FIGURE 4.

(Left) The average correlation of every participants’ vector to model 1 for each dataset. Since model 1 was built off of general observations from dataset 1, the high correlation of dataset 1 to model 1 is expected and the correlation coefficients of dataset 1 to model 1 are simply reported for descriptive purposes. All datasets were highly correlated with model 1, especially compared to a scrambled dataset “11”, but not all datasets were equal (one-way ANOVA across Datasets 1–10, F9,187 = 12.88, P <0.0001). Post-hoc Bonferroni’s multiple comparison tests were performed on all pairs of datasets; however, only tests of specific interest are reported here. Young participants (Dataset 3) in an incidental encoding task were significantly better correlated to Model 1 than older participants (Dataset 4) in the same exact task (t₃₃ = 4.28, P <0.01). There were also differences in task-related versus resting state data in similar participants. Dataset 3, an incidental encoding task, was significantly better correlated to Model 1 than Dataset 5, a resting state scan (t₃₅ = 6.57, P <0.001), despite both datasets being collected in healthy young adults with the same scanner sequence at the same MRI facility. (Right) The average correlation of every participants’ vector to an anatomical model representing the anatomical MTL connections reported in Lavenex and Amaral (2000). A two-way ANOVA on the correlation of each participants’ vector of coefficients in Datasets 1–10 to Model 1 and the anatomical model was run to compare the fit of each dataset to each model. Post-hoc Bonferroni’s multiple comparison tests revealed that each dataset was better correlated to Model 1 than to the anatomical model (all t >4.08, all P <0.001), suggesting that Model 1 is a better representation of the pattern of functional connectivity within each dataset than known anatomical connections.