Intracranial EEG signals disentangle multi-areal neural dynamics of vicarious pain perception

Neurology Medicine Medical Imaging Neurosurgery
Intracranial EEG Vicarious pain Neural dynamics brain regions empathy

Research Workflow Diagram

Research Background and Objectives

Empathy is the ability to understand and share the feelings of others and is a crucial foundation for human social interaction and prosocial behavior. Current neuroimaging studies have identified specific brain regions that play key roles in empathetic pain, including the anterior insula (AI), anterior cingulate cortex (ACC), amygdala, and inferior frontal gyrus (IFG). However, there are still many mysteries regarding the precise spatiotemporal characteristics of these regions and the mechanisms of interregional communication during empathic responses.

In recent years, functional magnetic resonance imaging (fMRI) studies have identified core neural networks for empathetic pain, including AI, ACC, amygdala, and IFG, providing a basis for understanding how empathy operates within the brain. However, fMRI has low temporal resolution, making it difficult to capture rapid neural dynamic changes. Therefore, this study aims to reveal the electrophysiological characteristics of empathetic pain by recording local field potentials (LFPs) using intracranial electroencephalography (iEEG).

Source and Authors

This study’s paper is titled “Intracranial EEG Signals Disentangle Multi-Areal Neural Dynamics of Vicarious Pain Perception” and is published in the 2024 issue of the journal “Nature Communications”. The primary authors, including Huixin Tan, Xiaoyu Zeng, and Jun Ni, come from several research institutions, including the State Key Laboratory of Cognitive Neuroscience and Learning at Beijing Normal University and the School of Psychological and Cognitive Sciences at Peking University.

Research Process

Experimental Design and Participants

The experimental design of the study is relatively complex, and participants included 22 epilepsy patients. These patients required intracranial electrode implantation for monitoring before surgical resection to determine the seizure onset zone.

  1. Experimental Task: Participants watched images showing human hands receiving painful or non-painful stimuli, as illustrated in Figure 1. After viewing each image, participants judged whether the person felt pain. The experiment phases included a 1200ms fixation period, a 500ms image presentation period, and a self-paced pain judgment.

  2. Data Collection and Processing: iEEG was used to record brain activity during the task, focusing on the AI, ACC, amygdala, and IFG—regions related to empathy. The electrode implantation site for each participant was determined based on clinical need.

Data Analysis Methods

  1. Time-Frequency Analysis: Morlet wavelet transform was used to analyze iEEG signals, obtaining the time-frequency characteristics of brain electrical activity across multiple frequency bands, from low-frequency (theta, 4-8Hz) to high-frequency (high-gamma, 70-150Hz).

  2. Power Correlation Analysis: The synchronization of low-frequency oscillations between different brain regions was assessed, analyzing the differences in power correlation between painful and non-painful conditions.

  3. Phase-Amplitude Coupling Analysis (PAC): This analysis further examined how the phase of low-frequency bands (e.g., beta band) modulates the amplitude of high-frequency bands (e.g., high-gamma), revealing interregional cross-frequency coupling relationships.

Main Research Results

Behavioral Data Results

  1. Response Accuracy and Reaction Time: The experimental analysis showed no significant difference in response accuracy and reaction time when participants judged painful and non-painful conditions, indicating equal attention investment for both types of stimuli.

  2. Subjective Emotional Ratings: In the postoperative subjective rating phase, participants reported significantly higher intensity of empathy response, perceived pain intensity, and their own distress when viewing painful stimuli compared to non-painful stimuli.

Neural Data Results

  1. Region-Specific Neural Activity: Time-frequency analysis showed that different brain regions exhibited distinct neural activity characteristics when viewing images of others being hurt. For example, in the IFG area, high-gamma band power significantly increased under painful conditions; in the ACC area, beta band power increased, whereas in AI and amygdala regions, beta band power decreased.

  2. Interregional Communication: Power correlation analysis in the low-frequency band indicated that, under painful conditions, the beta band power correlation significantly decreased between the ACC and AI and between the AI and the amygdala. Conversely, between the ACC and amygdala, low-frequency band correlation increased and high-frequency band correlation decreased.

  3. Cross-Frequency Coupling: Phase-amplitude coupling analysis demonstrated that, under painful conditions, the high-gamma amplitude in the IFG was significantly modulated by the beta phase of AI, ACC, and amygdala.

Conclusions and Contributions

This study, for the first time, used iEEG to reveal the specific time-frequency characteristics of AI, ACC, amygdala, and IFG in empathic pain perception and their interregional communication mechanisms, providing a new perspective for understanding the dynamic neural model of empathy. The results not only identified unique neural activity features of these regions during empathic responses but also, through cross-frequency coupling and power correlation analysis, uncovered the information transmission and integration mechanisms between different brain regions within the empathy network.

Scientific Significance and Application Value

  1. Basic Scientific Value: This study enriches the understanding of the neural basis of empathy, especially by using iEEG with high temporal and spatial resolution, revealing rapid neural dynamic changes that traditional fMRI cannot capture.

  2. Application Potential: The discovered neural characteristics and communication patterns related to empathy could aid the future development of interventions and therapeutic strategies for empathy-related deficits, holding potential clinical application value.

Research Highlights

  1. Novel Methodology: iEEG: The use of iEEG with high temporal and spatial resolution to reveal rapid neural dynamic changes and the activity of deep brain structures is a major highlight of this study.

  2. Complex Neural Mechanisms: By combining power correlation and phase-amplitude coupling analyses, the study uncovered complex communication mechanisms within the empathy neural network.

  3. Clinical Application Prospects: The study’s results not only have significant basic research value but also provide a scientific basis for designing empathy intervention measures.

Other Information

The detailed design of the experimental tasks and the analysis of both behavioral and neural data ensured the reliability and scientific validity of the study’s results. This research was a multidisciplinary team collaboration, encompassing cognitive neuroscience, clinical neurology, and psychology, pointing out new directions for future empathy research.