Abstract
Mapping of axon trajectories is crucial for understanding brain organization. Using whole-brain high-throughput fluorescence imaging, we developed a cytoarchitecture-based link estimation (CABLE) method for accurate fiber tract mapping at cellular resolution. This method infers the fiber direction from the inherent anisotropy of the nucleus or soma shape and spatial arrangement of adjacent cells. The inferred fiber tracts were validated by tracing virally labeled individual axons in the monkey brain. This CABLE method could disentangle complex intersecting or bending fibers that were uncertain in diffusion magnetic resonance imaging tractography, allowing accurate brain-wide fiber tract reconstruction in marmoset and macaque brains. Finally, we applied CABLE for rapid mapping of axon fiber abnormalities in diseased neonatal human brain tissues, establishing a path for high-resolution brain mapping of fiber tracts in the human brain.
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Data availability
The complete image datasets for macaque, marmoset, human and mouse brains exceed 300 TB in total size and are therefore impractical to upload in full to a public data repository. A subset of the data is available at https://cable.bigconnectome.org, including: demo datasets for testing the CABLE analysis code; a representative slice image of the macaque brain (RM009) used in Fig. 1c; the Stereo-seq dataset analyzed in Fig. 2, Extended Data Figs. 5 and 6 and Supplementary Figs. 9–11; and a multimodal marmoset brain dataset (CJ004) used in Figs. 3 and 4. Additional datasets related to any figure or video in this work are available from the corresponding author upon reasonable request, using feasible data transfer methods such as physical hard drives, cloud storage or on-site access.
Code availability
The code and installation guide for CABLE analysis can be found at the GitHub repository (https://github.com/BrainCABLE) under the MIT License. A frozen version of the code has been archived on Zenodo (https://doi.org/10.5281/zenodo.17092643)87. A step-by-step protocol for using CABLE analysis in various datasets has been deposited on the protocols.io repository88.
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Acknowledgements
We thank X. Qi, C. Liu, S. Li, X. Zou, R. Li, Y. Cai and F. Wu for experimental support; L. Ding, Z. Yi and H. Xia for software and computing resources maintenance; C. Xu, G. Wang and J. Xi for help with viral injections; and S. Chen for valuable suggestions on the paper. We thank the Single Cell Typing Platform and Non-human Primate Anatomical Research Platform of CEBSIT for assisting with marmoset transcriptomic data collection; thank the 9.4T MRI core facility of CEBSIT for assistance in the MRI imaging; and thank the Marmoset Animal Facility of CEBSIT for animal care. This work was supported by the STI 2030-Major Projects (2022ZD0205200 to F.X. and Y.X.; 2025ZD0219300 and 2022ZD0205000 to C.L.; 2021ZD0200104 to P.-M.L.), Shenzhen Science and Technology Program (RCYX20210706092100003 to F.X.), Shenzhen Medical Research Funds grant (A2303005 to F.X.), National Natural Science Foundation of China grants (32171088 and 32427802 to C.L.; T2522040 to F.X.), a Youth Innovation Promotion Association CAS grant (2022367 to F.X.) and the National Key R&D Program of China (2022YEF0203200 to G.-Q.B.).
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Conceptualization: F.X., C.L. and Y.X.; Formal analysis: Y.Z. and T.S.; Funding acquisition: F.X., C.L., Y.X., P.-M.L. and G.-Q.B.; Investigation: Y.S. (acquisition of VISoR data of macaque and human brains), Y.Y. (acquisition of VISoR data of marmoset brains), Xiaowei Hu (immunostaining and mouse HIE data acquisition), L.T., C.J. (mouse HIE model), C.-Y.Y. (prototype of structure tensor analysis), H.W. (human brain sample preparation), X.W., H.L. and H.Y. (viral labeling of marmoset brain); Methodology: Y.Z., T.S. and C.-Y.Y.; Project administration: F.X. and C.L.; Resources: J.-N.Z., H.H., X.W. (human brain samples) and Xintian Hu (macaque brains); Software: C.-Y.Y., R.Z., W.W., Y.L. and P.Z.; Supervision: F.X., C.L., Y.X. and G.-Q.B.; Writing—original draft: C.L., F.X., Y.Z. and T.S.; Writing—review and editing: C.L., F.X., Y.Z., T.S., Y.X. and M.-M.P.
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Extended data
Extended Data Fig. 1 ODF calculation with CABLE analysis.
CABLE extracts local image gradients from each pixel in the cytoarchitectonic image to construct the directional scattering density function (DSDF). Gradients within a local analysis window (illustrated by a grid cell) are aggregated into a single DSDF voxel. Spherical deconvolution is then applied to the DSDF to generate orientation distribution functions (ODF), which recover underlying fiber orientations in both unidirectional (for example, corpus callosum, cc) and crossing (for example, cingulum, cg) fiber regions.
Extended Data Fig. 2 Comparison of orientation detection methods based on image gradient or structure tensor in the fiber-crossing regions.
(a) A raw Nissl-stained section of a macaque hemibrain. (b-c) Visualization of cODFs in the area within the white rectangle in (a) by our gradient-based method (b) and the structure tensor (ST)-based method (c), showing similar results at the macroscopic scale. (d-f) Magnified views of the regions indicated in (b-c) and their corresponding raw images. The left column presents raw image within corpus callosum (d) and corona radiata (e-f). The middle and right columns show the gradient-ODFs (d’-f’) and ST-ODFs (d”-f”). Each ST-ODF gathered ST orientations in a region of 80×80×80 µm3, where each ST was calculated from a nonoverlapping 16×16×16 µm3 window.
Extended Data Fig. 3 Anisotropic cellular shape substantially contributes to cytoarchitectonic orientation estimation.
(a) An image of the marmoset corpus callosum, with a bar plot showing the distribution of cellular anisotropy within a representative local region. Fractional anisotropy was computed from ellipsoid-fitted cell masks. The inset illustrates the gradient distribution for a cell with FA = 0.6 (90th percentile), and that after rotated by the half-maximum width ( ~ 26°, in blue). (b) Binary mask of segmented cells in the original image. (c) Simulated data in which each segmented cell is replaced by a sphere of equal volume, keeping their spatial positions unchanged. (d) Comparison of orientation coherence between (b) and (c), assessed via structure tensor analysis. ***, P < 0.001, n = 98,587 sliding analysis windows, two-sided Mann-Whitney U test, p < 1e-300.
Extended Data Fig. 4 CABLE analysis of the thalamus and cortex of a newborn marmoset.
(a) A coronal-section view of cODFs derived from a newborn marmoset. (b) Enlarged coronal view of the thalami (upper left) with CABLE tractography (lower left) and the corresponding sagittal view (right). The dashed lines indicate the direction of the left-right fibers of the thalamus. (c-e) Enlarged views of several cortical areas. Dashed lines indicate the border of the meninges and cortical layer I.
Extended Data Fig. 5 Orientation coherence analysis and neuron subtype classification on the cortical area.
(a) Illustration showing the color mapping of relative radial position (laminar depth) and tangential position in the cortex region of T472 marmoset brain section. (b) 3D lines depicting the median orientations of neurons and glial cells changing similarly along the tangential axis. Each position on the 3D line represents a tangential position along the ascending tangential axis and the cellular orientation at that position, which is indicated by its projection to the bottom circle. (c) Violin plot showing significant high orientation coherence in both cortical neurons (NEU) and glial cells (GLIA), while the cortical neurons have a higher orientation coherence. n = 31,980 (NEU), n = 13,503 (GLIA). *** indicates P < 0.001 with two-sided Mann–Whitney U-test between NEU and GLIA, and between NEU/GLIA groups and the simulation group (random), n = 31,980 [NEU], 13,503 [GLIA], 254,530 [random]; P = 6.16e-178 [NEU-GLIA], less than 1.00e-300 [NEU-random], 2.22e-263 [GLIA-random]. The embedded box plots in violin plots indicate the median (central white horizontal line) and the interquartile range (25th and 75th percentiles, box edges). Whiskers, minima and maxima outside this range are not shown. (d) UMAP scatter plot of cortical neuron subtypes. The single-nucleus RNA sequencing dataset was used for the annotation of subtypes on spatial transcriptome sections. Each neuron subtype is colored according to its preferred laminar depth distribution as indicated in (g). (e) Mapping of neuron subtypes (01_I to 18_E) on spatial transcriptome slices T473 and T558. (f) Dot plot showing marker gene expression profiles of each neuron subtype (numbered from 01 to 18, and E for excitatory neurons and I for inhibitory neurons). (g) Relative radial position distribution (layer 1 to layer 6, L1-L6) of all neuron subtypes.
Extended Data Fig. 6 Orientation coherence analysis in sections T473 and T558.
(a) Contours of manually segmented cortex and white matter. (b) Violin plots showing high orientation coherence of all four glial cell types in segmented white matter regions. (c) Violin plots showing high orientation coherence of both white matter cells and cortical cells, while the cortical cytoarchitectonic orientation coherence is lower than the white matter (WM). (d) Violin plots showing high orientation coherence in both cortical neurons (NEU) and glial cells (GLIA), while the cortical neurons have a higher orientation coherence than glial cells. (e) Distribution of orientation coherence for neuron subtypes with null model comparisons, calculated from section T473 and T558. In (b-e), * P < 0.05, ** P < 0.01 and *** P < 0.001 (two-sided Mann–Whitney U-test). For the section T473, n = 4,966 [OLI], 134 [AST], 142 [OPC], 173 [MIC], 10,472 [WM], 103,070 [Cortex], 32,747 [NEU], 13,286 [GLIA], 684 [01_I], 766 [05_I], 870 [03_I], 137 [02_I], 412 [07_I], 1,751 [17_E], 704 [13_E], 1,723 [06_I], 875 [18_E], 12,499 [04_E], 587 [11_E], 2,011 [16_E], 561 [14_E], 1,745 [09_I], 4,995 [10_E], 57 [08_I], 2,035 [12_E], 321 [15_I], 238,500 [random]; P values (vs. random unless noted): <1.0e-300 [OLI], 2.6e-23 [AST], 2.9e-22 [OPC], 2.6e-21 [MIC], 5.8e-01 [OLI-AST], 3.0e-01 [OLI-OPC], 8.3e-03 [OLI-MIC], 6.6e-01 [AST-OPC], 1.5e-01 [AST-MIC], 3.3e-01 [OPC-MIC], 3.2e-242 [WM-Cortex], less than 1.0e-300 [WM], less than 1.0e-300 [Cortex], 2.9e-167 [NEU-GLIA], <1.0e-300 [NEU], 1.8e-250 [GLIA], 3.3e-69 [01_I], 2.6e-54 [05_I], 4.4e-84 [03_I], 4.8e-15 [02_I], 3.4e-40 [07_I], 1.0e-138 [17_E], 7.5e-60 [13_E], 4.3e-133 [06_I], 8.1e-67 [18_E], <1.0e-300 [04_E], 3.0e-41 [11_E], 1.6e-144 [16_E], 6.7e-36 [14_E], 7.4e-105 [09_I], 5.4e-282 [10_E], 1.5e-03 [08_I], 4.9e-110 [12_E], 5.4e-19 [15_I]. For the section T558, n = 5,490 [OLI], 224 [AST], 265 [OPC], 208 [MIC], 13,120 [WM], 182,721 [Cortex], 61,452 [NEU], 19,011 [GLIA], 955 [01_I], 1,299 [03_I], 23,175 [04_E], 224 [02_I], 1,262 [11_E], 3,276 [09_I], 3,036 [06_I], 1,249 [05_I], 724 [07_I], 3,596 [17_E], 1,652 [14_E], 2,195 [18_E], 3,512 [16_E], 3,986 [12_E], 592 [15_I], 1,351 [13_E], 9,048 [10_E], 265 [08_I], 480,791 [random]; p values (vs. random unless noted): <1.0e-300 [OLI], 8.3e-54 [AST], 1.4e-66 [OPC], 1.0e-44 [MIC], 4.1e-02 [OLI-AST], 9.3e-02 [OLI-OPC], 5.2e-01 [OLI-MIC], 7.3e-01 [AST-OPC], 5.0e-02 [AST-MIC], 9.0e-02 [OPC-MIC], <1.0e-300 [WM-Cortex], less than 1.0e-300 [WM], less than 1.0e-300 [Cortex], 7.4e-145 [NEU-GLIA], <1.0e-300 [NEU], 1.2e-257 [GLIA], 3.5e-72 [01_I], 4.5e-106 [03_I], <1.0e-300 [04_E], 1.3e-16 [02_I], 8.6e-57 [11_E], 1.5e-140 [09_I], 5.2e-127 [06_I], 3.2e-48 [05_I], 5.2e-36 [07_I], 1.9e-143 [17_E], 2.5e-58 [14_E], 7.0e-85 [18_E], 4.5e-121 [16_E], 1.9e-124 [12_E], 3.6e-19 [15_I], 4.5e-31 [13_E], 4.9e-178 [10_E], 5.2e-09 [08_I]. The embedded box plots in violin plots indicate the median (central white horizontal line) and the interquartile range (25th and 75th percentiles, box edges). Whiskers, minima and maxima outside this range are not shown.
Extended Data Fig. 7 Various types of glial cells exhibit coherent alignment with cytoarchitectonic orientation.
(a) First row: Co-staining of ASPA (green; mature oligodendrocyte marker) and SOX10 (magenta; marker of all oligodendrocyte lineage cells) in the mouse corpus callosum (CC); Second row: ASPA/SOX10 images merged with virus-labeled axons in cyan. Cells positive for SOX10 but negative for ASPA (magenta only) are presumptive OPCs. Third row: Co-staining of NG2 (magenta; direct OPC marker) and DAPI (white) in the mouse fimbria. Magenta and green dotted lines indicate the local orientations of OPCs (SOX10⁺/ASPA⁻ or NG2⁺) and overall cell populations (SOX10⁺ or DAPI⁺), respectively. Fourth row: Quantification of orientation coherence in the CC and fimbria shows no significant difference between OPCs and mature oligodendrocytes in the CC (P = 0.54, n = 20), or between OPCs and DAPI-labeled nuclei in the fimbria (P = 0.66, n = 25). (b–c) Co-staining of GFAP (astrocytes), Nissl, and Lectin (vasculature) in the mouse CC (b) and fimbria (c). Red line segments indicate local orientations derived from astrocytes (AST), Nissl (Overall), and vasculature (VAS). No significant difference was observed between AST and Nissl in either region (P = 0.43, n = 117 for CC; P = 0.38, n = 30 for fimbria). AST and VAS orientations differed slightly in the CC (P = 0.04, n = 117) and fimbria (P = 0.03, n = 30). VAS and Nissl orientations were significantly different in both CC (P = 0.002, n = 117) and fimbria (P = 0.003, n = 30). (d) Co-staining of IBA1 (microglia) and Nissl in the mouse CC. Red line segments indicate local orientations of microglia (MIC) and Nissl-inferred overall orientation. No significant difference was found between MIC and Nissl orientations (P = 0.55, n = 64). Two-sided Mann–Whitney U tests were used for all statistical comparisons. Violin plots show the distribution of orientation values using kernel density estimation. The embedded box plots indicate the median (central line), the interquartile range (25th and 75th percentiles; box edges), and the whiskers represent data within 1.5×IQR from the quartiles. Minima and maxima outside this range are not shown.
Extended Data Fig. 8 Comparison of CABLE with other methods for macaque brain mapping.
(a) Comparative visualization of occipital white matter fiber architecture using CABLE, PLI, and dMRI techniques. CABLE (left) delineates distinct white matter structures (medial to lateral): stratum calcarinum (strk), cingulum (cg), inferior forceps (if), forceps major (mf), sagittal stratum (ss), and vertical occipital fasciculus (vof). In dMRI images, the gap between strk and cg is hardly discernible. (b-c) Depiction of the ventral hippocampal commissure (vhc; red box) and medial longitudinal striae (ls; green box) by CABLE (b) and PLI (c). (d) Representative images of CABLE and dMRI ODFs in the macaque cerebellum. The lower row presents magnified views of the areas outlined in the upper row.
Extended Data Fig. 9 CABLE-derived tractograms in the rhesus monkey and human brains.
(a) Coronal view of a CABLE-derived tractogram in the macaque brain. (b) Tractogram of another coronal section of macaque brain, highlighting the corona radiata (middle) and internal capsule (lower). (c) Sagittal view of DAPI-stained macaque brainstem (left) with the box region enlarged (middle). Corresponding CABLE-derived tractogram (right) illustrates the interweaving between the pyramidal tract (PT) and the preculminate fissure (pcf). (d) Coronal view of an adult human brain tissue block from epilepsy surgery (left) and its corresponding CABLE-derived tractogram (right).
Supplementary information
Supplementary Information
Supplementary Note 1, Tables 1–3 and Figs. 1–16
Supplementary Video 1
Whole-brain imaging and reconstruction of a macaque brain reveals the structured cytoarchitectonic organization.
Supplementary Video 2
Comparison between axonal and cytoarchitectonic orientation in a marmoset brain. Multichannel imaging provides side-by-side comparison of the cytoarchitectonic organization (green, labeled with DAPI) and the axon traces (white, sparsely labeled with whole-brain viral tracing). The whole marmoset brain was imaged and reconstructed with the SMART pipeline. The corpus callosum region is enlarged to show high-resolution images of axons and adjacent cells oriented and arranged in the same direction as the axons.
Supplementary Video 3
Comparison of axon tracts and CABLE-derived tractogram in the marmoset brain.
Supplementary Video 4
Brain-wide CABLE-based tractography of a macaque brain.
Supplementary Video 5
Axonal fiber tracing showing turns of the cortical pyramidal neurons.
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Zhang, Y., Song, T., Yang, CY. et al. Whole-brain reconstruction of fiber tracts based on cytoarchitectonic organization. Nat Methods (2025). https://doi.org/10.1038/s41592-025-02865-2
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DOI: https://doi.org/10.1038/s41592-025-02865-2