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Journal ArticleDOI

Neuronal circuits of the neocortex

Rodney J. Douglas, +1 more
- 24 Jun 2004 - 
- Vol. 27, Iss: 1, pp 419-451
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TLDR
It is found 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.
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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Citations
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Dynamics of excitation and inhibition underlying stimulus selectivity in rat somatosensory cortex

TL;DR: In vivo intracellular recordings from thalamorecipient neurons in layers 3 and 4 of the rat barrel cortex are used to elucidate the dynamics of the synaptic inputs underlying direction selectivity, and it is shown that cells are direction selective despite a broadly tuned excitatory and inhibitory synaptic input.
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Neuromorphic Electronic Circuits for Building Autonomous Cognitive Systems

TL;DR: In this article, a set of neuromorphic engineering solutions for fast simulations of spiking neural networks is proposed, which can emulate neural and synaptic dynamics in real time and discuss the role of biophysically realistic temporal dynamics in hardware neural processing architectures.
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Selective Activation of the Deep Layers of the Human Primary Visual Cortex by Top-Down Feedback

TL;DR: FMRI at high field found that, whereas bottom-up stimulation activated all cortical layers, feedback activity induced by illusory figures led to a selective activation of the deep layers of V1, which helps elucidate the role of top-down signals during perceptual processing.
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A neural microcircuit for cognitive conflict detection and signaling

TL;DR: A neural MFC microcircuit model is proposed for processing conflict and generating theta oscillations and makes several novel predictions for the causes and consequences of MFC theta and conflict processing, and may be relevant for understanding the neural implementations of related cognitive processes.
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Bayesian Computation Emerges in Generic Cortical Microcircuits through Spike-Timing-Dependent Plasticity

TL;DR: The results suggest that the experimentally observed spontaneous activity and trial-to-trial variability of cortical neurons are essential features of their information processing capability, since their functional role is to represent probability distributions rather than static neural codes.
References
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Journal ArticleDOI

Receptive fields, binocular interaction and functional architecture in the cat's visual cortex

TL;DR: This method is used to examine receptive fields of a more complex type and to make additional observations on binocular interaction and this approach is necessary in order to understand the behaviour of individual cells, but it fails to deal with the problem of the relationship of one cell to its neighbours.
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Distributed Hierarchical Processing in the Primate Cerebral Cortex

TL;DR: A summary of the layout of cortical areas associated with vision and with other modalities, a computerized database for storing and representing large amounts of information on connectivity patterns, and the application of these data to the analysis of hierarchical organization of the cerebral cortex are reported on.
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Hierarchical models of object recognition in cortex

TL;DR: A new hierarchical model consistent with physiological data from inferotemporal cortex that accounts for this complex visual task and makes testable predictions is described.
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Neuromorphic electronic systems

TL;DR: It is shown that for many problems, particularly those in which the input data are ill-conditioned and the computation can be specified in a relative manner, biological solutions are many orders of magnitude more effective than those using digital methods.
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