Methodolgy:

The study used three separate fMRI experiments:

1. Experiment 1 - Auditory Event Segmentation (primary experiment):
• 18 right-handed participants (ages 19-27, 8 females) with minimal musical training
• Listened to Baroque music by William Boyce inside the scanner with focused attention
• Analyzed brain responses during "movement transitions" (salient boundaries between musical movements)
2. Experiment 2 - Visual Oddball Task:
• 13 subjects (mean age 24 years, 8 females)
• 200 visual stimuli (colored circles: blue or green) presented for 150ms with 2000ms intervals
• Frequency of colored circles counterbalanced across subjects
3. Experiment 3 - Resting State:
• 22 subjects (ages 19-21, 11 females)
• 8-minute resting state scan with eyes closed

Analysis Methods:

1. General Linear Model (GLM) Analysis: Identified activation/deactivation patterns in three networks (CEN, DMN, SN)
2. Independent Component Analysis (ICA): Model-free analysis to identify spatially independent networks
3. Latency Analysis:
• Used Henson et al.'s method to estimate peak latency of BOLD responses
• Computed onset latencies using Sterzer and Kleinschmidt's method
• Determined which regions activated earliest
4. Granger Causality Analysis (GCA):
• Applied bivariate model to examine causal interactions between six key regions
• Used bootstrap techniques to create null distributions
• Constructed causal connectivity graphs showing directionality of influence
5. Network Analysis:
• Calculated graph metrics: out-degree, in-degree, path length
• Identified hub regions based on connectivity patterns

Region of Interest Selection: Six key nodes defined from ICA peaks: right FIC, ACC, right DLPFC, right PPC, VMPFC, and PCC