The DOI matches its Crossref record; 189 of the 189 references it cites were found in a registry or an index.
NEURONAL CIRCUITS OF THE NEOCORTEX
Abstract
▪ Abstract We explore the extent to which neocortical circuits generalize, i.e., to what extent can neocortical neurons and the circuits they form be considered as canonical? We find that, as has long been suspected by cortical neuroanatomists, the same basic laminar and tangential organization of the excitatory neurons of the neocortex is evident wherever it has been sought. Similarly, the inhibitory neurons show characteristic morphology and patterns of connections throughout the neocortex. We offer a simple model of cortical processing that is consistent with the major features of cortical circuits: The superficial layer neurons within local patches of cortex, and within areas, cooperate to explore all possible interpretations of different cortical input and cooperatively select an interpretation consistent with their various cortical and subcortical inputs.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
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?
In the citing paper
“We chose to study L5 cells, because these are the main output neurons of the PFC (Douglas and Martin, 2004).”
From Social Play Behavior Is Critical for the Development of Prefrontal Inhibitory Synapses and Cognitive Flexibility in Rats (2022) · cites this paper as Douglas and Martin, 2004
In the citing paper
“the relative homogeneity of the two largest neuronal structures, with ~69 billion (cerebellar cortex) and ~16 billion (cortex) neurons out of the 86 billion neurons in the human brain33, is striking and suggests an evolutionary expansion of a canonical cortical blueprint34.”
From An anatomically comprehensive atlas of the adult human brain transcriptome (2012) · cites this paper as [34]
In the citing paper
“Layer 4 receives the vast majority of thalamocortical input, and so it plays a prominent role in the initial processing of sensory information (Douglas and Martin, 2004).”
From Development and Functional Diversification of Cortical Interneurons (2018) · cites this paper as Douglas and Martin, 2004
In the citing paper
“The concept of ‘modular organization’ of cortical architecture dates back more than four decades52,53,54.”
From The diversity of GABAergic neurons and neural communication elements (2019) · cites this paper as [53]
In the citing paper
“Thus, the communication element definition of neuron types should facilitate the delineation of higher-level modular organization of neural circuit architecture24,53 by clarifying the developmental genetic basis of elemental building blocks.”
From The diversity of GABAergic neurons and neural communication elements (2019) · cites this paper as [53]
In the citing paper
“Layer 2 and 3 neurons mainly mediate intracortical connections both locally and distantly.”
From Large-Scale Cellular-Resolution Gene Profiling in Human Neocortex Reveals Species-Specific Molecular Signatures (2012) · cites this paper as Douglas and Martin, 2004
In the citing paper
“Cortical excitatory neurons in different layers are believed to have differential input/output connections and play distinct roles in the cortical circuits (Douglas and Martin, 2004).”
From Large-Scale Cellular-Resolution Gene Profiling in Human Neocortex Reveals Species-Specific Molecular Signatures (2012) · cites this paper as Douglas and Martin, 2004
In the citing paper
“Layer 5 and 6 neurons mainly send output projections to various subcortical and contralateral regions.”
From Large-Scale Cellular-Resolution Gene Profiling in Human Neocortex Reveals Species-Specific Molecular Signatures (2012) · cites this paper as Douglas and Martin, 2004
In the citing paper
“Layer 4 neurons are the main targets of thalamocortical inputs.”
From Large-Scale Cellular-Resolution Gene Profiling in Human Neocortex Reveals Species-Specific Molecular Signatures (2012) · cites this paper as Douglas and Martin, 2004
In the citing paper
“Looking at the brain, we indeed seem to find highly conserved structures, e.g., cortex, where it is theorized that a similar type of learning and/or computation is happening in multiple places (Braitenberg and Schutz, 1991; Douglas and Martin, 2004).”
From Toward an integration of deep learning and neuroscience (2016) · cites this paper as Douglas and Martin, 2004
In the citing paper
“In addition to providing a template for understanding cortical circuits [15], the theory presented here can be useful in the modeling of physiological phenomena.”
From Towards a mathematical theory of cortical micro-circuits (2009) · cites this paper as [15]
In the citing paper
“The major projection (output) of layer 4 stellate neurons is to layer 3 cells [15].”
From Towards a mathematical theory of cortical micro-circuits (2009) · cites this paper as [15]
In the citing paper
“Layer 6 is known to be a primary source of cortical feedback connections [15].”
From Towards a mathematical theory of cortical micro-circuits (2009) · cites this paper as [15]
In the citing paper
“most of the inter-laminar and long distance connections within a cortical area are provided by the spiny excitatory neurons, whereas the smooth inhibitory interneurons more prevalently connect locally within their layer of origin.”
From Towards a mathematical theory of cortical micro-circuits (2009) · cites this paper as [15]
In the citing paper
“It is the excitatory cells that connect long distance in both vertical and lateral dimensions and their activity is then molded by local inhibitory neurons [15].”
From Towards a mathematical theory of cortical micro-circuits (2009) · cites this paper as [15]
Citations
Cites
Receptive fields, binocular interaction and functional architecture in the cat’s visual cortex
Hubel, D. H., & Wiesel, T. N. (1962) · The Journal of Physiology · doi:10.1113/jphysiol.1962.sp006837 · Cited by 13,680
Distributed hierarchical processing in the primate cerebral cortex
Felleman, D. J., & Van Essen, D. C. (1991) · Cerebral Cortex · doi:10.1093/cercor/1.1.1 · Cited by 7,783
Preface: Cerebral Cortex Has Come of Age
Goldman, P. S., & RAKIC, P. T. (1991) · Cerebral Cortex · doi:10.1093/cercor/1.1.1-a · Cited by 3,537
Hierarchical models of object recognition in cortex
Riesenhuber, M., & Poggio, T. (1999) · Nature Neuroscience · doi:10.1038/14819 · Cited by 3,309
Neuromorphic electronic systems
Mead, C. (1990) · Proceedings of the IEEE · doi:10.1109/5.58356 · Cited by 2,368
The Handbook of brain theory and neural networks
(2003) · Choice Reviews Online · doi:10.5860/choice.41-0300 · Cited by 1,540
GABAergic cell subtypes and their synaptic connections in rat frontal cortex
Kawaguchi, Y. (1997) · Cerebral Cortex · doi:10.1093/cercor/7.6.476 · Cited by 1,416
Histologie du Système Nerveux de Lʼhomme et des Vertébrés
MNH, &. (1998) · Journal of Neuropathology & Experimental Neurology · doi:10.1097/00005072-199809000-00011 · Cited by 1,351
Columnar specificity of intrinsic horizontal and corticocortical connections in cat visual cortex
Gilbert, C., & Wiesel, T. (1989) · Journal of Neuroscience · doi:10.1523/jneurosci.09-07-02432.1989 · Cited by 1,166
Concurrent overproduction of synapses in diverse regions of the primate cerebral cortex
Rakic, P., Bourgeois, J.-P., Eckenhoff, M. F., Zecevic, N., & Goldman-Rakic, P. S. (1986) · Science · doi:10.1126/science.3952506 · Cited by 1,133 · cited 1×
“…cells, can vary widely from area to area or species to species (see Elston 2002), other parameters, such as the overall density of synapses, shows remarkably little variance from area to area in different species (Cragg 1967, O'Kusky & Colonnier 1982, Rakic et al. 1986, Schuz & Palm 1989).”
Background
Research works printed but not linked: 7
- Cragg BG, 1967, J. Anat., 101, 639
- Elston GN, 2000, J. Neurosci., 20, 1
- 10.1002/(SICI)1096-9861(19960122)364:4<609::AID-CNE2>3.0.CO;2-7 · DOI
- Powell T, 1973, Symp. Zool. Soc. London, 33, 235
- Powell T, 1981, Brain Mechanisms and Perceptual Awareness, 1
- Rockland K, 1997, Cerebral Cortex, 12, 243
- Sun XZ, 2002, J. Med. Invest., 49, 35
Cited by
Sorted by citations
Items 101–142 of 142
Towards a Unified View on Pathways and Functions of Neural Recurrent Processing
Pennartz, C. M. A., Dora, S., Muckli, L., & Lorteije, J. A. M. (2019) · Trends in Neurosciences · doi:10.1016/j.tins.2019.07.005 · Cited by 73
“Themost prominent intra-areal excitatory projections are from layer 4 to layer 2/3 and from layer 2/3 to layer 5 [97].”
Plasticity during sleep is linked to specific regulation of cortical circuit activity
Niethard, N., Burgalossi, A., & Born, J. (2017) · Frontiers in Neural Circuits · doi:10.3389/fncir.2017.00065 · Cited by 89
Merker, B. (2013) · Frontiers in Psychology · doi:10.3389/fpsyg.2013.00501 · Cited by 92
Tang, R., & Dai, J. (2014) · PLoS ONE · doi:10.1371/journal.pone.0085643 · Cited by 91
The role of the primary auditory cortex in the neural mechanism of auditory verbal hallucinations
Kompus, K., Falkenberg, L. E., Bless, J. J., Johnsen, E., Kroken, R. A., Kråkvik, B., Larøi, F., Løberg, E.-M., Vedul-Kjelsås, E., Westerhausen, R., et al. (2013) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2013.00144 · Cited by 91
Distinct Lineage-Dependent Structural and Functional Organization of the Hippocampus
Xu, H.-T., Han, Z., Gao, P., He, S., Li, Z., Shi, W., Kodish, O., Shao, W., Brown, K. N., Huang, K., et al. (2014) · Cell · doi:10.1016/j.cell.2014.03.067 · Cited by 80
Attention – oscillations and neuropharmacology
Deco, G., & Thiele, A. (2009) · European Journal of Neuroscience · doi:10.1111/j.1460-9568.2009.06833.x · Cited by 85
Xu, X., Olivas, N. D., Ikrar, T., Peng, T., Holmes, T. C., Nie, Q., & Shi, Y. (2016) · The Journal of Physiology · doi:10.1113/jp271891 · Cited by 83
Dendritic calcium spikes are clearly detectable at the cortical surface
Suzuki, M., & Larkum, M. E. (2017) · Nature Communications · doi:10.1038/s41467-017-00282-4 · Cited by 70
A human-specific modifier of cortical connectivity and circuit function
Schmidt, E. R. E., Zhao, H. T., Park, J. M., Dipoppa, M., Monsalve-Mercado, M. M., Dahan, J. B., Rodgers, C. C., Lejeune, A., Hillman, E. M. C., Miller, K. D., et al. (2021) · Nature · doi:10.1038/s41586-021-04039-4 · Cited by 82
Frandolig, J. E., Matney, C. J., Lee, K., Kim, J., Chevée, M., Kim, S.-J., Bickert, A. A., & Brown, S. P. (2019) · Cell Reports · doi:10.1016/j.celrep.2019.08.048 · Cited by 78
Trongnetrpunya, A., Nandi, B., Kang, D., Kocsis, B., Schroeder, C. E., & Ding, M. (2016) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2015.00189 · Cited by 75
The empirical status of predictive coding and active inference
Hodson, R., Mehta, M., & Smith, R. (2024) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2023.105473 · Cited by 69
Rotaru, D. C., van Woerden, G. M., Wallaard, I., & Elgersma, Y. (2018) · The Journal of Neuroscience · doi:10.1523/jneurosci.0083-18.2018 · Cited by 74
Anderson, L. A., Christianson, G. B., & Linden, J. F. (2009) · Brain Research · doi:10.1016/j.brainres.2008.11.037 · Cited by 71
Optimizing neuronal differentiation from induced pluripotent stem cells to model ASD
Kim, D.-S., Ross, P. J., Zaslavsky, K., & Ellis, J. (2014) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2014.00109 · Cited by 70
Linking hippocampal multiplexed tuning, Hebbian plasticity and navigation
Moore, J. J., Cushman, J. D., Acharya, L., Popeney, B., & Mehta, M. R. (2021) · Nature · doi:10.1038/s41586-021-03989-z · Cited by 69
Neuronal structural remodeling: is it all about access?
Chen, J. L., & Nedivi, E. (2010) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2010.06.002 · Cited by 68
Contrast gain control and horizontal interactions in V1: A DCM study
Pinotsis, D. A., Brunet, N., Bastos, A., Bosman, C. A., Litvak, V., Fries, P., & Friston, K. J. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.01.047 · Cited by 68
“Lastly, in their revised model, dense (lateral) interconnections amongst the superficial pyramidal cells allow these cells to sample their diverse inputs on the dendritic tree and implement a version of a winner-take-all algorithm (Douglas and Martin, 2004).”
InfluentialLocal-circuit phenotypes of layer 5 neurons in motor-frontal cortex of YFP-H mice
Yu, J. (2008) · Frontiers in Neural Circuits · doi:10.3389/neuro.04.006.2008 · Cited by 64
Towards functional connectomics
Seung, H. S. (2011) · Nature · doi:10.1038/471170a · Cited by 67
Anastasiades, P. G., & Butt, S. J. B. (2012) · The Journal of Neuroscience · doi:10.1523/jneurosci.1262-12.2012 · Cited by 49
Reduced inhibition in depression impairs stimulus processing in human cortical microcircuits
Yao, H. K., Guet-McCreight, A., Mazza, F., Moradi Chameh, H., Prevot, T. D., Griffiths, J. D., Tripathy, S. J., Valiante, T. A., Sibille, E., & Hay, E. (2022) · Cell Reports · doi:10.1016/j.celrep.2021.110232 · Cited by 55
Thalamocortical Oscillations: Local Control of EEG Slow Waves
Timofeev, I., & Chauvette, S. (2011) · Current Topics in Medicinal Chemistry · doi:10.2174/156802611797470376 · Cited by 55
Bijlsma, A., Omrani, A., Spoelder, M., Verharen, J. P. H., Bauer, L., Cornelis, C., de Zwart, B., van Dorland, R., Vanderschuren, L. J. M. J., & Wierenga, C. J. (2022) · The Journal of Neuroscience · doi:10.1523/jneurosci.0524-22.2022 · Cited by 54
Miceli, S., Negwer, M., van Eijs, F., Kalkhoven, C., van Lierop, I., Homberg, J., & Schubert, D. (2013) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2013.00088 · Cited by 49
Identification and integration of sensory modalities: Neural basis and relation to consciousness
Pennartz, C. M. A. (2009) · Consciousness and Cognition · doi:10.1016/j.concog.2009.03.003 · Cited by 40
Pennartz, C. M. A., Oude Lohuis, M. N., & Olcese, U. (2023) · Philosophical Transactions of the Royal Society B · doi:10.1098/rstb.2022.0336 · Cited by 38
Turk, E., Scholtens, L. H., & van den Heuvel, M. P. (2016) · Human Brain Mapping · doi:10.1002/hbm.23141 · Cited by 27
An Atlas of Gene Regulatory Elements in Adult Mouse Cerebrum
Li, Y. E., Preissl, S., Hou, X., Zhang, Z., Zhang, K., Fang, R., Qiu, Y., Poirion, O., Li, B., Liu, H., et al. (2020) · doi:10.1101/2020.05.10.087585 · Cited by 187
Lyttle, K., Ohmura, Y., Konno, K., Yoshida, T., Izumi, T., Watanabe, M., & Yoshioka, M. (2015) · Brain Research · doi:10.1016/j.brainres.2015.04.058 · Cited by 26
Liu, Z., de Zwart, J. A., Chang, C., Duan, Q., van Gelderen, P., & Duyn, J. H. (2014) · Cerebral Cortex · doi:10.1093/cercor/bht164 · Cited by 22
Disrupted cross-laminar cortical processing in β amyloid pathology precedes cell death
Lison, H., Happel, M. F. K., Schneider, F., Baldauf, K., Kerbstat, S., Seelbinder, B., Schneeberg, J., Zappe, M., Goldschmidt, J., Budinger, E., et al. (2014) · Neurobiology of Disease · doi:10.1016/j.nbd.2013.11.014 · Cited by 23
Dora, S., Bohte, S. M., & Pennartz, C. M. A. (2021) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2021.666131 · Cited by 24
Snyder, H. R., Banich, M. T., & Munakata, Y. (2014) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_00652 · Cited by 24
Laminar circuit organization and response modulation in mouse visual cortex
Olivas, N. D., Quintanar-Zilinskas, V., Nenadic, Z., & Xu, X. (2012) · Frontiers in Neural Circuits · doi:10.3389/fncir.2012.00070 · Cited by 17
Laminar specificity of the auditory perceptual awareness negativity: a biophysical modeling study
Fernandez Pujol, C., Blundon, E. G., & Dykstra, A. R. (2023) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1011003 · Cited by 14
Hamilton, T. J., Xapelli, S., Michaelson, S. D., Larkum, M. E., & Colmers, W. F. (2013) · Journal of Neuroscience · doi:10.1523/jneurosci.5595-12.2013 · Cited by 11
Konsolaki, E., & Skaliora, I. (2015) · Cerebral Cortex · doi:10.1093/cercor/bhu019 · Cited by 9
Sleep and wake in a model of the thalamocortical system with Martinotti cells
Bugnon, T., Mayner, W. G. P., Cirelli, C., & Tononi, G. (2024) · European Journal of Neuroscience · doi:10.1111/ejn.15836 · Cited by 6
Berndt, L. C. S., Singh, K. D., & Shaw, A. D. (2026) · Schizophrenia Bulletin · doi:10.1093/schbul/sbaf149 · Cited by 3
The contributions of anatomical studies to knowledge of perceptual processing
Guillery, R. W. (2008) · Anatomy (International Journal of Experimental and Clinical Anatomy) · doi:10.2399/ana.08.009 · Cited by 1
Metadata
- Authors
- Douglas, R. J., & Martin, K. A. C.
- Affiliations
- ETH Zurich (CH)
- Venue
- Annual Review of Neuroscience
- Publisher
- Annual Reviews
- Published
- 2004-07-21
- Volume
- 27
- Issue
- 1
- Pages
- 419-451
- ISSN
- 0147-006X (ISSN-L)
- 1545-4126
- OpenAlex
- W2151718948
- Cited by
- 1,886
- References
- 189
- Citations by year
- 2026: 99 · 2025: 123 · 2024: 101 · 2023: 93 · 2022: 86 · 2021: 93 · 2020: 88 · 2019: 83 · 2018: 95 · 2017: 88 · 2016: 84 · 2015: 97 · 2014: 121 · 2013: 109 · 2012: 90
- FWCI
- 3.73
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Annual Review of Neuroscience (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Körber-Stiftung
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Keywords
- neocortex, cortical circuits, laminar organization, excitatory neurons, inhibitory neurons, neuronal morphology, cortical connectivity
- MeSH terms
- Animals, Humans, Models, Neurological, Nerve Net, Neural Inhibition, Neural Pathways, Synaptic Transmission, Neurons, Neocortex, Cell Size
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
