Large-Scale Brain Networks Track Gasoline Price Shifts.

Area of Science:

• Neuroscience
• Economics
• Psychology

Background:

• Macroeconomic conditions influence daily life and perception.
• The link between real-world economic dynamics and population-level intrinsic brain organization is not well understood.

Purpose of the Study:

• To investigate if macroeconomic time series correlate with large-scale resting-state brain networks.
• To examine population-level brain organization differences in response to economic events.

Main Methods:

• Utilized Human Connectome Project (HCP) resting-state fMRI data from 726 adults.
• Aligned fMRI data with quarterly macroeconomic indicators (gasoline price, consumer sentiment, unemployment, stock market return).
• Quantified intrinsic organization using network functional connectivity (FC) and amplitude of low-frequency fluctuations (ALFF).

Main Results:

• Participants post-gasoline price shock showed increased within-network FC and specific between-network coupling.
• ALFF showed bidirectional shifts, with increased Visual ALFF post-shock and higher Limbic/Frontoparietal ALFF pre-shock.
• Gasoline price and consumer sentiment exhibited the most significant associations with brain network measures.

Conclusions:

• Salient macroeconomic dynamics, especially energy price changes, are associated with population-level differences in intrinsic brain network architecture.
• Findings suggest economic factors can shape intrinsic brain organization at a population level.
• Further research with finer temporal resolution and individual-level data is needed to strengthen causal inference.