Extended Data Fig. 7: ROI-based spontaneous activity mapping of the PFC and correlation with intra-PFC hierarchy.
From: A prefrontal cortex map based on single-neuron activity
a, Flatmap of the PFC with subregions (black outlines) parcellated into 42 regions of interest (dataROIs, white outlines) and identified by an ID number. Box: enlargement of the corresponding box on the flatmap. The color gradient visualizes unit count (ww units, L5–6) per ROI. b, PFC flatmaps with dataROIs (black outlines) colored according to enrichment in ww units of category 2–7. c, Clustering of PFC dataROIs into activity modules based on their category enrichment profiles. Top to bottom, hierarchical tree derived from enrichment profiles; dataROI ID numbers; PFC subregion identity of the dataROIs (color-coded as in Fig. 4b); activity modules (A–E); category enrichment profile of dataROIs. d, Criteria for determining a suitable number of clusters when partitioning the PFC flatmap into modules based on the dataROI’s category enrichment profiles (c). Red dashed line: the five clusters (modules) used. Top, Euclidean distance in standardized metric space between the last pair of clusters joined as a function of the number of modules defined during hierarchical clustering (read graph from right to left). Lower values indicate more homogenous clusters47. Bottom, Dunn index as a function of the number of clusters. The Dunn index is the ratio between minimal between-cluster distance and maximal within-cluster distance, with a higher Dunn index implying more compact and well-separated clusters48. e, Flatmap of the PFC colored according to the count of ww units (deep layers, L5–6) per GaoROI (gray outlines). Each GaoROI is identified by an ID number. GaoROIs with fewer than 20 units (white) were not included in analyses. f, Clustering of PFC GaoROIs into activity modules based on their category enrichment profiles. Top to bottom, hierarchical tree derived from enrichment profiles; GaoROI ID numbers; PFC subregion identity of the GaoROIs (color-coded as in Fig. 4f); activity modules (A–E); category enrichment profiles of GaoROIs. g, Same as d, but for clustering of GaoROIs. h, PFC flatmap with GaoROIs colored according to activity module. i, Data availability for correlations of E-scores with intra-PFC hierarchy using the GaoROI parcellation of the PFC (Fig. 4g and j–p). GaoROIs with both intra-PFC hierarchy score and category enrichment profile ( ≥ 20 units available) are colored according to the PFC subregion (Fig. 4a) where most of the units were located. Gray: no intra-PFC hierarchy score and too low (n < 20) unit count; white: intra-PFC hierarchy score but too low (n < 20) unit count; dark gray: sufficient number of units (n ≥ 20) but no intra-PFC hierarchy score. j–p, Correlation between enrichment in unit categories (2–8) and intra-PFC hierarchy score. One dot per GaoROI, colors as in i. Gray line: least-squares regression. Statistics: Pearson correlation, two-sided p-values, n = 30. Data: dataset KI, PFC ww units, deep layers (L5–6), n = 9,284 units. Intra-PFC hierarchy scores from Gao et al.10.
