Distributed Intracranial Activity Underlying Human Decision-making Behavior

Area of Science:

• Neuroscience
• Cognitive Neuroscience
• Neuroeconomics

Background:

• Value-based decision-making engages distributed brain networks, but the neurophysiological basis of economic choices is not fully understood.
• The representation of reward-guided choices and associated computations (e.g., risk, win probability) across brain regions remains largely unexplored.

Purpose of the Study:

• To investigate the hypothesis that reward choices and related computations are represented in high-frequency neural activity (HFA).
• To determine if this neural activity is localized or widely distributed across the human brain.

Main Methods:

• Intracranial recordings were obtained from neurosurgical patients during a decision-making game.
• Recordings spanned multiple cortical (orbitofrontal, lateral prefrontal, parietal, cingulate) and subcortical (hippocampus, amygdala) regions.
• Analysis focused on high-frequency activity (HFA) and its correlation with choice-related computations and final choices.

Main Results:

• High-frequency activity (HFA) differentially represents choice-related computations and choice information.
• Choice computations (risk, win probability) showed local and uneven representation across brain regions.
• Choice information was widely distributed, appearing later and more prevalently across all examined regions.

Conclusions:

• Neural activity underlying economic choices is broadly distributed across the brain.
• Local HFA reflects the integration of choice-related information into a final decision.
• Findings illuminate the brain-wide reward processing and distributed neural basis of economic decision-making.