Intentional signal in prefrontal cortex generalizes across different sensory modalities.

Area of Science:

• Neuroscience
• Cognitive Science
• Brain-Computer Interfaces

Background:

• Biofeedback-EEG training aids understanding of brain control over external devices.
• Current methods often pre-select brain areas, limiting discovery of emergent activations.
• Exploring amodal, abstract signals across sensory modalities remains underexplored.

Purpose of the Study:

• To automatically uncover brain regional activity maximizing performance in a binary control task.
• To investigate the automatic recruitment of brain areas beyond pre-selected regions.
• To explore the prefrontal cortex's role in externally driven intention.

Main Methods:

• Developed a binary control task within a brain-computer interface (BCI) framework.
• Employed a Bayesian sparse probit classification algorithm for automatic activity detection.
• Trained and tested 19 participants using visual feedback.

Main Results:

• Quantified frontoparietal coupling and visual/auditory region involvement based on real-time feedback.
• Identified automatic recruitment of the prefrontal cortex during the testing phase.
• Observed significantly higher activation in Brodmann's areas 9, 10, and 11 compared to other brain regions.

Conclusions:

• The prefrontal cortex, particularly areas 9, 10, and 11, shows automatic recruitment in BCI tasks.
• This prefrontal signal may serve as a neural correlate for externally driven intention.
• Results contribute to understanding cognitive control and brain activity modulation.