Brain network dynamics during spontaneous strategy shifts and incremental task optimization.

Area of Science:

• Neuroscience
• Cognitive Psychology
• Neuroimaging

Background:

• Human performance improves with practice through strategy optimization or discovery.
• Understanding the neural basis of these distinct learning processes is crucial.

Purpose of the Study:

• Investigate the neural mechanisms differentiating strategy optimization from strategy discovery.
• Examine the role of brain network dynamics in adaptive learning.

Main Methods:

• Functional magnetic resonance imaging (fMRI) was employed during a task with two strategies.
• Analysis combined time-resolved network analysis with Coherence Density Peak Clustering, GLM, and pattern classification.
• Neural activity and connectivity patterns were analyzed in relation to performance changes.

Main Results:

• The posterior default network (precuneus, angular gyrus) was central to optimizing existing strategies.
• Increased connectivity within the posterior default network correlated with performance gains.
• The anterior default network and fronto-parietal network were linked to discovering new strategies, showing early connectivity increases in those who shifted.

Conclusions:

• The default network plays a dynamic role in both refining current strategies and exploring new ones.
• Distinct default network subregions support strategy exploitation (optimization) and exploration (discovery).
• Findings highlight the interplay between attention and cognitive control networks in balancing exploration and exploitation during learning.