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.
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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
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Goldman, P. S., & RAKIC, P. T. (1991) · Cerebral Cortex · doi:10.1093/cercor/1.1.1-a · Cited by 3,537
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Riesenhuber, M., & Poggio, T. (1999) · Nature Neuroscience · doi:10.1038/14819 · Cited by 3,309
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“…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
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Cited by
Sorted by citations
What we can do and what we cannot do with fMRI
Logothetis, N. K. (2008) · Nature · doi:10.1038/nature06976 · Cited by 3,612
An anatomically comprehensive atlas of the adult human brain transcriptome
Hawrylycz, M. J., Lein, E. S., Guillozet-Bongaarts, A. L., Shen, E. H., Ng, L., Miller, J. A., van de Lagemaat, L. N., Smith, K. A., Ebbert, A., Riley, Z. L., et al. (2012) · Nature · doi:10.1038/nature11405 · Cited by 3,083
Canonical Microcircuits for Predictive Coding
Bastos, A. M., Usrey, W. M., Adams, R. A., Mangun, G. R., Fries, P., & Friston, K. J. (2012) · Neuron · doi:10.1016/j.neuron.2012.10.038 · Cited by 2,421
“This section reviews laminar-specific connections that underlie the notion of a canonical microcircuit (Douglas et al., 1989; Douglas and Martin, 1991, 2004).”
How does the brain solve visual object recognition?
DiCarlo, J. J., Zoccolan, D., & Rust, N. C. (2012) · Neuron · doi:10.1016/j.neuron.2012.01.010 · Cited by 1,790
Pyramidal neurons: dendritic structure and synaptic integration
Spruston, N. (2008) · Nature Reviews Neuroscience · doi:10.1038/nrn2286 · Cited by 1,688
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
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