Architecture of the cerebral cortical association connectome underlying cognition
Open accessAbstract
Cognition presumably emerges from neural activity in the network of association connections between cortical regions that is modulated by inputs from sensory and state systems and directs voluntary behavior by outputs to the motor system. To reveal global architectural features of the cortical association connectome, network analysis was performed on >16,000 reports of histologically defined axonal connections between cortical regions in rat. The network analysis reveals an organization into four asymmetrically interconnected modules involving the entire cortex in a topographic and topologic core-shell arrangement. There is also a topographically continuous U-shaped band of cortical areas that are highly connected with each other as well as with the rest of the cortex extending through all four modules, with the temporal pole of this band (entorhinal area) having the most cortical association connections of all. These results provide a starting point for compiling a mammalian nervous system connectome that could ultimately reveal novel correlations between genome-wide association studies and connectome-wide association studies, leading to new insights into the cellular architecture supporting cognition.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Neural tracer data is the gold standard for mesoscale connectivity studies in a number of model organisms.
“Neural tracer data is the gold standard for mesoscale connectivity studies in a number of model organisms (Bota et al., 2015; Girard et al., 2020; Jbabdi et al., 2015; Markov et al., 2014; 2013; Oh et al., 2014).”
From The role of spatial embedding in mouse brain networks constructed from diffusion tractography and tracer injections (2021) · cites this paper as Bota et al., 2015
The Abstract says animal histological pathway-tracing data are needed to validate diffusion tractography, and Materials and Methods describes using tracing reports for a rat cortical connectome. But the paper studies regional macroconnections, while the Discussion describes a neuron-type mesoconnectome as future work; it does not establish tracer data as the gold standard for mesoscale studies across multiple model organisms. Page numbers are unavailable in our copy. (LLM, conf=0.85)
Experimental — accuracy not yet measuredThe LEC is a functional hub for integrating multisensory information, including both spatial and non-spatial characteristics, probably even time.
“This matches the anatomical features of LEC, as being a functional hub for integrating multisensory information (Bota et al., 2015), including both spatial and non-spatial characteristics, probably even time (Tsao et al., 2018).”
From The medial prefrontal cortex - hippocampus circuit that integrates information of object, place and time to construct episodic memory in rodents: Behavioral, anatomical and neurochemical properties (2020) · cites this paper as Bota et al., 2015
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Collective dynamics of ‘small-world’ networks
Watts, D. J., & Strogatz, S. H. (1998) · Nature · doi:10.1038/30918 · Cited by 43,060 · see citing works
Complex network measures of brain connectivity: Uses and interpretations
Rubinov, M., & Sporns, O. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2009.10.003 · Cited by 11,522 · see citing works
Self-citationThe Human Connectome: A Structural Description of the Human Brain
Sporns, O., Tononi, G., & Kötter, R. (2005) · PLoS Computational Biology · doi:10.1371/journal.pcbi.0010042 · Cited by 3,260 · see citing works
Self-citationA mesoscale connectome of the mouse brain
Oh, S. W., Harris, J. A., Ng, L., Winslow, B., Cain, N., Mihalas, S., Wang, Q., Lau, C., Kuan, L., Henry, A. M., et al. (2014) · Nature · doi:10.1038/nature13186 · Cited by 2,612 · see citing works
Rich-club organization of the human connectome
van den Heuvel, M. P., & Sporns, O. (2011) · The Journal of Neuroscience · doi:10.1523/jneurosci.3539-11.2011 · Cited by 2,354 · see citing works
Self-citationNetwork hubs in the human brain
van den Heuvel, M. P., & Sporns, O. (2013) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2013.09.012 · Cited by 2,123 · cited 1× · see citing works
“more centrally connected within the network, corresponding to so-called network hubs (20, 21).”
BackgroundSelf-citationZagrean, L. (2014) · Acta Endocrinologica (Bucharest) · doi:10.4183/aeb.2014.529 · Cited by 1,926 · see citing works
Brain Maps: Structure of the Rat Brain
Swanson, L. W. (1992) · Medical Entomology and Zoology · Cited by 1,851 · see citing works
Self-citationThe Human Central Nervous System
Nieuwenhuys, R., Voogd, J., & van Huijzen, C. (2008) · doi:10.1007/978-3-540-34686-9 · Cited by 1,262 · see citing works
Identification and classification of hubs in brain networks
Sporns, O., Honey, C. J., & Kötter, R. (2007) · PLoS ONE · doi:10.1371/journal.pone.0001049 · Cited by 1,165 · see citing works
Self-citationDetecting rich-club ordering in complex networks
Colizza, V., Flammini, A., Serrano, M. A., & Vespignani, A. (2006) · Nature Physics · doi:10.1038/nphys209 · Cited by 1,001 · see citing works
Cerebral hemisphere regulation of motivated behavior
Swanson, L. W. (2000) · Brain Research · doi:10.1016/s0006-8993(00)02905-x · Cited by 846 · see citing works
Self-citationNeural Networks of the Mouse Neocortex
Zingg, B., Hintiryan, H., Gou, L., Song, M. Y., Bay, M., Bienkowski, M. S., Foster, N. N., Yamashita, S., Bowman, I., Toga, A. W., et al. (2014) · Cell · doi:10.1016/j.cell.2014.02.023 · Cited by 797 · see citing works
Analysis of connectivity in the cat cerebral cortex
Scannell, J. W., Blakemore, C. B., & Mp, Y. (1995) · Journal of Neuroscience · doi:10.1523/jneurosci.15-02-01463.1995 · Cited by 554 · see citing works
The Connectome of a Decision-Making Neural Network
Jarrell, T. A., Wang, Y., Bloniarz, A. E., Brittin, C. A., Xu, M., Thomson, J. N., Albertson, D. G., Hall, D. H., & Emmons, S. W. (2012) · Science · doi:10.1126/science.1221762 · Cited by 474 · see citing works
Nieuwenhuys, R., Voogd, J., van Huijzen, C., & Papa, M. (2010) · Springer eBooks · doi:10.1007/978-88-470-1140-3 · Cited by 364 · see citing works
Swanson, L. W., & Köhler, C. (1986) · Journal of Neuroscience · doi:10.1523/jneurosci.06-10-03010.1986 · Cited by 340 · see citing works
Self-citationRich Club Organization of Macaque Cerebral Cortex and Its Role in Network Communication
Harriger, L., van den Heuvel, M. P., & Sporns, O. (2012) · PLoS ONE · doi:10.1371/journal.pone.0046497 · Cited by 300 · see citing works
Self-citationBrain Architecture: Understanding the Basic Plan
Swanson, L. W. (2002) · Cited by 273 · see citing works
Self-citationBohland, J. W., Wu, C., Barbas, H., Bokil, H., Bota, M., Breiter, H. C., Cline, H. T., Doyle, J. C., Freed, P. J., Greenspan, R. J., et al. (2009) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000334 · Cited by 261 · see citing works
Self-citationConnectivity differences in brain networks
Zalesky, A., Cocchi, L., Fornito, A., Murray, M. M., & Bullmore, E. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.01.068 · Cited by 260 · see citing works
Mapping the human brain: past, present, and future
Swanson, L. W. (1995) · Trends in Neurosciences · doi:10.1016/0166-2236(95)92766-j · Cited by 197 · see citing works
Self-citationThe rhinal cortices: a wall of inhibition between the neocortex and the hippocampus
DECURTIS, M., & Paré, D. (2004) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2004.08.005 · Cited by 185 · see citing works
Ome sweet ome: what can the genome tell us about the connectome?
Lichtman, J. W., & Sanes, J. R. (2008) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2008.08.010 · Cited by 179 · see citing works
CoCoMac 2.0 and the future of tract-tracing databases
Bakker, R., Wächtler, T., & Diesmann, M. (2012) · Frontiers in Neuroinformatics · doi:10.3389/fninf.2012.00030 · Cited by 176 · see citing works
What is a disconnection syndrome?
Catani, M., & Mesulam, M. M. (2008) · Cortex · doi:10.1016/j.cortex.2008.05.001 · Cited by 167 · see citing works
Rich Club Organization and Intermodule Communication in the Cat Connectome
de Reus, M. A., & van den Heuvel, M. P. (2013) · Journal of Neuroscience · doi:10.1523/jneurosci.1448-13.2013 · Cited by 164 · see citing works
Vulnerability of cortical neurons to Alzheimer's and Parkinson's diseases
Braak, H., Rüb, U., Schultz, C., & Tredici, K. D. (2006) · Journal of Alzheimer s Disease · doi:10.3233/jad-2006-9s305 · Cited by 163 · see citing works
From gene networks to brain networks
Bota, M., Dong, H., & Swanson, L. W. (2003) · Nature Neuroscience · doi:10.1038/nn1096 · Cited by 140 · see citing works
Self-citationSwanson, L. W. (1998) · Elsevier eBooks · Cited by 139 · see citing works
Self-citationJaskiw, G. E. (1987) · American Journal of Psychiatry · doi:10.1176/ajp.144.9.1233-a · Cited by 138 · see citing works
Brain Architecture Management System
Bota, M., Dong, H., & Swanson, L. W. (2005) · Neuroinformatics · doi:10.1385/ni:3:1:015 · Cited by 118 · see citing works
Self-citationThe neuron classification problem
Bota, M., & Swanson, L. W. (2007) · Brain Research Reviews · doi:10.1016/j.brainresrev.2007.05.005 · Cited by 108 · see citing works
Self-citationSwanson, L. W. (2005) · The Journal of Comparative Neurology · doi:10.1002/cne.20733 · Cited by 98 · see citing works
Self-citationRibeiro, P. F. M., Ventura-Antunes, L., Gabi, M., Mota, B., Grinberg, L. T., Farfel, J. M., Ferretti-Rebustini, R. E. L., Leite, R. E. P., Filho, W. J., & Herculano-Houzel, S. (2013) · Frontiers in Neuroanatomy · doi:10.3389/fnana.2013.00028 · Cited by 89 · see citing works
Swanson, L. W., & Bota, M. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1015128107 · Cited by 88 · see citing works
Self-citationGenome-scale neurogenetics: methodology and meaning
McCarroll, S. A., Feng, G., & Hyman, S. E. (2014) · Nature Neuroscience · doi:10.1038/nn.3716 · Cited by 87 · see citing works
Karlsen, A. S., & Pakkenberg, B. (2011) · Cerebral Cortex · doi:10.1093/cercor/bhr033 · Cited by 75 · see citing works
Bota, M., Dong, H.-W., & Swanson, L. W. (2012) · Frontiers in Neuroinformatics · doi:10.3389/fninf.2012.00002 · Cited by 52 · see citing works
Self-citationSwanson, L. (2000) · Trends in Neurosciences · doi:10.1016/s0166-2236(00)01639-8 · Cited by 52 · see citing works
Self-citationBrodmann, K., & Gary, L. J. (2006) · Springer eBooks · Cited by 48 · see citing works
Ein Koeffizient für die Organisationsröhe der Grosshirnrinde
Economo, C. V. (1926) · Journal of Molecular Medicine · doi:10.1007/bf01712216 · Cited by 41 · see citing works
Bota, M. (2010) · Frontiers in Neuroinformatics · doi:10.3389/fninf.2010.00003 · Cited by 39 · see citing works
Self-citationBota, M., & Arbib, M. A. (2004) · Neuroinformatics · doi:10.1385/ni:2:1:019 · Cited by 34 · see citing works
Self-citationJoseph, J. A., Fisher, D. R., & Bielinski, D. F. (2006) · Journal of Alzheimer s Disease · doi:10.3233/jad-2006-9103 · Cited by 34 · see citing works
Brown, R. A., & Swanson, L. W. (2013) · The Journal of Comparative Neurology · doi:10.1002/cne.23348 · Cited by 22 · see citing works
Self-citationBota, M., Talpalaru, Ş., Hintiryan, H., Dong, H., & Swanson, L. W. (2014) · The Journal of Comparative Neurology · doi:10.1002/cne.23592 · Cited by 12 · see citing works
Self-citation
Flagged first, then by citations
Research works printed but not linked: 2
- [15]Meynert T. Der bau der Gross-Hirnrinde und seine örtlichen verschiedenheiten, nebst einem pathologisch-anatomischen corollarium. Vierteljarsschr Psychiat. 1867–1868;1:77–93. 198–217 (1867), 2:88–113 (1868) [Google Scholar]
- [29]Goldschmidt R. Das nervensystem von Ascaris lumbricoides und megalocephala. III. Z Wiss Zool. 1909;92:306–357. [Google Scholar]
Cited by
Sorted by citations
Sporns, O., & Betzel, R. F. (2016) · Annual Review of Psychology · doi:10.1146/annurev-psych-122414-033634 · Cited by 1,334 · see citing works
Self-citationHierarchical organization of cortical and thalamic connectivity
Harris, J. A., Mihalas, S., Hirokawa, K. E., Whitesell, J. D., Choi, H., Bernard, A., Bohn, P., Caldejon, S., Casal, L., Cho, A., et al. (2019) · Nature · doi:10.1038/s41586-019-1716-z · Cited by 785 · see citing works
Brain networks and cognitive architectures
Petersen, S. E., & Sporns, O. (2015) · Neuron · doi:10.1016/j.neuron.2015.09.027 · Cited by 553 · see citing works
Self-citationIntegrating time from experience in the lateral entorhinal cortex
Tsao, A., Sugar, J., Lu, L., Wang, C., Knierim, J. J., Moser, M.-B., & Moser, E. I. (2018) · Nature · doi:10.1038/s41586-018-0459-6 · Cited by 490 · see citing works
Morphological diversity of single neurons in molecularly defined cell types
Peng, H., Xie, P., Liu, L., Kuang, X., Wang, Y., Qu, L., Gong, H., Jiang, S., Li, A., Ruan, Z., et al. (2021) · Nature · doi:10.1038/s41586-021-03941-1 · Cited by 417 · see citing works
van den Heuvel, M. P., Bullmore, E. T., & Sporns, O. (2016) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2016.03.001 · Cited by 328 · see citing works
Self-citationBrain Modularity: A Biomarker of Intervention-related Plasticity
Gallen, C. L., & D’Esposito, M. (2019) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2019.01.014 · Cited by 168 · see citing works
The physiological control of eating: signals, neurons, and networks
Watts, A. G., Kanoski, S. E., Sanchez-Watts, G., & Langhans, W. (2022) · Physiological Reviews · doi:10.1152/physrev.00028.2020 · Cited by 168 · see citing works
Chao, O. Y., de Souza Silva, M. A., Yang, Y.-M., & Huston, J. P. (2020) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2020.04.007 · Cited by 158 · see citing works
Cortical tau deposition follows patterns of entorhinal functional connectivity in aging
Adams, J. N., Maass, A., Harrison, T. M., Baker, S. L., & Jagust, W. J. (2019) · eLife · doi:10.7554/elife.49132 · Cited by 160 · see citing works
van den Heuvel, M. P., de Reus, M. A., Feldman Barrett, L., Scholtens, L. H., Coopmans, F. M. T., Schmidt, R., Preuss, T. M., Rilling, J. K., & Li, L. (2015) · Human Brain Mapping · doi:10.1002/hbm.22828 · Cited by 131 · see citing works
Prefrontal connectomics: From anatomy to human imaging
Haber, S. N., Liu, H., Seidlitz, J., & Bullmore, E. (2022) · Neuropsychopharmacology · doi:10.1038/s41386-021-01156-6 · Cited by 129 · see citing works
Peng, H., Xie, P., Liu, L., Kuang, X., Wang, Y., Qu, L., Gong, H., Jiang, S., Li, A., Ruan, Z., et al. (2019) · doi:10.1101/675280 · Cited by 47 · see citing works
Trinkle, S., Foxley, S., Wildenberg, G., Kasthuri, N., & La Rivière, P. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118576 · Cited by 8 · see citing works
- Authors
- Bota, M., Sporns, O., & Swanson, L. W.
- Affiliations
- University of Southern California (US)
- Indiana University Bloomington (US)
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2015-04-06
- Volume
- 112
- Issue
- 16
- Pages
- E2093-101
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC4413280
- OpenAlex
- W2069755236
- Cited by
- 231
- References
- 47
- Citations by year
- 2026: 8 · 2025: 16 · 2024: 14 · 2023: 19 · 2022: 26 · 2021: 18 · 2020: 24 · 2019: 20 · 2018: 24 · 2017: 22 · 2016: 28 · 2015: 12
- FWCI
- 17.23
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- HHS | NIH | National Institute of Neurological Disorders and Stroke (NS050792)
- James S. McDonnell Foundation (220020255)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Keywords
- cerebral cortex, cortical connectivity, network architecture, entorhinal cortex, temporal pole, topographic connectivity, cognitive function, rat brain, genome-wide association study
- MeSH terms
- Algorithms, Animals, Cerebral Cortex, Cognition, Humans, Nerve Net, Rats, Connectome
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review