Neuronal circuits of the neocortex.

By Rodney J. Douglas, Kevan A. C. Martin. 2004

1,942 citations recorded by the source corpus.

Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience, Neuroscience

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Citations in the corpus

An Integrated Micro- and Macroarchitectural Analysis of the Drosophila Brain by Computer-Assisted Serial Section Electron Microscopy (2010, background): “The study of macrocircuitry informs us of how the brain is built, which “packets of information” may interact, where in the brain this interaction takes place, and what output channels are activated to elicit a behavior that is correlated with the observed macroscopic brain activity. Addressing macr”
How does the brain solve visual object recognition? (2012, neutral): “…processing power required for object representation, many have emphasized the remarkable architectural homogeneity of the mammalian neocortex (e.g., Douglas and Martin, 2004; Rockel et al., 1980); with some exceptions, each piece of neocortex copies many details of local structure (number of…”
Toward an Integration of Deep Learning and Neuroscience (2016, background): “…be coordinated in a complex and dynamic fashion, 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).”
Compositional Few-Shot Recognition with Primitive Discovery and Enhancing (2020, methodology): “Winner-take-all mechanism is widely used in the brain cortex learning and the Spiking Neural Network [13].”
A Canonical Neural Circuit for Cortical Nonlinear Operations (2008, background): “The universality of the proposed neural circuit is consistent with two interestingobservations:thatthebasiccorticalstructureisquitesimilarwithin andacrossdifferentfunctionalareasandthattheremayexist“canonicalmicrocircuits”inthecortex( DouglasM Douglas,Martin,W Mountcastle, 2003; Nelson, 2002).”
Bayesian Computation Emerges in Generic Cortical Microcircuits through Spike-Timing-Dependent Plasticity (2013, methodology): “Our model consists of a network of spiking neurons, arranged in a WTA circuit, which is one of the most frequently studied connectivity patterns (or network motifs) of cortical microcircuits [16].”
Unsupervised Continual Learning and Self-Taught Associative Memory Hierarchies (2019, background): “The “canonical cortical circuit” by Douglas and Martin captures what is currently known about this module at the level of connections between the six cortical layers Douglas and Martin (2004); Douglas et al. (1989).”
The atoms of neural computation (2014, background): “…studied the computational versatility of soft winner-take-all or soft-MAX operations, which were suggested by Douglas and Martin to be central to the operation of the putative canonical cortical microcircuit (Douglas & Martin, 2004) and which also feature heavily in a variety of other models.”
Finding a roadmap to achieve large neuromorphic hardware systems (2013, result): “This result is consistent with data that most neurons have a high level of local interconnection (Douglas and Martin, 2004), such as nearby cortical neurons; any cortical architecture must explicitly incorporate these effects to achieve the necessary power efﬁciency gains.”
Population coding under normalization (2009, background): “The prevalence of normalization in the nervous system must surely reflect the fact that it evolved to address a problem that arises ll rights reserved. at different stages of processing (Douglas & Martin, 2004, 2007).”
Emergence of Dynamic Memory Traces in Cortical Microcircuit Models through STDP (2013, background): “In particular, as emphasized in Douglas and Martin (2004), ensembles of pyramidal cells on superficial and deep layers tend to form through mutual synaptic connections with inhibitory neurons into (soft) winner-take-all (WTA) circuits in which at most one pyramidal cell in the ensemble usually…”
A mechanistic cortical microcircuit of attention for amplification, normalization and suppression. (2015, methodology): “For example, the model contains only layer 4 and layer 2/3 of the cortical microcircuit (Douglas & Martin, 2004) and only the necessary part of its connectivity.”
What we can do and what we cannot do with fMRI (2008, background): “Buzsaki, Cellular‐synaptic generation of sleep spindles, spike‐and‐wave discharges, and evoked thalamocortical responses in the neocortex of the rat, 17(17), 6783 (1997).”
Decision making in recurrent neuronal circuits. (2008, background): “, 1998), the dynamics of synaptic connections (Abbott and Regehr, 2004), and the microcircuit wiring connectivity (Somogyi et al., 1998; Douglas and Martin, 2004).”