The Neurome Project

In humans, in other mammals, and in complex multicellular organisms in general, evolved cellular diversity is nowhere more evident than in the nervous system [1], whose nerve cells, or neurons, are necessary for the perception of sensation and feeling, the encoding and retrieval of memories, and the control of behavior and emotion—activities that are essential for individual and species survival. Charged with such varied and critical tasks, neurons may be thought of as the stars of the cellular universe, not only for their intrinsic diversity of form and function, but also because collectively, in the brain and nervous system, neurons are the primary cellular units of the single most complex biological system known to exist.

The Neurome Project aims to determine the organization of neuronal connections between the different parts of the nervous system—a connectome [2] for each part—with the eventual goal of obtaining a network map for the entire nervous system—a neurome [3]—composed of all subconnectomes, and including connections between neurons and non-neuronal cells [4]. Our current analysis is at a macroscale level of granularity—that is at the level of gray matter regions (a macroconnection [5] is a connection between two gray matter regions). 

Pan-mammalian applicability is central to our approach, with analysis of regional connections limited to brain regions with indicated representation across Mammalia. We selected the rat as a model mammal because it is the mammal for which the most comprehensive published connection data exists, and because analysis of this data is supported by a rat brain reference atlas that is ideally suited to these efforts [6].

The nervous system has 11 major parts or divisions (figure at top: including the intracranial central nervous system, spinal cord, and peripheral ganglia—the latter counted together), giving a total of 242 possible subconnectomes, including within and between each part (left / right side independent). Our data-driven approach combines rigorous analysis of connection reports (e.g. [7]) with current informatics and computational network analysis methods (e.g. [8]).

To date, our research has revealed principles of brain circuit organization for the mammalian forebrain: cerebral nuclei (or basal ganglia) [9] and cerebral cortex [10] and their combined structure—endbrain [11]; hypothalamus [12], thalamus [13] and their combined structure—interbrain [14]; the combined structure of the cerebral nuclei, cerebral cortex, hypothalamus, and thalamus—forebrain [15]; the midbrain [16]; the combined forebrain and midbrain—rostral sector [17]; the combined pons, cerebellum, and medulla (or afterbrain)—intermediate sector [22]; and the spinal cord—caudal sector [23].

The proximal goal of the Neurome Project was to complete construction and network analysis of macroconnection subconnectomes for the mammalian forebrain—a goal we achieved in 2020, within 5 years from project inception. Our distal goal is to achieve this for the rest of the brain, and eventually the entire nervous system, leading to integration with other brain data (such as gene-expression) at multiple levels of spatial resolution [4]. Through this work and our related efforts [18-21, for example] we seek to develop better models, and a clearer understanding, of the brain and nervous system.

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): E2093-2101. 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. Swanson, L.W. (2018). J Comp Neurol. 526(6): 935-943. DOI: 10.1002/cne.24381

7. Hahn, J.D. & Swanson, L.W. (2015). Distinct patterns of neural inputs and outputs of the dorsal and ventral zones of the juxtaventromedial region of the lateral hypothalamic area in the male rat. Front Syst Neurosci. 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. (2018) 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

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).