The Neurome Project

In humans and other animals, the evolved diversity of cell types is perhaps most striking in the nervous system [1]. Neurons—nerve cells responsible for sensation, memory, behavior, and emotion—are essential for individual survival and species adaptation. Given the breadth and precision of their roles, neurons may be regarded as the stars of the cellular universe: not only for their intrinsic diversity of form and function, but also because, collectively, they constitute the primary cellular units of one of the most complex biological systems known.

The Neurome Project seeks to elucidate the network organization of neuronal connections across the nervous system by constructing a connectome [2] (wiring diagram) and neuronal network models for each major part, combined parts, the whole nervous system, and ultimately including connections between the nervous system and the other systems of the body: a neurome [3] (see figure above). The neurome encompasses neuron-to-neuron connections as well as interactions between neurons and non-neuronal cells [4]. Our current analyses operate at the macroscale, focusing on gray matter regions and the macroconnections [5] that link them.

To ensure pan-mammalian relevance, our analysis is restricted to nervous system regions with established representation across Mammalia. The rat was selected as a model species because of the breadth of published connection data and the availability of a high-resolution reference atlas ideally suited to this work [6]. For the purposes of connectomic analysis, we divided the entire nervous system into 10 major parts, and treated the other systems of the body as an eleventh part (see figure above). Accounting for left-right independence and connections both within and between divisions yields 240 possible subconnectomes. Our approach integrates systematic review of published connection reports (e.g., [7]) with contemporary informatics and computational network-analysis methods (e.g., [8]).

Since the Neurome Project's initial publication [3], we have refined our analytical methods and have progressively extended our analyses across the entire nervous system. Our initial goal was to construct and analyze network models for the forebrain [3, 9–15], a milestone reached in 2020. We subsequently extended our analyses to the midbrain, rhombicbrain, spinal cord, and the whole brain [16, 17, 22–24]. In 2025, we assembled and analyzed a network model of the mammalian central nervous system (CNS) [25], followed by a model of the intrinsic neuronal network of the peripheral nervous system (PNS) [26]. Most recently, we have integrated the CNS and PNS connectomes to produce the first structure–function neuronal network model of the entire mammalian nervous system [27].

The next—and ultimate—goal of this phase of the Neurome Project is to extend the framework beyond the nervous system itself by incorporating its connections with the other (physiological) systems of the body. The resulting integrated model will provide a foundation for a comprehensive mammalian neurome and for alignment with gene expression and other neurobiological data modalities [4]. Through this work, and in parallel with related efforts in anatomical mapping and visualization [18–21], we continue to refine our models and deepen our understanding of the architecture and function of the nervous system as an integrated component of the whole organism.

References

1. Monro, A. secundus (1783). Observations on the Structure and Functions of the Nervous System: Illustrated with Tables (Creech & Johnson, Edinburgh).

2. Sporns, O., Tononi, G., Kotter, R. (2005). The human connectome: A structural description of the human brain. PLoS Comput Biol. DOI: 10.1371/journal.pcbi.0010042

3. Bota, M., Sporns, O., Swanson, L.W. (2015). Architecture of the cerebral cortical association connectome underlying cognition. Proc Natl Acad Sci USA. 112(16): E2093-E2101. DOI: 10.1073/pnas.1504394112

4. Swanson, L.W. & Lichtman, J.W. (2016). From Cajal to Connectome and Beyond. Annu Rev Neurosci. 39: 197-216. DOI: 10.1146/annurev-neuro-071714-033954

5. Swanson, L.W. & Bota, M. (2010). Foundational model of structural connectivity in the nervous system with a schema for wiring diagrams, connectome, and basic plan architecture. Proc Natl Acad Sci USA. 107(48): 20610-20617. DOI: 10.1073/pnas.1015128107

6. Swanson, L.W. (2018). Brain Maps 4.0—Structure of the rat brain: An open access atlas with global nervous system nomenclature ontology and flatmaps. J Comp Neurol. 526(6): 935-943. DOI: 10.1002/cne.24381

7. Hahn, J.D. & Swanson, L.W. (2015). Connections of the juxtaventromedial region of the lateral hypothalamic area in the male rat. Front Syst Neurosci. 9:66. DOI: 10.3389/fnsys.2015.00066

8. Jeub, L.G.S., Sporns, O., Fortunato, S. (2018). Multiresolution consensus clustering in networks. Sci Rep. 8:3259. DOI: 10.1038/s41598-018-21352-7

9. Swanson, L.W., Sporns, O., Hahn, J.D. (2016). Network architecture of the cerebral nuclei (basal ganglia) association and commissural connectome. Proc Natl Acad Sci USA. 113(40): E5972-E5981. DOI: 10.1073/pnas.1613184113

10. Swanson, L.W., Hahn, J.D., Sporns, O. (2017). Organizing principles for the cerebral cortex network of commissural and association connections. Proc Natl Acad Sci USA. 114(45): E9692-E9701. DOI: 10.1073/pnas.1712928114

11. Swanson, L.W., Hahn, J.D., Jeub, L.G.S., Fortunato, S., Sporns, O. (2018). Subsystem organization of axonal connections within and between the right and left cerebral cortex and cerebral nuclei (endbrain). Proc Natl Acad Sci USA. 115(29): E6910-E6919. DOI: 10.1073/pnas.1807255115

12. Hahn, J.D., Sporns, O., Watts, A.G., Swanson, L.W. (2019). Macroscale intrinsic network architecture of the hypothalamus. Proc Natl Acad Sci USA. 116(16): 8018-8027. DOI: 10.1073/pnas.1819448116

13. Swanson, L.W., Sporns, O., Hahn, J.D. (2019). The network organization of rat intrathalamic macroconnections and a comparison with other forebrain divisions. Proc Natl Acad Sci USA. 116(27): 13661-13669. DOI: 10.1073/pnas.1905961116

14. Swanson, L.W., Sporns, O., Hahn, J.D. (2019). The network architecture of rat intrinsic interbrain (diencephalon) macroconnections and a comparison with endbrain (telencephalon) architecture. Proc Natl Acad Sci USA. 116(52): 26991-27000. DOI: 10.1073/pnas.1915446116

15. Swanson, L.W., Hahn, J.D., Sporns, O. (2020). Structure–function subsystem models of female and male forebrain networks integrating cognition, affect, behavior, and bodily functions. Proc Natl Acad Sci USA. 117(49): 31470-31481. DOI: 10.1073/pnas.2017733117

16. Swanson, L.W., Hahn, J.D., Sporns, O. (2021). Subsystem macroarchitecture of the intrinsic midbrain neural network and its tectal and tegmental subnetworks. Proc Natl Acad Sci USA. 118(20): e2101869118. DOI: 10.1073/pnas.2101869118

17. Swanson, L.W., Hahn, J.D., Sporns, O. (2022). Structure–function subsystem model and computational lesions of the central nervous system's rostral sector (forebrain and midbrain).  Proc Natl Acad Sci USA. 119(45): e2210931119. DOI: 10.1073/pnas.2210931119

18. Swanson, L.W., Hahn, J.D. (2020). A qualitative solution with quantitative potential for the mouse hippocampal cortex flatmap problem. Proc Natl Acad Sci USA. 117(6): 3220-3231. DOI: 10.1073/pnas.1918907117

19. Swanson, L.W., Hof, P.R. (2019) A model for mapping between the human and rodent cerebral cortex. J Comp Neurol. 527(17): 2925-2927.  DOI: 10.1002/cne.24708

20. Hahn, J.D., Swanson, L.W. et al. (2021). An open access mouse brain flatmap and upgraded rat and human brain flatmaps based on current reference atlases. J Comp Neurol. 529(3): 576-594. DOI: 10.1002/cne.24966

21. Hahn, J.D., Duckworth, C. (2023) A brain flatmap data visualization tool for mouse, rat, and human.  J Comp Neurol. 531(10): 1008-1016. DOI: 10.1002/cne.25478

22. Swanson, L.W., Hahn, J.D., Sporns, O. (2023). Intrinsic circuitry of the rhombicbrain (central nervous system’s intermediate sector) in a mammal.  Proc Natl Acad Sci USA. 120(52): e2313997120. DOI: 10.1073/pnas.2313997120

23. Swanson, L.W., Hahn, J.D., Sporns, O. (2024). Network architecture of intrinsic connectivity in a mammalian spinal cord (the central nervous system's caudal sector).  Proc Natl Acad Sci USA. 121(5): e2320953121. DOI: 10.1073/pnas.2320953121

24. Swanson, L.W., Hahn, J.D., Sporns, O. (2024). Neural network architecture of a mammalian brain.  Proc Natl Acad Sci USA. 121(39): e2413422121. DOI: 10.1073/pnas.2413422121

25. Swanson, L.W., Hahn, J.D., Sporns, O. (2025). The intrinsic neuronal network of the central nervous system and its modular (subsystem) architecture in a mammal.  Proc Natl Acad Sci USA. 122(40): e2519768122. DOI: 10.1073/pnas.2519768122

26. Swanson, L.W., Hahn, J.D., Sporns, O. (2025). Intrinsic neuronal network organization of a mammalian peripheral nervous system.  Proc Natl Acad Sci USA. 122(51): e2528657122. DOI: 10.1073/pnas.2528657122

27. Swanson, L.W., Hahn, J.D., Sporns, O. (2026). A structure–function neuronal network model of the rat nervous system.  Proc Natl Acad Sci USA. [in press]

Media Coverage

Neurobiologists help untangle the brain’s life-support network (EurekAlert, March 26, 2019; USC, April 3, 2019).

Header Image: (left line diagram) A theoretical prototypical circuit for the control of behavior involving visual sensory input, central integration, and motor output (adapted from L'Homme. René Descartes. 1664); (right line diagram) A later empirical theoretical schema for control of behavior based on neuronal architecture and connections (adapted from Les nouvelles idées sur la structure du système nerveux chez l'homme et chez les vertébrés. Santiago Ramón y Cajal. 1894). The line diagrams are overlaid on an image acquired from the Hubble space telescope in 2016. Light from the stars of several galaxies is visible in a field parallel to galaxy cluster Abell S1063, located some 4 billion light years distant to planet Earth (coincidentally about the same period of time since the earliest appearance of life on Earth).