Directed causal effect with PCMCI in hyperscanning EEG time series

Area of Science:

• Neuroscience
• Cognitive Science
• Computational Neuroscience

Background:

• Social interactions involve complex brain activity and inter-brain communication.
• Analyzing directed causality in neural data, especially during social tasks, remains challenging.
• Hyperscanning electroencephalography (EEG) offers a window into simultaneous brain activity of interacting individuals.

Purpose of the Study:

• To assess the efficacy of Tigramite, a novel time-domain causal discovery method, for analyzing directed causality in hyperscanning EEG data.
• To investigate inter-brain and intra-brain causal relationships within the prefrontal cortex (PFC) during a structured social task.

Main Methods:

• Utilized hyperscanning EEG to record brain activity from individuals engaged in a leader-follower finger-tapping task.
• Applied Tigramite, a graph-based causal discovery algorithm, to analyze time-series EEG data from the prefrontal cortex (PFC).
• Examined directed causal connections both within individual brains and between the brains of interacting partners.

Main Results:

• Significantly directed causal influences were detected within individual brains during the task.
• Directed causal effects were also identified between the brains of interacting individuals.
• This marks the first empirical demonstration of Tigramite's ability to detect inter- and intra-brain causality in hyperscanning EEG.

Conclusions:

• TigraMite is a viable method for identifying directed causality in time-domain hyperscanning EEG data.
• The findings provide empirical evidence for neural causality during social interactions.
• This approach holds promise for future research into neural network dynamics during social cognition and behavior.