The Role of Prefrontal-Subthalamic θ Signals in Regulating Delayed Responses in Conflict Processing

Background and Research Objectives

Conflict processing plays a crucial role in human behavioral regulation. When faced with conflicting information, making an accurate decision requires delaying the response to gain time to choose the appropriate behavior. Existing models, such as the “hold-your-horses” model, suggest that the medial frontal cortex (MFC) detects the conflict, signals the subthalamic nucleus (STN), and subsequently raises the motor threshold. However, it remains unclear how specific areas within the MFC detect conflict, the direction and causality of information transmission, and how these signals lead to motor changes.

Study Source

This study was conducted by Jeong Woo Choi et al., with authors hailing from UT Southwestern Medical Center, University of California, among other institutions. The paper was published in the 236th issue of Progress in Neurobiology in 2024.

Research Methods

Experimental Procedure

1. Participants and Surgical Procedure:

   • 20 patients with Parkinson’s Disease (PD) or Dystonia who underwent deep brain stimulation (DBS) implantation surgery participated in this study.
   • DBS electrodes were implanted bilaterally or unilaterally in the STN and GPI (internal Globus Pallidus).
   • Neural signals were simultaneously recorded from the prefrontal supplementary motor area (pre-SMA), M1 (primary motor cortex), STN, and GPI.

2. Task Design:

   • Participants performed the Eriksen Flanker task, which included congruent (<<<<< or >>>>>) and incongruent (<<><< or >><>>) conditions.
   • Participants were required to move a lever as quickly as possible in the direction indicated by the central arrow, with the reaction time and error rate recorded.
   • The experiment aimed to observe behavioral differences between conflict conditions and congruent conditions.

3. Data Recording and Signal Analysis:

   • Time-frequency domain analysis was performed on each signal to identify oscillatory activities within the theta and beta bands.
   • Filters (θ band: FWHM=3Hz, β band: FWHM=6Hz) were designed to extract the time series signals in the θ and β bands.
   • Multivariate Granger Causality (MVGC) analysis was used to evaluate functional connectivity.

Experiment Steps and Data Analysis

• Behavioral Performance Analysis:

  • Measured reaction times (MO) and error rates for congruent and incongruent trials.
  • Observed movement delays during incongruent trials and used the “conflict adaptation effect” (Gratton Effect) to study behavioral changes.

• Neural Signal Time-Frequency Analysis:

  • Assessed the power changes within the θ and β bands in the pre-SMA, M1, STN, and GPI regions.
  • Analyzed Granger causality to examine information flow between brain areas.

Main Findings

Behavioral Analysis

• Reaction Time:
  • Incongruent trials showed a significant delay in reaction time compared to congruent trials (incongruent: 676.80±141.07 ms, congruent: 559.84±117.10 ms, p<0.001).
  • The error rate also significantly increased in incongruent trials (incongruent: 8.23±10.96%, congruent: 1.32±2.78%, p=0.0102).

Neural Signal Analysis

1. θ Band Power Changes:

   • Conflict conditions during the flanker task led to increased local θ power in the pre-SMA, STN, and M1, and were significantly correlated with movement delays (STN θ power and MO delay correlation, rho=0.72, p=0.037).

2. Functional Connectivity:

   • Significantly increased θ band Granger causality was observed from pre-SMA to STN, and from STN to M1, appearing before MO.
   • The study provided preliminary exploration of the functional roles of various brain regions, such as the dACC and pre-SMA.

3. β Band Power and Connectivity:

   • β band power continuously decreased after target onset and significantly recovered before MO.
   • A transient increase in β band Granger causality from M1 to GPI was observed before MO during incongruent trials.

Research Conclusions

Main Conclusions

• Conflict-Related θ Network and Movement-Related β Network: The study identified two independent but interactive brain networks: a conflict-related θ network and a movement-related β network. These networks are spatially, spectrally, and temporally separate but dynamically interact to regulate motor performance.

• Role of θ Band Signals in Conflict Detection: The pre-SMA detects conflicts and transmits information through a high-frequency direct pathway to the STN. The STN’s θ band signals then propagate through M1, ultimately leading to action delays.

• Role of β Band Signals in Motor Pausing: Increased STN β power is crucial for effective motor inhibition. Particularly during conflict processing, the transient increase in the M1 to GPI β band Granger causality reflects the mechanism of action delay.

Research Significance

This study is the first to provide high spatiotemporal resolution intracerebral recordings in humans, revealing the complex mechanisms within the BG network during conflict processing. It elucidates different stages of conflict detection, information transmission, and subsequent motor response regulation, offering important insights for the field of neuroscience.

Highlights

• Utilizing invasive recording methods in human brains with high spatiotemporal and spectral resolution to reveal two independent but interactive mechanisms of the BG network.
• Demonstrating the causal relationship between conflict detection and motor changes, with θ band signal flow from pre-SMA to STN and then to M1.
• Highlighting distinct roles of pre-SMA and STN in conflict processing, enriching the understanding of the “hold-your-horses” model.

This study not only enhances the understanding of the BG network in conflict processing but also provides a critical foundation for future research on the conflict adaptation effect and guides further neural regulation studies.