To examine individual differences, we used K-means clustering in an exploratory analysis. We determined subpopulations across the DTI data based on the trajectory and total level of FA across all brain tracts, the corpus callosum, the fornix and the anterior thalamic radiations. For each region, you can see:

1: Cluster determined based on average level and trajectory.
2: Cluster determined based on trajectory.
3: Cluster determined based on average level.

All tracts

A1: Cluster determined based on average level and trajectory. All tracts.

#Elbow Method
Elb <- fviz_nbclust(AdvDTI[,19:20], kmeans, method = "wss") +  #within cluster sums of squares
     labs(subtitle = "Elbow method_AllTracts")
Elb

#Silhouette Method
Sil <- fviz_nbclust(AdvDTI[,19:20], kmeans, method = "silhouette")+   #average silhouette
      labs(subtitle = "Silhouette method_AllTracts")
Sil

A2: Cluster determined based on trajectory. All tracts.

#Silhouette Method
SilShape <- fviz_nbclust(AdvDTI[,19], kmeans, method = "silhouette") +
      labs(subtitle = "Silhouette method_AllTracts_Shape")
SilShape

#Elbow Method
ElbShape <- fviz_nbclust(AdvDTI[,19], kmeans, method = "wss") +  #within cluster sums of squares
     labs(subtitle = "Elbow method_AllTracts_Shape")
ElbShape

A3: Cluster determined based on average level. All tracts.

#Silhouette Method
SilSize <- fviz_nbclust(AdvDTI[,20], kmeans, method = "silhouette") +
      labs(subtitle = "Silhouette method_AllTracts_Size")
SilSize

#Elbow Method
ElbSize <- fviz_nbclust(AdvDTI[,20], kmeans, method = "wss") +  #within cluster sums of squares
     labs(subtitle = "Elbow method_AllTracts_Size")
ElbSize

Corpus Callosum

B1: Cluster determined based on average level and trajectory. Corpus Callosum.

#Elbow Method
Elb <- fviz_nbclust(AdvDTI[,21:22], kmeans, method = "wss") +  #within cluster sums of squares
     labs(subtitle = "Elbow method_CC")
Elb

#Silhouette Method
Sil <- fviz_nbclust(AdvDTI[,21:22], kmeans, method = "silhouette")+   #average silhouette
      labs(subtitle = "Silhouette method_CC")
Sil

B2: Cluster determined based on trajectory. Corpus Callosum.

#Elbow Method
ElbShape <- fviz_nbclust(AdvDTI[,21], kmeans, method = "wss") +
     labs(subtitle = "Elbow method_CC_Shape")
ElbShape

#Silhouette Method
SilShape <- fviz_nbclust(AdvDTI[,21], kmeans, method = "silhouette") +
      labs(subtitle = "Silhouette method_CC_Shape")
SilShape

B3: Cluster determined based on average level. Corpus Callosum.

#Elbow Method
ElbSize <- fviz_nbclust(AdvDTI[,22], kmeans, method = "wss") +  #within cluster sums of squares
     labs(subtitle = "Elbow method_CC_Size")
ElbSize

#Silhouette Method
SilSize <- fviz_nbclust(AdvDTI[,22], kmeans, method = "silhouette") +
      labs(subtitle = "Silhouette method_CC_Size")
SilSize

Fornix

C1: Cluster determined based on average level and trajectory. Fornix.

#Elbow Method
Elb <- fviz_nbclust(AdvDTI[,23:24], kmeans, method = "wss",iter.max = 10000, nstart = 50, algorithm="Lloyd") +  #within cluster sums of squares
     labs(subtitle = "Elbow method_Fornix")
Elb

#Silhouette Method
Sil <- fviz_nbclust(AdvDTI[,23:24], kmeans, method = "silhouette",iter.max = 10000, nstart = 50, algorithm="Lloyd")+   #average silhouette
      labs(subtitle = "Silhouette method_Fornix")
Sil

C2: Cluster determined based on trajectory. Fornix.

#Silhouette Method
SilShape <- fviz_nbclust(AdvDTI[,23], kmeans, method = "silhouette", iter.max = 10000, nstart = 50, algorithm="Lloyd") +
      labs(subtitle = "Silhouette method_Fornix_Shape")
SilShape

#Elbow Method
ElbShape <- fviz_nbclust(AdvDTI[,23], kmeans, method = "wss", iter.max = 10000, nstart = 50, algorithm="Lloyd") +  #within cluster sums of squares
     labs(subtitle = "Elbow method_Fornix_Shape")
ElbShape

C3: Cluster determined based on average level. Fornix.

#Silhouette Method
SilSize <- fviz_nbclust(AdvDTI[,24], kmeans, method = "silhouette", iter.max = 10000, nstart = 50, algorithm="Lloyd") +
      labs(subtitle = "Silhouette method_Fornix_Size")
SilSize

#Elbow Method
ElbSize <- fviz_nbclust(AdvDTI[,24], kmeans, method = "wss",iter.max = 10000, nstart = 50, algorithm="Lloyd") +  #within cluster sums of squares
     labs(subtitle = "Elbow method_Fornix_Size")
ElbSize

ATR

D1: Cluster determined based on average level and trajectory. ATR.

#Elbow Method
Elb <- fviz_nbclust(AdvDTI[,25:26], kmeans, method = "wss") +  #within cluster sums of squares
     labs(subtitle = "Elbow method_ATR")
Elb

#Silhouette Method
Sil <- fviz_nbclust(AdvDTI[,25:26], kmeans, method = "silhouette")+   #average silhouette
      labs(subtitle = "Silhouette method_ATR")
Sil

D2: Cluster determined based on trajectory. ATR.

#Silhouette Method
SilShape <- fviz_nbclust(AdvDTI[,25], kmeans, method = "silhouette") +
      labs(subtitle = "Silhouette method_ATR_Shape")
SilShape

#Elbow Method
ElbShape <- fviz_nbclust(AdvDTI[,25], kmeans, method = "wss") +  #within cluster sums of squares
     labs(subtitle = "Elbow method_ATR_Shape")
ElbShape

D3: Cluster determined based on average level. ATR.

#Silhouette Method
SilSize <- fviz_nbclust(AdvDTI[,26], kmeans, method = "silhouette") +
      labs(subtitle = "Silhouette method_ATR_Size")
SilSize

#Elbow Method
ElbSize <- fviz_nbclust(AdvDTI[,26], kmeans, method = "wss") +  #within cluster sums of squares
     labs(subtitle = "Elbow method_ATR_Size")
ElbSize

Ayla Pollmann - 2023

Script - Making Connections: Neurodevelopmental Changes in Brain Connectivity after Adverse Experiences in Early Adolescence