Functional and effective connectivity of stopping
René J Huster1, Sergey M Plis2, Christina F Lavallee3
1Experimental Psychology Lab, Carl von Ossietzky University, Oldenburg, Germany; Research Center Neurosensory Science, Carl-von-Ossietzky University Oldenburg, Oldenburg, Germany.
Neuroimage
|March 18, 2014
Summary
This study reveals that early changes in brain connectivity patterns, not just later amplitude differences, are key indicators of successful behavioral inhibition. These findings offer new insights into the neurocognitive processes underlying stopping behavior.
Area of Science:
- Neuroscience
- Cognitive Science
- Computational Neuroscience
Background:
- Behavioral inhibition is often studied using electroencephalography (EEG) by analyzing event-related potentials (ERPs) like N200 and P300, linked to theta and delta frequency bands.
- Previous research has not reliably identified indicators for successful behavioral inhibition or explored the causal relationships within stop-related neurocognitive processes.
Purpose of the Study:
- To investigate functional and effective connectivity underlying stopping behavior using EEG data.
- To identify temporal dynamics of causal dependencies between brain networks during a stop-signal task.
Main Methods:
- Group independent component analysis (ICA) was employed to identify functionally coherent neural networks from EEG data.
- Bayesian network estimation was used to determine the temporal dynamics of causal dependencies between these components.
- Connectivity metrics (clustering coefficient, path length) were analyzed across different time windows.
Main Results:
- Significant differences in connectivity profiles were observed between 130-180 ms and 420-500 ms.
- Three independent components showed correlations with behavioral inhibition measures (reaction times, failed stops) between 120-260 ms.
- Two components acted as causal sources, one linked to P300/delta activity and another to alpha power depletion.
Conclusions:
- Early changes in causal brain connectivity patterns, preceding peak ERP amplitude differences, are critical for behavioral inhibition.
- The P300 and delta activity appear statistically dependent on earlier inhibitory processes.
- Analyzing stopping-related brain connectivity reveals novel patterns crucial for understanding behavioral inhibition.
