• Background
• Reference
• Code Release
• Data
• Atlas Used
• Other related papers that might interest you
• Questions

Hemispheric specialization is a fundamental characteristic of human brain organization, where most individuals exhibit left-hemisphere dominance for language and right-hemisphere dominance for visuospatial attention. While some lateralized functions are evident in other species, the human brain displays a strong, species-wide bias. Despite the evolutionary and functional significance of these asymmetries, their molecular and cellular foundations remain poorly understood. Here, we identify key neurochemical and cellular asymmetries that underpin cortical lateralization. Specifically, we demonstrate lateralized gradients in neurotransmitter receptor densities, particularly along the acetylcholine-norepinephrine axis, as well as asymmetries in mitochondrial distribution and the spatial prevalence of microglia and glutamatergic excitatory neurons. Using a multimodal approach that integrates in vivo functional MRI, PET imaging, and post-mortem transcriptomic and cellular data, we delineate two distinct cortical clusters: a left-lateralized network centered on language processing and a right-lateralized network supporting visuospatial attention. These results highlight a biologically embedded substrate for lateralized cognition that may inform both evolutionary theory and our mechanistic understanding of neuropsychiatric illnesses characterized by disrupted lateralization.

For usage of the manuscript, please cite:

• Labache, L., Chopra, S., Zhang (张喜寒), X-H., & Holmes, A. J. (2025). The molecular and cellular underpinnings of human brain lateralization. BioRxiv. DOI: 10.1101/2025.04.11.648388

For usage of the associated code, please also cite:

• Labache, L. (2025). The molecular and cellular underpinnings of human brain lateralization. loiclabache/Labache_2025_MolCelLat. DOI: 10.5281/zenodo.15207454

The Script folder includes five R scripts. These R scripts are designed to facilitate the replication of results as detailed in the Method Section of the manuscript.

• 1_CCA.R: R script to conduct the Canonical Correlation Analysis (CCA) to assess the functional cortical lateralization – neurotransmitters density asymmetries associations.
• 2_MolecularPhenotypes_Analysis.R: R script to identify the molecular biomarkers spatially correlated to the acetylcholine-norepinephrine axis.
• 3_CellularSubtypes_Analysis.R: R script to explore the multimodal cellular underpinning of the acetylcholine-norepinephrine axis.
• 4_NetworkProfil_Analysis.R: R script to identify the mitochondrial and cellular fingerprints of large-scale brain networks.
• 5_SørensenDiceIndex_NetworksComparison.R: R script to compute similarities between the identified clusters’ topography and a set of task-defined networks using the Sørensen-Dice index (SDI).

Note that the R scripts also contain the code to reproduce the figures found in the manuscript. The brain renderings in the paper require Surf Ice.

All the data necessary to reproduce the results are available in the Data folder.

• 4tasks_typicalStrong_370ROIs_AICHA.csv corresponds to the average brain activity of 125 strongly typical participants (see Labache, L., et al. 2020) during three language tasks and a visuospatial attention task in each of the 370 regions of the AICHA atlas. 4tasks_typicalStrong_185ROIs_AICHA_asym.csv corresponds to the asymmetry for each of the 185 regions of the AICHA atlas during these four tasks.

• 19neurotransmitters_163ROIs_AICHA_asym_zScored.csv corresponds to the asymmetry of the 19 neurotransmitter systems maps (see Hansen, J. Y., et al. 2022) for each of the 163 regions of the AICHA atlas. 19neurotransmitters_384ROIs_AICHA_zScored.csv corresponds to the left and right values of the 19 neurotransmitter maps for each of the 384 regions of the AICHA atlas.

• 24_CellularSubtypes_304ROIs_AICHA_zscored.csv corresponds to 24 cell-type maps (see Zhang, X-H., et al. 2024) for each of the 304 regions of the AICHA atlas.

• MitoDMap_384ROIs_AICHA_zscored.csv, MRC_384ROIs_AICHA_zscored.csv, and TRC_384ROIs_AICHA_zscored.csv corresponds to three mitochondrial phenotypes maps (see Mosharov, E. V., et al. 2025) for each of the 384 regions of the AICHA atlas.

• modeOne_CCA_163ROIs_AICHA.csv corresponds to the CCA weights (assymetries) for the neurotransmitter and task modes for each of the 163 regions of the AICHA atlas.

• SynapticDensityMap_384ROIs_AICHA_zscored.csv corresponds to the synaptic density map (see Johansen, A., et al. 2024) for each of the 384 regions of the AICHA atlas.

The atlases used in the paper are available in the Atlas folder.

• Atlas/AICHA contains the AICHA atlas, a functional brain ROIs atlas (384 brain regions) based on resting-state fMRI data acquired in 281 individuals. AICHA regions cover the whole brain, each regions are characterized by: 1) their homogeneity of its constituting voxels intrinsic activity, and 2) a unique homotopic contralateral counterpart with which it has maximal intrinsic connectivity. Full description of the atlas can be found there: AICHA, and the related paper there: Joliot, M., et al. 2015.
  • The version of AICHA used in the paper corresponds to the file AICHA.nii (MNI ICBM 152 space). AICHA_description.txt is a description of each atlas’ regions. comparison_AICHA_Yan2023_400_2mm.txt provides the correspondance between the AICHA regions and the seven canonical intrinsic network as defined by Yan and colleagues Yan, X., et al. 2023. The compressed file permutation_23k_AICHA.zip contains the files permutation_23k_AICHA_Seed1893.csv and permutation_23k_AICHA_Seed1942.csv. Those are null maps used during the “spin test”. They have been generated with the netneurotools Python toolbox (release 0.2.5).
• Atlas/ALANs contains ALANs, an atlas of the Lateralized visuospatial Attentional Networks in standardized MNI volume space (ALANs_MNI_ICBM_152_2mm.nii).
  • The related paper can be found there: Labache, L., et al. 2024. ALANs_description.txt is a description of each atlas’ regions.
• Atlas/SENSAAS contains SENSAAS, an atlas of the SENtence Supramodal Areas AtlaS in standardized MNI volume space (SENSAAS_MNI_ICBM_152_2mm.nii).
  • The related paper can be found there: Labache, L., et al. 2019. SENSAAS_description.txt is a description of each atlas’ regions.
• Atlas/Yan2023_v0283 contains the version of the atlas from Yan and colleagues used in this work (400Parcels_Yeo2011_7Networks_FSLMNI152_2mm.nii.gz, version 0.28.3). See their Github repository for more relevant information.
  • The related paper can be found there: Yan, X., et al. 2023. 400Parcels_Yeo2011_7Networks_LUT.txt is a description of each atlas’ regions.
• The file Atlas/Cognitive_Atlases.txt corresponds to the association of each AICHA region with one of the four atlases of lateralized cognitive functions: ALANs, HAMOTA, SENSAAS, and WMCA.

• Sentence Supramodal Areas Atlas; Labache, L., et al. 2019. DOI: 10.1007/s00429-018-1810-2, and related GitHub repository: SENSAAS
• Lateralized visuospatial Attentional Networks; Labache, L., et al. 2024. DOI: 10.1162/imag_a_00208, and related GitHub repository: ALANs
• The cell-type underpinnings of the human functional cortical connectome; Zhang, X-H., et al. 2025. DOI: 10.1038/s41593-024-01812-2, and related GitHub repository: human-cellular-func-con
• A human brain map of mitochondrial respiratory capacity and diversity; Mosharov, E. V., et al. 2025. DOI: 10.1038/s41586-025-08740-6
• Influence of Language Lateralisation on Gradient Asymmetry: Labache, L., et al. 2023. DOI: 10.1038/s41467-023-39131-y, and related GitHub repository: Labache_2022_AO

Please contact me (Loïc Labache) at: loic.labache@rutgers.edu and/or loic.labache@ensc.fr