Economic Adversity and dynamic neural changes during fear conditioning

<p>&nbsp;</p> <p>The "depression_anxiety_symptoms.RData" file contains data on depression and anxiety across four time points, which can be used for trajectory analysis.</p> <p>The "fp_use_dataframes.RData" file contains data from four blocks of fear learning, specifically including functional activation analysis data of five key regions of interest (ROIs) under conditions such as CS+, CS-, and CS+&gt;CS-, learning slope data, and data for moderation analysis.</p> <p>The "fp_use_dataframes-fc-analysis.RData" file contains data from four blocks of fear learning, specifically including generalized PPI connectivity analysis data under conditions such as CS+, CS-, and CS+&gt;CS-.</p> <p>The "BLA_slope_trajectory_analysis.csv" file contains data that can be used to examine the relationships between brain activity data, inflammation composite scores, and symptom trajectory development.</p> <p>The "code_in_study.R" file contains code for linear mixed model analysis (including three-way and two-way interactions), between-group difference analysis of learning slopes, and related plotting code.</p> <p>The "ANOVA-plot_code.R" file contains code for interaction analysis between economic adversity and background factors (such as childhood maltreatment, subjective SES), post-hoc between-group difference tests, and plotting.</p> <p>The "LCGMs-model fit-comparison.R" file contains code for comparing the differences between unconditional models, linear models, and quadratic change models in trajectory analysis.</p> <p>The "trajectory_analysis.R" file contains code for examining the relationship between the basolateral amygdala's learning slope and depression/anxiety trajectories, as well as code for testing the mediating effect of anxiety trajectories between the basolateral amygdala's learning slope and inflammation.</p>