theta coherence during conflict resolution is poorly understood in noncortical areas. In this study, coherence between the hippocampus and orbitofrontal cortex (OFC) was measured during a conflict resolution task. Although both brain areas have been previously implicated in the Stroop task, their interactions are not well understood.

METHODS

Nine patients were implanted with stereotactic electroencephalography contacts in the hippocampus and OFC. Local field potential data were sampled throughout discrete phases of a Stroop task. Coherence was calculated for hippocampal and OFC contact pairs, and coherence spectrograms were constructed for congruent and incongruent conditions. Coherence changes during cue processing were identified using a nonparametric cluster-permutation t test. Group analysis was conducted to compare overall theta coherence changes among conditions.

RESULTS

In 6 of 9 patients, decreased theta coherence was observed only during the incongruent condition (P < 0.05). Congruent theta coherence did not change from baseline. Group analysis showed lower theta coherence for the incongruent condition compared with the congruent condition (P < 0.05).

CONCLUSIONS

Theta coherence between the hippocampus and OFC decreased during conflict. This finding supports existing theories that theta coherence desynchronization contributes to improved response accuracy and processing efficiency during conflict resolution. The underlying theta coherence observed between the hippocampus and OFC during conflict may be distinct from its previously observed role in memory.