Large-Scale Functional Brain Network Organization Is Largely Preserved in Neuropathic Pain Despite Selective Circuit-Level Adaptations - Dataset-1

This depository is a part (one of of two depositories) of the daset of our article entitled ‘Large-Scale Functional Brain Network Organization Is Largely Preserved in Neuropathic Pain Despite Selective Circuit-Level Adaptations’, accepted for publication in the journal Cummunications Biology in August 2026. The uploaded dataset consists of Python scripts for functional connectivity (FC) results visualization and functional ultrasound (fUS) imaging data. 1. Imaging data The fUS imaging data are divided into two main experimental conditions: Anesthetized and Awake. A total of 20 Microsoft Excel (.xlsx) files are provided, organized as follows: Inclusion Table: This file contains the inclusion criteria for all animals included in the study. It is divided into two worksheets corresponding to the Anesthetized and Awake datasets. VonFrey_test_data: This file contains the results of the Von Frey behavioral assay. Data are organized into two worksheets, one for the Anesthetized condition and one for the Awake condition. Timepoint_Group_Condition: The remaining Excel files contain individual Z-scored functional connectivity correlation matrices, organized according to experimental group (NAIVE, SHAM, NP), time point (T0, 2W, 8W, 12W), and experimental condition (Anesthetized or Awake). Each worksheet contains the correlation matrix of a single subject. 2. Python scripts Three Python scripts used to visualize functional connectivity (FC) results, either as heatmaps or circular connectivity diagrams, are provided together with a README file. · batch_correlation_heatmaps_v5_coolwarm.py generates square functional connectivity matrices (heatmaps) using the perceptually uniform coolwarm colormap from symmetric correlation matrices stored in Microsoft Excel (.xlsx) files. The script automatically creates an output directory containing PDF, SVG, and PNG figures (600 dpi), averaged matrices (CSV format), a color bar, and a processing summary. · circular_connectivity_awake_18ROI.py generates circular functional connectivity diagrams using the perceptually uniform coolwarm colormap from symmetric correlation matrices stored in Microsoft Excel (.xlsx) files. It is designed for 18 unilateral regions of interest (ROIs). The script automatically creates an output directory containing PDF, SVG, and PNG figures (600 dpi), averaged matrices (CSV format), a color bar, and a processing summary. · circular_connectivity_anesthetized_40ROI.py generates circular functional connectivity diagrams using the perceptually uniform coolwarm colormap from symmetric correlation matrices stored in Microsoft Excel (.xlsx) files. It is designed for 40 bilateral regions of interest (ROIs). The script automatically creates an output directory containing PDF, SVG, and PNG figures (600 dpi), averaged matrices (CSV format), a color bar, and a processing summary.