Scientists at the University of Iowa have conducted new research examining the frontoparietal cortex, a critical neural network responsible for managing information processing and coordinating responses throughout the brain. This region functions similarly to an air traffic controller, continuously receiving signals from various brain areas while filtering and prioritizing information based on relevance to the task at hand.
Using a combination of functional MRI brain imaging and computational modeling, researchers found that the frontoparietal cortex does not communicate with other brain regions in a static manner. Instead, its connection patterns shift dynamically based on the type of information needed at different stages of decision-making. Rather than simply increasing overall activity during challenging tasks, the network strategically adjusts which brain regions it communicates with depending on the specific demands of the moment.
To conduct their investigation, the research team recruited 38 participants and had them learn associations between visual stimuli and specific finger responses. The researchers then changed these learned pairings, forcing participants to recognize the changes and adapt their behavior. This manipulation created measurable uncertainty as participants attempted to determine what had changed and learn the new associations. Brain imaging during this process revealed how the frontoparietal cortex modified its communication patterns as participants navigated the uncertain decision-making process.
The findings have potential implications for understanding neurological and psychiatric conditions characterized by difficulty adjusting behavior when circumstances change. Conditions such as attention-deficit/hyperactivity disorder and schizophrenia may involve impaired integration of information across brain regions. Better understanding how the frontoparietal cortex normally integrates information from multiple sources could eventually guide future investigations into these disorders and their underlying mechanisms.
The research was published in the Journal of Neuroscience, with contributions from multiple team members including graduate student Stephanie Leach, who served as first author, and computational modeling specialist Jiefeng Jiang.
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