Fig. 4: Behavioral Tractography Analysis across six bundles, describing consistent behavioral trajectories across High-vs-Low Intensity and Predominant Positive-vs-Negative subgroups. | npj Digital Medicine

Fig. 4: Behavioral Tractography Analysis across six bundles, describing consistent behavioral trajectories across High-vs-Low Intensity and Predominant Positive-vs-Negative subgroups.

From: Shedding light on the dynamic interplay of positive and negative symptoms of psychosis with Behavioral Tractography

Fig. 4

Figures have been derived using a dedicated open-source software (https://dev.mlnetwork-diplab.ch/) developed by the authors and available at (https://github.com/andreaimparato/Behavioral-Tractography-Toolbox/tree/main/MLNetwork). For each figure, we provide a link to an online platform allowing 3D interactive network visualization. Comparison of population-specific trajectories of Behavioral Tractography (BT) Bundles (1–6) in High-Symptom-Intensity vs Low-Symptom-Intensity subgroups defined according to SIPS-Dimension-1; and Predominantly-Positive-Symptoms vs Predominantly-Negative-Symptoms subgroups defined according to SIPS-Dimension-2. 1–6 Results of Behavioral-Tractography trajectory for each of 6 Bundles in High-Symptom-Intensity (A), Low-Symptom-Intensity (B), Predominantly-Positive-Symptoms (C) and Predominantly-Negative-Symptoms (D) subgroups; Green to Yellow color coding reflects the dynamic progressing of paths from TL1 to TL2 (Start-TL1 ➔ Exit-TL1: Dark Green; Exit-TL1 ➔ Entry-TL2: Light Green; Entry-TL2 ➔ End-TL2: Yellow). 1A–1D Bundle 1: TL1-Affective-Distress➔TL2- Affective-Distress. 2A–2D Bundle 2: TL1- Cognitive-Distress➔TL2-Affective-Distress. 3A–3D: Bundle 3: TL1-Lack-Affective-Wellbeing➔TL2- Lack-Affective-Wellbeing. 4A–4D: Bundle 4: TL1- Lack-Affective-Wellbeing➔TL2-Lack-Cognitive-Wellbeing. 5A–5D: Bundle 5: TL1- Lack-Affective-Wellbeing➔TL2-Cognitive-Distress. 6A–6D: Bundle 6: TL1- Lack-Cognitive-Wellbeing➔TL2-Affective-Distress. Links to 3D interactive visualization: HSI: https://dev.mlnetwork-diplab.ch/3dvisualizer/dim1_dim1_cl1/. https://dev.mlnetwork-diplab.ch/3dvisualizer/dim1_dim1_cl2/. https://dev.mlnetwork-diplab.ch/3dvisualizer/dim1_dim1_cl3/. https://dev.mlnetwork-diplab.ch/3dvisualizer/dim1_dim1_cl4/. https://dev.mlnetwork-diplab.ch/3dvisualizer/dim1_dim1_cl5/. https://dev.mlnetwork-diplab.ch/3dvisualizer/dim1_dim1_cl6/. LSI: https://dev.mlnetwork-diplab.ch/3dvisualizer/dim1_dim2_cl1/. https://dev.mlnetwork-diplab.ch/3dvisualizer/dim1_dim2_cl2/. https://dev.mlnetwork-diplab.ch/3dvisualizer/dim1_dim2_cl3/. https://dev.mlnetwork-diplab.ch/3dvisualizer/dim1_dim2_cl4/. https://dev.mlnetwork-diplab.ch/3dvisualizer/dim1_dim2_cl5/. https://dev.mlnetwork-diplab.ch/3dvisualizer/dim1_dim2_cl6/. PNS: https://dev.mlnetwork-diplab.ch/3dvisualizer/dim2_dim1_cl1/. https://dev.mlnetwork-diplab.ch/3dvisualizer/dim2_dim1_cl2/. https://dev.mlnetwork-diplab.ch/3dvisualizer/dim2_dim1_cl3/. https://dev.mlnetwork-diplab.ch/3dvisualizer/dim2_dim1_cl4/. https://dev.mlnetwork-diplab.ch/3dvisualizer/dim2_dim1_cl5/. https://dev.mlnetwork-diplab.ch/3dvisualizer/dim2_dim1_cl6/. PPS: https://dev.mlnetwork-diplab.ch/3dvisualizer/dim2_dim2_cl1/. https://dev.mlnetwork-diplab.ch/3dvisualizer/dim2_dim2_cl2/. https://dev.mlnetwork-diplab.ch/3dvisualizer/dim2_dim2_cl3/. https://dev.mlnetwork-diplab.ch/3dvisualizer/dim2_dim2_cl4/. https://dev.mlnetwork-diplab.ch/3dvisualizer/dim2_dim2_cl5/. https://dev.mlnetwork-diplab.ch/3dvisualizer/dim2_dim2_cl6/.

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